Shuttle Radar Topography Mission Data Research Articles

Elevation and Mass Changes of the Southern Patagonia Icefield Derived from TanDEM-X and SRTM Data

The contribution to sea level rise from Patagonian icefields is one of the largest mass losses outside the large ice sheets of Antarctica and Greenland. However, only a few studies have provided large-scale assessments in a spatially detailed way to address the reaction of individual glaciers in Patagonia and hence to better understand and explain the underlying processes. In this work, we use repeat radar interferometric measurements of the German TerraSAR-X-Add-on for Digital Elevation Measurements (TanDEM-X) satellite constellation between 2011/12 and 2016 together with the digital elevation model from the Shuttle Radar Topography Mission (SRTM) in 2000 in order to derive surface elevation and mass changes of the Southern Patagonia Icefield (SPI). Our results reveal a mass loss rate of −11.84 ± 3.3 Gt·a−1 (corresponding to 0.033 ± 0.009 mm·a−1 sea level rise) for an area of 12573 km2 in the period 2000–2015/16. This equals a specific glacier mass balance of −0.941 ± 0.19 m w.e.·a−1 for the whole SPI. These values are comparable with previous estimates since the 1970s, but a magnitude larger than mass change rates reported since the Little Ice Age. The spatial pattern reveals that not all glaciers respond similarly to changes and that various factors need to be considered in order to explain the observed changes. Our multi-temporal coverage of the southern part of the SPI (south of 50.3° S) shows that the mean elevation change rates do not vary significantly over time below the equilibrium line. However, we see indications for more positive mass balances due to possible precipitation increase in 2014 and 2015. We conclude that bi-static radar interferometry is a suitable tool to accurately measure glacier volume and mass changes in frequently cloudy regions. We recommend regular repeat TanDEM-X acquisitions to be scheduled for the maximum summer melt extent in order to minimize the effects of radar signal penetration and to increase product quality.

Geomorphology Classification of Shandong Province Based on Digital Elevation Model in the 1 Arc-second Format of Shuttle Radar Topography Mission Data

Based on gigital elevation model in the 1 arc-second format of shuttle radar topography mission data, using the window analysis and mean change point analysis of geographic information system (GIS) technology, programmed with python modules this, automatically extracted and calculated geomorphic elements of Shandong province. The best access to quantitatively study area relief amplitude of statistical area. According to Chinese landscape classification standard, the landscape type in Shandong province was divided into 8 types: low altitude plain, medium altitude plain, low altitude platform, medium altitude platform, low altitude hills, medium altitude hills, low relief mountain, medium relief mountain and the percentages of Shandong province’s total area are as follows: 12.72%, 0.01%, 36.38%, 0.24%, 17.26%, 15.64%, 11.1%, 6.65%. The results of landforms are basically the same as the overall terrain of Shandong Province, Shandong province’s total area, and the study can quantitatively and scientifically provide reference for the classification of landforms in Shandong province.

Using spatial technology to locate the view illustrated in Eugene von Guérard’s painting of the Kosciuszko massif

The colonial artist Eugene von Guérard travelled extensively throughout south-eastern Australia sketching thousands of views during his three-decade-long sojourn in Australia. His field drawings are renowned for their fidelity to nature and observational accuracy, but the validity of the latter claim depends on comparing drawings with the view at the sites where he sketched. The location of the view in some artworks, such as Mount Kosciusko, seen from the Victorian Border, has eluded art historians and aficionados who have ventured into the field. This article discusses the collation of clues from historical narratives, maps and surveying techniques to limit the search area for the vantage point where he sketched the view on which he based his painting of the Kosciuszko massif. Novel use of spatial technology utilising satellite imagery, Global Positioning System (GPS) and Shuttle Radar Topography Mission (SRTM) data, particularly digital elevation models, to locate the actual site is explored, and the topographical accuracy of his sketches evaluated when compared with photographs taken from close to the site. Finally, the potential value of using spatial technology in art history field work is discussed.

