Advanced Spaceborne Thermal Emission And Reflection Radiometer Digital Elevation Model Research Articles

Locating Potential Run-of-River Hydropower Sites by Developing Novel Parsimonious Multi-Dimensional Moving Window (PMMW) Algorithm with Digital Elevation Models

We developed a Parsimonious Multi-dimensional Moving Window (PMMW) algorithm that only requires Digital Elevation Model (DEM) data of a watershed to efficiently locate potentially optimal hydropower sites. The methodology requires only open source DEM data; therefore, it can be used even in remotest watersheds of the world where in situ measurements are scarce or not available at all. We used three parameters in this algorithm, and tested the method using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Shuttle Radar Topography Mission (SRTM) derived DEMs. Our case study on the Morony Watershed, Montana, USA shows that (1) along with 6 out of the 7 existing hydropower plants being successfully located, 12 new potential hydropower sites were also identified, using a clearance of 1 km, diversion of 90 m, and Hydropower Index (HI) threshold of 109 m as the criteria. For the 12 new potential hydropower sites, 737.86 Megawatts (MW) ± 84.56 MW untapped hydropower potential in the Morony Watershed was also derived; (2) SRTM DEM is more suitable for determining the potential hydropower sites; (3) although the ASTER and SRTM DEMs provide elevation data with high accuracy, micro-scale elevation differences between them at some locations may have a profound impact on the HI.

Mapping the spatial distribution of fossil geothermal manifestations and assessment of geothermal potential of the Tangyin rift, Southeast of Taihang Mountain in China

The spatial prediction of geothermal sites along the southeast side of Taihang Mountain in the Tangyin rift is a critical goal in the development of renewable energy resources in cities such as Hebi in Henan province, which has significant potential for geothermal energy production due to the existence of deep faults and Cenozoic volcano. The study aimed to delineate areas with high geothermal manifestations for detailed geothermal exploration and well-test drilling. To define favorable zones for geothermal potentiality, multi-source datasets were chosen to generate evidence thematic layers that demonstrate the distribution of geothermal anomalies such as geologic maps, structural maps, Land Surface Temperature maps (LST), and hydrothermal mineral alterations maps. The remote sensing and Geographical Information System (GIS) approaches were integrated to map fossil geothermal manifestations and appraise the promising geothermal zones from Landsat 8 OLI/TIRS and Advanced Spaceborne Thermal Emission and Reflection Radiometer-Digital Elevation Model (ASTER-DEM) dataset using the Analytic Hierarchy Process (AHP), which is one of the Mult-criteria Decision Making methods. Results show LST values ranging from 22.6°C to 45.4°C, with the highest values found along the faults and volcanic areas. The hydrothermal alteration minerals discriminated from band ratios of 4/2, 6/5, and 6/7 for iron oxide, ferrous minerals, and clays reveal the presence of high amount of montmorillonite and illite minerals along the faults and volcanoes which are related to hot fluid circulation from subsurface. Structural analysis shows that the major structural trend follows the NNE Tangdong and Tangxi faults, with high density on the west side of the Tangxi fault where there is good exposure of outcrop but less fault density on the east side due to sedimentation in a low land which may conceal geological structures. Lastly, all the thematic layers of geothermal factors were reclassified, ranked, and integrated by the weight overlay logic model based on the influence of geothermal suitability to map potential areas for geothermal resources whereby 5 zones were obtained ranging from very poor to very good. The promising potential sites are mostly found along the highly deep structures of the major Tangxi fault crosscutting the permeable lithology of carbonate rocks and around the Hebi volcanoes. The distribution of hot springs and geothermal wells of the Hebi field were correlated and verified against the potential geothermal anomalies map. The overall integrated method proposes an advanced technique for designing the Tangyin rift’s exploration plan and development actions for geothermal resources utilization, which can be used for exploration of any unveiling geothermal potential sites.

Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model (DEM) data. The unique terrain characteristics of a particular landscape are derived from DEM, which are responsible for initiation and development of ephemeral gullies. As the topographic features of an area significantly influences on the erosive power of the water flow, it is an important task the extraction of terrain features from DEM to properly research gully erosion. Alongside, topography is highly correlated with other geo-environmental factors i.e. geology, climate, soil types, vegetation density and floristic composition, runoff generation, which ultimately influences on gully occurrences. Therefore, terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility (GES) mapping. In this study, remote sensing-Geographic information system (GIS) techniques coupled with machine learning (ML) methods has been used for GES mapping in the parts of Semnan province, Iran. Current research focuses on the comparison of predicted GES result by using three types of DEM i.e. Advanced Land Observation satellite (ALOS), ALOS World 3D-30 m (AW3D30) and Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) in different resolutions. For further progress of our research work, here we have used thirteen suitable geo-environmental gully erosion conditioning factors (GECFs) based on the multi-collinearity analysis. ML methods of conditional inference forests (Cforest), Cubist model and Elastic net model have been chosen for modelling GES accordingly. Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods (Cforest = 21.4, Cubist = 19.65 and Elastic net = 17.08), followed by lithology and slope. Validation of the model’s result was performed through area under curve (AUC) and other statistical indices. The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs (AUC value of Cforest in ALOS DEM is 0.994, AW3D30 DEM is 0.989 and ASTER DEM is 0.982) used in this study, followed by elastic net and cubist model. The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.

Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs

Soil erosion is a key concern for the environment and natural resources since it leads to a decline in-field productivity and soil quality, resulting in land degradation. In this study, assessment of uncertainty in soil erosion modelling of the Karso watershed, India, was carried out by employing the revised universal soil loss equation (RUSLE) and geospatial technologies to evaluate the effect of multi-source digital elevation models (DEMs) [Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Cartosat and Shuttle Radar Topography Mission (SRTM)] with resampled multi-resolution grids. The rainfall erosivity factor (R) was computed using the mean monthly Tropical Rainfall Measuring Mission rainfall estimates for 1998 to 2012. The slope length factor was derived using the ASTER and Cartosat DEMs at grid sizes of 30 m, 50 m, 100 m, 150 m, 200 m, and 250 m, and for the SRTM DEM at 100 m, 150 m, 200 m and 250 m resolutions for the Karso watershed, Jharkhand, India. Significant differences were obtained in the soil loss estimates across the different DEM sources and resampled grid sizes. The Cartosat DEM with a 200 m grid was found to estimate the soil loss the best out of all the DEM combinations considered. The Cartosat DEM proved to be more reliable than the ASTER and SRTM DEMs. The results indicated that the RUSLE is a scale-dependent model since the model estimates were affected not only by the DEM source but also by its resolution. The prediction of erosion potential by employing the multisource, multiresolution DEMs and the RUSLE helped to identify the soil erosion's spatial pattern within the watershed. The study provided an impact analysis of the uncertainties when selecting the multisource, multiresolution DEMs for soil erosion modelling.

Comparison of LiDAR-based morphometric analysis of a drainage basin with results obtained from UAV, TOPO, ASTER and SRTM-based DEMs

Morphometric parameters are important elements in water and land resource management studies. In this study, 23 morphometric parameters of drainage networks were extracted using a Shuttle Radar Topography Mission (SRTM)–based digital elevation model (DEM), an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)–based DEM, a 1:25,000 scale topographical map (TOPO)–based DEM, an unmanned aerial vehicle (UAV) –based DEM and an airborne light detection and ranging (LiDAR)–based DEM. Generally, LiDAR sensors provide more accurate results than other DEM sources, and for that reason, we used LiDAR-based DEM data as a reference for comparing results of analyses made by the other DEM sources. According to the results, as resolution increases, many morphometric parameter values also tend to increase. In addition, for all of the morphometric parameter values (basic, derived and shape), the values obtained using the TOPO, UAV, ASTER and SRTM DEMs closely resembled the values obtained using LiDAR DEM-based parameters.

GIS-based geomorphometric analysis for potential applications in reversing land and biosystem degradation.

