ASTER Digital Elevation Model Research Articles

Two-Decadal Glacier Changes in the Astak, a Tributary Catchment of the Upper Indus River in Northern Pakistan

Snow and ice melting in the Upper Indus Basin (UIB) is crucial for regional water availability for mountainous communities. We analyzed glacier changes in the Astak catchment, UIB, from 2000 to 2020 using remote sensing techniques based on optical satellite images from Landsat and ASTER digital elevation models. We used a surface feature-tracking technique to estimate glacier velocity. To assess the impact of climate variations, we examined temperature and precipitation anomalies using ERA5 Land climate data. Over the past two decades, the Astak catchment experienced a slight decrease in glacier area (−1.8 km2) and the overall specific mass balance was −0.02 ± 0.1 m w.e. a−1. The most negative mass balance of −0.09 ± 0.06 m w.e. a−1 occurred at elevations between 2810 to 3220 m a.s.l., with a lesser rate of −0.015 ± 0.12 m w.e. a−1 above 5500 m a.s.l. This variation in glacier mass balance can be attributed to temperature and precipitation gradients, as well as debris cover. Recent glacier mass loss can be linked to seasonal temperature anomalies at higher elevations during winter and autumn. Given the reliance of mountain populations on glacier melt, seasonal temperature trends can disturb water security and the well-being of dependent communities.

Accuracy assessment of global DEMs for the mapping of coastal flooding on a low-lying sandy environment: Cassino Beach, Brazil

Projected sea level rise in the 21st century, driven by climate change, threatens low-lying coastal areas with the risk of persistent flooding. Accurately estimating flooding extent and depth is crucial to implementing effective coastal management, with digital elevation models (DEMs) playing a pivotal role. Intrinsic inaccuracies of DEMs might lead to uncertainty in the flooding projections due to SLR scenarios, which are problematic for decision-makers. This work assessed the accuracy of five global digital elevation models for coastal flooding mapping on a low-lying sandy coastal environment in the south of Brazil (Cassino Beach). Five global DEMs were assessed, namely ALOS-AW3D30, ALOS-PALSAR, ASTER, SRTM, and TanDEM-X, and a high-resolution digital elevation model (created using local aerial vehicle (UAV) imagery) was used as a benchmark. A morphometric comparison was conducted between the five global DEMs and the high-resolution local DEMs. Several statistical metrics were calculated, including the root mean squared error, correlation coefficient, and bias.Additionally, flood depths and extent were computed for different scenarios of sea level rise, and comparisons between the different DEMs were quantified. Results show that among the DEMs evaluated, TanDEM-X DEM achieved the highest correlation with the UAV DEM elevation in the beach and dune region, presenting R² equal to 0.56 and RMSE equal to 0.88 m. On the other hand, the ALOS-AW3D30, ALOS-PALSAR, ASTER, and SRTM DEMs presented low correlation and RMSE values above 2.49 m. The analysis of coastal flooding extension and depths confirms that the TanDEM-X DEM exhibited the highest similarity with the UAV DEM across various sea level scenarios, and it was the only global DEM analyzed capable of capturing dune depressions and roads, which serve as primary pathways for flooding in the type of coastal region under consideration.

Assessment of the global Copernicus, NASADEM, ASTER and AW3D digital elevation models in Central and Southern Africa