The validation of hydrodynamic modelling for 2014 flood in Kuala Krai, Kelantan

Flood catastrophe that struck Kelantan in 2014 has marked as the worst in history. The absence of structural approach such as dam has increased the risks of the flood to this state. In this paper, the simulation of 2014 flood event focuses in Kuala Krai area has been carried out before and after the occurrence of the proposed dams along Galas and Lebir rivers, respectively using hydrodynamic model. The Digital Terrain Model (DTM) from Airborne Light Detection and Ranging (LiDAR) combining with Shuttle Radar Topography Mission (SRTM) data resources have been used for hydrodynamic modelling. The flow hydrograph and water level are generated as input data for initial and boundary conditions. River cross-sections and Manning’s roughness coefficient values that been estimated based on landcover map obtained in 2010 also used in the model. The model produces the outputs of flood depth and velocity. To validate the simulation results, the flood depths were compared against the flood marks depth from field survey at 16 locations collected by researchers from Disaster Prevention Research Institute, Kyoto University, Japan and Department of Irrigation and Drainage (DID). From the validation, it reveals that the average accuracy percentage obtained was about 90% and it can be said that the flood model was acceptable.

Shoreline change and potential sea level rise impacts in a climate hazardous location in southeast coast of India.

Climate change impact on the environment makes the coastal areas vulnerable and demands the evaluation of such susceptibility. Historical changes in the shoreline positions and inundation based on projected sea-level scenarios of 0.5 and 1m were assessed for Nagapattinam District, a low-lying coastal area in the southeast coast of India, using high-resolution Shuttle Radar Topography Mission data; multi-dated Landsat satellite images of 1978, 1991, 2003, and 2015; and census data of 2011. Image processing, geographical information system, and digital shoreline analysis system methods were used in the study. The shoreline variation indicated that erosion rate varied at different time scales. The end point rate indicated the highest mean erosion of - 3.12m/year, occurred in 73% of coast between 1978 and 1991. Weighted linear regression analysis revealed that the coast length of 83% was under erosion at a mean rate of - 2.11m/year from 1978 to 2015. Sea level rise (SLR) impact indicated that the coastal area of about 14,122ha from 225 villages and 31,318ha from 272 villages would be permanently inundated for the SLR of 0.5 and 1m, respectively, which includes agriculture, mangroves, wetlands, aquaculture, and forest lands. The loss of coastal wetlands and its associated productivity will severely threaten more than half the coastal population. Adaptation measures in people participatory mode, integrated into coastal zone management with a focus on sub-regional coastal activities, are needed to respond to the consequences of climate change.

Kajian Awal Penentuan Daerah Prospek Panas Bumi di Gunung Bur Ni Telong berdasarkan Analisis Data DEM SRTM dan Citra Landsat 8

Research for a preliminary study of Bur Ni Telong, geothermal area, Bener Meriah district using remote sensing techniques has been done. The aims of the research were to determine the morphological condition based on the fault and fracture (FFD) map from the interpreted digital elevation model (DEM) shuttle radar topography mission (SRTM) and to know the vegetation density and surface temperature distribution using Landsat 8 image. The DEM SRTM data were analyzed using the lineament pattern which related to faults and fractures. The vegetation density was calculated using normalized difference vegetation index (NDVI) transformation. The estimated surface temperature was used to locate temperature anomaly. Referring to the geographical map, the dense class area include Silih Nara-Ketol-Peulimbang to Peudada, Juli to Sawang, and Bandar area. The fault and fracture dominantly have directions in East-West and Northwest-Southeast. While based on NDVI map we conclude that the area is covered by dense vegetation, dominated by intermediate to dense of vegetation. The LST map shows the location of maximum surface temperature values are in agreement with residential areas and uncovered areas, as in the areas of Simpang Tiga Redelong and Takengon. Some geothermal manifestations are located in sparse to intermediate vegetation areas with high temperature.

A practical method for creating a digital topographic surface for ecological plots using ground-based measurements

Digital elevation models (DEMs) are widely used in landscape ecology to link topographic features with biotic and abiotic factors. However, to date, high-resolution, affordable, and easy to process elevation data are not available for many regions. Here we propose a field-based method for efficiently and inexpensively collecting or analysing already existing slope data. We compare the field approach to two commonly used remote sensing techniques to test the similarly of the DEMs using different methods. To provide an ecological example of the method, we selected four 1-ha forest plots and compared the DEM generated by using our field method with those derived from: (i) coarse (~ 30 m pixel) data from the Shuttle Radar Topography Mission and (ii) high-resolution (~ 1 m) data from Light Detection and Ranging devices (LiDAR). Field- and LiDAR-based DEMs showed strong concordance in two of the four sites. The sites where field-based and LiDAR DEMs substantially differed, suffered from relatively few LiDAR sampling points. Diagnostic tests suggested that the field–LiDAR discrepancy was due to dense over-storey vegetation, which reduced LiDAR’s accuracy due to a failure to penetrate the forest canopy adequately in some areas. Our method has the advantage of being quick and cheap to collect yet able to produce small-scale (plot-scale) DEMs of high quality. By using the R-code we have provided, ecologists will be able to use slope data (collected using any means) to generate a DEM without the need of specific skills in spatial sciences.

