Search

Changes in hydrological processes in watersheds are triggered by various factors, including land use land cover changes (LULCC) emerging from human activities. Hence, it is crucial to elucidate the interaction among hydrological processes to improve sustainable water management plans. The current study explored the effects of LULCC on hydrological processes in the Gala Lake catchment over a 30‐year temporal period. In this context, to evaluate LULCC, land cover maps were obtained using the supervised classification method with Landsat images (5 TM, 7 ETM+, 8 OLI) of 1993, 2008, and 2023. Hydrological processes were assessed using the Soil and Water Assessment Tool (SWAT), a commonly applied eco‐hydrological model. The model was utilized to evaluate the potential effect of LULCC on processes like surface runoff, infiltration, evapotranspiration, and erosion. Between 1993 and 2023, significant LULCC have been observed in the study area. There has been a decrease of 4.3%, 1%, 1.6%, and 5.3% in agricultural lands, forested lands, inland marshes, and pasture lands, respectively, while artificial surfaces, rice fields, and water bodies have seen an increase of 7%, 3.4%, and 1.9%, respectively. The potential effects of these changes were observed as a decrease in the runoff, a decrease in permeability, and an increase in processes such as evapotranspiration and erosion throughout the basin and sub‐basin. In general, LULCC significantly affect the hydrological status of the catchment. Therefore, establishing different conservation and utilization strategies that consider land use dynamics to maintain the resilience of ecosystems in the basins is vital in the sustainable management of water resources. [ABSTRACT FROM AUTHOR]

The Western Himalayan Region (WHR) is under constant threat from Land Use and Land Cover Change (LULCC) brought on by various socioeconomic activities such as urbanization, agricultural expansion, and population growth. Detailed research into the scope of these changes is necessary to comprehend the challenges they represent. This study aimed at (1) examining and quantifying spatiotemporal patterns of LULCC from 1975 to 2015, (2) mapping the hotspots of forest loss, and (3) modelling future LULCC for the year 2055 using medium spatial resolution multispectral satellite imagery (MSS, TM, LISS-I, LISS-III, AWiFS), field data, visual interpretation and logistic regression model in the WHR. Logistic regression integrated various drivers of LULCC, including climatic, topographic, and socio-economic factors and past LULCC trends to forecast potential LULC in the WHR by 2055. The results highlight an outrageous 184% increase in regional urbanization. Expansion of urban and cropland (12%) led to deforestation which reduced the area of natural habitats, specifically forests (−11%), water bodies (−8%) and scrubland (−6%). A significant rise in barren land by 30% was noted, while there was a decrease of 20% in glacier/snow melt. The future projection for 2055 anticipates continuing current trends, emphasizing an intensified urban expansion of 63% and an approximate 9% reduction in overall forest coverage. The accuracy of the predicted 2015 LULC map was assessed using ROC/AUC (Receiver Operating Characteristic/Area under Curve) which was found to be 0.79. [ABSTRACT FROM AUTHOR]

This study investigates the potential anthropogenic land use activities in the 114,000-km2 Chindwin River Watershed (CRW) in northwestern Myanmar, a biodiversity hotspot. This research evaluates current and future land use scenarios, particularly focusing on areas that provide ecosystem services for local communities and those essential for biodiversity conservation. Remote sensing and geographical information systems were employed to evaluate land use changes in the CRW. We used a supervised classification approach with a random tree to generate land use and land cover (LULC) classifications. We calculated the percentage of change in LULC from 2010 to 2020 and projected future LULC change scenarios for approximately 2030 and 2050. The accuracy of the LULC maps was validated using Cohen's Kappa statistics. The multilayer perceptron artificial neural network (MLP-ANN) algorithm was utilized to predict future LULC. Our study found that human settlements, wetlands, and bare land areas have increased while forest land has declined. The area covered by human settlements (0.36% of the total in 2000) is projected to increase from 264 km2 in 2000 to 424 km2 by 2050. The study also revealed that forest land has connections to other land categories, indicating a transformation of forest land into other types. The predicted future land use until 2050 reflects the potential impacts of urbanization, population growth, and infrastructure development in the CRW. [ABSTRACT FROM AUTHOR]

Land use and land cover changes (LULCCs) are vital indicators for assessing the dynamic relationship between humans and nature, particularly in diverse and evolving landscapes. This study employs remote sensing (RS) data and machine learning algorithms (MLAs) to investigate LULCC dynamics within the Indus River Delta region of Sindh, Pakistan. The focus is on tracking the trajectories of land use changes within mangrove forests and associated ecosystem services over twenty years. Our findings reveal a modest improvement in mangrove forest cover in specific areas, with an increase from 0.28% to 0.4%, alongside a slight expansion of wetland areas from 2.95% to 3.19%. However, significant increases in cropland, increasing from 22.76% to 28.14%, and built-up areas, increasing from 0.71% to 1.66%, pose risks such as altered sedimentation and runoff patterns as well as habitat degradation. Additionally, decreases in barren land from 57.10% to 52.7% and a reduction in rangeland from 16.16% to 13.92% indicate intensified land use conversion and logging activities. This study highlights the vulnerability of mangrove ecosystems in the Indus Delta to agricultural expansion, urbanization, resource exploitation, and land mismanagement. Recommendations include harmonizing developmental ambitions with ecological conservation, prioritizing integrated coastal area management, reinforcing mangrove protection measures, and implementing sustainable land use planning practices. These actions are essential for ensuring the long-term sustainability of the region's ecosystems and human communities. [ABSTRACT FROM AUTHOR]

