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Conventional water quality measurements are nearly impossible during and immediately after extreme storms due to dangerous conditions. In this study, remotely sensed reflectance is used to develop a regression equation that quantifies total suspended solids (TSS) in near real-time after Hurricane Harvey. The application focused specifically on sediment loading and deposition and its potential impacts on the Houston Ship Channel and Galveston Bay riverine-estuarine system. The European Space Agency’s Sentinel-2 satellite captured images at critical points in the storm’s progression, necessitating the development of a new algorithm for this relatively new satellite mission. Several linear regressions were analyzed with the goal of developing a simple one- or two-band equation, and the final model uses the red and near infrared bands (R2 = 0.74). Results show that record flows during Harvey delivered unprecedented suspended sediment loads to the Gulf of Mexico at concentrations above 125 mg/L with a mean concentration of 43 mg/L across the bay. The study findings demonstrated that it took up to 11 days after the storm for sediment transport to abate.

Remote sensing data from Indian geostationary satellites (Kalapana-1, INSAT 3A) were used for the first time for early warning of agricultural drought and forewarning of crop vigour. An Early warning indicator (EWI) was developed from operational product of rainfall and reference evapotranspiration from observations of Kalpana-1 very high resolution radiometer (VHRR). The effectiveness of EWI was evaluated for the two drought years (2009 and 2012). The positive correlation (r = 0.66–0.68 for 2009 and r = 0.64–0.70 for 2012) between the EWI in the month of June–July and standardized precipitation index-1 (SPI-1) averaged over administrative unit (called district) indicates that EWI can be used successfully for drought early warning. Lag-response behaviour between EWI and crop vigour in terms of normalized difference vegetation index (NDVI) and LAI (leaf area index) over cropland was studied. Systematic patterns emerged for 30 days lag period between negative EWI and NDVI at both grid-scale (0.25°) and at district level. Linear relations were found between 10-day EWI and NDVI or LAI at 30 days lag during June–July period. Linear models were developed to forewarn crop vigour which was validated with realized NDVI from INSAT 3A charge-coupled device (CCD) observations within 95% accuracy. The EWI is recommended as potential indicator for early-season agricultural drought assessment and can be used for sub-district scale with finer scale rainfall and evaporation products from advanced next-generation geostationary meteorological satellites.

Urbanization produced significant landscape changes throughout the world. China has been experiencing accelerated urbanization during the past decades. Rapid land use/land over conversion occurred nationwide in urbanization, manifesting noteworthy characteristics of landscape dynamics. In this study, we investigated the spatial differentiation in settlement change rates among 1-km(2) land units in the Nanjing metropolitan region, a representative rapidly urbanizing region in China. Remotely sensed detection using Landsat TM data of 1988-2006 showed that settlement increase, termed as positive growth (PG), was predominant in the study area; while settlement decrease, termed as negative growth (NG), also had a considerable proportion, which was mainly attributed to the increase of green lands and the shrink of rural settlements. Along the urban-rural gradient, PG and NG showed similar mono-peaked patterns. The urban fringe zone with a consistent width of about 4 km was identified as the hot zone of both PG and NG over the three unequal periods. For both PG and NG, high-rated changes tended to exhibit more aggregative patterns along the gradient in the urban fringe zone. Settlement changes showed apparent anisotropy across directions. The directional distribution of PG was significantly negatively correlated to the topographic variables, suggesting that the mountains constrained urban expansion in an "area-weighted inverse-distance power" form. Significant correlation between PG and NG in a time-lagged manner showed the "increase-decrease" fluctuation occurred in settlement changes, reflecting the "urban expansion-land reconfiguration" process in rapid urbanization in Nanjing.

As part of a regional study by the Atlantic Slope Consortium (ASC) to develop ecological and socioeconomic indicators of aquatic ecosystem condition, we developed and tested a protocol for rapidly assessing condition of the stream, wetland, and riparian components of freshwater aquatic ecosystems. Aspects of hydrology, vegetation, in-stream and wetland characteristics, and on-site stressors were measured in the field. The resulting metrics were used to develop an index of overall condition, termed the Stream-Wetland-Riparian (SWR) Index. Values of this Index were compared to existing biotic indices and chemical measures, and to a Landscape Index created using satellite-based land cover data and a geographic information system (GIS). Comparisons were made at several levels of spatial aggregation and resolution, from site to small watershed. The SWR Index and associated Landscape Indices were shown to correlate highly with biological indicators of stream condition at the site level and for small contributing areas. The landscape patterns prevalent throughout the entire watershed do not necessarily match the patterns found adjacent to the stream network. We suggest a top-down approach that managers can use to sequentially apply these methods, to first prioritize watersheds based on a relative condition measure provided by the Landscape Index, and then assess condition and diagnose stressors of aquatic resources at the subwatershed and site level.

The Nawarangpur district, Orissa, a tropical region with Sal mixed moist deciduous and Sal mixed dry deciduous forests, has been affected by extensive deforestation. The district was surveyed using Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) satellite imagery. From 1973 to 1990, more than 888.6 km(2) of dense forest (rate of deforestation = 3.62) and from 1990 to 2004, 429.7 km(2) (rate of deforestation = 3.97) were found to have been deforested. The analysis of results identified the reduction in area of dense forest and increase of agricultural land, degraded areas of abandoned agricultural land and unproductive scrub. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. From this study it can be concluded that temporal changes and the factors affecting these changes should be determined for sustainable management of natural resources.

