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The Assessment of forest cover change is important for the urban development and making the policy for forest management policy. Forest depletion is a common topic in the North-east India, especially in Mizoram as most of the agricultural practices are based on shifting cultivation. So, it is very important to have knowledge about the changing pattern of forest. In this paper, it shows the changing pattern of forest in Aizawl District, Mizoram. This forest has been declining at an alarming rate as a result of land use and land cover change (LULCC). For supporting decision-making processes, identifying LULCC and comprehending the underlying forces are crucial. We examined and analyze the changing variation of forest cover during the period of 2000 to 2018 using Landsat Thematic Mapper (TM) 4-5 C1 level-1 satellite imagery for 2000 and Landsat 8 OLI/TIRS C1 level-1 imagery for 2018. The methodologies are Transitional Probability Matrix (TPM), Kappa coefficient, post-classification change (PCC) detection approach and simple statistical techniques. Detecting the Land Use Land Cover (LULC) showed that in 2000 dense forest cover an area of 827.59 sq.km which was 36.67 per cent of the total study area while in 2018 forest cover changed drastically with an area of only 284.22 sq.km which was 12.59 per cent of the total study area. On the other hand, open forest during 2000 was 51.25 sq.km and in 2018 it increased to 107.76 sq.km. The results showed that settlement, light vegetation and barren land were increasing, while forest cover was declining. The loss of forest cover could lead to an unpleasant environment and have an impact on people's wellbeing. Keywords: Land Use Land Cover Change, approach, management, Aizawl. Title: SAPTIO-TEMPORAL STUDY OF FOREST COVER CHANGE IN AIZAWL DISTRICT, MIZORAM Author: Remlalruata International Journal of Recent Research in Interdisciplinary Sciences (IJRRIS) ISSN 2350-1049 Vol. 10, Issue 2, April 2023 - June 2023 Page No: 67-74 Paper Publications Website: www.paperpublications.org Published Date: 15-June-2023 DOI: https://doi.org/10.5281/zenodo.8042758 Paper Download Link (Source) https://www.paperpublications.org/upload/book/SAPTIO-TEMPORAL%20STUDY-15062023-5.pdf, International Journal of Recent Research in Interdisciplinary Sciences (IJRRIS), ISSN 2350-1049, Paper Publications, Website: www.paperpublications.org

The Assessment of land use and land cover change is important for the development of a policy by the government. Land cover change is still a very interesting and hot topic in todays world even in Mizoram. For supporting decision-making processes, identifying LULCC and comprehending the underlying forces are crucial. We examined and analyze the changing variation of land use and land cover during the period of 2000 to 2020 using Three Landsat Thematic Mapper (TM) 4-5 C1 level-1 satellite imagery for 2000, 2010 and Landsat 8 OLI/TIRS C1 level-1 imagery for 2020. Accuracy assessment were taken out and land cover changed was also calculated using ArcMap 10.4. The results showed that there were a lot of changing in the LULC classes. During 2000 to 2020, agriculture land decreased by 8.78%, Barren land increased by 7.89%, Built-up land increased by 21.52%, Dense Forest decreased by 34.71%, Medium Dense Forest increased by 3.83%, Open Forest increased by 19.4% and waterbody decreased by 9.14%. Therefore, land use and land cover change should be given some in-depth interest for the future generations. Keywords: Land use and Land cover, Land Use Land Cover Change, approach, management, Aizawl. Title: STUDIES ON LAND USE AND LAND COVER CHANGE IN AIZAWL DISTRICT, MIZORAM Author: Remlalruata International Journal of Recent Research in Social Sciences and Humanities (IJRRSSH) ISSN 2349-7831 Vol. 10, Issue 2, April 2023 - June 2023 Page No: 107-116 Paper Publications Website: www.paperpublications.org Published Date: 15-June-2023 DOI: https://doi.org/10.5281/zenodo.8042670 Paper Download Link (Source) https://www.paperpublications.org/upload/book/STUDIES%20ON%20LAND%20USE-15062023-4.pdf, International Journal of Recent Research in Social Sciences and Humanities (IJRRSSH), ISSN 2349-7831, Paper Publications, Website: www.paperpublications.org

Land surface temperature (LST) and surface air temperature (SAT) are important environmental variables that describe the temperature of the Earth's surface as measured by satellite sensors or ground-based instruments. Changes in land cover, such as deforestation, urbanization, and agriculture, can have a significant impact on LST, as they alter the surface energy balance and affect the amount of solar radiation that is absorbed or reflected by the land surface. The effects of increased LST are often complex and depend on a range of factors, including the specific location, the type and intensity of urbanization, and the surrounding natural environment. However, it is clear that high LSTs and SAT can have a range of negative impacts on both natural and built environments, and that efforts to reduce LSTs can have significant benefits for human health, the environment, and the economy. This study examines the impact of spatio-temporal land cover changes (built-ups) on land surface temperature (LST) over Dormaa from 1990-2020. Using the Mann-Kendall trend test, remote sensing data, and GIS techniques, we analyse the relationship between land cover changes and LST at the local scale, taking into account factors such as vegetation cover, land use patterns, and weather conditions. The analysis of LULCC, LST, and SAT with their corresponding percentage annual rate of change showed a deterministic factor R=0.89, with a significant F-change of 0.014 at a 95% confidence interval of their difference. The results provide strong evidence that the increase in LST and SAT across the years over the Dormaa area correlated with the significant changes in land cover as observed from 1990 – 2020. The most significant land cover changes were observed within the Dormaa Municipal, which also recorded the highest LST and SAT anomaly change of 0.091°C compared to the other districts. The results further showed that the rapid urbanization that occurred between 2000-2020 in the Dormaa Municipal was the primary cause of the observed increase in LST and SAT. The quick changes in the land cover, which caused a greater portion of the green vegetated surface in the Dormaa Municipal to be converted to a more non-transpiring and reduced evaporative built-up environment forhousing, provision of social amenities, and supporting other significant socio-economic activities, resulted in an increased LST and SAT. Our results indicate that land cover changes have had a significant impact on LST over Dormaa during the study period. In particular, urbanization and agricultural land use changes have led to increases in LST, while changes in forest cover have had a more complex relationship with temperature, depending on factors such as the type and intensity of forest management. We also found that the relationship between land cover changes and LST is non-linear and dependent on interactions between multiple factors, highlighting the importance of considering the specific context when analysing this relationship. Our study provides new insights into the complex relationship between land cover changes and LST at the local scale, which can be used to inform local decision-making, such as land use planning and management, and contribute to our broader understanding of the impact of human activities on the environment. The study also urges all interested parties to ensure and integrate vegetation conservation in modern city planning models, as green environments act as carbon sinks (a role in global warming) by implementing rules and regulations in the districts, particularly in the Dormaa Municipal.

Urban area expansion and the increase in the built-up area are major threats to agriculture, the natural environment, and ecology throughout the world. The population of the city of Larkana is rapidly increasing due to natural growth and uncontrolled migration from the surrounding areas, which have resulted in a haphazard increase in the built-up area over the fertile agricultural land and affected the city’s thermal environment. This research aims to evaluate the impacts of urban area expansion on agricultural land and the thermal environment of the study area by assessing the change in land use/ land cover (LULC) from 1990 to 2020 and land surface temperature (LST). For this purpose, the Random Forest (RF) algorithm was applied, and LST was calculated in Google Earth Engine (GEE) using Landsat imageries for the years 1990, 2000, 2010, and 2020. For the RF classifier algorithm, 3500 reference random points were generated for each year, which were then randomly divided into two datasets, i.e., a training sample consisting of 70% of the points and a validation dataset (30% of the points). After LULC classification, the results were validated for 1990, 2000, 2010, and 2020, and the accuracy was 88.3%, 89%, 90.01%, and 90.8%, respectively. The study results showed that the built-up area increased from 12.31 to 43.83 km2 while the barren land in the study region decreased from 56.51 km2 to 11.62 km2. The agricultural land was 66.66 km2 in 1990, expanded to 101.38 km2, and then decreased to 79.49 km2 in 2020. The results also revealed that most of the urban expansion in the last decade (2010-2020) took place on agricultural land. The urban thermal environment also showed a gradual increase in surface temperatur,e as recorded by the LST results. The LST results revealed that the maximum LST was 33.4°C in 1990, which increased to 36.1°C in 2020, and similarly, the minimum LST was 25.1°C, which also increased to 26.6°C in 2020. This study provides useful results for stakeholders to devise better policies and plans to control further haphazard urban expansion on fertile agricultural land in the study area.