ABSTRACT Validation studies of global Digital Elevation Models (DEMs) in the existing literature are limited by the diversity and spread of landscapes, terrain types considered and sparseness of groundtruth. Moreover, there are knowledge gaps on the accuracy variations in rugged and complex landscapes, and previous studies have often not relied on robust internal and external validation measures. Thus, there is still only partial understanding and limited perspective of the reliability and adequacy of global DEMs for several applications. In this study, we utilize a dense spread of LiDAR groundtruth to assess the vertical accuracies of four medium-resolution, readily available, free-access and global coverage 1 arc-second (30 m) DEMs: NASADEM, ASTER GDEM, Copernicus GLO-30, and ALOS World 3D (AW3D). The assessment is carried out at landscapes spread across Cape Town, Southern Africa (urban/industrial, agricultural, mountain, peninsula and grassland/shrubland) and forested national parks in Gabon, Central Africa (low-relief tropical rainforest and high-relief tropical rainforest). The statistical analysis is based on robust accuracy metrics that cater for normal and non-normal elevation error distribution, and error ranking. In Cape Town, Copernicus DEM generally had the least vertical error with an overall Mean Error (ME) of 0.82 m and Root Mean Square Error (RMSE) of 2.34 m while ASTER DEM had the poorest performance. However, ASTER GDEM and NASADEM performed better in the low-relief and high-relief tropical forests of Gabon. Generally, the DEM errors have a moderate to high positive correlation in forests, and a low to moderate positive correlation in mountains and urban areas. Copernicus DEM showed superior vertical accuracy in forests with less than 40% tree cover, while ASTER and NASADEM performed better in denser forests with tree cover greater than 70%. This study is a robust regional assessment of these global DEMs.

A Framework to Identify Rock Glaciers and Model Mountain Permafrost in the Jhelum Basin, Kashmir Himalaya, India

AbstractDeglaciation has led to the transformation of glaciers into rock glaciers in various mountainous regions worldwide. However, the science of permafrost and rock glaciers remains under‐researched in the Himalayan region. This study presents a detailed inventory, dynamics, and permafrost distribution map for the Jhelum basin in the Kashmir Himalaya. The Permafrost Zonation Map (PZM) is created using a Logistic Regression Model based on topographic and climatic variables. High‐resolution satellite images are used to identify rock glaciers as visual indicators. Active and relic rock glaciers are classified based on surface topography and geomorphology. Results reveal 207 rock glaciers in the Jhelum basin, covering ∼50 km2, with over 100 falling into the active category. The PZM aligns well with the global permafrost zonation index map. Slope, aspect, and elevation of rock glaciers are computed using the ASTER Digital Elevation Model. The average elevations range from 3,700 m to 4,550 m, and the average surface slope ranges from 12° to 26°, with maximum slopes from 25° to 65°. Most rock glaciers are oriented toward the south or southeast. Field investigations confirm that these rock glaciers occur in highly elevated regions with steep slopes. This study provides valuable information on the high areal abundance of permafrost in the Himalayan region and suggests increased risks of thawing permafrost due to climate warming in the future. The findings contribute to the understanding of permafrost and rock glaciers, filling knowledge gaps in the Himalayan context.

Assessment of On-going tectonic deformation in the Goriganga River Basin, Eastern Kumaon Himalaya Using Geospatial Technology

The Goriganga river basin lies in the Northeast Kumaon Himalaya and is found suitable for assessing active tectonics at different scales. In addition, this study focuses on the assessment of ongoing tectonic activity through morphotectonic measurement of the Goriganga river basin, which is an ideal location for such analysis and Goriganga river basin transects with three major domains of Himalaya’s lithotectonic structures viz., Tethys, Vaikrita, and Lesser Himalayan Domain. To realize this task, the ASTER Digital Elevation Model was used and found suitable to extract different morphotectonic indices such as Stream Length Gradient (SL), Hypsometric Integral (HI), Length of Overland Flow (Lg), Drainage Density (Dd) and Channel Sinuosity (Cs). Results of these important indices, including SL (18- 4737) HI (0.26- 0.57), and Lg (0.08- 0.19) depict greater variability in the tectonics activity while these values are correspondingly high in the close proximity of lithotectonic units, showing strong tectonic activity. In the extreme south, the Rauntis Gad basin strongly influences tectonism due to transecting syncline and anticline as well as unknown active faults.