The objective of this research was to explore an accurate and fast way of estimating chlorophyll-a amount, a water quality parameter (WQP), using IKONOS satellite sensor image and in situ measurements. Since the in situ data of WQPs are limited with the number of sampling locations, deriving a correlation between these measurements and remotely sensed image allows synoptic estimates of the related parameter over large areas even if the areas are in remote and inaccessible locations. In this study, simultaneously collected satellite image data and in situ measurements of chlorophyll-a were correlated using multivariate regression model. Different experiments were designed by changing the numbers and distributions of in situ measurements. Regression coefficients of each design and differences between model-derived data and in situ measurements were calculated to find out the optimum design to produce chlorophyll-a map of study region. Results illustrated that both the number and distribution of in situ measurements have impact on regression analysis, therefore should be selected attentively. Also, it is found that IKONOS imagery is an efficient and effective source to derive chlorophyll-a map of the large areas using limited number of ground measurements.

This study aims to investigate the change in spatial-temporal configuration of secondary forest succession and generate measurements for monitoring the changes in structural plant diversity in Yalnizçam Scots pine forest in NE Turkey from 1972 to 2005. The successional stages were mapped using the combination of Geographic Information System (GIS), Global Positioning System (GPS), aerial photos and high resolution satellite images (IKONOS). Forest structure and its relationship with structural plant diversity along with its changes over time were characterized using FRAGSTATS. In terms of spatial configuration of seral stages, the total number of fragments increased from 572 to 735, and mean size of patch (MPS) decreased from 154.97 ha to 120.60 ha over 33 years. The situation resulted in forestation serving appropriate conditions for plant diversity in the area. As an overall change in study area, there was a net increase of 1823.3 ha forest during the period with an average annual forestation rate of 55.25 ha year(-1) (0.4% per year). In conclusion, the study revealed that stand type maps of forest management plans in Turkey provide a great chance to monitor the changes in structural plant diversity over time. The study further contributes to the development of a framework for effective integration of biodiversity conservation into Multiple Use Forest Management (MUFM) plans using the successional stages as a critical mechanism.

The catastrophic earthquake, 7.3 on the Richter scale, occurred on September 21, 1999 in Central Taiwan. Much of standing vegetation on slopes was eliminated and massive, scattered landslides were induced at the Jou-Jou Mountain area of the Wu-Chi basin in Nantou County. We evaluated three methods for assessing landslide hazard and vegetation recovery conditions. (1) Self-organizing map (SOM) neural network coupled with fuzzy technique was used to quickly extract the landslide. (2) The NDVI-based vegetation recovery index derived from multi-temporal SPOT satellite images was used to evaluate vegetation recovery rate in the denudation sites. (3) The spatial distribution index (SDI) based on land-cover topographic location was employed to analyze vegetation recovery patterns, including the invading, surviving and mixed patterns at the Jou-Jou Mountain area. On September 27, 1999, there were 849.20 ha of landslide area extracted using the self-organizing map and fuzzy technique combined model. After six years of natural vegetation succession, the landslide has gradually restored, and vegetation recovery rate reached up to 86%. On-site observation shows that many native pioneer plants have invaded onto the denudation sites even if disturbed by several typhoons. Two native surviving plants, Arundo formosana Hack and Pinus taiwanensis Hayata, play a vital role in natural vegetation succession in this area, especially for the sites on ridgeline and steep slopes.

Mentougou District acts as a crucial component in the ecological buffer in western Beijing mountainous areas, Beijing, China. Using two Landsat MSS/TM images acquired on July 14, 1979 and July 23, 2005, the vegetation coverage of Mentougou District was calculated based on normalized difference vegetation index and spectral mixture analysis (NDVI-SMA) model. Its temporal and spatial changes were analyzed according to digital elevation model (DEM) image, social and economic data. The results showed that the vegetation coverage decreased from 76.4% in 1979 to 72.7% in 2005. Vegetation degradation was probably the result of human disturbance, such as outspreading of resident areas, and coal and stone mining activities, while vegetation restoration might be contributed by the combined effects of both natural processes and ecological construction effort. Vegetation changes were closely related to topographical characteristics. Plants at high altitude were more stable and less degraded than the plants at low altitude, while the plants on steep slope or northwest aspect were more vulnerable to degradation. During the period of 26 years, landscape appeared to become more fragmental, and ecological quality of the land seemed deteriorated sharply in that highly-covered vegetation area has been decreased by 24%.

Habitat preserve systems have been established adjacent to the densely populated regions of southern California to support indigenous plant and animal species that are listed as rare, threatened, or endangered. Monitoring the condition of habitat across these broad preserves is necessary to ensure their long-term viability and may be effectively accomplished using remote sensing techniques with high spatial resolution visible and near-infrared (VNIR) multispectral imagery. The utility of 1 m spatial resolution VNIR imagery for detailed change detection and monitoring of Mediterranean-type ecosystems is assessed here. Image acquisition and preprocessing procedures were conducted to ensure that image-detected changes represented real changes and not artifacts. Change classification products with six spectral-based transition classes were generated using multiband image differencing (MID) for three change periods: 1998-1999, 1998-2001, and 1998-2005. Land cover changes relevant to habitat quality monitoring such as human-induced disturbance, fire, vegetation growth/recovery, and drought related vegetation stress were readily detected using the multitemporal VNIR imagery. Suggestions for operational habitat monitoring using image products and mobile geographic information system technologies are provided.