Land use and land cover changes significantly impact carbon storage capacity, potentially causing long-term climate change, as examined in the Upper Awash Basin over three decades. This study aimed to examine the spatial and temporal dynamics of carbon stocks in the Upper Awash Basin over three decades due to land use and land cover changes. Remote sensing, ArcGIS, and the InVEST model were used to map changes in land use and land cover, as well as changes in carbon storage. The model and software have proven as accurate and useful tools for mapping changes in land use, cover, and carbon storage, allowing researchers to assess environmental impacts, plan conservation strategies, and effectively monitor ecosystems. Between 1993 and 2023, forests, shrublands, and wetlands decreased by 27.7%, 41.7%, and 60.7%, respectively, while cropland and built-up areas increased by 9.7% and 154.7%, respectively. As a result, the overall carbon stock decreased by 15%, from 17,342,625 tons to 14,810,521 tons of carbon. Agriculture expansion, overexploitation of forests for wood and charcoal production, settlement, population growth, and urban development are the primary drivers of carbon loss. Despite the upper Awash River Basin’s importance for carbon storage and sequestration, changes in land use and cover increased carbon emissions, contributing to climate change. Thus, this study highlights the link between land use land cover change and shifts in carbon stocks, emphasizing the importance of sustainable land management practices for maintaining or increasing carbon storage capacity, mitigating the effects of climate change, and improving overall ecosystem function.

This study was conducted to investigate the effect of farming and pasture area extensions on land use and land cover in the North Eastern Corridor of Ghana. Landsat 5 TM+ image period of 2000 and Landsat 8 TOA satellite for the periods 2013 and 2022 were used. All images were captured at approximately the same period to ensure the selected images had the same reflectance values. A supervised machine learning technique using the algorithm of the random forest classifier was employed for the preparation of the classification of thematic maps. The Markov chain model was used to examine the dynamics of land use and land cover (LULC) changes in the study area. Visual appraisal of the images indicated some level of notable changes across the various classes from 2000 to 2022. The trend of the various changes in percentage terms also supports this observation. The results reveal that there was an improvement in the vegetation cover from 2000 to 2013 as reflected in the maximum and median NDVI values of the classified images within the period. However, the results show a considerable decline in vegetation health from 2013 to 22. Based on these results, we recommend that a more in-depth analysis to identify other possible anthropogenic activities and factors, that may serve as significant underlying causes of these vegetation cover changes in the region. The Ministry of Food and Agriculture (MoFA) should train farmers to incorporate tree planting into their farming whilst avoiding deforestation and bush burning within the area.

Integrated watershed management plays a vital role in promoting sustainable water resource management and addressing environmental challenges. This study aims to analyze and assess the effectiveness of existing IWM practices and develop new strategies to improve watershed management. The data collection process encompassed comprehensive field observations, surveys, and consultations with the stakeholders. According to a hydrometer test, loam soil was the average dominant soil type in Elgo and Kola shell kebele. The assessment of existing soil water conservation initiatives adhered to the rigorous standards set by the Ministry of Agriculture. From 2016 to 2022, Elgo Kebele saw significant land use changes: agriculture expanded by 11.24 %, bare land by 2.05 %, water bodies by 1.79 %, and settlements by 0.54 %, while forests declined by 15.34 %. In Kola Shele, agriculture, water bodies, and settlements slightly increased by 0.5 %, 1.03 %, and 0.033 %, respectively, with decreases in bare land (1.82 %) and forest (0.05 %). Only 25 % of sampled plots met the criteria for effective soil water conservation systems, indicating challenges in current practices. For cultivated land with less than a 15 % slope and vertisol, recommended conservation practices include broad bed and furrow, conservation tillage, grass strips, grassland improvement, and mulching. For slopes greater than 50 %, hillside terracing, graded bunds, and trenches are advised. Additional measures, such as water harvesting, grass waterways, revegetation, and actions against illegal farming, were proposed. In summary, this study highlights the urgent need for improved IWM practices, and used to enhance watershed management, address environmental and socio-economic issues, and promote sustainable land use in the study.

This study examines Islamabad's landscape changes over four decades, attributing land degradation to shifts in land use and cover. Using Landsat imagery from 1980 to 2023, it analyzes urban growth in five categories. By employing the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI), it notes built-up areas expanding to 61% by 2023, agricultural land contraction, and fluctuating forest cover. Water bodies and bare land decrease significantly. With high accuracy values, NDVI fluctuates from +0.4523 in 1980 to +0.1596 in 2010, rebounding to +0.4422. Fluctuations in barren soil, vegetation, and built-up areas potentially contribute to temperature and rainfall changes. The study explores LULC and land surface temperature correlation. Surveyed respondents (755) express concerns about environmental changes, anticipating reduced rainfall and increased drought. Valuable for sustainable development goals, the study informs policy formulation for effective urban planning and land use control. HIGHLIGHTS This study unveils Islamabad's four-decade urban expansion and its transformative impact on land use.; This study explores how this growth has led to significant environmental changes, affecting land surface temperature and water resources.; This study highlights the city's growing climate awareness, emphasizing the need for sustainable urban planning.;

In landscape ecology, it has become increasingly essential to understand the consequences of past, current, and future human land use patterns for biodiversity and ecosystem function. The most significant factor affecting biodiversity loss is land-use and land-cover change (LULCC). We examine here the impact of long-term changes in LULCC from 2000–2020 on the biodiversity of Marghazar valley in Swat District. Information was also gathered on the perceptions of the surrounding communities based on the flow of ecosystem services (ES), historical changes, and the causes of those changes. Satellite imagery data were used to map LULCC, identify possible causes, and assess the impact of LULCC on the population of partridges. In the last 20 years, forest area has reduced by 23 km2 (33%) and the seasonal water body has declined by 1.015 km2 (2.15%). There was a 38.5 km2 decrease in agricultural land. In contrast, the built-up area increased by 384%, resulting in a total growth of 26.3 km2 and an expansion of 41.1 km2 grassland. Deforestation, agricultural expansions, urbanization, economic considerations and changes in land tenure policy were identified to be the main drivers of LULCC. The primary impact of LULCC on partridges in the studied area are land degradation, population declines, habitat disruption, displacement of partridges by livestock and increasing human-wildlife conflicts. Despite ongoing human pressure, the Marghazar valley still provides extensive habitat for wildlife. Interventions may be needed to maintain biodiversity and ensure long-term ecological services in the area. [ABSTRACT FROM AUTHOR]