GIS-based flash flooding susceptibility analysis and water management in arid mountain ranges: Safaga Region, Red Sea Mountains, Egypt

The Safaga Region (SR) is part of the Red Sea mountain range in Egypt. Catastrophic flash flooding is now an inescapable event, wreaking havoc and causing massive loss of life and property. The majority of the floodwater, however, has been wasted as runoff to the Red Sea, which, if used wisely, could meet a fraction of the water demands for a variety of applications in this area. The current work aims to use GIS techniques to integrate remote sensing data for evaluating, mitigating, and managing flash floods in SR. The data set comprised Tropical Rainfall Measuring Mission (TRMM) thematic rainfall data, 1:50,000 scale topographical map sheets, geological maps, the ASTER Digital Elevation Model (ASTER GDEM), Landsat 7 Enhanced Thematic Mapper” (ETM7+), and Landsat 8 Operational Land Imager. The flash flood risk model of SR is developed using ArcGIS-10.3 geoprocessing tools integrating all the causal factors thematic maps. The final flood risk model for the SR suggests that 57% of the total basins in the SR are at high risk of flooding. Almost 38% of all basins are at moderate flood risk. The remaining 5% of basins are less prone to flooding. Flood-prone zones were identified, suitable dam-building sites were located, and extremely probable areas for water recharge were recognized. On the basis of reliable scientific data, structural and non-structural mitigation strategies that might reduce the damage susceptibility, alleviate the sensitivity of the flash flood, and best utilize its water supply were recommended.

Erosion patterns, drainage dynamics, and their environmental implications: a case study of the hammamet basin using advanced geospatial and morphometric analysis

AbstractUnderstanding erosion patterns and drainage conditions is crucial for optimizing agricultural productivity and for addressing the challenges of wastewater treatment. To achieve this, we employed a comprehensive approach, combining the morphometric method with weighted sum and Geospatial techniques. Utilizing a 30-m-wide Digital Elevation Model (DEM), specifically the Aster DEM, and leveraging ArcGIS software, we meticulously delineated drainage systems and watershed boundaries. Through the application of standard formulas, we calculated areal, linear, and relief parameters to effectively rank and prioritize the sub-watersheds. Our examination led to the calculation of a composite factor, determined through an assessment of 18 morphometric criteria employing a weighted summation approach for each subcatchment. The outcomes of our research unveiled a wide range of compound factor values, spanning from − 0.128 to 9.28. This study underscores the pivotal role of the minimal compound factor value in determining the sustainability of sub-watersheds. As a practical illustration, we found that Basin 3 exhibited superior sustainability when compared to Basin 4, primarily attributable to soil erosion issues in the latter. Sub-watersheds were additionally grouped into classes according to their composite factor values, commonly characterized as highly favorable, favorable, intermediate, or unfavorable, providing insights into their vulnerability to erosion. Moreover, our research pinpointed Basin 4 and Basin 7 as highly vulner able to soil erosion, with a combined area of 294.9 km2. The implications for wastewater treatment are significant in these areas, as proper water and soil conservation techniques are imperative not only for the sustainable management of these lands but also for mitigating the environmental impact of the wastewater treatment process.

Vertical accuracy assessment for open-source digital elevation models using GPS control points and watershed basins delineation using GIS