Watershed morphometric assessment is about measurements and calculations of land surface forms for the purpose of understanding hydro-geomorphological character and patterns. Important natural environment geo-information and summary of the spatial characteristics of Tana River Basin (TRB) in Kenya have been obtained through hydro-geomorphometric analysis. Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model (ASTERDEM) data and ArcGIS (ESRI Inc., version 10.4.1) together with published mathematical equations were applied to extract morphometric parameters of the drainage basin, which covers a total area of 94,930 km2 and a span of 527.75 km. The quantitative morphometric analysis considered a total of 28 relief, areal, and linear hydro-morphometric characteristics of the TRB. Relief parameters of the basin suggest moderate-to-low overall watershed steepness, upland with rolling land surface patterns, rugged landforms susceptible to erosion and sediment transportation, and a landscape in evolution process tending towards maturity. This means stability of the land surface can be attained with intensive land degradation reversing strategies like erosion control measures. Areal characteristics further support the basin's susceptibility to erosion as shown by stream length, stream drainage density, and circulatory ratio values. Also, the areal aspects portray peak runoffs with short duration flashes. Linear parameter value results such as bifurcation ratio imply that infiltration capacity varies with stream orders across the watershed. This hydro-geomorphometric analysis would be useful to land and water managers, researchers and practitioners of TRB, and other similar systems in designing and planning soil and water conservation and management practices such as soil erosion control, groundwater recharge activities, catchment modelling, runoff and flood studies, prospecting groundwater mapping, and biological applications.

HYDROLOGIC ASSESSMENT OF FOOD USING SWAT AS GEOSPATIAL TECHNIQUES IN THE CATCHMENT AREA OF TERENGGANU MALAYSIA

Risks and hazards are two important issues currently threatening humanity and the environment. Flood has claimed many lives and destroyed properties in Malaysia and Africa and Nigeria. It is global catastrophe. The application of geospatial science is, therefore, very important advantages that it offers solutions to flood. This stud uses of Advanced Space-borne Thermal Emission and Reflection Radiometer Digital Elevation Model (ASTER-DEM), and the Soil Water Assessment Tool (SWAT) in visualizing floods disaster risk. The whole catchment area of Terengganu has been delineated. The 25 sub-basins have been identified and the flood risk zones have been modeled. The complete watersheds are characterized by different sub-basins and Hydrologic Respond Units (HRUs) which can be viewed in 3D environment.

Using remote sensing techniques to interpret geomorphological features along the east coast of the Red Sea, at Yanbu, Saudi Arabia

Yanbu is the second largest port and population settlement on the Saudi Arabian Red Sea coast. With the increasing development of its nearby coast, the geomorphological characteristics of the region must be studied in detail in order to inform future developments of the region. This study examines the region’s suitability for future development. A high-resolution map of the coastal area under study was drawn by analysing Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) data and Advanced Spaceborne Thermal Emission and Reflection Radiometer-Digital Elevation Model (ASTER-DEM) data, using remote sensing images from Landsat satellites. Landsat ETM+ images taken in 2000 and 2015, alongside remote sensing analyses, field observations, and geological mapping, were used to describe the geomorphological and topographical characteristics of the Yanbu coast. Both principal component analysis (PCA) and false colour composite (FCC) were the most effective remote sensing techniques for mapping the geomorphological characteristics of the coastal plain. The true colour of the combination bands 3, 2, and 1 was the best at showing the areas and features of coral reefs. Thus, the main geomorphological units in the study area were identified, including wadi systems, dunes, alluvial fans and fan deltas, fluvial terraces, sabkhas, coral reefs, platform reefs, islands, sharms, and sea heads.