The increased rate of urbanization has led to the transformation of landscapes at a higher rate, making the accurate assessment of land use and land cover changes (LULCC) imperative for sustainable urban planning and environmental management. This study presents the geospatial assessment of LULCC in the FCT (Federal Capital Territory) of Nigeria over a 35-year period, selecting the following years: 1987, 2002, 2011, and 2022, based on low cloud cover using remote sensing imagery and GIS techniques. By incorporating integrated cellular automata (CA)-Markov module from IDRISI-TerrSet software, the year 2050 was predicted. The overall accuracy for the four years (1987, 2002, 2011, and 2022) was 89.76%, 88.93%, 87.97%, and 86.54%, respectively. The Kappa coefficients were 0.88, 0.85, 0.86, and 0.83, respectively, which is considered acceptable. From 1987–2022, built-up land gained 881.74 km² in area, barren land gained 73.93 km² in area, forest lost 1,761.85 km² in area, wetland lost 97.44 km² in area, water body gained 1.75 km², shrub land lost 905.77 km², and grassland gained 1,806.47 km². The results of the predicted year (2050) showed that from 2022–2050, built-up land will gain 182.93 km² in area, barren land will gain 119.20 km² in area, forest will lose 39.78 km² in area, wetland will lose 99.94 km² in area, water bodies will gain 1.75 km², shrub land will lose 499.51 km², and grassland will gain 237.91 km². Results from the study will provide insight for urban planners, policymakers, and environmentalists in making decisions geared towards sustainable development and resilient urban growth in the FCT. [ABSTRACT FROM AUTHOR]

The increasing global population and in-country migration have a significant impact on global land use land cover (LULC) change, which reduces green spaces and increases built-up areas altering the near-surface radiation and energy budgets, as well as the hydrological cycle over an urban area. The LULC change can lead to a combination of hazards such as increasing urban temperatures and intensified rainfall, ultimately resulting in increased flooding. This present study aims to discuss the changing pattern in urban temperature, daily rainfall, and flooding in Jakarta. The daily urban temperature and daily rainfall were based on a 30-year dataset from three meteorological stations of Jakarta in the period between 1987 and 2013. The changing trend was analyzed by using the Mann–Kendall and the Pettitt's tests. The relation between daily rainfall and flooding was analyzed using a 30-year flooding dataset collected from several sources including the international disaster database, research, and newspaper. The results show that there was an increasing trend in the daily temperature and the daily rainfall in Jakarta. The annual maximum daily temperature showed that an increasing trend started in 2001 at the KMY station, and in 1996 at the SHIA station. In general, the highest annual maximum daily temperature was about 37 °C, while the lowest was about 33 °C. Moreover, the maximum daily rainfall started increasing from 2001. An increase in the maximum daily rainfall was observed mainly in January and February, which coincided with the flood events recorded in these months in Jakarta. This indicates that Jakarta is not only vulnerable to high urban temperature but also to flooding. While these two hazards occur in distinct timeframes, there is potential for their convergence in the same geographical area. This study provides new and essential insights to enhance urban resilience and climate adaptation, advocating a holistic approach required to tackle these combined hazards. [ABSTRACT FROM AUTHOR]

Background Studies which have been conducted so far have focused on the processes of land use/cover changes in different areas at regional and global scale. Little is known about factors that influence land use/ cover dynamics at finer scales such as Melela ward in Mvomero district, Morogoro, Tanzania. Goals and Objectives The overall objective of the study therefore was to evaluate the land use land cover dynamics and their impacts on pastoralism in Melela. Specifically, the study intended to examine land use/cover dynamics from 1991 to 2016, to identify socio-economic factors that influence land use/cover dynamics and to determine the effects of land use/ cover dynamics on pastoral communities and agricultural production. Methodology Remote sensed satellite data were used for change detection analysis to assess the spatial and temporal land use/ cover change for the study area. Satellite images were processed and analysed to detect changes in land use/ cover at the site by using change detection analysis technique to evaluate transition in land use/ cover and to estimate changes in the area. A geographical positioning system (GPS) receiver was used for georeferencing the points for supervised classification and accuracy assessment. Change detection analysis and post classification comparison was used for the analysis of data. The analyses involved the application of an algorithm used to detect changes in spectral signature of the image. The products were the matrices and the categories of land use/ cover changes at the site. Descriptive statistics was employed to analyse the social economic data. Results and Discussion The study findings indicated a significant change in LULC as evidenced by an increase in agriculture and a loss of woodland within the plain. The period 2000-2016 has shown gains of agriculture and losses of woodland areas. Changes in the crops grown, increased immigrants of pastoralists, population growth, charcoal burning and livestock keeping contributed to an overuse of the existing land resources, which resulted in significant variations in the spatiotemporal patterns of land use changes with respect to specific socio-economic drivers. The assessment of changes in grazing land in Melela has shown that the current patterns are going to increase the existence of pastoralists in the region. Farmers on the other hand feel the grazing pressure brought about by the pastoral immigrants on their farms. The results of this study quantify the dynamics of land use/cover and its drivers on sustainable use of land. In the face of increasing population, pastoralism, and charcoal burning, there is a need for sustainable utilization of land resources.