Digital elevation models (DEMs) are crucial for numerous assessments of the Earth's surface, so this research aim to evaluate the quality of several open source DEMs like advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTM DEM), SENTINEL-1, and TerraSAR-X for digital elevation measurement (TanDEM-X). TanDEM-X is one of the newest DEM models; however, ASTER and SRTM are still the most used. To evaluate the qualities of these DEMs, the vertical accuracies of ASTER, STRM (all 30 m), SRTM, TanDEM-X (90 m), and SENTINEL 1 (range from 5 to 12.5 m) were tested using GPS reference points and The RMSE gave the values of ± 3.56 m ± 57.68 m, ±5.89 m, ±10.21 m and ± 20.25 mfor used SRTM1, SENTINEL-1, SRTM3, TanDEM-X, and ASTER DEMs respectively. As is well known, obtaining a high-quality DEM is exceedingly challenging since it is time-consuming, expensive, and often constrained, therefore this study examined how to enhance SRTM1 as it gave the best result and assessed the effects of increasing the number of points on digital elevation model accuracy by using raster calculator and merge model in ArcGIS. The results showed that the merge model method gave the best result and, by increasing the number of reference points, the accuracy increased. The DEM produced by the enhanced SRTM (iSRTM) demonstrated noticeably better outcomes than the baseline SRTM DEM, with around 3.56 m RMSE.In this research, STRM-1 DEM is used to determine watershed basin delineation. The topographic map showed significant variations in the level of the Earth's surface, as the heights of the area ranged between 20 m and 120 m. The number of watersheds extracted in the Benban is 132 with different areas, the large area is about 72.14 km2, while the small area is about 1.13 km2, and between those areas, there are various areas. The largest recorded watershed circumference reached 48.94 km in area (72.14 km2), while the lowest recorded perimeter is 5.40 km for the area (1.13 km2).

Effectiveness of UAV‐based DTM and satellite‐based DEMs for local‐level flood modeling in Jamuna floodplain

AbstractOpen‐source, satellite‐based digital elevation models (DEMs) are widely used for flood modeling. However, studies on effectiveness of these DEMs in depicting local‐level flood processes are limited. This study generated a high‐resolution digital terrain model (DTM) based on unmanned aerial vehicle (UAV) photogrammetry and used in a two‐dimensional (2D) hydrodynamic model (HEC‐RAS) to simulate the flood processes in a floodplain environment of the Jamuna River in northern Bangladesh. The effectiveness of a few satellite‐based DEMs was also compared with this DTM by using the DEMs in the same hydrodynamic model. Field data for two flood seasons were collected to develop the model. The results indicate that the 2D model with UAV‐based DTM provides the flood parameters, such as flood arrival time, depth, duration and extent, better than those from the satellite‐based DEMs. Of the open‐source DEMs, the FABDEM and the WorldDEM™ have the least errors and provide better results compared to the SRTM30, ALOS PALSAR, and ASTER DEMs. The UAV technique with ground control points and field measurements for the tree‐canopy and water areas is very useful in generating a fit‐for‐purpose DTM. The findings of this study would be useful for terrain generation and DEM selection for local‐level flood modeling elsewhere.

Performance of the flood models in different topographies

Climate change leads to more severe floods, which needs to be modeled properly. This study uses two hydraulic models including Hydrologic Engineering Center River Analysis System (HEC-RAS) and LISFLOOD-FP to simulate floods in two basins (Kashkan and Missouri) with different topographies (mountain and plain terrain). The impacts of different parameters like input resolutions, Digital Elevation Models (DEMs), roughness coefficient, and modeling techniques on flood simulation are examined. Results indicate that the performance of the models varies based on topography, input resolutions, and modeling approach. Indeed, the 2D modeling of both models in different topography types leads to better results compared to 1D/2D modeling. In Kashkan basin, HEC-RAS and LISFLOOD-FP models simulate floodplain flow with accuracies of 74% and 70%, respectively, and the accuracies of the models in Missouri basin are 80% and 84%, respectively. Although both models, particularly HEC-RAS with ALOS 30 m, can provide reasonable results, with an accuracy of 74% for Kashkan and 63% for Missouri basin, LISFLOOD-FP can perform better (about 4% higher accuracy) than HEC-RAS with a higher resolution of DEM (3DEP) in Missouri basin with significantly lower computational costs. In addition, the performance of the two models significantly decreases using ASTER DEM in plain topography. Results confirm that HEC-RAS outperforms LISFLOOD-FP in coarser resolution DEMs, while LISFLOOD-FP performs better in plain topography, which requires higher resolution DEMs. Despite the low sensitivity of the two models to roughness coefficients, the variability of the LISFLOOD-FP simulations is smaller than HEC-RAS. This work uses the best setting and factors to simulate floodplain zones, which is valuable for flood risk and hazard assessment to reduce and manage damages and losses.