Land Use Land Cover Change (LULCC) and urban growth prediction and analysis are two of the best methods that can help decision-makers for better sustainable management and planning of socioeconomic development in the countries. In the present paper, the growth of urban land use was analyzed and predicted in all districts of the El Baha region (Kingdom of Saudi Arabia) based on high-resolution Landsat, 5, 7, and 8 satellite imagery during the period of study between 1985–2021. Using remote sensing techniques, the LULCC were obtained based on the maximum likelihood classification (MLC), where the geographic information system (GIS) had been used for mapping LULCC classes. Furthermore, Markov cellular automata (MCA) in Idrisi TerrSet was applied for assessing the future growth of urban land use between 2021–2047. The findings of the LULCC analysis based on the MLC indicate great socioeconomic development during the study period and that the urban expansion was at the expense of rangeland, forest and shrubland, and barren land and sand areas, with the contribution of each in the built-up area estimated to be around 9.1% (179.7 km2), 33.4% (656.3 km2) and 57.5% (1131.5 km2), respectively. The simulation of the future LULCC period 2021–2047 revealed a loss in rangeland, forest and shrubland, and barren land and sand by 565, 144 and 105 km2, respectively, where rangeland is the most influenced, its land cover will decrease from 4002 to 3437 km2. From the obtained results based on MCA, urban growth is predicted to be large and it is estimated at around 2607 km2 until the year 2047 with a net increase of 811 km2. The results obtained from this study may provide information to help decision-makers to implement efficient practices for future planning and management of the growth of urban land use, especially Saudi vision 2030.

Made available in DSpace on 2022-04-28T19:48:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-02-01 In this paper, we address the impact of agricultural expansion on hydrological patterns of water and sediment budget in one of the largest floodplains along the Cambodian Mekong since the 1980s, using field (water level, discharge, sediment, rainfall, and groundwater level) and remote sensing (land use, surface suspended sediment) data, and numerical simulations. Specifically, while both the surface suspended sediment concentration and water level in the Mekong River around Kampong Cham and Neak Luong decreased, the floodplain seasonal water storage increased. In addition, the rate of sediment input from the river to the floodplain was almost constant throughout the studied period. The investigation of the floodplain's annual sediment budget, however, reveals a significant drop during the analyzed period, mainly due to the decreased sediment trapping rate (66% in the 1980s to 46% in the 2010s). Currently, a good amount of sediment bypass the floodplain and return back to the river. The observed hydrological patterns in the floodplain could have been triggered by the agricultural expansion that has increased surface erodibility (due to removals of primary vegetation) and lowered the land surface elevation (due to groundwater extraction). Despite the well-known impacts of the hydropower dams on the Mekong Delta hydrological conditions, particularly the reduction of sediment reaching the delta due to sediment trapping by dam reservoirs, our observations point to new and more localized driving factors of sediment deficit in floodplain: agricultural expansion. Finally, we used 2D hydrodynamic simulation (Telemac-2D) to visualize the processes of water routing and sedimentation in the floodplain accounting for land cover change since the 1980s. The floodplain hydrology reported in this paper is an unexplored environmental consequence of agricultural expansion in the lower Mekong. Geomorphologically, this study presents a peculiar case of floodplain showing how agricultural expansion can diminish the role of a floodplain as a sediment sink through decreasing the trapping rate. National Institute of Education Earth Observatory of Singapore and Asian School of the Environment Nanyang Technological University Water Engineering and Management School of Engineering and Technology Asian Institute of Technology Disaster Prevention Research Institute Kyoto University Master Program in Water Technology Reuse and Management Vietnamese-German University Department of Environmental Engineering São Paulo State University Faculty of Hydrology and Water Resources Institute of Technology of Cambodia Institute of Earth Science Academia Sinica Department of Environmental Engineering São Paulo State University

This doctoral thesis examines independent variables as explanatory drivers influencing urban growth, axis of urban expansion and the impact of current and future land use and land cover (LULC) and climate change on the landscape of the Harare Metropolitan Province. Monitoring urban growth trends and LULC changes utilised multispectral remote sensing data, geographic information system technologies and binomial logistic regression. The LULC maps used in the study were generated by implementing machine learning support vector machines (SVMs), a supervised classification technique on Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager satellite images. The moderate resolution satellite images were enhanced with soil adjusted vegetation index (SAVI), enhanced built-up bareness index (EBBI), and modified normalized water difference index (MNWDI) spectral indices to improve feature delineation during data training and other classification procedures. The transformation of croplands and green spaces was revealed to occur at alarming rates predominantly in the south, south east, south west and north west parts of the Harare Metropolitan Province. The predominant variables significant for urban expansion were distance to trunk and secondary roads. In addition, steep slopes were determined as a topographic characteristic limiting rapid construction developments in the north and north-eastern parts of the province. Further, the eruption and sprouting of informal settlements due to political connotations and demand for shelter resulting from increasing urban migration overwhelmed the city and government plans to provide decent shelter. The study also provides insights on the declining spatial soil loss rates between 1984 and 2018 with localized high soil erosion risk within active build-up areas, croplands, areas along footpaths and paved road sides. The validation of the RUSLE model using field mapping and measurements of soil erosion phenomena in urban environment was successful. This provides confidence to apply the RUSLE model to predict future spatial soil loss and potential soil erosion risk in the Epworth district of the Harare Metropolitan Province. The application of Markov chain model coupled with cellular automata provided future LULC distribution patterns for 2034 and 2050 for Epworth district. This displayed accelerated LULC change through the conversion of croplands and green spaces to built-up area mainly for residential purposes. Further, similar trends of declining soil loss rates were predicted for future scenarios between 2034 and 2050; with high soil erosion risk predicted along drainage channels and downslope. Therefore, by virtue of rampant LULC changes in Epworth district, green spaces and croplands were modified to impervious surfaces due to the increasing population and predominant demand for shelter leading to setting up of informal settlements. This exacerbates concentrated runoff and overland flow, increasing soil erosion risk along drainage channels and sloping areas as a result of minimized infiltration capacity. In addition, trampling induced compaction on unpaved roads due to high traffic volumes and movements further contributes to accelerated overland flow. This facilitates the development of rills and ephemeral gullies on road sides and weak parts of the roads reducing mobility and access to properties. The encroachment of wetlands and river banks through the expansion of built-up areas and sand poaching activities does not only affect ecosystem functions but also impact negatively on livelihoods, nutrition and endangering lives due to the abandonment of disused pits. The study results show that spatiotemporal urban growth monitoring is fundamental in understanding urban growth patterns and revealing the more likely drivers influencing growth. Furthermore, mapping of soil erosion risk and estimating soil loss rates allow the application of the RUSLE method at a larger scale and to direct resources on areas potentially vulnerable to high soil erosion risk. The study results are highly valuable and highlight the need to promote reproducible documentation of data. Overall, this study provides insights that are imperative for authorities, land managers and policy makers to embrace for the advancement and attainment of sustainable smart cities as set by the UN agenda on Sustainable Development Goals. As such the findings contribute to enhance our understanding of the implications of LULC and climate changes on the environment and human wellbeing., Im Rahmen dieser Doktorarbeit werden unabhängige Variablen als erklärende Faktoren für das städtische Wachstum und die Achse der Stadterweiterung sowie die Auswirkungen der künftig zu erwartenden Landnutzung und -bedeckung ebenso wie des Klimawandels auf die Harare Metropolitan Province untersucht. Diese Untersuchungen basieren auf der Verwendung multispektraler Fernerkundungsdaten und dem Einsatz geographischer Informationssysteme und binomialer logistischer Regressionen. Die durchgeführten Analysen der Landnutzungs- und -bedeckungsveränderungen basiert auf einer überwachten Klassifizierung von Satellitenbildern des Landsat 5 Thematic Mapper und des Landsat 8 Operational Land Imager. Dazu wurden Methoden des maschinellen Lernens mit Hilfe von Support Vector Machines (SVMs) eingesetzt. Die Satellitenbilder mit mittlerer Auflösung wurden mit dem bodenangepassten Vegetationsindex (SAVI), dem verbesserten Index für die bebaute Fläche (EBBI) und dem modifizierten normalisierten Wasserdifferenzindex (MNWDI) transformiert, um die Klassifizierungsverfahren zu verbessern. Die Ergebnisse zeigen, dass die Umwandlung von Ackerland- und Grünlandflächen vor allem im Süden, Südosten, Südwesten und Nordwesten der Metropolregion Harare in Folge von Urbanisierungsprozessen stattfindet. Die in ihrem Einfluß auf die Stadterweiterung dominierenden Variablen sind die Entfernung zu Haupt- und Nebenstraßen. Steile Hänge schränken hingeben die bauliche städtische Entwicklung in den nördlichen und nordöstlichen Teilen der Metropolregion Harare ein. Die politisch bedingte Entstehung von informellen Siedlungen und der Bedarf an Behausungen infolge der zunehmenden Landflucht stellen die Pläne der Stadt und der Regierung zur Bereitstellung angemessener Unterkünfte vor große Herausforderungen. Die Studie zeigt außerdem, dass die Bodenverlustraten durch Bodenerosion zwischen 1984 und 2018 in der Tendenz abgenommen haben. Nichtsdestotrotz gibt es lokal ein hohes Bodenerosionsrisiko vor allem in Baugebieten, auf Ackerflächen und entlang von Fußwegen und befestigen Straßen. Die Modellierung des Bodenerosionsrisikos erfolgte unter Einsatz der Bodenabtragsgleichung RUSLE. Zur Validierung der Ergebnisse wurden Feldkartierungen und Messungen von Bodenerosionsphänomenen im städtischen Umfeld durchgeführt. Hier zeigt sich eine deutliche Übereinstimmung der Modellierungs- und Kartierungsergebnisse. Die Anwendung des RUSLE-Modells zur Vorhersage zu erwartender räumlicher Bodenverluste und des potenziellen Bodenerosionsrisikos im Epworth-Bezirk in der Harare Metropolitan Province ist damit zuverlässig möglich. Unter Anwendung von Markov-Ketten in Verbindung mit zellulären Automaten wurde das Muster der zukünftigen Verteilung von Landbedeckungs- und -nutzungklassen im Bezirk Epworth für die Jahre 2034 und 2050 simuliert. Es zeigt sich, dass der Wandel der Landbedeckung und -nutzung durch die Umwandlung von Ackerland und Grünflächen in bebautes Gebiet vornehmlich durch eine Zunahme der Wohnbebauung geprägt sein wird. Dies ist vornehmlich auf die wachsende Bevölkerung und den vorherrschenden Bedarf an Unterkünften zurückzuführen, die bereits zur Errichtung informeller Siedlungen geführt hat. Entsprechend dieser Landbedeckungs- und Landnutzungsszenarien wurden für die Jahre abnehmende Bodenverlustraten vorhergesagt, wobei auch weiterhin von einem hohen Bodenerosionsrisiko vor allem entlang von Entwässerungskanälen und am Hangfuß auszugehen ist. Darüber hinaus trägt die durch Trittschäden hervorgerufene Verdichtung auf unbefestigten Straßen als Folge des hohen Verkehrsaufkommens zu einer Zunahme des konzentrierten Oberflächenabfluss bei. Dies begünstigt die Entstehung von ephemeren Abflussrinnen entlang von Straßenrändern, was den Verkehr und den Zugang zu Grundstücken einschränkt. Die Ausdehnung bebauter Gebiete und illegaler Sandabbau beeinträchtigt darüber hinaus nicht nur Feuchtgebiete und Flussufer und damit deren Ökosystemfunktionen, sondern wirkt sich auch negativ auf die Lebensgrundlagen und die Ernährungssicherung aus; aufgegebene Sandgruben stellen zudem ein Sicherheitsrisiko dar. Die Ergebnisse der Studie verdeutlichen, dass die raum-zeitliche Beobachtung des städtischen Wachstums von grundlegender Bedeutung für ein Verständnis der auf dieses städtische Wachstum Einfluß nehmenden Faktoren ist und damit für eine zuverlässige Prognose der zukünftigen Entwicklung. Die verwendeten Modellierungen des Bodenerosionsrisikos und die Schätzung der Bodenverlustraten mit der können im größeren Maßstab auch in anderen Gebieten eingesetzt werden. Zudem verdeutlicht die Studie die Notwendigkeit, eine reproduzierbare Dokumentation der Daten zu durchzuführen. Insgesamt liefert die Studie damit Erkenntnisse, die von Behörden, Landverwaltern und politischen Entscheidungsträgern für die Förderung und Verwirklichung nachhaltiger Stadtentwicklung im Sinne der UN-Agenda für nachhaltige Entwicklung berücksichtigt werden sollten. Somit tragen die Ergebnisse dazu bei, das Verständnis für die Auswirkungen von Landbedeckungs- und Landnutzungswandel und Klimaveränderungen auf die Umwelt und das menschliche Wohlergehen zu verbessern.