Informal settlement is a global problem practised by all social classes. However, the extent and the context of the problem are serious in developing countries. The objective of this study was to identify the determinant factors for the escalation of informal settlements and their consequences in Butajira town, central Ethiopia. A mixed research approach with a sequential explanatory design was employed. Both qualitative and quantitative data were systematically collected and analysed using softwares like ArcGIS 10.3, ENVI 5.3, and SPSS. Primary data was collected through a household questionnaire survey from 221 samples and thirteen key informant interviews. Secondary data was also generated from different governmental reports, previous studies, and books. Employing a multiple linear logistic regression analysis, the empirical findings revealed that the informality was determined by a combination of factors such as monthly income, previous residence, mode accession of the respondent’s current holding, and brokers’ agitation as they were found to be statistically significant in determining the informality at a 95% confidence interval. It is found that informal settlements are expanded alarmingly in the study areas at the expense of the nearby agricultural fields. The effects are witnessed in the town resulting disorganised infrastructures and a spontaneous network of villages. The Municipality is engaged in preventive measures like demolitions and punishments but it did not bring any meaningful solutions. The researchers recommend the ‘punitive approach of marginality theory’ that insists on the forceful relocations of the informal settlers, but with the provision of adequate services

Planning for continuing natural resource management requires current information on the dynamics of land use and land cover. The aim of this paper was to analyze the impacts of the villagization program on land use land cover dynamics in Benishangul-Gumuz region, western Ethiopia. The study has employed a mixed-method research design using both primary and secondary sources. Multispectral LANDSAT satellite images with a 30 m resolution were acquired for land use land cover change detection between the years 1999, 2009, and 2022. Arc GIS 10.8, QGIS 3.28, ERDAS Imagine 2014, and Microsoft Excel software were used for image classification, accuracy assessment, and change detection. Six different land use land cover types: forest land, shrub and grassland, cultivated land, residential, bare land, and water bodies were identified between 1999 and 2022. The trends indicated a dramatic decrease at the rate of 27.2 ha of forestland, 17.1 ha of shrub and grassland, and 4.6 ha of water bodies per year, while the share of cultivated land, residential, and bare land has expanded at an average rate of 34.3 ha, 11.7 ha, and 2.9 ha per year respectively between 1999 and 2022. The phenomenon was caused by added population pressure due to villagization program, which in turn triggered farmland expansion and deforestation. It is recommended that raising local community awareness, reforestation, practicing land use plans, and promoting successful livelihood diversification could help to alleviate the issue and reroute the course of events in order to achieve sustainable natural resource management.

This study investigates the potential anthropogenic land use activities in the 114,000-km2 Chindwin River Watershed (CRW) in northwestern Myanmar, a biodiversity hotspot. This research evaluates current and future land use scenarios, particularly focusing on areas that provide ecosystem services for local communities and those essential for biodiversity conservation. Remote sensing and geographical information systems were employed to evaluate land use changes in the CRW. We used a supervised classification approach with a random tree to generate land use and land cover (LULC) classifications. We calculated the percentage of change in LULC from 2010 to 2020 and projected future LULC change scenarios for approximately 2030 and 2050. The accuracy of the LULC maps was validated using Cohen’s Kappa statistics. The multilayer perceptron artificial neural network (MLP-ANN) algorithm was utilized to predict future LULC. Our study found that human settlements, wetlands, and bare land areas have increased while forest land has declined. The area covered by human settlements (0.36% of the total in 2000) is projected to increase from 264 km2 in 2000 to 424 km2 by 2050. The study also revealed that forest land has connections to other land categories, indicating a transformation of forest land into other types. The predicted future land use until 2050 reflects the potential impacts of urbanization, population growth, and infrastructure development in the CRW.

Land use and land cover changes (LULCCs) are vital indicators for assessing the dynamic relationship between humans and nature, particularly in diverse and evolving landscapes. This study employs remote sensing (RS) data and machine learning algorithms (MLAs) to investigate LULCC dynamics within the Indus River Delta region of Sindh, Pakistan. The focus is on tracking the trajectories of land use changes within mangrove forests and associated ecosystem services over twenty years. Our findings reveal a modest improvement in mangrove forest cover in specific areas, with an increase from 0.28% to 0.4%, alongside a slight expansion of wetland areas from 2.95% to 3.19%. However, significant increases in cropland, increasing from 22.76% to 28.14%, and built-up areas, increasing from 0.71% to 1.66%, pose risks such as altered sedimentation and runoff patterns as well as habitat degradation. Additionally, decreases in barren land from 57.10% to 52.7% and a reduction in rangeland from 16.16% to 13.92% indicate intensified land use conversion and logging activities. This study highlights the vulnerability of mangrove ecosystems in the Indus Delta to agricultural expansion, urbanization, resource exploitation, and land mismanagement. Recommendations include harmonizing developmental ambitions with ecological conservation, prioritizing integrated coastal area management, reinforcing mangrove protection measures, and implementing sustainable land use planning practices. These actions are essential for ensuring the long-term sustainability of the region’s ecosystems and human communities.

Land degradation due to population growth, climate change and variability and other anthropogenic activities are main factors for the occurrence of flooding in Ethiopia. This study aimed to investigate flood incidence causes in the Ribb river. Possible causes of flooding were identified from literature. To recognize the causes, trend analysis of rainfall to know possible climate change, stream flow analysis to know possible land cover change and lake water level trend analysis to know backwater effect were conducted using the Mann-Kendall test. Land use land cover change review was also conducted. El Niño Southern Oscillation (ENSO) correspondence on rainfall extremes to know the climate pattern effect was conducted using correlation of Southern Oscillation Index (SOI) with summer rainfall anomaly. Structured interview with purposely and systematically selected flood plain community, focus group discussion with Woreda level early warning and response group leaders and natural resource conservation experts were used to confirm causes of flooding. At the end, landscape based mitigation measures from watershed morphometric analysis were proposed using integrated mission for sustainable development (IMSD) and FAO guidelines. The results indicated that the causes of flooding are combination of factors such as anthropogenic activities (expansion of cultivated land, significant lake water level rise and decreasing channel conveyance), climate change (significant increase in wet conditions), inadequate drainage and torrential rainfall. From the landscape based mitigation measures, a total of 7 check dams, 55 farm ponds, 29 percolation ponds and terracing were proposed.