Accuracy assessment and improvement of SRTM, ASTER, FABDEM, and MERIT DEMs by polynomial and optimization algorithm: A case study (Khuzestan Province, Iran)

Abstract Satellite digital elevation models (DEMs) are used for decision-making in various fields. Therefore, evaluating and improving vertical accuracy of DEM can increase the quality of end products. This article aimed to increase the vertical accuracy of most popular satellite DEMs (i.e., the ASTER, Shuttle Radar Topography Mission [SRTM], Forest And Buildings removed Copernicus DEM [FABDEM], and Multi-Error-Removed Improved-Terrain [MERIT]) using the particle swarm optimization (PSO) algorithm. For this purpose, at first, the vertical error of DEMs was estimated via ground truth data. Next, a second-order polynomial was applied to model the vertical error in the study area. To select the polynomial with the highest accuracy, employed for vertical error modeling, the coefficients of the polynomial have been optimized using the PSO algorithm. Finally, the efficiency of the proposed algorithm has been evaluated by other ground truth data and in situ observations. The results show that the mean absolute error (MAE) of SRTM DEM is 4.83 m while this factor for ASTER DEM is 5.35 m, for FABDEM is 4.28, and for MERIT is 3.87. The obtained results indicated that the proposed model could improve the MAE of vertical accuracy of SRTM, ASTER, FABDEM, and MERIT DEMs to 0.83, 0.51, 0.37, and 0.29 m, respectively.

Determination of a new gravimetric geoid modelling for Sudan using the least-squares collocation technique

The main purpose of this study is to compute a new gravimetric geoid model for Sudan by using the least-square collocation technique (LSC method) and applying the remove-compute-restore (RCR) technique. The computation of the model contains different datasets which are the gravity contribution of the model GO_CONS_GCF_2_TIM_R6e degree/order 300, BGI free-air gravity dataset in Sudan, GPS/levelling data, and high-resolution topographic information from ASTER digital elevation model. The “residual gravity anomalies” were run through the GEOCOL program using the GRAVSOFT software package, and the effects were restored to calculate the quasi-geoid surface (height anomalies). The gravimetric geoid was computed by adding the (N − \U0001d701 h ) separation term to the quasi-geoid and was fitted to the GPS and levelling data provided by Sudan. The accuracy of our gravimetric geoid model SDN-LSC-G22 of the area of Sudan and some areas of bordering countries has been investigated by using geoid undulations computed from GPS and levelling data and by investigating the differences between the geoids of the GGM models which are EGM2008 and SGG-UGM-2. Our gravimetric geoid model (SDN-LSC-G22) has indicated an accuracy of 17.4 cm, in terms of a standard deviation compared with 66 GPS and Leveling data distributed in the area of Khartoum (most of these points are control points and benchmarks). Also, we evaluated our gravimetric geoid model by using 19 points distributed in the area of Sudan, and they indicated a standard deviation of 51.3 cm. The overall accuracy of SDN-LSC-G22 compared with the geoid undulation of all GPS and levelling has indicated an STD of 34.1 cm. The model SDN-LSC-G22 has shown better accuracy and significant differences compared with the GGM models EGM2008 and SGG-UGM-2 in terms of the differences with the available GPS and levelling data which have shown ~17 cm differences using (Abdalla, 2009) GPS and levelling data. It has demonstrated STD of ~17 cm differences by using 66 GPS and levelling data. Therefore, the model SDN-LSC-G22 provided better improvements and reliable geoid heights over Sudan compared to EGM2008 and SGG-UGM-2 gravity field models.