Because of their intense vegetation and the fact that they include areas of coastline, deltas situated in the vicinity of big cities are areas of great attraction for people who wish to get away from in a crowded city. However, coasts, with their fertile soil and unique flora and fauna, need to be protected. In order for the use of such areas to be planned in a sustainable way by local authorities, there is a need for detailed data about these regions. In this study, the changes in land use of the area between Topburnu and Uçburun Musa Bey Harbour on the Ceşme peninsula, which is to the immediate west of Turkey's third largest city Izmir, from 1976 up to the present day, were investigated. In the study, using aerial photographs taken in 1976, 1995 and 2000 and an IKONOS satellite image from the year 2007, the natural and cultural characteristics of the region and changes in the coastline were determined spatially. Using aerial photographs from 1976, 1995 and 2000 and an IKONOS satellite image from the year 2007, together with "1/25,000 scale Conservation-Oriented Development Plans" prepared in 1979, 1990 and 2000 by the committee for the Preservation of Natural and Cultural Entities attached to the Ministry of Culture and Tourism of the Turkish Republic, the natural and cultural characteristics of the region and the land use changes and their connection with conservation rulings were determined spatially. In this study, spatial changes in land use over the years were compared with changing conservation rulings over the years and the emerging results have brought a new perspective to the subject in contrast to other similar studies.

Primary objectives of our work were to spatially delineate post industrial areas of the EU-27 and indicate key environmental, social and economic sensitivity issues for these regions. The density of industrial sites within NUTS-x regions for EU-27 countries was assessed by using CORINE 2000 land cover layer. A development of postindustrial society in Europe represents a strong geographic diversity. There are distinct historical and current differences between regions which form major groups, comprising similar internal characteristics and definable trends in environmental and socioeconomic sense. Regions grouped into postindustrial clusters are fundamentally different from the European average, and are facing specific problems related to global market and political changes. Eastern postindustrial regions can be characterized as socially and economically weak, exhibiting high unemployment rate, low GDP, negative population growth and a strong environmental pressure, represented by a high density of dump sites. Most of the western EU postindustrial areas have been successfully recovered and moved into new economy as shown by most of the indicators. In urban postindustrial zones, however, emission sources of pollutants seem to continually be a major problem--not necessarily in terms of exceeding thresholds, but through a remarkable difference in the amount of pollutants produced relative to other regions.

Rapid and unplanned urbanization and industrialization are the main reasons of environmental problems. If urban growth is not based on resource sustainability criteria and urban plans are not applied, natural and human resources are damaged dramatically. In this study, land use change and urban expansion in Edremit region of Turkey is determined by means of remote sensing techniques between 1971 and 2002. To improve the accuracy of land use/cover maps, the contribution of SAR images to optic images in defining land cover types was investigated. To determine the situation of land use/cover types in 2002 accurately, Landsat-5 images and Radarsat-1 images were fused, and the land use/cover types were defined from the fused images. Comparisons with the ground truth reveal that land use maps generated using the fuse technique are improved about 6% with an accuracy of 81.20%. To define land use types and urban expansion, screen digitizing and classification methods were used. The results of the study indicate that the urban areas have been increased 1,826 ha across the agricultural fields which are in land use capability classes of I and II, and significant environmental changes such as land degradation and degeneration of ground water quality occurred.

How to assess the potential habitat integrating landscape dynamics and population research, and how to reintroduce animals to potential habitats in environments highly human disturbed are still questions to be answered in conservation biology. According to behavioral research on Elaphurus davidians, we have developed a suitability index and a risk index to evaluate the potential habitats for the deer. With these indices, we conducted two transect assessments to evaluate the gradient change of the target region. Then, taking rivers as border lines, we tabulated the forest areas, high grassland area and total area and then compared the forest and high grassland area in each subregion. Furthermore, we computed the land use transfer matrix for the whole Yancheng coast during 1987–2000. We also computed human modified index (HMI) in six subregions. Lastly with a geographical information system support we obtained the spatial distribution of the indices and evaluation of the whole potential habitats from a neighborhood analysis. The transect assessment showed that the suitability of the coastal area was higher than that of the inland area for the deer, while the southern area was higher than the northern. Landscape metrics and HMI analysis showed that different landscape patterns and different anthropogenic disturbance existed within the region, and the increasing human disturbance was the key factor causing the pattern dynamics. The evaluation of potential habitats showed that there was an estimated carrying capacity of no more than 10,000 for David’s deer reintroduction into the natural area. Also the reintroduction strategy was discussed. This integrated approach linked the population research and the landscape metrics, and the dataset with different scale; thus, it is an approach likely to be useful for the protection of other large animal in a landscape highly disturbed by humans.

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.

The South-to-North Water Transfer (SNWT) Project of China is the largest of its kind ever implemented. Of its three routes (i.e., East, Middle and West), the middle one will transfer 14 billion m(3) of water annually from the Han River, a tributary of the Yangtze and the water supplying area, to Beijing by 2030. Thus water quality in the 95,000 km(2) upper Han River basin is of great concern. A watershed management initiative has been implemented in the basin, and the ultimate objectives are to quantify basin's ecosystem functioning and to develop an integrated management system with respect to water resources conservation. Specifically, the program includes five activities: characterization of riparian ecosystems, detection of land use and land cover change, quantification of nutrient cycling of representative ecosystems, determination of spatial and temporal variations of water quality, and finally development of a watershed management system for water conservation. This article provides the justifications of the watershed management initiative and the initial results are comprehended with respect to the water conservation in the Han River basin.