Mass tourism is a major driver of economic growth in the Caribbean. One major trade-off of this economic growth model is the loss of natural areas due to tourism activities and increasing urbanization. Aruba is one of the most tourist intense destinations within the region with a total of 1.1 million stay-over tourists in 2019. Moreover, this island has one of the largest population densities in the Caribbean and high-speed urbanization takes place in this formerly rural island state. Therefore, this study aims to assess the islands' carrying capacity in relation to its limited land resources by means of a geospatial methodological analysis coupled with a correlation analysis between socio-economic indicators and statistics. First, the past and present drivers and characteristics of urbanization are analyzed. Second, the correlation between socio-economic indicators and the number of tourists was assessed. Third, two future scenarios were developed to assess the maximum carrying capacity. From 1986 till 2020, Aruba's built environment increased from ~29–60 km2 and translates to one-third of the island. Expansion was characterized by sprawl in the earlier years and changed to infilling in the latter. Furthermore, the results indicate that all socio-economic indicators are strongly positive correlated to tourism. Lastly, the possible maximum physical carrying capacity for yearly visitors and number of inhabitants was calculated to be ~1.7 million and 150.000, respectively. We conclude that the proposed methodological framework is robust and adequate to serve as a low budget decision-making tool for sustainable tourism development on islands.

Informal settlement is a global problem practised by all social classes. However, the extent and the context of the problem are serious in developing countries. The objective of this study was to identify the determinant factors for the escalation of informal settlements and their consequences in Butajira town, central Ethiopia. A mixed research approach with a sequential explanatory design was employed. Both qualitative and quantitative data were systematically collected and analysed using softwares like ArcGIS 10.3, ENVI 5.3, and SPSS. Primary data was collected through a household questionnaire survey from 221 samples and thirteen key informant interviews. Secondary data was also generated from different governmental reports, previous studies, and books. Employing a multiple linear logistic regression analysis, the empirical findings revealed that the informality was determined by a combination of factors such as monthly income, previous residence, mode accession of the respondent's current holding, and brokers' agitation as they were found to be statistically significant in determining the informality at a 95% confidence interval. It is found that informal settlements are expanded alarmingly in the study areas at the expense of the nearby agricultural fields. The effects are witnessed in the town resulting disorganised infrastructures and a spontaneous network of villages. The Municipality is engaged in preventive measures like demolitions and punishments but it did not bring any meaningful solutions. The researchers recommend the 'punitive approach of marginality theory' that insists on the forceful relocations of the informal settlers, but with the provision of adequate services [ABSTRACT FROM AUTHOR]

Land use and Land cover change (LULCC) is a major global problem, and projecting change is critical for policy decision-making. Understanding LULCCs at the watershed level is essential for transboundary river basin management. The present study aims to analyse the past and future LULCCs in two significant watersheds of the Senegal River basin (SRB) in West Africa: Bafing and Faleme. This study used Landsat images from 1986, 2006 and 2020 and the Random Forest classification method to analyze past LULCCs in these two watersheds. The results revealed: In Bafing, vegetation, settlement, agricultural areas and water increased, while the bareground decreased significantly between 1986-2020. In Faleme, two periods have different trends. Between 1986-2006, vegetation, settlement, agricultural areas and water increased, while bareground decreased. Between 2006-2020, settlement increased, while vegetation, agricultural areas, water and bareground decreased. To predict LULCCs in 2050 under business-as-usual assumptions, the Multilayer Perceptron and Marcov Chain model (MLP-MC) was used. The MLP-MC shows better results on Bafing than on Faleme but without questioning its application on the two watersheds. Bafing has seen a trend towards "more people, more trees", while Faleme has seen a trend towards "more people, more deforestation". These results contribute to develop appropriate land management policies and strategies to achieve or to maintain sustainable development in the SRB. [ABSTRACT FROM AUTHOR]

Context and Background Studies which have been conducted so far have focused on the processes of land use/cover changes in different areas at regional and global scale. Little is known about factors that influence land use/cover dynamics at finer scales such as Melela ward in Mvomero district, Morogoro, Tanzania. Goals and Objectives The overall objective of the study therefore was to evaluate the land use land cover dynamics and their impacts on pastoralism in Melela. Specifically, the study intended to examine land use/cover dynamics from 1991 to 2016, to identify socioeconomic factors that influence land use/cover dynamics and to determine the effects of land use/cover dynamics on pastoral communities and agricultural production. Methodology Remote sensed satellite data were used for change detection analysis to assess the spatial and temporal land use/cover change for the study area. Satellite images were processed and analysed to detect changes in land use/cover at the site by using change detection analysis technique to evaluate transition in land use/cover and to estimate changes in the area. A geographical positioning system (GPS) receiver was used for georeferencing the points for supervised classification and accuracy assessment. Change detection analysis and post classification comparison was used for the analysis of data. The analyses involved the application of an algorithm used to detect changes in spectral signature of the image. The products were the matrices and the categories of land use/cover changes at the site. Descriptive statistics was employed to analyse the social economic data. Results and Discussion The study findings indicated a significant change in LULC as evidenced by an increase in agriculture and a loss of woodland within the plain. The period 2000-2016 has shown gains of agriculture and losses of woodland areas. Changes in the crops grown, increased immigrants of pastoralists, population growth, charcoal burning and livestock keeping contributed to an overuse of the existing land resources, which resulted in significant variations in the spatiotemporal patterns of land use changes with respect to specific socio-economic drivers. The assessment of changes in grazing land in Melela has shown that the current patterns are going to increase the existence of pastoralists in the region. Farmers on the other hand feel the grazing pressure brought about by the pastoral immigrants on their farms. The results of this study quantify the dynamics of land use/cover and its drivers on sustainable use of land. In the face of increasing population, pastoralism, and charcoal burning, there is a need for sustainable utilization of land resources. [ABSTRACT FROM AUTHOR]