Flash flooding hazard assessment, modeling, and management in the coastal zone of Ras Ghareb City, Gulf of Suez, Egypt

The assessment of flash flood hazards in the coastal zone of Ras Ghareb City (RGC), Red Sea, Egypt, was accomplished through the use of GIS tools and the spatial multi-criteria approach. The presented work aims to assess, integrate, and generate potential flash flood hazard maps. The analytic hierarchy process was utilized to calculate weights of hazard and vulnerability of flash flood controlling factors and their parameters such as topographical, geological, and hydrological factors. In addition, the risk degree of each specific basin and its sub-basins is estimated by combining standardized parameter values. Despite its location in an arid region, the basin may receive a large amount of rainwater, which can cause flash floods at the basin's outlet. Recently, flash flooding took place in the coastal region of RGC in October 2016 and September 2020, resulting in the loss of many human lives and catastrophic effects on local infrastructure and surrounding environments. According to reports from Hurghada, Red Sea Governorate, the RGC experienced exceptional flooding that exceeded 120 million cubic meters as a result of 51 mm of rainfall. Based on the remote sensing satellite data such as Aster Digital Elevation Model (GDEM) and the GIS tools, the basin and sub-basin drainage patterns were delineated and compared with reference topographical map sheets of a scale of 1: 50,000. The sub-basins have been isolated and morphometrically studied to determine vulnerability to flash flooding. In addition, the flash flood threat model was developed using geoprocessing tools provided by ArcGIS software to incorporate all contributing factors spatially. The flash flood risk in the Ras Ghareb (RG) basins and their sub-basins has been identified and classified into three classes (high, medium, and low hazard degree). High and moderate flood-risk basins require comprehensive studies to introduce measures to protect certain areas from flood danger. Finally, the GIS and the spatial multi-criteria analyses were effective ways to carry out a flash flood management system in order to support the decision-makers by recommendations to conserve and mitigate the possible flash flood hazards in the study areas.

Urban Growth Prediction by Land Suitability Index for Erbil City using Remote Sensing data, road networks and GIS Techniques

Using remote sensing data and Geographical Information System (GIS) methods, this study tries to anticipate the optimal urban expansion areas in Erbil city. The Analytical Hierarchy Process (AHP) concept was used to create a map of urban expansion. Several social, economic, environmental, utility and physical characteristics including land cover, roads, slope, aspect, elevation, soil texture, power lines, water and exclusion, were combined to construct a final land suitability index map. ASTER Digital Elevation Model (DEM) was also followed to derive slope and aspect variables. While organic growth is prominent, considerable growth is expected to occur around the outskirts of current settlements. This research highlights the use of modelbased prediction of urban sprawl in the development of the city’s master plan and road network plan. The findings of this study can help planners and policymakers adopt preventative or regulating measures in advance and make better informed strategic decisions.

Quality Assessment of TanDEM-X DEM 12m Using GNSS-RTK and Airborne IFSAR DEM: A Case Study of Tuba Island, Langkawi

Digital elevation models (DEMs) have been recognized as a primary spatial dataset and essential for numerous scientific applications. The advent of TerraSAR-X for digital elevation measurement (TanDEM-X) has opened a new potential to obtain an accurate DEM. Nowadays, the demand/use of TanDEM-X DEM in scientific applications has become increasingly popular as it offers an alternative to the widely used DEMs: ASTER and SRTM DEM. Although many researches have been conducted to assess the performance of the TanDEM-X DEM at different locations in the world, however, only several multi-regional studies have been performed in Malaysian region. Currently, there are two types of DEMs published by DLR i.e., non-open access (12m and 30m resolution) and open access (90m resolution). In this article, the accuracy of TanDEM-X 12m has been comprehensively and systematically evaluated using 1284 GNSS-RTK control points over Tuba Island and airborne IFSAR-DEM as a reference height. Besides, four available global DEMs: TanDEM-X 90m, AW3D30 DEM, SRTM DEM, and ASTER DEM have also been evaluated to identify the accuracy of TanDEM-X DEM 12m. Based on the evaluation using GNSS-RTK points, TanDEM-X 12m exhibits the highest accuracy with an RMSE of ±1.553m. Unexpectedly, AW3D30 DEM shows a better performance compared to TanDEM-X 90m with RMSE of ±1.964m, followed by SRTM DEM with RMSE of ±3.296m Meanwhile, ASTER DEM exhibits the lowest accuracy with RMSE of ±4.100m The comparison of TanDEM-X 12m and the well-known DEM, SRTM DEM with airborne IFSAR-DEM shows the opposite results. Based on the topographic profile at flat and forest area, the SRTM-DEM exhibits better accuracy than TanDEM-X 12m