Consistent and optimized territorial planning, imply the use of numerous variables aimed at improving life quality and reduction of environmental impacts. The resilience of the territory to climate change threats is strongly linked to its progressive transformation. This fact is extremely evident in coastal systems, which are intrinsically fragile systems due to their high environmental value and strong anthropogenic pressure. The existing tools and techniques provide to outline future transformation effects through the scenarios analysis. This work has the objective to evaluate the effects of land use changes in the territory of the Abruzzo coast. The conversion from natural soils to artificial uses has a significant impact on several ecosystem services. The regulation services considered in this work are flood regulation, carbon storage and sequestration, and habitat for biodiversity. The first is directly connected to soil sealing which determines a reduction of water infiltration with the consequent overloading of the existing sewerage systems. The quantitative evaluation is made using the concept of surface runoff coefficient. Instead, the estimation of the last two ecosystem services has been made using InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) models, specifically the Carbon Storage and Sequestration model and the Habitat Quality model. The results show that Land Use Changes (2012–2018) caused a potential increase of 10% in runoff and an annual Carbon Sequestration loss estimated at about €820,000.

Global urbanization has the most tremendous negative effects on the changing landscapes in many developing countries&rsquo, cities. It is necessary to develop appropriate monitoring techniques for tracking transport space evolution. The work explores the impacts of urban growth dynamics of transport space over the past decades as a basis for predicting future space demands in Kano, Nigeria. Three epochs of Landsat images from 1984, 2013 and 2019 were processed, classified and analyzed. Spatial classifications of land-use/land-cover (LULC) types in Kano include transport space, built-up areas, vegetation, farmland, bare land and water. The data analysis involves model calibration, validation and prediction using areas using the hybrid modeling techniques&mdash, cellular automata-Markov (CA-Markov) in IDIRISI SELVA 17.0 and remote-sensing ARC-GIS 10.7 softwares. The result finds significant expansion of transport and built-up areas while other LULC receded throughout the entire study period. Predictive modeling of transport infrastructure shows spatial expansion by 345 km2 (3.9%) and 410 km2 (11.7%) in 2030 and 2050 respectively. Kappa reliability indices of agreement (KIA) classified images and ground maps were 85%, 86% and 88%, respectively, for 1984, 2013 and 2019 time series. The calibration quality met the 80% minimum suggested in literature for the spatial-temporal track and prediction of urban growth phenomena.

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

Carbon sequestration in terrestrial ecosystems is critical for combating global climate change and achieving regional carbon neutrality, and LUCC is a vital factor influencing the carbon cycle process of terrestrial ecosystems and causing changes in carbon sources/sinks. This study analyzes the drivers of LUCC based on a review of the dynamics of LUCC in Changzhi from 2000 to 2020, analyzes the driving factors of LUCC using the Clue-S model and binary logistic regression analysis model, then simulates land-use patterns under different scenarios in 2030 by the CA-Markov model, and finally analyzes carbon stock changes and spatial distribution characteristics in different periods from the perspective of carbon source/sink interconversion with the help of InVEST model. The results show: (1) in the past two decades, more than 90% of the expansion of artificial surfaces in Changzhi comes from cultivated land. Ecological conservation policies are more decisive in influencing LUCC than natural, social, and transportation accessibility factors. (2) During the 20 years, the total carbon stock increased by 680,989.73 t, with the carbon emission control area accounting for 7.5%, mainly distributed near urban centers and coal mining areas. The carbon sink enhancement area accounts for 5.5% and is mainly concentrated near forest land and ecological and nature reserves. (3) The spatial location of cities influences the density of carbon stock in the adjacent range. Carbon stock density increases within the buffer zone with the distance from urban center, county center, expressways, national highway, settlements, rivers, provincial roads, reservoirs, railways, county highway, and village roads. The rate of carbon stock increase per 100 m is 0.12 t/ha, 0.25 t/ha, 0.17 t/ha, 0.36 t/ha, 0.71 t/ha, 0.33 t/ha, 0.38 t/ha, 0.57 t/ha, 0.23 t/ha, 0.46 t/ha, and 0.48 t/ha respectively. The higher the administrative center and road grades, the lower the carbon density will be instead. (4) In the 2030 CD scenario, compared with the ND scenario, the cultivated land and grassland are effectively protected and the cultivated land area is increased by 445.68 km2, while the expansion of artificial surface is suppressed and the area is reduced by 448.2 km2, which ultimately leads to a reduction in carbon loss of 392,011.85 t. Future ecological management should focus on protecting high-value carbon sink areas and carbon sink enhancement areas and the ecological management and restoration of low-value carbon sink areas and carbon emission control areas.