In fragile transitional freshwater ecosystems, such as wetlands, the increasing anthropogenic and natural pressures, including climate change and industrialisation, have impacted the land use/land cover (LULC). The present study aims to identify the LULC changes occurring in Loktak Lake, a Ramsar Wetland of International Importance, included in the Montreux Record between 2009 and 2020 using LANDSAT imageries. In order to quantify the LULC, a Maximum Likelihood Classifier was carried out in Arc GIS 10.8.1. A total of six land use classes were classified viz., open water body, athaphum, phumdi, built up, agriculture and barren area. It also attempts to undertake landscape modelling to look at the fragmentation of phumdi class through FRAGSTATS utilising the Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI) and Cohesion metrics. An overall decline in phumdi, athaphum, agriculture and open water body land uses at the rate of 5.9, 14.54, 110.1 and 1%, respectively, was observed. Meanwhile, built-up and barren land uses showed an overall increase at the rate of 18.31 and 31.25%, respecively. These LULC changes observed have been primarily because of anthropogenic factors, which threaten an already fragile ecosystem. The landscape modelling exercise showed that phumdi is aggregated at the innermost portions of the lake. It also showed that the patches of phumdi were higher in years 2011 and 2020, which may be due to the use of phumdi strips in athaphum (fish farms on the lake). The study indirectly revealed the effectiveness of past management actions by relevant organisations, as remotely sensed information requires ground validation. It also highlighted the absence of baseline data information and emphasised integrating present, past and future LULC modelling for management purposes. [ABSTRACT FROM AUTHOR]

Planning for continuing natural resource management requires current information on the dynamics of land use and land cover. The aim of this paper was to analyze the impacts of the villagization program on land use land cover dynamics in Benishangul-Gumuz region, western Ethiopia. The study has employed a mixed-method research design using both primary and secondary sources. Multispectral LANDSAT satellite images with a 30 m resolution were acquired for land use land cover change detection between the years 1999, 2009, and 2022. Arc GIS 10.8, QGIS 3.28, ERDAS Imagine 2014, and Microsoft Excel software were used for image classification, accuracy assessment, and change detection. Six different land use land cover types: forest land, shrub and grassland, cultivated land, residential, bare land, and water bodies were identified between 1999 and 2022. The trends indicated a dramatic decrease at the rate of 27.2 ha of forestland, 17.1 ha of shrub and grassland, and 4.6 ha of water bodies per year, while the share of cultivated land, residential, and bare land has expanded at an average rate of 34.3 ha, 11.7 ha, and 2.9 ha per year respectively between 1999 and 2022. The phenomenon was caused by added population pressure due to villagization program, which in turn triggered farmland expansion and deforestation. It is recommended that raising local community awareness, reforestation, practicing land use plans, and promoting successful livelihood diversification could help to alleviate the issue and reroute the course of events in order to achieve sustainable natural resource management. [ABSTRACT FROM AUTHOR]

AbstractIn Ethiopia, particularly in Southern Oromia and Eastern Halaba, land degradation is a common challenge for the pastoral community and farmers. As a result, the sub-watershed has closed for the past five years. However, little is known about the effects of topography on the rehabilitation of various land uses and land covers (LULCs). This study determined how the main topographic variables affect the rate of rehabilitation. Sentinel-2 images were used to quantify land use and land cover for the years 2017 and 2021. The aspect, altitude, and slope were calculated using the SRTM of 1 Arc-Second Global. The Maximum Likelihood classifier algorithm was used for supervised image classification. Changes in LULCs were analyzed using the post-classification technique. The LULC maps were overlaid with the topographic variabilities. The topographic variability’s influences were clearly observed on the rehabilitation rate of area enclosure. In the slope class of 0 to 5%, agriculture is the dominant cover. The bushland was largely detected in the slope classes of 0 to 10 in 2017. Agriculture and barren land were influenced as altitude and slope increased. Forest and bushland were found to be highly restored at an altitude of 1841 to 1880, an aspect of the south, and slope classes of 0 to 5 percent.

ABSTRACTLand use and Land cover change (LULCC) is a major global problem, and projecting change is critical for policy decision-making. Understanding LULCCs at the watershed level is essential for transboundary river basin management. The present study aims to analyse the past and future LULCCs in two significant watersheds of the Senegal River basin (SRB) in West Africa: Bafing and Faleme. This study used Landsat images from 1986, 2006 and 2020 and the Random Forest classification method to analyze past LULCCs in these two watersheds. The results revealed: In Bafing, vegetation, settlement, agricultural areas and water increased, while the bareground decreased significantly between 1986-2020. In Faleme, two periods have different trends. Between 1986-2006, vegetation, settlement, agricultural areas and water increased, while bareground decreased. Between 2006-2020, settlement increased, while vegetation, agricultural areas, water and bareground decreased. To predict LULCCs in 2050 under business-as-usual assumptions, the Multilayer Perceptron and Marcov Chain model (MLP-MC) was used. The MLP-MC shows better results on Bafing than on Faleme but without questioning its application on the two watersheds. Bafing has seen a trend towards ”more people, more trees”, while Faleme has seen a trend towards ”more people, more deforestation”. These results contribute to develop appropriate land management policies and strategies to achieve or to maintain sustainable development in the SRB.

Abstract Bhubaneswar is the first designed ‘smart city’ in India and has experienced rapid urbanization since 2000. The question undertaken in this study is to assess if there is a change in the rainfall over this rapidly urbanizing region, and if so, what are the characteristics of the change? The broader intent is to understand if the change in urbanization and rainfall are interlinked? The India Meteorological Department (hourly station and daily gridded) and Tropical Rainfall Measurement Mission (3-hourly) datasets are analyzed for the 1980–2018 period (39 years) for different seasons separately. Wavelet and trend analysis reveal that precipitation intensity has increased over the study period. The assessments of the hourly rainfall data show an interesting feature. There is a decrease in the midnight to early-morning rain, with a corresponding increase in the late-afternoon to midnight rainfall. The increase in the rainfall is preferentially downwind and on the east side of the city. A supervised classified land use land cover map of the Bhubaneswar region is developed for 1980, 1990, 2000, 2010, and 2019 using Landsat imagery to compute the urban sprawl. The urban area and population density over Bhubaneswar is increasing with time. Analysis of the LULC and rainfall data indicates that the rainfall over urban regions and the shift in the timing of rains to evenings is highly correlated with the urban sprawl.