Performance Assessment of TanDEM-X DEM for Mountain Glacier Elevation Change Detection

TanDEM-X digital elevation model (DEM) is a global DEM released by the German Aerospace Center (DLR) at outstanding resolution of 12 m. However, the procedure for its creation involves the combination of several DEMs from acquisitions spread between 2011 and 2014, which casts doubt on its value for precise glaciological change detection studies. In this work we present TanDEM-X DEM as a high-quality product ready for use in glaciological studies. We compare it to Aerial Laser Scanning (ALS)-based dataset from April 2013 (1 m), used as the ground-truth reference, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) V003 DEM and SRTM v3 DEM (both 30 m), serving as representations of past glacier states. We use a method of sub-pixel coregistration of DEMs by Nuth and Kääb (2011) to determine the geometric accuracy of the products. In addition, we propose a slope-aspect heatmap-based workflow to remove the errors resulting from radar shadowing over steep terrain. Elevation difference maps obtained by subtraction of DEMs are analyzed to obtain accuracy assessments and glacier mass balance reconstructions. The vertical accuracy (± standard deviation) of TanDEM-X DEM over non-glacierized area is very good at 0.02 ± 3.48 m. Nevertheless, steep areas introduce large errors and their filtering is required for reliable results. The 30 m version of TanDEM-X DEM performs worse than the finer product, but its accuracy, −0.08 ± 7.57 m, is better than that of SRTM and ASTER. The ASTER DEM contains errors, possibly resulting from imperfect DEM creation from stereopairs over uniform ice surface. Universidad Glacier has been losing mass at a rate of −0.44 ± 0.08 m of water equivalent per year between 2000 and 2013. This value is in general agreement with previously reported mass balance estimated with the glaciological method for 2012–2014.

Comparative analysis of lineaments extracted from Cartosat, SRTM and ASTER DEM: a study based on four watersheds in Konkan region, India

In this study, lineaments have been extracted from Cartosat, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Shuttle Radar Topographic Mission (SRTM) Digital Elevation Models (DEM) of different spatial resolution. The extracted lineaments were analysed to understand which DEM is most suitable for extraction of lineaments accurately. The results have shown that maximum number of lineaments can be extracted by using Cartosat DEM while ASTER DEM provides lowest number of lineaments. As a result of this study, it is suggested to make use of Cartosat DEM for the extraction of lineaments in Indian territory (data is only available for India), because it provides the most detailed geological information among all the datasets. Cartosat DEM is also suitable for studying very small areas as detailed surface information can be extracted by using this data. SRTM DEM can be used for countries other than India, and it has the capability to deliver moderate structural information. Likewise, SRTM data is more suitable for a large study area. ASTER DEM is not recommended for the study of structural and geological surface features because most of the features cannot be extracted and the result could not be applied in the detailed geological study.

COMPARISON OF ASTER AND SRTM DIGITAL ELEVATION MODELS AT ONE-ARC-SECOND RESOLUTION OVER TURKEY

In February 2000, the “Shuttle Radar Topography Mission (SRTM)” satellite captured elevation data by scanning the Earth landmasses between the 60 o North and South latitudes. After the mission of 11 days, the collected data were processed, and a Digital Elevation Model (DEM) within one arc-second resolution for United States and three arc-second resolutions for the other parts of the globe was created and published on the NASA servers. Recently, a global SRTM DEM with one-arc-second resolution has been released. Additionally, ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) is a sensor boarded on the Terra satellite in 1999. The sensor has been collecting satellite imagery since 2000. The ASTER GDEM at one-second resolution was released to the public, which is the most complete DEM of the earth ever made. In this study, SRTM and ASTER DEMs with one arc-second resolution over Turkish territory was evaluated by means of a local DEM produced from 1:25K national topographic maps. Results show that the accuracy of the SRTM DEM is better than the ASTER GDEM with respect to the local DEM.

The causes and mechanisms of rain-induced highway and pavement collapse in Obolo-eke, Southeast Nigeria