The main focus of the paper is to assess the land use/ land cover (LULC) change in northern Chhattisgarh due to industrialization using remote sensing and Geographical Information System (GIS). The impact was assessed using an information extraction method applied to temporal satellite data (LANDSAT and IRS scenes) in GIS domain. For assessing the impact on natural resources, the classification scheme was restricted to (1) Forest patches ((a) completely cleared, (b) partially cleared, (c) least affected), (2) Non-Forest ((d) completely changed, (e) least changed), (3) Industrial/Mining area, and (4) River. Over the three decades 22.22% of forests have been completely cleared and converted to industrial setup. Another 25% is completely cleared and 10% is degraded. Around 4% of agricultural area is totally affected due to industrial activity. Random assessment of plant distribution (Trees, Shrubs and Herbs) indicates significant changes in the herb distribution directly related to distance gradient form the industrial/mining setup. Visual recording, socio-economic survey and satellite data also helped in delineation of extent of environmental pollution in forest and non-forest areas. The paper presents methodology for the environmental impact assessment.

This paper concentrates on determining the areas for afforestation and the development of conservation strategies and actions in the case where there is high demand for the conservation of a particular land area. The analysis of hydrological landscape structure and of erodibility was prerequisite in the methodological design considering the site-specific natural landscape characteristics of the study area. The Golbasi Specially Protected Area ( SPA) being the case area has many local environmental disturbances, especially with respect to its hydrological system, and the area is beset by increasing demands for its use by the burgeoning human population. It is obviously clear that the present intensive demand for recreational use will be forecasted further increase in the future. The count of rural residences is estimated to increase by 50% over the next decade. This intensive demand shall further strain the carrying capacity of the ecological milieu, which has already suffered to a significant degree because of the present urban and rural activities. The Golbasi district is located only 20 km from the city center of Ankara, and its surroundings were legally designated to be a Specially Protected Area primarily for the existence of lacustral and fluvial systems where two interconnected lakes exist: Mogan and Egmir Lakes. Essentially, the continuity of the lacustral and fluvial system of Lakes Mogan and Egmir depends on the preservation and improvement of the water sources. However, interconnected surface water bodies of these lakes are actually quite contaminated, and a decline in the water flow from Mogan to Egmir has been observed. For the elaboration of the present method, required conventional maps ( at 1/25,000 scale) of topography ( for slope analysis) and geology ( for erodibility and permeability analysis) were transferred to computer media using AutoCAD(R) R.14 software. The rectification of the transferred data was done using ERDAS(R) Imagine 8.3. All data were then transferred into a GIS engine (Arcview(R) 3.2). This software provided the ability to create, manipulate, analyze and display topologically correct geographic data in digital form. The method proceeded according to the following phases: 1. Analysis of the hydrologic landscape structure; 2. Permeability of the soil structure; 3. Permeability of the geological structure; 4. Conservation zones.

These days, wildfires are prevalent in almost all areas of the world. Researchers have been actively analyzing wildfire damage using a variety of satellite images and geospatial datasets. This paper presents a method for detailed estimation of wildfire losses using various geospatial datasets and an actual case of wildfire at Kang-Won-Do, Republic of Korea in 2005. A set of infrared (IR) aerial images acquired after the wildfire were used to visually delineate the damaged regions, and information on forest type, diameter class, age class, and canopy density within the damaged regions was retrieved from GIS layers of the Korean national forest inventory. Approximate tree heights were computed from airborne LIDAR and verified by ground LIDAR datasets. The corresponding stand volumes were computed using tree volume equations (TVE). The proposed algorithm can efficiently estimate fire loss using the geospatial information; in the present case, the total fire loss was estimated as $5.9 million, which is a more accurate estimate than $4.5 million based on conventional approach. The proposed method can be claimed as a powerful alternative for estimating damage caused by wildfires, because the aerial image interpretation can delineate and analyze damaged regions in a comprehensive and consistent manner; moreover, LIDAR datasets and national forest inventory data can significantly reduce field work.

Although remote sensing is increasingly in use for habitat mapping, traditional image classification methods tend to suffer shortcomings due to non-normality of spectral signatures, as well as overlapping and heterogeneity in radiometric responses of natural and semi natural vegetation. Methods using non-parametric classifiers and object-oriented analysis have been suggested as possible solutions for overcoming these limitations. In this paper, we aimed at evaluating the performance of some of these techniques for the European Natura 2000 network of protected areas habitats mapping. For this purpose, we tested different methods of supervised image classification in the Northern Mountains of Galicia, Spain, an area included in the Natura 2000 network, which is characterized by a highly heterogeneous landscape. Methods involved the use of maximum likelihood and nearest neighbour decision rules in per-pixel and per-object classification analyses on Landsat TM imagery. Per-object classifications were completed using the segment mean and segment means plus standard deviation feature spaces. The results showed the existence of significant differences in the accuracies for the different methodologies, their strengths and weaknesses and identified the most adequate approach for habitat mapping. Analyses pointed out that significant improvements in accuracy were achieved only under certain combinations of per-object analysis, non-parametric classifiers and high dimensionality feature space.

To feed its rapidly growing energy demand, oil exploitation in China has never been more intensive. The most obvious characteristics of oil exploitation are progressive and regional, which can be monitored by remote sensing, such as land use and cover change, either perpetual or temporary, during oil field development such as construction of oil well, roads, transportation systems and other facilities. In this paper, the oil field located on the north edge of Taklimakan Desert, in the Tarim River watershed in northwest of China. The disturbance effects of regional oil exploitation were the main content of regional environmental managements and monitoring. Based on Enhanced Thematic Mapper Plus (ETM+) and Aster images, analyzed regional land use and landscape change from 2001 to 2003. By the comparison, it can be concluded that the ecological quality was deteriorating in these 3 years. The woodland was degrading to grass and desert. The area of woodland dropped from 9.06 km(2) in 2001 to 3.24 km(2) in 2003 with a 64.23% decrease. At the same time, the area of shrubbery lessened 18.23%. On the other hand, the whole area of desert and Saline soils inflated from 15.08 km(2) in 2001 to 25.36 km(2) in 2003. The patch number of bare land did climb dramatically, but single patch area increased. The research demonstrated that desert and Saline soils patches were activated by the human behavior and climate change. The information from the ETM+ and Aster images was proved be an effective and efficient way to be applied in regional environmental managements.