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.

Estimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data

The knowledge of biomass stocks in tropical forests is critical for climate change and ecosystem services studies. This research was conducted in a tropical rain forest located near the city of Libreville (the capital of Gabon), in the Akanda Peninsula. The forest cover was stratified in terms of mature, secondary and mangrove forests using Landsat-ETM data. A field inventory was conducted to measure the required basic forest parameters and estimate the aboveground biomass (AGB) and carbon over the different forest classes. The Shuttle Radar Topography Mission (SRTM) data were used in combination with ground-based GPS measurements to derive forest heights. Finally, the relationships between the estimated heights and AGB were established and validated. Highest biomass stocks were found in the mature stands (223 ± 37 MgC/ha), followed by the secondary forests (116 ± 17 MgC/ha) and finally the mangrove forests (36 ± 19 MgC/ha). Strong relationships were found between AGB and forest heights (R2 > 0.85).

Flooding Model as the Analysis of the Sea Level Increase as a Result of Global Warming in Coastal Area in Lampung

The melting of ice layers, as a direct impact on global warming, is indicated from a lesser thickness of ice layers is specifically causing an increase on the sea level. Lampung, as a province that has an ecosistem of regional coast, can be estimated to submerge. Flood modelling can be done to know the estimated flood range. The model of the flooded region is taken from Shuttle Radar Topography Mission(SRTM) data, which is nomalized to get the visualisation of Digital Elevation Model (DEM). The purpose of this research is to know the estimated region of provincial coast of Lampung that is going to be flooded because of the raising of sea surface. This research uses flood inundation technique that uses one of the GIS mapping software. The result can be used as consideration to achieve policy in the building of regional coast. The regions that are flooded based on the scenario of the raising of two and three meter surface sea level are East Lampung Regency, West Lampung Regency, South Lampung Regency, Tanggamus Regency, Pesawaran Regency, and Bandar Lampung.

Two-Dimensional Dam-Break Flood Analysis in Data-Scarce Regions: The Case Study of Chipembe Dam, Mozambique

This paper presents the results of a modeling study of the hypothetical dam break of Chipembe dam in Mozambique. The modeling approach is based on the software Iber, a freely available dam break and two-dimensional finite volume shallow water model. The shuttle radar topography mission (SRTM) online digital elevation model (DEM) is used as main source of topographic data. Two different DEMs are considered as input for the hydraulic model: a DEM based on the original SRTM data and a hydrologically-conditioned DEM. A sensitivity analysis on the Manning roughness coefficient is performed. The results demonstrate the relevant impact of the DEM used on the predicted flood wave propagation, and a lower influence of the roughness value. The low cost modeling approach proposed in this paper can be an attractive option for modeling exceptional flood caused by dam break, when limited data and resources are available, as in the presented case. The resulting flood-inundation and hazard maps will enable the Regional Water Management Administration of Mozambique (ARA) to develop early warning systems.

IMPACT ASSESSMENT OF MIKANIA MICRANTHA ON LAND COVER AND MAXENT MODELING TO PREDICT ITS POTENTIAL INVASION SITES

Abstract. Mikania micrantha is one of the major invasive alien plant species in tropical moist forest regions of Asia including Nepal. Recently, this weed is spreading at an alarming rate in Chitwan National Park (CNP) and threatening biodiversity. This paper aims to assess the impacts of Mikania micrantha on different land cover and to predict potential invasion sites in CNP using Maxent model. Primary data for this were presence point coordinates and perceived Mikania micrantha cover collected through systematic random sampling technique. Rapideye image, Shuttle Radar Topographic Mission data and bioclimatic variables were acquired as secondary data. Mikania micrantha distribution maps were prepared by overlaying the presence points on image classified by object based image analysis. The overall accuracy of classification was 90 % with Kappa coefficient 0.848. A table depicting the number of sample points in each land cover with respective Mikania micrantha coverage was extracted from the distribution maps to show the impact. The riverine forest was found to be the most affected land cover with 85.98 % presence points and sal forest was found to be very less affected with only 17.02 % presence points. Maxent modeling predicted the areas near the river valley as the potential invasion sites with statistically significant Area Under the Receiver Operating Curve (AUC) value of 0.969. Maximum temperature of warmest month and annual precipitation were identified as the predictor variables that contribute the most to Mikania micrantha's potential distribution.