An analytical review of physical blue and green water scarcity in terms of agricultural use, and its amenability to economic interpretation, is presented, employing more than 600 references. The main definitions and classifications involved and information about reserves and resources are critically analyzed, blue and green water scarcity are examined along with their interchange, while their causal connection with climate in general is analyzed along with the particular instances of Europe, Africa, Asia and the WANA region. The role of teleconnections and evaporation/moisture import-export is examined as forms of action at a distance. The human intervention scarcity driver is examined extensively in terms of land use land cover change (LULCC), as well as population increase. The discussion deals with following critical problems: green and blue water availability, inadequate accessibility, blue water loss, unevenly distributed precipitation, climate uncertainty and country level over global level precedence. The conclusion singles out, among others, problems emerging from the inter-relationship of physical variables and the difficulty to translate them into economic instrumental variables, as well as the lack of imbedding uncertainty in the underlying physical theory due to the fact that country level measurements are not methodically assumed to be the basic building block of regional and global water scarcity.

This essay approaches land degradation by targeting its ultimate thermodynamic causes, rather than its immediate environmental consequences. The objective is to make some propositions that could help understand the essence of the process, and contribute to a theoretical framework to be developed. These propositions are: 1. Human populations are an ecosystem component, not an external driver. 2. Coupled Human and Natural Systems (CHANS) tend to increase their overall complexity over time. CHANS complexity cannot feasibly be managed. 3. CHANS are made up of two types of subsystems, a consuming Foreland (FL) consisting of the human population, and a producing Backland (BL) in its environment. 4. The FL maintains its order at the expense of simplifying the BL, which becomes an entropy sink. This is the essence of ecological degradation, which is inherent to CHANS persistence. 5. Land degradation is an ecological state, not a landscape type. Hence it should be assessed within a complete range of states of ecological maturity. 6. Land use creates degradation proportional to the simplification of the ecosystems involved. Such degradation can be defined as a decrease in exergy, and results in loss of management options. Three associated corollaries are: a) A more effective target may be to regulate rather than attempt to eliminate land degradation; b) Monitoring ecological degradation trajectories may be more effective than assessing land degradation states; c) Land degradation can be decreased by maximizing the potential for interconversion between land uses. This work was supported by the European Commission under the DeSurvey IP [FP6 Integrated Project contract no. 003950], the European Space Agency under the DesertWatch Extension project [DUE contract no. 18487/04/I-LG] and Tragsatec (Grupo Tragsa) [contract no. 25.604].

Afforestation is gaining popularity as a climate mitigation policy in many countries, including high latitude regions such as Norway. However, the impacts of afforestation on local‐to‐regional climate is poorly understood. This study uses the Weather Research and Forecasting model to investigate the biogeophysical impacts of different forestry scenarios on the local‐to‐regional climate of Norway. The forestry scenarios considered are the conversion of open spaces to either evergreen forest by active afforestation or to mixed forest by natural succession. Results show both forestry scenarios lead to additional warming of surface temperatures in winter and spring (between 1.0°C and 1.5°C) and cooling in summer (between −1.6°C and −1.3°C). A temperature decomposition analysis shows that the warming in winter and spring is driven by surface albedo changes while summer cooling is driven by changes in sensible heat fluxes for afforestation and surface albedo for natural succession. Maximum 2 m air temperature increases considerably in spring in both forestry scenarios (∼0.8°C to 1.0°C). Analysis of precipitation, multiple climate indices and extremes, reveal little or no response to the different forestry scenarios. The largest societally relevant response to the forestry scenarios is the partial mitigation of the reduction in snow days expected from global warming by 10–20 days. This suggests that implementing current afforestation policies for climate mitigation in Norway may adversely exacerbate some effects of global warming locally while mitigating others. As such, the impacts of afforestation on the local‐to‐regional climate at high latitudes are complex and cannot support or dismiss afforestation as a climate mitigation policy.

This research was conducted to review land use land cover change in the catchment area of Musi Hydropower Plant in Bengkulu Province. The data used in this research is land use land cover map year 2000 to 2018 from Ministry of Environment and Forestry of the Republic of Indonesia. The analyse was done by overlaying time series map of land use land cover map from 2000 to 2018 on the map of forest area. The result shows that primary dryland forest degradated significantly, around 568 ha less than 20 years. In the other side, settlements and built-up area significantly increase, 1.331 ha in 20 years. Meanwhile, the land use of agricultural dry land mixed with shrubs, in agregat decreased by 1.078 ha. The area of agricultural dry land mixed with shrubs was increase during period of 2000 to 2014, and then slightly decrease in the period of 2014 to 2018. Land use changes on the catchment area have negative impact on the quality of environmental services, such as erosion and sedimentation on the reservoir of Musi Hydropower Plant. Intervention needed to reduce the negative impact of the land use change on ecosystem services.

Janus is an open source Python package for agent-based modeling (ABM) of land use and land cover change (LULCC). Many ABMs of LULCC have been created across platforms, some of which are not ideal for large scale, high resolution scenarios. This model provides a simple object-oriented framework for creating ABMs specific to LULCC. The organizational philosophy of the modeling framework is to create software objects (agents) that are associated with specific and contextual attributes which are isolated from where those agents exist in the spatial setting of the model, and still provide clear linkages between the agent, their environment, and other agents in the simulation. In this way, the framework allows for assembly of LULCC ABMs with low (programmatic) overhead, making the models extensible and providing clear mechanisms for integrating them with process-oriented biophysical models. Provided with Janus is a suite of geospatial data preprocessing tools that can use arbitrary land cover products as an input. Crop choice decisions are based on potential crop prices, these can be created synthetically, or drawn from integrated human-Earth systems models such as the Global Change Assessment Model. Janus is publicly accessible through GitHub and provides an example dataset for testing.

The Lower Mekong Basin (LMB) is biologically diverse, economically important, and home to about 65 million people. The region has undergone extensive environmental changes since the 1990s due to such factors as agricultural expansion and intensification, deforestation, more river damming, increased urbanization, growing human populations, expansion of industrial forest plantations, plus frequent natural disasters from flooding and drought. The Mekong river is also heavily used for human transportation, fishing, drinking water, and irrigation. This paper discusses use of pre-existing LULC maps from 1997 and 2010 to derive a LMB regional LULC change map for 9 classes per date using GIS overlay techniques. The change map was derived to aid SWAT hydrologic modeling applications in the LMB, given the 2010 map is currently used in multiple LMB SWAT models, whereas the 1997 map was previously used. The 2010 LULC map was constructed from Landsat and MODIS satellite data, while the 1997 map was from before the MODIS era and therefore based on available Landsat data. The 1997-2010 LULC change map showed multiple trends. Permanent agriculture had expanded in certain sub-basins into previously forested areas. Some agricultural areas were converted to industrial forest plantations. Extensive forest changes also occurred in some locations, such as areas changed to shifting cultivation or permanent crops. Also, the 1997 map under classified some urban areas, whereas the 2010 LULC map showed improved identification of such areas. LULC map accuracy were assessed for 213 randomly sampled locations. The 1997 and 2010 LULC maps showed high overall agreements with reference data exceeding 87%. The LULC change map yielded a moderately high level of overall agreement (78%) that improved to ~83% once LULC classification scheme specificity was reduced (forests and agriculture were each mapped as singular classes). The change map regionally showed a 4% decrease in agriculture and a 4 % increase in deciduous and evergreen forests combined, though deforestation hot spot areas also were evident. The project yielded LULC map data sets that are now available for aiding additional studies that assess LMB LULC change and the impacts such change may pose to water, agriculture, forestry, and disaster management efforts. More work is needed to map, quantify and assess LULC change since 2010 and to further update the 2010 LULC map currently used in the LMB SWAT models.

Knowledge coproduction that draws on local and scientific knowledge presents opportunities for more holistic understanding of environmental change. We describe our use of a multiple-evidence based approach to investigate the causes and consequences of environmental change in a community-protected grassland and its surrounding landscape in the Ethiopian highlands. We explore the interaction of biophysical change (precipitation and vegetation) and social change (political and management institutions), and discuss potential impacts for ecosystem service provisioning. We quantified current distributions of locally defined land use/cover classes using a supervised classification, with an overall accuracy of 87.1%. Local community members then described and ranked the ecosystem services associated with each land class according to their perceived importance for society. Vegetation and precipitation changes were assessed using satellite time series beginning in the early 1980s, while local narratives describe changes back to the 1970s. The knowledge coproduction process brought together ethnographic and remote sensing approaches, revealing both complementary and contradictory findings across knowledge systems. Results with high agreement across knowledge systems clarify and reinforce understanding of certain threats and changes to the area, such as the rapidly declining native forests, the disappearing belg rainy season (p = 0.01), and the impact of insecure land tenure on natural resource extraction. Compelling areas of disagreement point to topics in need of further investigation, including increased attention to the spatial and temporal variability of change across a seemingly homogeneous cultural landscape, and the process of shrub encroachment into the protected grassland.