Lassa fever virus (LASV) is the causative agent of Lassa fever, a disease endemic in West Africa. Exploring the relationships between environmental factors and LASV transmission across ecologically diverse regions can provide crucial information for the design of appropriate interventions and disease monitoring. We investigated LASV exposure in 2 ecologically diverse regions of Guinea. Our results showed that exposure to LASV was heterogenous between and within sites. LASV IgG seropositivity was 11.9% (95% CI 9.7%–14.5%) in a coastal study site in Basse-Guinée, but it was 59.6% (95% CI 55.5%–63.5%) in a forested study site located in Guinée Forestière. Seropositivity increased with age in the coastal site. We also found significant associations between exposure risk for LASV and landscape fragmentation in coastal and forested regions. Our study highlights the potential link between environmental change and LASV emergence and the urgent need for research on land management practices that reduce disease risks.

Soil erosion by water and wind is among the most crucial land degradation processes in Ethiopia. This is also the case for Alage watershed located in the cental Rift Valley system. This study aimed at assessment of soil erosion hazard and its relation to land use land cover change in the watershed during the period from 1984 to 2016 for a better land management. The study is based on application of Remote Sensing (RS) and Geographical Information System (GIS) to extract inputs factor values for the Revised Universal Soil Loss Equation (RUSLE). Time-series satellite imageries of Landsat TM 1984, ETM+ 2000 and OLI 2016 were used for land use land cover change detection and determination of cover management (C) factor of the RUSLE. Biophysical data such as rainfall, soil properties, land management practices including soil and water conservation measures within the watershed were collected using field survey and secondary data sources. Slope steepness and slope length factors were derived using Digital Elevaition Model (DEM). Long-term average annual soil loss rates were estimated by the RUSLE integrated with GIS for 1984, 2000 and 2016. Using satellite imageries, the land use land cover and changes within the watershed during the three periods were obtained through a supervised classification with maximum likelihood algorithim. The results of land use land cover change indicated that the proportion of rain-fed cropland, bare land and built up areas increased by 17.4%, 5.9% and 2.9% respectively over the three study period. In contrast the proportion of bush/shrub land, irrigated cropland, grass land, forested areas and waterbodies decresaed by 15.5%, 4.7%, 3.4%, 2.3% and 0.3% respectively during the same period. Estimated average annual soil loss rates showed an increasing trend from 24.3 ton ha−1 yr−1 in 1984 to 38 ton ha−1 yr−1 in 2016. Increasing trends of average annual soil loss rate is attributed to increased proportion of cropland, bare land and built up areas during those periods leading to decreased protective vegetation cover. Hotspot areas within the watershed require implementation of land management practices to prevent further degradation and expansion of gullies. This study is relevant to demonstrate environmental implication of land use land cover change for future land management practices and land use policy in the Rift Valley of central Ethiopia.

In the context of Global Change Research, detection, monitoring and characterization of land use/land cover (LULC) changes are of prime importance. The increasing availability of dense satellite image time series (SITS) has led to a shift in the change detection paradigm, with algorithms able to exploit the full temporal information laid down in SITS. So far, most of these algorithms have focused on the detection of abrupt and gradual changes, and thus developed breakpoint detection based on significant deviations from the mean. However, LULC changes may manifest themselves in other patterns, particularly changes in seasonality (amplitude, number and length of the growing seasons) that are harder to detect. In this paper, we propose a simple method to automatically select the breakpoint linked to the biggest seasonal change in long and dense SITS with multiple breakpoints. This approach - BFASTm-L2 - relies on linking a high-speed algorithm (BFAST monitor) with a time series similarity metric (Euclidian distance L2) sensitive to seasonal changes. The capacity of BFASTm-L2 to identify the date of change in different situations was tested on two data sets, and compared to the performances of three other algorithms (BFAST monitor, BFAST lite, and Edyn). The data sets are 1. a published benchmark data set composed of 25 200 simulated SITS with different change types and change magnitudes, and 2. the 2000–2020 MODIS NDVI SITS over a 200x200 pixels area in Senegal including different study sites which have undergone recent LULC changes due to agricultural large-scale land acquisitions (LSLAs) (as reported in the ground field database used in this study). The results show that BFASTm-L2 is efficient in accurately detecting in time most of the changes, and, in contrast with BFAST Lite and BFASTmonitor, to spatially highlight LSLAs-induced changes without the need of any prior knowledge. The automatic proposed approach, faster than BFAST Lite and Edyn, and with very few tuneable parameters, may thus be easily implemented in unsupervised pipelines to map and analyse generic LULC changes at regional scale.

In an effort to forecast and estimate the value of ecosystem services (ESVs) and land use and land cover changes (LULC), recent global events and research have centered on the evaluation of LULC. This study evaluates the effectiveness of an integrated approach using multi-layer perceptron-Markov chain analysis (MLP-MCA) and remote sensing data for monitoring land use and land cover (LULC) changes. The study area comprises the three Bangladeshi upazilas that the Padma Bridge connects: Shariatpur, Louhajang, and Janjira. The Ecosystem Services Valuation Database (ESVD) was used to evaluate the impacts of changes in land use and land cover (LULC) on Ecosystem Service Values (ESVs). The LULC of the study area was estimated for the years 2000, 2010, and 2020, and the forecast period for urban development was 2030 and 2040. Additionally, the monetary value of ecosystem services was evaluated across the time. As per the LULC change analysis, there is a projected 4.35% growth in the built-up area from 2000 to 2020. After the bridge is constructed, the built-up area is projected to increase by 7% in 2030 and 14% in 2040, according to the forecast. The exponential expansion of developed land has a paradoxical effect on the value of ecosystem services. From 2020 to 2040, it is expected that the ESVs for provision, regulation, culture, and support will experience a reduction of approximately 213.24 million USD/ha. Even if the establishment of a bridge results in economic stability and investment attraction for the nation, unforeseen ecosystem service losses cannot contribute to long-term, sustainable development. This study, by establishing a correlation between urban area expansion and the deterioration of ecosystem services, can serve as a standard and basis for guiding management decisions.