Optimization of area–volume–elevation curve using GIS–SRTM method for rainwater harvesting in arid areas

The major limitation in planning water harvesting is the lack of knowledge in the estimation of surface area and storage volume at any depth of dam reservoir. The area–volume–elevation (AVE) curve of a reservoir plays a key role in estimating the most suitable depth, optimum surface area and highest capacity of reservoir storage. The existing methods to estimate the AVE curve are costly and time-consuming and require laborious work. This study attempts to develop a method to optimize the AVE curve for earth dams, using the digital elevation model generated by the Shuttle Radar Topography Mission (SRTM) data, and integrate it with the geographic information system (GIS), known as the GIS–SRTM. The proposed method was tested using field data in the Western Desert of Iraq, which is an arid environment. Three constructed small earth dams were selected for this study. The AVE curves were extracted for Horan 2 (H2), Al-gara 2 (G2) and Al-gara 4 (G4) earth dams. Comprehensive analyses have been carried out to evaluate the performance of the AVE curves using the proposed GIS–SRTM method and the field data. From the comparison, the proposed GIS–SRTM method was able to produce reliable AVE curves with a relative error less than 20%. Additionally, the proposed method was less time-consuming and the AVE curves can be visualized immediately. The proposed GIS–SRTM method is relatively supportive in analyzing spatial data to select the optimal site for rainwater harvesting and prevent excessive evaporation losses.

Impacts of uncertainty in land surface information on simulated surface temperature and precipitation over China

ABSTRACTThis study mainly focuses on the effects of uncertainty in land surface information on mesoscale numerical simulation. The Weather Research and Forecasting (WRF) model was used to simulate meteorological fields over China at a spatial resolution of 10 km during 2006. Near‐surface temperature and precipitation values obtained from WRF were evaluated using site observations. The effects of accurate and updated land surface information, including Shuttle Radar Topography Mission (SRTM) data, Moderate resolution imaging spectroradiometer (MODIS) land use data, vegetation fraction derived from MODIS normalized difference vegetation index (NDVI) and Harmonized World Soil Database (HWSD) data (LAST simulation), on WRF's performance were investigated by comparison with a simulation using the default land surface information (BASE simulation). WRF reproduced the temporal and spatial variations of near‐surface temperature and precipitation over China accurately, although its performance varied significantly by season and region. WRF underestimated near‐surface temperatures in most areas of the Yunnan–Guizhou Plateau, the Tibetan Plateau, the Northeast Plain, and the southeastern coastal regions, but temperatures were overestimated in most areas of the North China Plain, the Loess Plateau, Sichuan Basin, and western Xinjiang. WRF overestimated (underestimated) precipitation in most humid (arid) areas. A positive (negative) bias in simulated precipitation is found in summer (winter). With updated land surface information, WRF's performance in terms of both daily average values and extremes improved, and the root mean squared error values for daily mean temperature and daily accumulated precipitation decreased by 7 and 2.3%. These improvements are significant for temperature, but not significant for precipitation. The uncertainty in land surface information has a greater influence on temperature than on precipitation. These findings are very important for weather forecasting and studies involving climatological analyses covering East Asia.