Lake Hawassa Watershed, in the Central Rift Valley, is one of the most environmentally vulnerable areas in Ethiopia. The rapidly increasing population and vegetation clearance in search of farming and grazing land, firewood, and construction materials have exerted pressure on the natural resources of the region. To understand the ongoing resource degradation and formulate mitigation strategies, accurate and timely information about land use land cover (LULC) changes and the driving forces is indispensable. Remote sensing and GIS are important tools for monitoring, mapping, and modelling of LULC changes at different spatial and temporal scales in order to assess the extent, direction and causes of the changes. The present research aimed at filling the biophysical data gap in the area underrepresented by existing literature and thereby contribute knowledge to support informed decision making in sustainable resource management. Specifically, the study intended to: (a) Classify multi-temporal image data to produce land cover (LC) maps and quantify changes that have occurred over the study period, (b) Classify image data sets in the urban environment and extract the magnitude of built-up areas in order to quantify the rate of urban growth, test the relationship between observed and expected growth, and examine the degree of urban sprawl, (c) Delineate forest cover using remotely sensed data for the base year 2011, estimate above ground biomass (AGB) and carbon stock using forest inventory data and allometric equations, and evaluate the diversity and dominance of species in the ecosystem, and (d) Quantify the spatial and temporal dimensions of LULC conversions from the classified Landsat images extending over the period of 38 years, conduct key informant interviews and identify the most prominent underlying driving forces (UDFs) of LULC changes, and analyze the identified driving forces with a particular focus on LULC conversion and deforestation. Nedbørsfeltet til Lake Hawassa i Central Rift Valley, er et av de mest sårbare områdene med hensyn til miljø i Etiopia. Den raske befolkningsveksten som medfører avskoging for å dekke behovet for jordbruks- og beiteområder, ved, kull og bygningsmaterialer, har lagt press på naturressursene i regionen. For å forstå den pågående forringelsen av naturressursene og videre utforme strategier som kan begrense denne utviklingen, er det avgjørende å ha tilgang til korrekt og oppdatert informasjon om endringene i arealbruk/arealdekke (landuse/landcover-LULC) samt de faktorene som ligger til grunn for disse. Fjernmåling og GIS er viktige verktøy for overvåking, kartlegging og modellering av LULC-endringer med ulik oppløsning i rom og tid for å fastslå omfanget, retningen og årsaken til slike endringer. Dette forskningsarbeidet har tatt sikte på å bøte på mangelen på biofysiske data slik den kommer til uttrykk gjennom det bortimot totale fravær av eksisterende litteratur relevant for det aktuelle området, for på denne måten å bidra med kunnskap til støtte for informasjonsbaserte beslutningsprosesser i en bærekraftig naturressursforvaltning. Mer spesifikt tok undersøkelsen sikte på å: (a) Fremstille arealdeknings(LC)-kart basert på klassifisering av multi-temporale bildedata, for på denne måten å kunne gi et kvantitativt uttrykk for de endringer som har skjedd i løpet av undersøkelsesperioden, (b) Klassifisere bildedatasett fra den urbane delen av området og bestemme omfanget av bebygde områder, for på denne måten å kunne kvantifisere graden av urban vekst, teste forholdet mellom observert og forventet vekst samt å undersøke graden av overdreven/ukontrollert byvekst (urban sprawl), c) Avgrense områdene dekket av skog ved bruk av fjernmålte data for referanseåret 2011, anslå biomasse over bakken (Above Ground Biomass - AGB) og karbonlager (carbon stock) på grunnlag av feltmålinger kombinert med allometriske likninger og i tillegg vurdere biologisk mangfold og angi dominerende arter i økosystemet, og (d) Ved hjelp av utvalgte klassifiserte Landsat satellittbilder tatt opp i løpet av et tidsrom på 38 år å gi en kvantitativ beskrivelse av de LULC endringer som har funnet sted, romlig så vel som over tid, gjennomføre intervjuer med nøkkelinformanter og finne de viktigste underliggende endringsmekanismene (underlying driving forces-UDFs) for LULC-endringer, samt å analysere de identifiserte endringsmekanismene med særlig vekt på LULC-endringer og avskoging. NORAD

Surface and groundwater are important resources for human life and health. Land use changes and mining activities, however, have the potential to compromise the safety of these resources. This study aims to investigate the land cover conditions before and during mining activities and assess the impact on forests, surface, and groundwater resources in the Asutifi North District, Ghana. Landsat data of 30 m resolution was used to assess the land cover change from 2000 to 2020. A cross-sectional analysis of data between April to June 2004 to 2019 was used to assess water quality. The overall accuracy of the land cover classification ranged between (91.33–99.41)% and (78.01–85.95)% respectively for ground-truth validation and validation using the MODIS annual 500 m land cover dataset. Forest cover decreased by 11.47% while agriculture doubled from 12.13% to 24.06% between 2000 and 2020. The introduction of mining is responsible for major land cover changes including the conversion of forest to agricultural land through shifting cultivation. For a general assessment of water quality, the percentage of pH, TB, TDS, NH3, Mg and SO4 measurements outside the EPA admissible limits for drinking water is 16.67%, 83.33%, 0.69%, 0%, 10.42%, and 16.67% respectively. Turbidity is the most impacted water quality parameter affected by land cover changes while NH3 is the least impacted parameter. The incidences of water quality outside EPA/WHO limits for drinking water at all monitoring points call for education and collective action to safeguard water sources from further deterioration. It is necessary mining companies adhere to environmental protection guidelines.

Purpose. The main aim of the study was to assess land use land cover change detection (LULCC) from 1990 to 2016 in case of Gibe Sheleko National Park (GSNP), Southwestern Ethiopia. Methodology / approach. Multi-temporal Landsat images and topographic map were acquired in 2016. Field observation using GPS was carried out to generate the ground truth points for image classification and accuracy assessment from December 2016 to June 2017. A total 200 GPS points were purposively collected. The data were analysis by using ERDAS IMGINE 2010 and ArcGIS 10.3.1 software. Supervised classification was carried out to identify the overall land use land cover class. Results. Forest land was rapidly declined with average of 478.5 ha/year for the last 27 years. This revealed that over 66.8% of forest was diminished from 1990 to 2016 due to anthropogenic factors in the study area. Bush & shrub land was upraised from 12600 ha (31.5 %) to 20600 ha (51.5 %) from 1990 to 2016. Grazing land and bare land was also showed an increment of 3500 ha and 2240 ha with average increment of 134.6 ha/year and 86.5 ha/year respectively from 1990 to 2016. This indicated as most forest land was changed in to bush & shrub land due to human induced factors. Hence, it brings negative effects on the wildlife conservation and socio-economic development. Originality / scientific novelty. This study is orginal research finding by employ above indicated methedology and stated the last 27 years land use land cover change of Gibe Sheleko National Park for fist time. It also discovered that the rate of land use land cover change in the study area for the past 27 years. Practical value / implications. The main results of the study of land cover change can be used to ensure planning to be sustainable and integrated management of the natural resources. Participatory management practice should be implemented in the study area to regenerate the changed land use type.

Land use land cover (LULC) change is one of the main drivers contributing to global climate change. It alters surface hydrology and energy balance between the land surface and atmosphere. However, its impacts on surface air temperature have not been well understood in a dynamic region of LULC changes like Southeast Asia (SEA). This study quantitatively examined the contribution of LULC changes to temperature trends in Myanmar and Thailand as the typical parts of SEA during 1990–2019 using the “observation minus reanalysis” (OMR) method. Overall, the average maximum, mean, and minimum temperatures obtained from OMR trends indicate significant warming trends of 0.17 °C/10a, 0.20 °C/10a, and 0.42 °C/10a, respectively. The rates of minimum temperature increase were larger than maximum and mean temperatures. The decreases of forest land and cropland, and the expansions of settlements land fractions were strongly correlated with the observed warming trends. It was found that the effects of forest land converted to settlement land on warming were higher than forest conversion to cropland. A comprehensive discussion on this study could provide scientific information for the future development of more sustainable land use planning to mitigate and adapt to climate change at the local and national levels.