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzed spatial and temporal changes in land use and land cover patterns in a typical mountain watershed in the Gumushane district along the Northeastern part of Turkey. The area is investigated by comparing LANDSAT images from 1987 to 2000 and evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1971 and 1987 using GIS and FRAGSTATS.The results show a general decreasing trend in area of natural land cover types including broadleaf and conifer forests as well as coppice between 1971 and 1987 (0.54%, respectively). In contrast, between 1987 and 2000 this natural land cover types show increasing trend (1.6%). In parallel with forest dynamics, the area of managed land including lowland and upland agricultural areas, rangelands and grasslands increased during the first period and decreased during second period. In terms of spatial configuration, Gümüşhane forests aren't generally fragmented by intensive forest utilization in the latter periods. This is partially due to out-migration of rural population in Gümüşhane. Nevertheless, land use pattern significantly changed over time depending on a few factors such as unregulated management actions, social pressure and demographic movements. The study revealed that demographic movements have a major effect on landscape dynamics.

The mangrove formations of Godavari estuary are due to silting over many centuries. The estuary covers an area of 62,000 ha of which dense Coringa mangrove forest spread in 6,600 ha. Satellite sensor data was used to detect change in the mangrove cover for a period of 12 years (1992-2004). It was found that an area of about 1,250 ha of mangroves was destroyed by anthropogenic interference like aquaculture, and tree felling etc. It was found that mangrove's spectral response/digital number (DN) value is much lower than non-mangrove vegetation such as plantation and paddy fields in SWIR band. By taking this as an advantage, spectral data was utilized for clear demarcation of mangroves from nearby paddy fields and other vegetation. Simpson's diversity index, which is a measure of biodiversity, was found to be 0.09, showing mangroves dominance. Ecological parameters like mud-flats/swamps, mangrove cover alterations, and biodiversity status are studied in detail for a period of 12 years. The increase in mangrove front towards coast was delineated using remote sensing data. The major advantages of remote sensing data is monitoring of change periodically. The combination of moderate and high-resolution data provided detailed coastal land use maps for implementing coastal regulation measures. The classification accuracy has been achieved is 90%. Overall, simple and viable measures are suggested based on multi-spectral data to sustain this sensitive coastal ecology.

Land use change resulted in land degradation is a focus of research on global environmental changes and plays a significant role in the stability and economic development of oases in arid regions of China. Jinta Oasis, a typical oasis of temperate arid zone in northwestern China, was investigated to assess land-use change dynamics during 1988-2003 with the aid of satellite remote sensing and GIS, and to explore the interaction between these changes and oasis environment. Six land-use types were identified, namely: cropland, forestland, grassland, water, urban or built-up land, and barren land. The results indicate that cropland, urban/built-up land, and barren land increase greatly by 30.03, 13.35, and 15.52 km(2), respectively; but grassland and forestland areas decrease rapidly by 58.06, and 1.76 km(2), respectively. These results also show that obvious widespread changes in land-use occur within the whole oasis over the study period and result in severe problems of environmental degradation (i.e. land desertification, decline of groundwater, and vegetation degeneracy).

Ecological security has become so important that it will affect the national security and social sustainable development. In this paper, a case study on the ecological security indexes of modern oasis landscapes in Beitun Oasis, Xinjiang, was carried out. The spatial neighbouring parameters, such as the contiguous length, measure of area and patch quantity of oasis landscape patches, affected by desert landscape patches were calculated by using GIS-based buffer analysis, the method of calculating ecological security indexes of oasis landscape was developed, and the dynamic changes of patterns and ecological security indexes of the oasis landscapes since recent 30 years were analyzed. The results showed that soil salinization or alkalization and paludification were major factors affecting the ecological security in Beitun Oasis. Therefore, measures should be taken actively to prevent and control secondary salinization and paludification. The ecological security indexes of the oasis landscape in 1972, 1990 and 2005 were 78.91, 82.28 and 83.86, respectively, which showed the degree of security is improving, and the environment was developing harmoniously between human and nature. The methods of evaluating ecological security based on the spatial neighbouring relations between landscape patches can be used to reflect preliminarily the ecological security patterns of landscapes.

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).

In this study, we present the digital evaluation of Landsat TM data and field spectral measurements for retrieving chlorophyll-a (chl-a) concentration and trophic state index in Lake Chagan of Northeast China. Chl-a concentration of the lake can be estimated from the band ratio (TM4/TM3) and the field spectral data at 670 nm (absorption peak) and at 700 nm (reflectance peak). The results show that the best determination coefficient (R (2)) is 0.67 from the TM data, by which chl-a distribution can be mapped. Based on chl-a determination from laboratory analysis, field spectral and TM data, the modified trophic state index (TSI(M)) was applied to assess the lake's trophic state. With the available data in Lake Chagan, each algorithm demonstrates the similar result for assessing the lake's chl-a and trophic state. Our results indicate that Landsat TM and field spectral data could be used effectively to determine chl-a concentration and evaluate the trophic state of Lake Chagan in the study.