Effect of uncertainty in Digital Surface Models on the extent of inundated areas

The impact of uncertainty in ground elevation on the extent of areas that are inundated due to flooding is investigated. Land surface is represented through a Digital Surface Model (DSM). The effect of uncertainty in DSM is compared to that of the uncertainty due to rainfall. The Monte Carlo method is used to quantify the uncertainty. A typical photogrammetric procedure and conventional maps are used to obtain a reference DSM, later altered to provide DSMs of lower accuracy. Also, data from the Shuttle Radar Topography Mission (SRTM) are used. Floods are simulated in two stages. In the first stage flood hydrographs for typical return periods are synthesized using generated storm hyetographs, the SCS-CN method for effective rainfall and the SCS synthetic Unit Hydrograph. In the second stage hydrographs are routed via a 1D hydraulic model. Uncertainty in DSM is considered only in the second stage. Data from two real-world basins in Greece are used.. To characterize the inundated area we employ the 90% quantile of the inundation extent and inundation topwidth for peak water level at specific river cross-sections. For topwidths, apart from point estimates, also interval estimates are acquired using the bootstrap method. The effect of DSM uncertainty is compared to that for rainfall. Low uncertainty in DSM is found to widen the inundated area, whereas the opposite occurred with high uncertainty. SRTM data proved unsuitable for our test basins and modelling context.

Uncertainties in the Shuttle Radar Topography Mission (SRTM) Heights: Insights from the Indian Himalaya and Peninsula

The Shuttle Radar Topography Mission (SRTM) Digital Terrain Elevation Data (DTED) are used with the consensus view that it has a minimum vertical accuracy of 16 m absolute error at 90% confidence (Root Mean Square Error (RMSE) of 9.73 m) world-wide. However, vertical accuracy of the data decreases with increase in slope and elevation due to presence of large outliers and voids. Therefore, studies using SRTM data “as is”, especially in regions like the Himalaya, are not statistically meaningful. New data from ~200 high-precision static Global Position System (GPS) Independent Check Points (ICPs) in the Himalaya and Peninsular India indicate that only 1-arc X-Band data are usable “as is” in the Himalaya as it has height accuracy of 9.18 m (RMSE). In contrast, recently released (2014–2015) “as-is” 1-arc and widely used 3-arc C-Band data have a height accuracy of RMSE 23.53 m and 47.24 m and need to be corrected before use. Outlier and void filtering improves the height accuracy to RMSE 8 m, 10.14 m, 14.38 m for 1-arc X and C-Band and 3-arc C-Band data respectively. Our study indicates that the C-Band 90 m and 30 m DEMs are well-aligned and without any significant horizontal offset implying that area and length computations using both the datasets have identical values.

On the Contribution of GOCE Satellite-Based GGMs to Improve GNSS/Leveling Geoid Heights Determination in Saudi Arabia

The global geopotential models (GGMs) derived from the gravity field and steady-state ocean circulation explorer (GOCE) mission provide important information about Earth gravity functionals (e.g., geoid heights, gravity anomalies, and disturbances). Among gravity functionals, we utilize geoid heights which have been determined from several recent GOCE-based GGMs and validate them against 5187 collocated Global Navigation Satellite System (GNSS)/leveling observations over a network of dedicated benchmarks in Saudi Arabia. Our aim is to consider the spectral consistency between GOCE-based GGMs and ground-based data. Accordingly, we incorporate high/very high frequencies of gravity functionals, i.e., the gravity signal beyond the maximum d/o of GOCE-based GGMs, using EGM2008 and a high-resolution digital terrain model based on the Shuttle Radar Topography Mission (SRTM). This investigation indicates that completing the missing high-frequency component of geoid heights in GOCE-based GGMs, using EGM2008 and SRTM data, results in an improvement of about 16% in the reduction in the standard deviation (SD) of the differences. This is provided by DIR_R5 at SH d/o 230, which shows improvement from 37.5 cm, without applying the spectral enhancement method (SEM), compared to 31.4 cm when applying the SEM. Finally, three types of transformation models, namely four-, five-, and seven-parameter transformations, are examined to deal with the data biases and to provide a better fitting of geoid heights obtained from the studied GOCE-based GGMs to those from GNSS/leveling data. These models reveal that the SD of vertical datum over the region of Saudi Arabia is at the level of about 22 cm.

High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations

The absence of a high-quality seamless global digital elevation model (DEM) dataset has been a challenge for the Earth-related research fields. Recently, the 1-arc-second Shuttle Radar Topography Mission (SRTM-1) data have been released globally, covering over 80% of the Earth’s land surface (60°N–56°S). However, voids and anomalies still exist in some tiles, which has prevented the SRTM-1 dataset from being directly used without further processing. In this paper, we propose a method to generate a seamless DEM dataset blending SRTM-1, ASTER GDEM v2, and ICESat laser altimetry data. The ASTER GDEM v2 data are used as the elevation source for the SRTM void filling. To get a reliable filling source, ICESat GLAS points are incorporated to enhance the accuracy of the ASTER data within the void regions, using an artificial neural network (ANN) model. After correction, the voids in the SRTM-1 data are filled with the corrected ASTER GDEM values. The triangular irregular network based delta surface fill (DSF) method is then employed to eliminate the vertical bias between them. Finally, an adaptive outlier filter is applied to all the data tiles. The final result is a seamless global DEM dataset. ICESat points collected from 2003 to 2009 were used to validate the effectiveness of the proposed method, and to assess the vertical accuracy of the global DEM products in China. Furthermore, channel networks in the Yangtze River Basin were also extracted for the data assessment.