Streamflow perturbation is highly prevalent in Kikuletwa catchment. However, little is known concerning land use/cover change (LULCC) with regard to streamflow perturbation in the catchment. This study aims to detect the historical and predict future LULCC and assess their impacts on streamflow amounts using the Soil and Water Assessment Tool (SWAT) model. Supervised classification of Landsat imagery data for 1985, 2000 and 2015 years was done in ERDAS 14 Imagine software. Future prediction of LULCC was done using Module for Land Use Change Evaluation (MOLUSCE) tool, a QGIS plug-in. An accuracy ranging from 79% to 82% was obtained for all steps. The results revealed that, from 1985 to 2000; 1985 to 2015; 1985 to 2030 and 1985 to 2050 the percentage of area change in cultivated land is +21.1%; +29.2%; +38.2% and +42.7%, respectively; forest is - 2.3%, -3.1%, -3.8% and -5.8%, respectively; and shrubland is -6.3%, -10%, -15.7% and - 16%, respectively. The performance of SWAT model during calibration were 0.74, 0.75, 0.51 and -0.5% for NSE, R2, RSR and PBIAS, respectively. The impacts of LULCC indicated that, between 1985 to 2000; 1985 to 2015; 1985 to 2030 and 1985 to 2050, the percentage increase in average simulated annual flow is 4.7%, 6.8%, 12.6% and 19.3%, respectively. Surface runoff increased from 25.2 mm (baseline) to 34.5 mm (36.9%); 36.2 mm (42.4%); 41.4 mm (64.3%) and 47.6 mm (88.9%), respectively. Base flow decreased marginally from 82.2 mm (baseline) to 79 mm (-3.8%); 77.8 mm (5.4%); 75.4 mm (-8.3%) and 73.9 mm (- 10.1%), respectively. Thus, apart from climate effects, streamflow perturbation in the catchment is also related to disturbances of catchment influences such as LULCC as revealed in this study. The study is useful for land planners and water resources managers and policy makers in managing resources sustainably.&nbsp

Study Region: Pra River Basin, Ghana. Study Focus: The study modelled the changes in water yield using regional, sub-regional and local climate conditions from modelling outputs at spatial resolutions of 44 km, 12 km and 0.002 km respectively to drive the Integrated Valuation of Ecosystem Services and Trade-offs model at three time periods of land use land cover (LULC). Changes in historical water yield (simulated for 1986, 2002 & 2018 LULC using the mean climatic parameters from 1981-2010) and future scenario (simulated for 2018 LULC using the mean climatic parameters from 2020-2049) for annual, seasonal and monthly periods were assessed. New Hydrological Insights for the Region: The results show that future annual water yield could change by -46%, -48%, +44% and -35% under the regional, sub-regional, local and ensemble mean of the climate scenarios respectively. Seasonal water yield from the ensemble mean of the future climate scenario was projected to decrease between 2-16 mm, with a mean decrease of 33.39% during the December–February season. There was no directional effect of spatial resolution on water yield. The future period could be impacted by both drought and flood. We recommend that re/afforestation should be encouraged to improve infiltration and reduce deforestation which was 2.27% per annum in the assessed period to prevent flood causing runoffs, while irrigation technology will help to improve resilience to drought. Keywords: Climate change, InVEST model, Land use land cover change, Pra River Basin, Regional climate models, SDSM-DC, water yield

Research Highlights: This paper provides an alternative approach to contextualize mangrove forest loss by integrating available environmental and socio-economic data sets and products. Background and Objectives: Mangrove forest ecosystems grow in brackish water especially in areas exposed to accumulation of organic matter and tides. This forest type is widely distributed in tropical and subtropical coastal areas. Recent studies have revealed that the mangrove forest ecosystem had significantly degraded due to Land Use and Cover Changes (LUCC) in the recent past. Therefore, contribution of mangrove deforestation drivers has to be assessed to ensure a comprehensive analysis for ecosystem conservation and restoration and facilitate decision making. Materials and Methods: Firstly, a correlation analysis was conducted between individual data products and mangrove deforestation. Each data product was associated with the Dominant Land Use of Deforested Mangrove Patches data for 2012. Next, calculations were performed for specific data combinations to estimate the contributions of anthropogenic factors to mangrove deforestation. Results: In general, our study revealed that 22.64% of the total deforested area was converted into agriculture, 5.85% was converted into aquaculture, 0.69% was converted into infrastructure, and 16.35% was not converted into any specific land use class but was still affected by other human activities. Conclusions: We discovered that the percentage of land affected by these anthropogenic factors varied between countries and regions. This research can facilitate trade-off analysis for natural resources and environmental sustainability policy studies. Diverse management strategies can be evaluated to assess the trade-offs between preserving mangrove forests for climate change mitigation and transforming them for economic purposes.

首都大学東京, 2019-09-30, 博士（観光科学）

Woody alien plant species have been deliberately introduced globally in many arid and semi-arid regions, as they can provide services and goods to the rural poor. However, some of these alien trees and shrubs have become invasive over time, with important impacts on biodiversity, ecosystem services, and human well-being. Prosopis was introduced in Baringo County, Kenya, in the 1980s, but since then, it has spread rapidly from the original plantations to new areas. To assess land-use and land-cover (LULC) changes and dynamics in Baringo, we used a combination of dry and wet season Landsat satellite data acquired over a seven-year time interval between 1988–2016, and performed a supervised Random Forest classification. For each time interval, we calculated the extent of Prosopis invasion, rates of spread, gains and losses of specific LULC classes, and the relative importance of Prosopis invasion on LULC changes. The overall accuracy and kappa coefficients of the LULC classifications ranged between 98.1–98.5% and 0.93–0.96, respectively. We found that Prosopis coverage increased from 882 ha in 1988 to 18,792 ha in 2016. The highest negative changes in LULC classes were found for grasslands (−6252 ha; −86%), irrigated cropland (−849 ha; −57%), Vachellia tortilis-dominated vegetation (−3602 ha; −42%), and rainfed cropland (−1432 ha; −37%). Prosopis invasion alone directly accounted for over 30% of these negative changes, suggesting that Prosopis invasion is a key driver of the observed LULC changes in Baringo County. Although the management of Prosopis by utilization has been promoted in Baringo for 10–15 years, the spread of Prosopis has not stopped or slowed down. This suggests that Prosopis management in Baringo and other invaded areas in East Africa needs to be based on a more integrated approach.

Woody alien plant species have been deliberately introduced globally in many arid and semi-arid regions, as they can provide services and goods to the rural poor. However, some of these alien trees and shrubs have become invasive over time, with important impacts on biodiversity, ecosystem services, and human well-being. Prosopis was introduced in Baringo County, Kenya, in the 1980s, but since then, it has spread rapidly from the original plantations to new areas. To assess land-use and land-cover (LULC) changes and dynamics in Baringo, we used a combination of dry and wet season Landsat satellite data acquired over a seven-year time interval between 1988−2016, and performed a supervised Random Forest classification. For each time interval, we calculated the extent of Prosopis invasion, rates of spread, gains and losses of specific LULC classes, and the relative importance of Prosopis invasion on LULC changes. The overall accuracy and kappa coefficients of the LULC classifications ranged between 98.1−98.5% and 0.93−0.96, respectively. We found that Prosopis coverage increased from 882 ha in 1988 to 18,792 ha in 2016. The highest negative changes in LULC classes were found for grasslands (−6252 ha; −86%), irrigated cropland (−849 ha; −57%), Vachellia tortilis-dominated vegetation (−3602 ha; −42%), and rainfed cropland (−1432 ha; −37%). Prosopis invasion alone directly accounted for over 30% of these negative changes, suggesting that Prosopis invasion is a key driver of the observed LULC changes in Baringo County. Although the management of Prosopis by utilization has been promoted in Baringo for 10−15 years, the spread of Prosopis has not stopped or slowed down. This suggests that Prosopis management in Baringo and other invaded areas in East Africa needs to be based on a more integrated approach.

Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes. In Ethiopia, Africa, the rapid variations of LULC observed in the last decades are mainly due to population pressure, resettlement programs, climate change, and other human- and nature-induced driving forces. Anthropogenic activities are the most significant factors adversely changing the natural status of the landscape and resources, which exerts unfavourable and adverse impacts on the environment and livelihood. The main goal of the present work is to review previous studies, discussing the spatiotemporal LULC changes in Ethiopian basins, to find out common points and gaps that exist in the current literature, to be eventually addressed in the future. A total of 25 articles, published from 2011 to 2020, were selected and reviewed, focusing on LULC classification using ArcGIS and ERDAS imagine software by unsupervised and maximum likelihood supervised classification methods. Key informant interview, focal group discussions, and collection of ground truth information using ground positioning systems for data validation were the major approaches applied in most of the studies. All the analysed research showed that, during the last decades, Ethiopian lands changed from natural to agricultural land use, waterbody, commercial farmland, and built-up/settlement. Some parts of forest land, grazing land, swamp/wetland, shrubland, rangeland, and bare/ rock out cropland cover class changed to other LULC class types, mainly as a consequence of the increasing anthropogenic pressure. In summary, these articles confirmed that LULC changes are a direct result of both natural and human influences, with anthropogenic pressure due to globalisation as the main driver. However, most of the studies provided details of LULC for the past decades within a specific spatial location, while they did not address the challenge of forecasting future LULC changes at the watershed scale, therefore reducing the opportunity to develop adequate basin-wide management strategies for the next years.