Fires are one of the major causes of forest disturbance and destruction in several dry deciduous forests of southern India. In this study, we use remote sensing data sets in conjunction with topographic, vegetation, climate and socioeconomic factors for determining the potential causes of forest fires in Andhra Pradesh, India. Spatial patterns in fire characteristics were analyzed using SPOT satellite remote sensing datasets. We then used nineteen different metrics in concurrence with fire count datasets in a robust statistical framework to arrive at a predictive model that best explained the variation in fire counts across diverse geographical and climatic gradients. Results suggested that, of all the states in India, fires in Andhra Pradesh constituted nearly 13.53% of total fires. District wise estimates of fire counts for Andhra Pradesh suggested that, Adilabad, Cuddapah, Kurnool, Prakasham and Mehbubnagar had relatively highest number of fires compared to others. Results from statistical analysis suggested that of the nineteen parameters, population density, demand of metabolic energy (DME), compound topographic index, slope, aspect, average temperature of the warmest quarter (ATWQ) along with literacy rate explained 61.1% of total variation in fire datasets. Among these, DME and literacy rate were found to be negative predictors of forest fires. In overall, this study represents the first statewide effort that evaluated the causative factors of fire at district level using biophysical and socioeconomic datasets. Results from this study identify important biophysical and socioeconomic factors for assessing 'forest fire danger' in the study area. Our results also identify potential 'hotspots' of fire risk, where fire protection measures can be taken in advance. Further this study also demonstrate the usefulness of best-subset regression approach integrated with GIS, as an effective method to assess 'where and when' forest fires will most likely occur.

In this paper we discuss a pilot study where we have mapped urban air pollution using mobile carbon monoxide (CO) sensors. Our objective is to use inexpensive Global Positioning System (GPS) receivers to track the sensors and explore CO variations at a fine geographic scale. The critical issue in data processing is the treatment of the imprecise logs from the GPS. By using knowledge about the route and the geometry of the buildings, we are able to increase the position accuracy significantly, while at the same time showing that certain events, such as CO profiles while crossing roads, can be detected with a high degree of accuracy. Comparisons between data from our own mobile sensors and a fixed sensor site show good agreement in the vicinity of the fixed sensor, while at the same time identifying significant CO peaks within 100 m of this location. Using the mobile sensors to collect data along two of the main roads in the area, we are able to show CO variations along an urban canyon for parallel and perpendicular wind directions. Finally, a number of significant sources of CO were discovered during the course of the study, which suggest possible locations for fixed sensor sites in the future. We conclude by discussing the results in the context of the push towards large sensor networks and mobile communications. The potential for ad hoc mobile sensor networks may be very large.

Water quality monitoring using remote sensing has been studied in Finland for many years. But there are still few discussions on water quality monitoring using remote sensing technology in support of water policy and legislation in Finland under the WFD. In this study, we present water quality monitoring using remote sensing in the Gulf of Finland, and focus on the spatial distribution of water quality information from satellite-based observations in support of water policy by a case study of nitrate concentrations in surface waters. In addition, we briefly describe instruments using a system of river basin districts (RBD), highlighting the importance of integrated water resources and river-basin management in the WFD, and discuss the role of water quality monitoring using remote sensing in the implementation of water policy in Finland under the WFD.

Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

Monitoring environmental processes is becoming increasingly important wherever there is increasing population and economic development pressure placed on fragile environments. Remote sensing, digital image processing, and spatial analysis have proven to be useful technologies in both assessing and monitoring environmental change. In this study, they were used to assess desertification processes and change in Minqin County, China from 1988 to 1997. The results suggest that wind erosion was the dominant cause of desertification in more than half of the study area. Coupled with this were increases in salinization processes, affecting 33.62% of the land area in 1997. Overall, moderate desertification was found to be the dominant desertification grade (43.64% of total area), followed by extreme/severe desertification (26.15% of total area) in 1997. In addition, examination of landscape pattern changes indicated that desertification processes at the landscape level were becoming evident at increasing levels of fragmentation, complexity in shape, and isolation of patches. Major fluctuations in desertification type and grade were found at the fringes of oases, where an ongoing shift was taking place between cultivation, abandonment, and reclamation.

The temporal turbidity and surface temperature changes and effects of the 17 August 1999 earthquake in the Izmit Gulf, Turkey have been investigated using Landsat TM/ETM data. The gulf is in the Mediterranean-Black Sea transition climatic zone and is partially surrounded by green vegetation cover and degraded and densely urbanized-industrialized areas. Landsat TM/ETM data acquired in 1990-1999 confirms increase in turbidity. Turbidity is always low in the southern part and high in the northern part of the gulf, because the more urbanized and industrialized areas are located in the northern part. The Landsat-7 ETM data acquired in the same year (1999) shows seasonal changes in turbidity. Moreover, the two high turbidity and surface temperature anomalies, one of which is parallel to the 17 August 1999 earthquake surface rupture (east-west) and the other which is in the northwest-southeast direction were mapped from Landsat-5 TM data acquired the day (18.08.1999) following the earthquake in the east end of the gulf. On the basis of turbidity implying the sea bottom movement, it is possible to state that a second rupture in the northwest and southeast direction could have occurred at the sea bottom during the earthquake. The distribution of the seismicity centers and the orientation of the lineaments in the area support this finding.

Knowledge and detecting impacts of human activities on the coastal ecosystem is an essential management requirement and also very important for future and proper planning of coastal areas. Moreover, documentation of these impacts can help in increasing public awareness about side effects of unsustainable practices. Analysis of multidate remote sensing data can be used as an effective tool in environmental impact assessment (EIA). Being synoptic and frequent in coverage, multidate data from Landsat and other satellites provide a reference record and bird's eye viewing to the environmental situation of the coastal ecosystem and the associated habitats. Furthermore, integration of satellite data with field observations and background information can help in decision if a certain activity has caused deterioration to a specific habitat or not. The present paper is an attempt to utilize remote sensing data for assessment impacts of some human activities on the major sensitive habitats of the NW Egyptian Red Sea coastal zone, definitely between Ras Gemsha and Safaga. Through multidate change analysis of Landsat data (TM & ETM+ sensors), it was possible to depict some of the human infringements in the area and to provide, in some cases, exclusive evidences for the damaging effect of some developmental activities.

The Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

Landsat 7’s recent malfunctioning will result in significant gaps in long-term satellite monitoring of Earth, affecting not only the research of the Earth science community but also conservation users of these data. To determine whether or how important Landsat monitoring is for conservation and natural resource management, we reviewed the Landsat program’s history with special emphasis on the development of user groups. We also conducted a bibliographic search to determine the extent to which conservation research has been based on Landsat data. Conservation biologists were not an early user group of Landsat data because a) biologists lacked technical capacity – computers and software – to analyze these data; b) Landsat’s 1980s commercialization rendered images too costly for biologists’ budgets; and c) the broad-scale disciplines of conservation biology and landscape ecology did not develop until the mid-to-late 1980s. All these conditions had changed by the 1990s and Landsat imagery became an important tool for conservation biology. Satellite monitoring and Landsat continuity are mandated by the Land Remote Sensing Act of 1992. This legislation leaves open commercial options. However, past experiments with commercial operations were neither viable nor economical, and severely reduced the quality of monitoring, archiving and data access for academia and the public. Future satellite monitoring programs are essential for conservation and natural resource management, must provide continuity with Landsat, and should be government operated.

Management of coral reef resources is a challenging task, in many cases, because of the scarcity or inexistence of accurate sources of information and maps. Remote sensing is a not intrusive, but powerful tool, which has been successfully used for the assessment and mapping of natural resources in coral reef areas. In this study we utilized GIS to combine Landsat TM imagery, aerial photography, aerial video and a digital bathymetric model, to assess and to map submerged habitats for Alacranes reef, Yucatán, México. Our main goal was testing the potential of aerial video as the source of data to produce training areas for the supervised classification of Landsat TM imagery. Submerged habitats were ecologically characterized by using a hierarchical classification of field data. Habitats were identified on an overlaid image, consisting of the three types of remote sensing products and the bathymetric model. Pixels representing those habitats were selected as training areas by using GIS tools. Training areas were used to classify the Landsat TM bands 1, 2 and 3 and the bathymetric model by using a maximum likelihood algorithm. The resulting thematic map was compared against field data classification to improve habitats definition. Contextual editing and reclassification were used to obtain the final thematic map with an overall accuracy of 77%. Analysis of aerial video by a specialist in coral reef ecology was found to be a suitable source of information to produce training areas for the supervised classification of Landsat TM imagery in coral reefs at a coarse scale.

The present study outlines an approach to classify forest density and to estimate canopy closure of the forest of the Andaman and Nicobar archipelago. The vector layers generated for the study area using satellite data was validated with the field knowledge of the surveyed ground control points. The methodology adopted in this present analysis is three-tiered. First, the density stratification into five zones using visual interpretation for the complete archipelago. In the second step, we identified two island groups from the Andaman to investigate and compare the forest strata density. The third and final step involved more of a localised phytosociological module that focused on the North Andaman Islands. The results based on the analysis of the high-resolution satellite data show that more than 75% of the mangroves are under high- to very high-density canopy class. The framework developed would serve as a significant measure to forest health and evaluate management concerns whilst addressing issues such as gap identification, conservation prioritisation and disaster management--principally to the post-tsunami assessment and analysis.

Today, as a result of erratic and unplanned urbanization, towns are rapidly becoming a mass of concrete and town-dwellers are suffocated by their busy and stressful professional lives. They feel a need for places where they can find breathing-space in their free time. Green areas within towns are important spaces where townspeople are able to carry out recreational activities. These places form a link between townspeople and nature. The importance of urban green areas is increasing with every passing day due to their social, psychological, ecological, physical and economic functions and their impact on the quality of towns. In this study it has been attempted to demonstrate the pressures of urban development on agricultural land by determining the changing land use situation over the years in the district of Akhisar. In this research, an aerial photograph from year 1939 and satellite images of the town from the years 2000 and 2007 were used. Land use changes in the region were determined spatially. As a result of this study, which aims to determine in which direction urbanization is progressing in the district, the importance of town planning emerges. This study will be informative for the local authorities in their future town planning projects. With its flat and almost flat fertile arable land, the district of Akhisar occupies an important position within the province of Manisa. From the point of view of olive production the region is one of Turkey's important centres. Fifty-five percent of the olive production in the province of Manisa is realized in Akhisar. However, the results of the present study show that while agricultural areas comprised 2.5805 km(2) in 1939, these had diminished to 1.5146 km(2) in the year 2000 and had diminished to 1.0762 km(2) in the year 2007 and residential area (dense) 0.449 km(2) occupied in 1939, in the year 2000 this had risen to 1.9472 and 2.3238 km(2) in the year 2007. This planless urbanization in the study area has led to great losses of farmland.