Majority of highway failures in Nigeria occur during or immediately after heavy rainfall. Although rapid rise in pore water pressure is usually adduced as the major factor leading to these failures, the mechanisms that initiate or propagate the failures have not been adequately clarified. To investigate these mechanisms, a series of laboratory experiments, detailed field survey and digital elevation model produced from Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) digital elevation models (DEM) were integrated to investigate the failure processes on the unconsolidated sandy terrains where failures were common. The study area is underlain by loosely consolidated, moderately sorted sandstone sequence and shale intercalations. Results of the ASTER DEM clearly revealed the topographic, geomorphic, and hydrologic features associated with instability and showed that streams played key roles in the failure processes. While many collapsed portions were observed where rivers were close to the highway, there were no failures on the parts far from the streams. Field analysis showed that the failures were restricted to only the portions of the highway with damaged man-made drainage systems. The broken drainages probably facilitated saturation and erosion of the underlying sediments. The liquefaction resistance of the saturated sediments was weakened and transient surface flows arising from prolonged rainfall initiated failure. The rapid post-failure strength reduction and the low steady-state strength suggested the sediments were liquefiable. The results showed that a good drainage system can serve as an effective preventive measure for protecting engineering structures on collapsible sands.

Comparison of basin morphometry derived from topographic maps, ASTER and SRTM DEMs: an example from Kerala, India

The drainage network of a sixth-order tropical river basin, viz. Ithikkara river basin, was extracted from different sources such as Survey of India topographic maps (1: 50,000; TOPO) and digital elevation data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (30 m) and Shuttle Radar Topography Mapping Mission (SRTM) (90 m). Basin morphometric attributes were estimated to evaluate the accuracy of the digital elevation model (DEM)-derived drainage networks for hydrologic applications as well as terrain characterization. The stream networks derived from ASTER and SRTM DEMs show significant agreement (with slight overestimation of lower order streams) with that of TOPO. The study suggests that SRTM (despite the coarser spatial resolution) provides better results, in drainage delineation and basin morphometry, compared to ASTER. Further, the variability of basin morphometry among the data sources might be attributed to spatial variation of elevation, raster grid size and vertical accuracy of the DEMs as well as incapability of the surface hydrologic analysis functions in the GIS platform.

Effect of ASTER DEM on the prediction of mean gravity anomalies: a case study over the Auvergne test region

A precise gravimetric geoid determination requires height information and terrestrial gravity data with high accuracy and resolution. The height data is utilized for predicting mean free-air gravity anomalies as well as computing the topographic, atmospheric and downward continuation effects which are fundamental components of any geoid model. Nowadays the Digital Elevation Model (DEM) obtained from the Shuttle Radar Topography Mission (SRTM) has been widely used when an accurate regional DEM does not exist. In addition the DEM generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) was newly released by researchers from Japan and United States. In this study the effect of ASTER DEM on the estimating mean free-air gravity anomalies in geoid determination were investigated in the Auvergne test area where one of its regions exhibits one of the most rugged topography over the world. The numerical results show that ASTER DEM gives worse statistics than SRTM DEM with respect to the accuracy of the height. Using ASTER DEM introduces discrepancies (compared to SRTM DEM) in the range of \(-\)4 to 10 mGal in the interpolation of free-air gravity anomalies. It is also proven that the geoid differences due to the use of ASTER DEM are a few centimeters, which remain below the accuracy level of the external GPS-levelling data.

Impact of uncertainty in remote sensing DEMs on topographic amplification of seismic response and Vs 30

Impact of topography on spatial variation of seismic response is well-observed synthetically, experimentally, and visually during seismic events. Numerical and experimental investigations for predicting topographic impact on seismic response are often limited to isolated and/or synthetic hills and ridges. Furthermore, most of these studies only focus on one of the many terrain parameters necessary for evaluating the impact of topographic features on amplification or de-amplification of seismic response. Seismic events located in rough terrain, like the 2005 Kashmir earthquake in northern Pakistan, exhibit intensified seismic response and associated devastation at hill ridges and on inclined slopes. Satellite remote sensing-derived digital elevation models (DEMs) are frequently and effectively used to compute topographic attributes and seismic parameters to evaluate topographic seismic response. However, the influence of DEM random errors on computed topographic attributes and seismic response is often overlooked. This study uses the Shuttle Radar Topography Mission (SRTM) DEM (90 m) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) GDEM (30 m) to quantify uncertainties in the computed topographic attributes and seismic parameters and ultimately the impact of these uncertainties on topographic seismic response. Accuracy assessment of the DEMs shows root mean square error (RMSE) of 13.78 m in the ASTER DEM and 23.71 m in the SRTM DEM. The influence of DEM errors on derived topographic attributes quantified through Monte Carlo simulations shows higher uncertainty in slope and aspect computed from ASTER DEM than from SRTM DEM. The influence of uncertainty in the SRTM and ASTER DEMs shows significant impact on the computed seismic parameters of slope, relative height, and V s 30 and ultimately derived topographic seismic response.