Artisanal and Small-Scale Mining (ASM) landscapes form integral part of the Land use land cover (LULC) in the developing worlds. However, the spatial, spectral, and temporal footprints of ASM present some challenges for using most of the freely available optical satellite sensors for change analysis. The challenge is even profound in tropical West African countries like Ghana where there is prolonged cloud cover. Whiles very few studies have used Sentinel-2 data to map change analysis in ASM landscape, none examined the contribution of individual S2 bands to the ASM classifications. Also, despite the capabilities of Machine Learning (ML) and Deep Learning (DL) models for LULC classifications, few studies have compared the performances of different classifiers in mapping ASM landscape. This study utilized Sentinel-2 data, four ML and DL models (Artificial Neural Network –ANN, Random Forest – RF, Support Vector Machines –SVM, a pixel-based Convolutional Neural Network-CNN) and image segmentation to examine the performance of S2 bands and ML and DL algorithms for change analysis in ASM landscape, with the Birim Basin in Ghana as a study area. The result of the change analysis was used to assess changes in LULC during the recent ban on the expansion of ASM in the country. It was found out that ANN is a better classifier of ASM achieving the highest overall accuracy (OA) of 99.80% on the segmented Sentinel-2 bands. The study also found out that the Band 5 Vegetation Red Edge (VRE) 1 contributed most to classifying ASM, with the segmented VRE 1 being superlative over the other predictors. In terms of expansion, ASM increased by 59.17 km2 within the period of the study (January 2017 to December 2018), suggesting that ASM still took place under the watch of the ban. The classification results showed that most of the peripheral of forest and farmland have been converted to ASM with little disturbance within the interior of the forest reserves. The study revealed that, the ban was yielding very little or no results due to a number of policy deficiencies including low staff strength, lack of logistics and low remuneration. Enforcement of legal instruments against ASM and farming activities within the forest reserves, improvement in the monitoring systems and intensification of public education on the value of forest and the need to protect it are some of the major recommendations that could control encroachment on the forest reserves.

© 2016, Springer-Verlag Berlin Heidelberg. The population of the Sahel region of West Africa has approximately doubled in the past 50 years, and could potentially double again by the middle of this century. This has led to the northward expansion of agricultural areas at the expense of natural savanna, leading to widespread land use -land cover change (LULCC). Because there is strong evidence of significant surface-atmosphere coupling in this region, one of the main goals of the West African Monsoon Modeling and Evaluation project phase II is to provide basic understanding of LULCC on the regional climate, and to evaluate the sensitivity of the seasonal variability of the West African Monsoon to LULCC. The prescribed LULCC is based on the changes from 1950 through 1990, representing a maximum feasible degradation scenario in the past half century. It is applied to 5 state of the art global climate models (GCMs) over a 6-year simulation period. Multiple GCMs are used because the magnitude of the impact of LULCC depends on model-dependent coupling strength between the surface and the overlying atmosphere, the magnitude of the surface biophysical changes, and how the key processes linking the surface with the atmosphere are parameterized within a particular model framework. Land cover maps and surface parameters may vary widely among models; therefore a special effort was made to impose consistent biogeophysical responses of surface parameters to LULCC using a simple experimental setup. The prescribed LULCC corresponds to degraded vegetation conditions, which mainly cause increases in the Bowen ratio and decreases in the surface net radiation, and result in a significant reduction in surface evaporation (upwards of 1 mm day−1 over a large part of the Sahel). This, in turn, mainly leads to less moisture convergence and precipitation over the LULCC zone. The overall impact is a rainfall reduction with every model, which ranges across models from 4 to 25 % averaged over the Sahel, and a southward shift of the rainfall peak in three of the five models which evokes a precipitation dipole pattern which is consistent with the observed pattern for dry climate anomalies over this region. The African Easterly Jet shifts equator-ward, although the strength of this change varies considerably among the models. In most of the models, the main factor causing diabatic cooling of the upper troposphere and enhanced subsidence over the region of LULCC is the reduction of convective heating rates linked to reduced latent heat flux and moisture flux convergence. In broad agreement with previous studies, the impact of degradation on the regional climate is found to vary among the different models, however, the signal is stronger and more consistent between the models here than in previous inter-comparison projects. This is likely related to our emphasis on prioritizing a consistent impact of LULCC on the surface biophysical properties.

Background A healthy wetland provides a range of goods and services contributing to human wellbeing. Inle Lake, the first Biosphere Reserve in Myanmar, has been supporting the local inhabitants with ecosystem services (ES) including habitat for a wide range of biodiversity. In the recent years, influenced by land use land cover change (LULCC), the lake has witnessed changes with altered flow of ES, affecting human well-being. Communities’ perceptions are often undermined, when it comes to research LULCC. We analyzed LULCC change data from 1989–2000 to 2000–2014 using Landsat imageries. This was then linked to ES considering dependency through qualitative data collated from participatory rural appraisal tools and structured questionnaires focusing on people’s perception to understand the LULCC dynamics and its implication. Results During 25 years (1989–2014), there has been a sharp reduction of 164 km2 perennial wetland area in the Inle Lake, which is 4.2-fold higher in 2014 to that of 1989. Similarly, forest area has been declined by 92 km2 (8.56%) in last 25 years. Contrary to this, cropland area showed an increment of 60.67% in 2000 and 64.53% in the year 2014 alone giving a total increase by 268 km2 over the last 25 years and an expansion of 40 km2 seasonal freshwater area were observed showing periodic increment over the time. Communities from the three study areas, namely, Kyaung Taung, Zay Gon and Kyar Taw are found to have high dependence in their surrounding ecosystems. These villages utilizes 17 ES from forest ecosystem, 13 from agro-ecosystem, 10 from seasonal and 4 from perennial water body for their livelihood respectively. Around 93% of the respondents opined that forest ecosystem has decreased over the last 10 years. Around 40% of the respondents reflected an increase in area used for cropland; 43% conversely perceived a declination. About 63% of the respondents perceived such changes have brought huge reduction in availability of freshwater ES. A significant number of respondents (92%) perceived an enormous reduction in seasonal water body during the dry season. Conclusion Observed decreasing trends in forest and perennial wetland areas were consistent with people’s perceived changes. Communities associate loss of forest and wetland area with reduced availability of ES as well as degraded health of the lake.

Background The spatiotemporal analysis of urban land use/land cover change (LULCC) helps to understand the dynamics of the changing environment of green infrastructure (GI) on the basis of sustainable city development. There are important links between spatiotemporal land use/land cover and GI change in urban areas. Therefore, the main objective of this study was to examine the spatiotemporal trends of urban land use/land cover and GI changes in Bahir Dar and Hawassa cities for the last four decades (1973–2015). Three different sets of Landsat satellite data were procured from EMA for Bahir Dar and Hawassa from 1973, 2000 and 2015 using Landsat 4 MSS, 7 TM and 8 OLI respectively. Based on this, using ERDAS Imagine (ver. 9.2) and Arc GIS (Ver.10.3) five LULCC classes were identified for analysis purpose. Result The results show that vegetation decreased by 30 and 14% in Bahir Dar and Hawassa respectively for the period 1973–2015, while built-up areas expanded by 10 and 24% respectively in the two cities. These land use changes have significant impacts on spatiotemporal trends of GI in urban areas. GI has increased in Bahir Dar and Hawassa in association with built-up area expansion and deliberate activity of city administrations with effective implementation of spatial plans of corresponding cities. Conclusions There is a growing concern about GI in cities. Policy makers and stakeholders should also decide on how to use the land at present and in the future. LULCC policymaking processes should aim to balance GI and other types of land use/land cover for sustainable urban development. Urban LULCC has important effects on the urban GI system.

International audience; Monitoring and understanding the changes in mangrove ecosystems and their surroundings are required to determine how mangrove ecosystems are constantly changing while influenced by anthropogenic, and natural drivers. Consistency in high spatial resolution (30 m) satellite and high performance computing facilities are limiting factors to the process, with storage and analysis requirements. With this, we present the Google Earth Engine (GEE) based approach for long term mapping of mangrove forests and their surroundings. In this study, we used a GEE based approach: 1) to create atmospheric contamination free data from 1987-2017 from different Landsat satellite imagery; and 2) evaluating the random forest classifier and post classification change detection method. The obtained overall accuracy for the years 1987 and 2017 was determined to be 0.87 and 0.96, followed by a Kappa coefficient 0.80 and 0.94. The change detection results revealed a significant decrease in the agricultural area, while there was an increase in mangrove forest, shrimp/fish farm, and bareland area. The results suggest that interconversion of land use and land cover is affecting the landscape dynamics within the study area.

Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management. First, the authors would like to thank the European Commission and the Erasmus Mundus Consortium for providing the master scholarship in Geospatial Technologies. We acknowledge the USGS-NASA due to their freely accessible Landsat data. Thanks are also due to the Laboratory for Geographic Information Analysis (Department of Geography, Hanoi National University of Education) for providing valuable tools and software. This work has also been partially supported by the Spanish Ministry of Economy under project ESP2013-48458-C4-3- P.