DEM sourcing guidelines for computing 1 Eö accurate terrain corrections for airborne gravity gradiometry

In this paper we investigate digital elevation model (DEM) sourcing requirements to compute gravity gradiometry terrain corrections accurate to 1Eötvös (Eö) at observation heights of 80m or more above ground. Such survey heights are typical in fixed-wing airborne surveying for resource exploration where the maximum signal-to-noise ratio is sought. We consider the accuracy of terrain corrections relevant for recent commercial airborne gravity gradiometry systems operating at the 10Eö noise level and for future systems with a target noise level of 1Eö. We focus on the requirements for the vertical gradient of the vertical component of gravity (Gdd) because this element of the gradient tensor is most commonly interpreted qualitatively and quantitatively.Terrain correction accuracy depends on the bare-earth DEM accuracy and spatial resolution. The bare-earth DEM accuracy and spatial resolution depends on its source. Two possible sources are considered: airborne LiDAR and Shuttle Radar Topography Mission (SRTM). The accuracy of an SRTM DEM is affected by vegetation height. The SRTM footprint is also larger and the DEM resolution is thus lower. However, resolution requirements relax as relief decreases. Publicly available LiDAR data and 1arc-second and 3arc-second SRTM data were selected over four study areas representing end member cases of vegetation cover and relief.The four study areas are presented as reference material for processing airborne gravity gradiometry data at the 1Eö noise level with 50m spatial resolution. From this investigation we find that to achieve 1Eö accuracy in the terrain correction at 80m height airborne LiDAR data are required even when terrain relief is a few tens of meters and the vegetation is sparse. However, as satellite ranging technologies progress bare-earth DEMs of sufficient accuracy and resolution may be sourced at lesser cost. We found that a bare-earth DEM of 10m resolution and 2m accuracy are sufficient for achieving 1Eö accuracy in the terrain correction independent of relief or vegetation cover. For AGG systems operating at greater noise levels the 3arc-second SRTM is adequate for areas having tens of meters of relief and sparse vegetation and even for areas of greater relief and sparse vegetation if a constant elevation survey is flown at 80m above terrain peak.

Assessing groundwater accessibility in the Kharga Basin, Egypt: A remote sensing approach

We used multi-map analysis of remote sensing and ancillary data to identify potentially accessible sites for groundwater resources in the Kharga Basin in the Western Desert of Egypt. This basin is dominated by Cretaceous sandstone formations and extends within the Nubian Sandstone Aquifer. It is dissected by N-S and E-W trending faults, possibly acting as conduits for upward migration of groundwater. Analysis of paleo-drainage using Digital Elevation Model (DEM) generated from the Shuttle Radar Topography Mission (SRTM) data shows that the Kharga was a closed basin that might have been the site of a paleo-lake. Lake water recharged the Nubian Sandstone Aquifer during the wetter Holocene time. We generated the following layers for the multi-map analysis: (1) Fracture density map from the interpretation of Landsat Operational Land Imager (OLI), SRTM DEM, and RADARSAT data. (2) Thermal Inertia (TI) map (for moisture content imaging) from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. (3) Hydraulic conductivity map from mapping lithological units using the Landsat OLI and previously published data. (4) Aquifer thickness map from previously published data. We quantitatively ranked the Kharga Basin by considering that regions of high fracture density, high TI, thicker aquifer, and high hydraulic conductivity have higher potential for groundwater accessibility. Our analysis shows that part of the southern Kharga Basin is suitable for groundwater extraction. This region is where N-S and E-W trending faults intersect, has relatively high TI and it is underlain by thick aquifer. However, the suitability of this region for groundwater use will be reduced significantly when considering the changes in land suitability and economic depth to groundwater extraction in the next 50 years.