Land use and land cover change is gaining recognition as a key driver of environmental change. Rapid change of land use has occurred in the red soil hilly region of southeast China in the past three decades due to rural land reform, population pressure and rapid economic growth. In this paper, land use change and its impacts on environmental quality of Xianning County were investigated using technologies of remote sensing (RS), geographic information systems (GIS), and spatial principal components analysis (SPCA). It was indicated that the area of paddy field and upland decline rapidly while the area of woodland, horticulture farm and residential land increased sharply between 1978 and 2002. The driving forces probably were land use policy of the State government, structural adjustment of agricultural sectors and implementation of environmental conservation measures. Based on the assessment of environmental implications of land use practices, the environmental quality of some land use types (i.e. Woodland, sparse woodland, and paddy field) tended to improve, while horticulture farms, water body, and residential land showed a deterioration trend of environmental quality during 1978-2002. Perhaps the most significant finding of this study is that environment appears a negative tendency in the study area from 1991 to 2002, because little attention has been paid to the status and management of agricultural lands, which account for a substantial proportion of total land area. Therefore, for further improving environment in red soil hilly region in China, urgent action is required to improve the advisory services support to farmers on new tillage practices, soil and water conservation practices, raising the efficiency of fertilizer and manure use.

This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.

WOS: 000272615400036, PubMed ID: 19083107, The main objective of this study is to generate a knowledge base which is composed of user-defined variables and included raster imagery, vector coverage, spatial models, external programs, and simple scalars and to develop an expert classification using Landsat 7 (ETM+) imagery for land cover classification in a part of Trabzon city. Expert systems allow for the integration of remote-sensed data with other sources of geo-referenced information such as land use data, spatial texture, and digital elevation model to obtain greater classification accuracy. Logical decision rules are used with the various datasets to assign class values for each pixel. Expert system is very suitable for the work of image interpretation as a powerful means of information integration. Landsat ETM data acquired in the year 2000 were initially classified into seven classes for land cover using a maximum likelihood decision rule. An expert system was constructed to perform post-classification sorting of the initial land cover classification using additional spatial datasets such as land use data. The overall accuracy of expert classification was 95.80%. Individual class accuracy ranged from 75% to 100% for each class.

This study focused on the prediction of a 22 km meandering channel migration of the Sabine River between the states of Texas and Louisiana. The meander characteristics of 12 bends, identified from seven orthophotos taken between 1974 and 2004, were acquired in a GIS environment. Based on that earlier years' data acquisition, channel prediction was performed for the two years 1996 and 2004 using least squares estimation and linear extrapolations, yielding a satisfactory agreement with the observations (the median predicted and observed migration rates were 3.1 and 3.6 [m/year], respectively). The best-predicted migration rate was found to be associated with the longest orthophoto-recorded interval. The study confirmed that channel migration is strongly correlated with bend curvature and that the maximum migration rate of the bend corresponded to a radius of curvature [bend radius (R(C))/channel width (W(C))] of 2.5. In tight bends of a smaller radius of curvature than 1.6, secondary flow scouring near the bend apex increases bend curvature. The stability index of the dimensionless bend radius was determined to be 2.45. Overall, this study proves the effectiveness of least squares estimation with historical orthophotography for characterization of meandering channel migration.

Managing natural resources in wide-scale areas can be highly time and resource consuming task which requires significant amount of data collection in the field and reduction of the data in the office to provide the necessary information. High performance LiDAR remote sensing technology has recently become an effective tool for use in applications of natural resources. In the field of forestry, the LiDAR measurements of the forested areas can provide high-quality data on three-dimensional characterizations of forest structures. Besides, LiDAR data can be used to provide very high quality and accurate Digital Elevation Model (DEM) for the forested areas. This study presents the progress and opportunities of using LiDAR remote sensing technology in various forestry applications. The results indicate that LiDAR based forest structure data and high-resolution DEMs can be used in wide-scale forestry activities such as stand characterizations, forest inventory and management, fire behaviour modeling, and forest operations.

WOS: 000261581800021 PubMed: 18214696 Land quality assessment is of great important for decisions on sustainable land uses and the conservation of ecosystems of high biodiversity value. The main objective of this study was to determine properties of land quality of specially protected area of the Salt Lake using CORINE land quality assessment methodology and to propose a revision for this model. In addition to field study and laboratory analysis, digital soil map, digital elevation model, satellite image and climatic data were used and analyzed with remote sensing and geographic information systems techniques to generate actual land quality map and to form database for study area. Results show that 42.1% of the study area has high quality, 28.7% was classified as moderate quality and 4.0% was determined as low quality. On the other hand, some places classified as moderate quality, were not accurately classified. These places should be low land quality due to content of high salt concentration. Therefore, to resolve this insufficient situation, some soil parameters such as chemical properties should be collaborated with this model. In this case, moderate land quality level of the study area decreased from 28.7 to 12.3%, whereas 4.0% of low quality land of the study area increased to 20.8%. In addition, this research was also carried out to provide guidance for planner or decision makers about specially protected area of the Salt Lake. Organization of Authority from Protection of Special Areas; General Directory of Rural Services-Ankara Research InstituteGida Tarim Ve Hayvancilik Bakanligi This research was funded by the Organization of Authority from Protection of Special Areas, and General Directory of Rural Services-Ankara Research Institute. This article has benefited from valuable contribution of Suat AKGUL, Fatma ELBASI, Dilek YATMAN during GIS process. I am thankful to each of them.

A landscape index LI is proposed to evaluate the intensity of the daytime surface urban heat island (SUHI) effect at a local scale. Three aspects of this landscape index are crucial: the source landscape, the sink landscape, and the contribution of source and sink landscapes to the intensity of the SUHI. Source and sink landscape types are identified using the thermo-band of Landsat 7 with a spatial resolution of 60 m, along with appropriate threshold values for the Normalized Difference Vegetation Index, Modified Normalized Difference Water Index, and Normalized Difference Built-up Index. The landscape index was defined as the ratio of the contributions of the source and sink landscapes to the intensity of the SUHI. The intensity of the daytime SUHI is assessed with the help of the landscape index. Our analysis indicates the landscape index can be used to evaluate and compare the intensity of the daytime SUHI for different areas.