Land use land cover change have an impact on hydrology of the watershed on the Dedissa sun basin. The study mainly focused on estimating land use change and stream flow under different land use land cover changes of the sub basin. L and use land cove map s of 1986 and 2010 were developed using satellite image through maximum likelihood algorithm of supervised classification using ERDA S Imagine 2014. A physical - based,semi - distributed hydrological model,SWAT was used to simulate LULC effects on the hydrological response of Didessa sub - basin.During the study period the land use land cover has changed due to population growth . The cultivated land increase d by 12% and while forestland decreased by 3.61%. The simulated Stream flow results were utilized to analyze seasonal variability stream flow due to land use and land cover changes https://www.ijiert.org/paper-details?paper_id=140942

This study examines the spatial and temporal patterns of the surface urban heat island (SUHI) intensity in the Phoenix metropolitan area and the relationship with land use land cover (LULC) change between 2000 and 2014. The objective is to identify specific regions in Phoenix that have been increasingly heated and cooled to further understand how LULC change influences the SUHI intensity. The data employed include MODerate-resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) 8-day composite June imagery, and classified LULC maps generated using 2000 and 2014 Landsat imagery. Results show that the regions that experienced the most significant LST changes during the study period are primarily on the outskirts of the Phoenix metropolitan area for both daytime and nighttime. The conversion to urban, residential, and impervious surfaces from all other LULC types has been identified as the primary cause of the UHI effect in Phoenix. Vegetation cover has been shown to significantly lower LST for both daytime and nighttime due to its strong cooling effect by producing more latent heat flux and less sensible heat flux. We suggest that urban planners, decision-makers, and city managers formulate new policies and regulations that encourage residential, commercial, and industrial developers to include more vegetation when planning new construction.

Appropriate location and operation of the developmental activities across different policy zones of National capital Region of India (NCR), to facilitate mutually productive “Centre - Periphery” relationship, requires detailed spatial-temporal mapping and long term change detection analysis of the regional resources of the study area. Scanning of literature revealed that this is acutely lacking for the study area. Hence, the present investigation was primarily aimed at quantifying the spatial-temporal pattern of the Land Use/ Land Cover Change (LULCC) during last two decades (i.e., 1989 to 2006) in the NCR and identifying the major bio-physical factors governing LULCC through modern geo-spatial techniques. Geo-spatial analysis of the above data showed that the study area experienced a steep (67.4%) increase in its croplands during 1989 to 1998 but relatively a small (5.7%) increase during 1998 to 2006 period. This was also associated with a similar steep increase in its built-up areas, due an increase in its urban population, during the same period. The change detection analysis further showed that 1989-1998, associated with change in croplands, change in built-up, ridge and forest lands, change in water-bodies, water levels and rainfall, change in single/ double cropped areas, change in degraded croplands and change in cropping pattern. With comparison of above results and collected socio-economic data in this region, the impact of changing land use & bio-physical/ economic factors on agricultural profitability were analyzed. The result of this study could thus lead to a detailed and lucid spatial-temporal (quantitative) assessment of the major bio-physical factors governing agricultural business – profitability and the overall food security of the National Capital Region. It is expected that the study would go a long way in facilitating better policy making and developing valid change detection methodologies for the National Capital Region and other similar regions of the country.

Surface mining and reclamation is the dominant driver of land cover land use change (LCLUC) in the Central Appalachian Mountain region of the Eastern U.S. Accurate quantification of the extent of mining activities is important for assessing how this LCLUC affects ecosystem services such as aesthetics, biodiversity, and mitigation of flooding. We used Landsat imagery from 1976, 1987, 1999 and 2006 to map the extent of surface mines and mine reclamation for eight large watersheds in the Central Appalachian region of West Virginia, Maryland and Pennsylvania. We employed standard image processing techniques in conjunction with a temporal decision tree and GIS maps of mine permits and wetlands to map active and reclaimed mines and track changes through time. For the entire study area, active surface mine extent was highest in 1976, prior to implementation of the Surface Mine Control and Reclamation Act in 1977, with 1.76% of the study area in active mines, declining to 0.44% in 2006. The most extensively mined watershed, Georges Creek in Maryland, was 5.45% active mines in 1976, declining to 1.83% in 2006. For the entire study area, the area of reclaimed mines increased from 1.35% to 4.99% from 1976 to 2006, and from 4.71% to 15.42% in Georges Creek. Land cover conversion to mines and then reclaimed mines after 1976 was almost exclusively from forest. Accuracy levels for mined and reclaimed cover was above 85% for all time periods, and was generally above 80% for mapping active and reclaimed mines separately, especially for the later time periods in which good accuracy assessment data were available. Among other implications, the mapped patterns of LCLUC are likely to significantly affect watershed hydrology, as mined and reclaimed areas have lower infiltration capacity and thus more rapid runoff than unmined forest watersheds, leading to greater potential for extreme flooding during heavy rainfall events.

The objectives of this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue's Land Transformation Model (LTM), has been used to better understand these very important issues; (2) summarize the current state-of-the-art in LUCC modeling in an attempt to provide a context for the advances in LUCC modeling presented here; (3) use a variety of statistical, data mining and machine learning algorithms to model single LUCC transitions in diverse regions of the world (e.g. United States and Africa) in order to determine which tools are most effective in modeling common LUCC patterns that are nonlinear; (4) develop new techniques for modeling multiple class (MC) transitions at the same time using existing LUCC models as these models are rare and in great demand; (5) reconfigure the existing LTM for urban growth boundary (UGB) simulation because UGB modeling has been ignored by the LUCC modeling community, and (6) compare two rule based models for urban growth boundary simulation for use in UGB land use planning. The review of LTM applications during the last decade indicates that a model like the LTM has addressed a majority of land change science issues although it has not explicitly been used to study terrestrial biodiversity issues. The review of the existing LUCC models indicates that there is no unique typology to differentiate between LUCC model structures and no models exist for UGB. Simulations designed to compare multiple models show that ANN-based LTM results are similar to Multivariate Adaptive Regression Spline (MARS)-based models and both ANN and MARS-based models outperform Classification and Regression Tree (CART)-based models for modeling single LULC transition; however, for modeling MC, an ANN-based LTM-MC is similar in goodness of fit to CART and both models outperform MARS in different regions of the world. In simulations across three regions (two in United States and one in Africa), the LTM had better goodness of fit measures while the outcome of CART and MARS were more interpretable and understandable than the ANN-based LTM. Modeling MC LUCC require the examination of several class separation rules and is thus more complicated than single LULC transition modeling; more research is clearly needed in this area. One of the greatest challenges identified with MC modeling is evaluating error distributions and map accuracies for multiple classes. A modified ANN-based LTM and a simple rule based UGBM outperformed a null model in all cardinal directions. For UGBM model to be useful for planning, other factors need to be considered including a separate routine that would determine urban quantity over time.

Changes in land use and land cover are associated with many environmental issues observed on the earth’s surface. In the last decades, these changes were unprece-dented, mainly in tropical forest areas. The Brazilian Amazon, the world’s largest tropical forest, lost around 200.000 km² of primary forest in the last ten years (INPE, 2005). Considering this, and the consequences caused by this deforestation, it is important to know and define correctly the responsible agents, aiming at better pub-lic policies that can help preserve the forest. Searching for indicators that could help to identify the deforestation agents, some studies, such as Mertens and Lambin (1997), suggest that every deforestation process shapes the forest land in a specific way, producing a spatial pattern that can be interpreted as indicative of the agents with specific economic activities. Based on this hypothesis, the objective of this study was to contribute to a better understanding of land change processes in the Amazon forest, investigating the linkages between spatial patterns of deforestation, as visualized in satellite images, and different agents and their specific economic activities. To reach this objective, our methodological approach was based on socio-economic data acquired at a household level combined with data from satellite im-ages. First, different spatial patterns of deforestation were identified on the satellite images, based on the typologies proposed by Husson et al. (1995). Then, some of the identified spatial patterns were isolated and analyzed for specific aspects, such as, the deforestation rate calculated through satellite images. socio-economic character-istics based on household survey data and evolution of land use and land cover based on thematic maps derived from satellite images. In addition, cluster analysis was applied using the socio-economic data (household survey) and land use and land cover data (satellite images) in a search for homogeneous groups related to the spa-tial pattern. In the end, an Analysis of Variance (ANOVA) was applied to confirm the differences between spatial patterns. The results suggested that the different spatial patterns of deforestation found in the study area can be related to specific economic activities. Nevertheless, the re-sults have indicated that the spatial configuration is not a consequence of its main economic activity. They suggest that the spatial configuration is linked to the settle-ment project, and the main economic activity in the spatial patterns is a consequence of a set of factors such as: size of property, location and disposition of the property, presence or absence of infrastructure (road, market, transportation, economic and technical). (GEOG 3) -- UCL, 2008