Comparative evaluation of horizontal accuracy of elevations of selected ground control points from ASTER and SRTM DEM with respect to CARTOSAT-1 DEM: a case study of Shahjahanpur district, Uttar Pradesh, India

Digital elevation model (DEM) data of Shuttle Radar Topography Mission (SRTM) are distributed at a horizontal resolution of 90 m (30 m only for US) for the world, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM data provide 30 m horizontal resolution, while CARTOSAT-1 (IRS-P5) gives 2.6 m horizontal resolution for global coverage. SRTM and ASTER data are available freely but 2.6 m CARTOSAT-1 data are costly. Hence, through this study, we found out a horizontal accuracy for selected ground control points (GCPs) from SRTM and ASTER with respect to CARTOSAT-1 DEM to implement this result (observed from horizontal accuracy) for those areas where the 2.6-m horizontal resolution data are not available. In addition to this, the present study helps in providing a benchmark against which the future DEM products (with horizontal resolution less than CARTOSAT-1) with respect to CARTOSAT-1 DEM can be evaluated. The original SRTM image contained voids that were represented digitally as −140; such voids were initially filled using the measured values of elevation for obtaining accurate DEM. Horizontal accuracy analysis between SRTM- and ASTER-derived DEMs with respect to CARTOSAT-1 (IRS-P5) DEM allowed a qualitative assessment of the horizontal component of the error, and the appropriable statistical measures were used to estimate their horizontal accuracies. The horizontal accuracy for ASTER and SRTM DEM with respect to CARTOSAT-1 were evaluated using the root mean square error (RMSE) and relative root mean square error (R-RMSE). The results from this study revealed that the average RMSE of 20 selected GCPs was 2.17 for SRTM and 2.817 for ASTER, which are also validated using R-RMSE test which proves that SRTM data have good horizontal accuracy than ASTER with respect to CARTOSAT-1 because the average R-RMSE of 20 GCPs was 3.7 × 10−4 and 5.3 × 10−4 for SRTM and ASTER, respectively.

A regional investigation of urban land-use change for potential landslide hazard assessment in the Three Gorges Reservoir Area, People's Republic of China: Zigui to Wanzhou

The near-completion of the Three Gorges Dam has led to the creation of a narrow reservoir that, when completed in 2009, will stretch over 660 km upstream and result in the displacement of approximately 1.2 million people. This reservoir will drown more than 100 towns, some of which have already been lost due to the rising waters, and result in a significant change in land use. New urban areas have been constructed at higher elevations to avoid the rising water but it is feared that some of these settlements may now be exposed to a greater risk of landslides due to slope failure. A geographic information system (GIS) consisting of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat Thematic Mapper (TM), and Environmental Satellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) data has been created and used to monitor the urban changes from before the Dam's construction to the present day as well as changes in landslide susceptibility. To perform this analysis, a new 30 m high-resolution digital elevation model (DEM) was derived by combining an ASTER and Shuttle Radar Topography Mission (SRTM) DEM. Fieldwork was carried out along the Yangtze River, where the urban boundaries were field-checked using GPS to navigate to the satellite-derived checkpoints. The results show that a majority of the new urban areas are in fact located on shallow slopes, but are often positioned below steep slopes, which could pose a future threat of landslide risk to the inhabitants of the new towns.