Using 2001 and 2016 land use (LU) data and three developed deforestation LU scenarios, namely Deforest I, II and III, the possible impacts of the ongoing land use land cover change (LULCC) over West Africa (WA) and the uncertainty regarding the impacts on regional climate were assessed. Twelve Weather Research and Forecasting (WRF) model simulations were configured with the default and integrated MODIS satellite dataset for two sets of 3 months (December–February DJF 2011–2012 and July–September JAS 2012) over WA. Between 2001 and 2016, changes that occurred in precipitation, temperature and dew point temperature due to LULCC are mostly not significant at the 95% level with a decrease of 0.8, 0.0 and 0.1%, respectively. Deforest I, II and III caused significant changes with an increase of 44.4, 44.7, 41.5%; 0.8, 0.9, 1.1%; and 0.3, 0.1, −0.2%, respectively, for precipitation, temperature and dew point temperature. Precipitation was lower in the simulation with 2016 LU than it was with 2001 LU, which may have also been influenced by the reforestation that occurred between the periods. However, Deforest III resulted in a widespread nonsignificant rise in precipitation, as the modified areas showed a significant decrease during JAS period. Areas where forests were converted into barren lands revealed severe increase in the surface albedo which is a strong factor that its alteration is capable of influencing precipitation and other variables over WA. LULCC also altered the atmospheric column by modifying the strength of the African Easterly Jet (AEJ), Tropical Easterly Jet (TEJ), wind speed, and monsoonal, vertical, meridional and zonal winds. Heat related fields, such as dew point and air temperature, and moisture fields such as relative humidity were also modified by LULCC. Therefore, as WA reacts strongly to LULCC, sustainable land management practices should be encouraged to control its adverse effects. [ABSTRACT FROM AUTHOR]

Urban flooding is a frequent disaster in cities. With the increasing imperviousness caused by rapid urbanization and the rising frequency and severity of extreme events caused by climate change, the hydrological status of the urban area has changed, resulting in urban floods. This study aims to identify trends and gaps and highlight potential research prospects in the field of urban flooding in South Asia. Based on an extensive literature review, this paper reviewed urban flood hazard assessment methods using hydraulic/hydrological models and urban flood management practices in South Asia. With the advancement of technology and high-resolution topographic data, hydrologic/hydraulic models such as HEC-RAS/HMS, MIKE, SWMM, etc., are increasingly used for urban flood hazard assessment. Urban flood management practices vary among countries based on existing technologies and infrastructures. In order to control urban flooding, both conventional physical structures, including drainage and embankments, as well as new innovative techniques, such as low-impact development, are implemented. Non-structural flood mitigation measures, such as improved flood warning systems, have been developed and implemented in a few cities. The major challenge in using process-based hydraulic models was the lack of high-resolution DEM and short-duration rainfall data in the region, significantly affecting the model's simulation results and the implementation of flood management measures. Risk-informed management must be implemented immediately to reduce the adverse effects of climate change and unplanned urbanization on urban flooding. Therefore, it is crucial to encourage emergency managers and local planning authorities to consider a nature-based solution in an integrated urban planning approach to enhances urban flood resilience. [ABSTRACT FROM AUTHOR]

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.

Nepal—one of the most rapidly urbanizing countries in the world—has witnessed unplanned urbanization in recent decades. Nevertheless, spatial-temporal dynamics of land use land cover (LULC) in major cities of Nepal are not well understood. This study investigates LULC changes in the 12 rapidly urbanizing cities of Nepal from 1990 to 2020. Freely accessible Landsat images and Google Earth Engine (GEE), a cloud-based analysis platform were used to classify the city landscape into five major classes: vegetation, agriculture, barren, water body, and built-up using a random forest algorithm. Built-up areas have continuously increased in the Nepali cities mostly at expense of agricultural lands thus agriculture areas have decreased, and vegetation areas have followed mixed trends during each of the three decades. Biratnagar, Janakpur, Kathmandu, Nepalgunj, and Rajbiraj showed an overall increase in built-up areas at the expense of vegetation and agricultural lands while Bharatpur, Birendranagar, Dhangadhi, Ghorahi, Hetauda, Pokhara, and Tulsipur showed an overall decrease in agricultural areas with increased built-up areas and vegetation from 1990 to 2020. This study will assist the policymakers, city planners, and local governments to formulate sustainable urban development strategies and plans to prevent haphazard urban growth while preserving the city's agricultural lands to promote local food supply and green areas to ensure an uninhibited flow of ecosystem services in the cities.

The effects of land use and land cover (LULC) change on environmental systems across the land surface's “critical zone” are highly uncertain, often making prediction and risk management decision difficult. In a series of numerical experiments with an integrated hydrologic model, overland flow generation is quantified for both present day and forest thinning scenarios. A typhoon storm event in a watershed near the Fukushima Dai-ichi Nuclear Power Plant is used as an example application in which the interplay between LULC change and overland flow generation is important given that sediment-bound radionuclides may cause secondary contamination via surface water transport. Results illustrate the nonlinearity of the integrated system spanning from the deep groundwater to the atmosphere, and provide quantitative tools when determining the tradeoffs of different risk-mitigation strategies.