Development of Water Management Modeling by using GIS in Chirchik River Basin, Uzbekistan

The management of water resources has become a critical need for Chirchik river basin in Uzbekistan due to water deficit and salt damage. Hence, plans must be developed for water efficient use through better management at the river basin level. In this paper, fundamental concept of the proposed water management modeling of the Chirchik river basin and overview of hydrological model using Geomorphology Based Hydrological Model (GBHM). Furthermore, various spatial data such as land-use layers and hydrological layers are developed in this study by conducting latest GIS (Geographical Information System) technology. By extracting ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Digital Elevation Model (DEM) and ALOS (Advanced Land Observing Satellite) data on autumn and spring, a series of land-use classification is created using the supervised classification method. For regional-scale hydrological modeling, GBHM as a powerful tool is used to analyze the river basin by utilizing the geomorphological properties data for each catchment and hillslope hydrological processes. As a result, development of spatial modeling is obtained and GIS-based analysis is an effective method to study water management in Chirchik river basin in Uzbekistan.

STcorr: An IDL code for image based normalization of lapse rate and illumination effects on nighttime TIR imagery

Thermal infrared imagery (TIR) is a useful tool to detect and quantify the surface temperature anomalies associated with geothermal fields. Accurate detection of anomalies in surface temperature is an important aspect of geothermal research. Although day-time TIR images have long been used for temperature anomaly mapping, the increase in the spatial resolution and the number of acquisitions of nighttime thermal imagery provide new perspectives to the remote geothermal monitoring and exploration. However, the nighttime thermal imagery requires appropriate corrections in order to minimize some major artefacts. These corrections are namely: the masking of small scale thermal anomalies by the lapse rate, the relict diurnal heat due to the radiation of sun and the slope effect. Moreover, the correction of nighttime TIR imagery according to the altitude, slope aspect and the slope of the study area provide more reliable data.STcorr is an Interactive Data Language (IDL) code for the correction of altitude, aspect and slope effects in nighttime thermal imagery using image based polynomial regression analysis. Standard ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Surface Kinetic Temperature (ST) image and Digital Elevation Model (DEM) are used to calculate a lapse rate model. Upon the retrieval of lapse rate, an illumination correction is performed based on the relationship between the corrected image and the aspect and slope images, interactive and “step by step” structure of the code permit user to improve the quality of the output. An ASTER nighttime ST image of the Mt. Nemrut volcano has been corrected using STcorr as an example. The procedure improves the reliability of the output after the retrieval of altitude, aspect and slope effects. Thermal anomalies observed in the Mt. Nemrut are consistent with the hydrothermal activity and the hot spots detected by self-potential measurements in the area.

Mapping of debris-covered glaciers in the Garhwal Himalayas using ASTER DEMs and thermal data

Mapping of debris-covered glaciers using remote-sensing techniques is recognized as one of the greatest challenges for generating glacier inventories and automated glacier change analysis. The use of visible (VIS) and near-infrared (NIR) bands does not provide sufficient continual information to detect debris-covered ice with remote-sensing data. This article presents a semi-automated mapping method for the debris-covered glaciers of the Garhwal Himalayas based on an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model (DEM) and thermal data. Morphometric parameters such as slope, plan curvature and profile curvature were computed by means of the ASTER DEM and organized in similar surface groups using cluster analysis. A thermal mask was generated from a single band of an ASTER thermal image, while the clean-ice glaciers were identified using a band ratio based on ASTER bands 3 and 4. Vector maps were drawn up from the output of the cluster analysis, the thermal mask and the band ratio mask for the preparation of the final outlines of the debris-covered glaciers using geographic information system (GIS) overlay operations. The semi-automated mapped debris-covered glacier outline of Gangotri Glacier derived from 2006 ASTER data varied by about 5% from the manually outlined debris-covered glacier area of the Cartosat-1 high-resolution image from the same year. By contrast, outlines derived from the method developed using the 2001 ASTER DEM and Landsat thermal data varied by only 0.5% from manually digitized outlines based on Indian Remote Sensing Satellite (IRS)-1C panchromatic (PAN) data. We found that post-depositional sedimentation by debris flow/mass movement was a great hindrance in the fully automated mapping of debris-covered glaciers in the polygenetic environment of the Himalayas. In addition, the resolution of ASTER stereo data and thermal band data limits the automated mapping of small debris-covered glaciers with adjacent end moraine. However, the results obtained for Gangotri Glacier confirm the strong potential of the approach presented.