Application of Unmanned Aerial Vehicle DEM in flood modeling and comparison with global DEMs: Case study of Atrak River Basin, Iran.

Digital Elevation Models (DEMs) play a significant role in hydraulic modeling and flood risk management. This study initially investigated the effect of Unmanned Aerial Vehicle (UAV) DEM resolutions, ranging from 1m to 30m, on flood characteristics, including the inundation area, mean flow depth, and mean flow velocity. Then, the errors of flood characteristics for global DEMs, comprising ALOS (30m), ASTER (30m), SRTM (30m), and TDX (12m) were quantified using UAV DEM measurements. For these purposes, the HEC-RAS 2D model in steady-state conditions was used to simulate the flood with return periods of 5- to 200 years along 20km reach of Atrak River located in northeastern Iran. Results indicated when UAV DEM resolution decreased from 1m to 30m, inundation area and mean flow depth increased 17.0% (R2=0.94) and 10.2% (R2=0.96) respectively, while mean flow velocity decreased 16.8% (R2=-0.94). Validation of the hydraulic modeling using the modified normalized difference water index demonstrated that the HEC-RAS 2D model in conjunction with UAV DEM simulates the flood with ⁓92% accuracy. Comparing the global DEMs with UAV DEM showed that the root mean square error (RMSE) values of the flow depth for ASTER, SRTM, ALOS, and TDX DEMs were 1.77, 1.12, 1.02, and 0.93m, and the RMSE values of the flow velocity for the same DEMs were 0.81, 0.66, 0.55, and 0.47m/s, respectively. Furthermore, TDX DEM with a 6.15% error in the inundation area was the nearest to UAV measurements. Overall, TDX DEM revealed a better performance in hydraulic modeling of the fluvial flood characteristics. Hence, it is recommended for environments where high-resolution topography data is scarce. The results of this study could potentially serve as a guideline for selecting global DEMs for hydraulic simulations.

REVIEW-EFFECT OF FLASH FLOOD

Flash flood assessment by using physiographic features, flooded areas effect can be seen quickly by satellite imagery data. Radar and microwave data is improved to an extent that it can process images even on cloudy days. Aster digital elevation model data is preferred by most of authors to extract DEM from satellite data. Individual data used in evaluation of flood flow for future safety planning and to take precautions to reduce risk damage. These criteria used for identifying areas effected by flash floods.

Spatial mapping of hydrothermal alterations and structural features for gold and cassiterite exploration

Mineral deposits show an intrinsic relationship with hydrothermal alteration and structures features which may be invaluable for regional scale exploration survey using spaceborne data. Within the Kaiama sheet, spatial data such as Landsat 8 OLI and ASTER digital elevation model were processed by enhancing hydrothermal alteration and geological lineaments. Image processing techniques such as band ratio and principal component analysis were used for alteration mapping, while Fry analysis and distance correlation analysis were applied for evaluating the structural attributes of gold and cassiterite mineralization. Evidence from image processing suggests the presence of clay and iron alterations within zones of known mineral deposits, while structural studies by application of the Fry and distance correlation analysis suggests gold and cassiterite occurrence is effectively controlled mainly by a NE-SW tectonic trend. The proximal association of gold and cassiterite mineralization with geological structures and hydrothermal alterations may be invaluable for defining a digital exploration criterion for the Kaiama sheet.

Implications and interrelations of litho-boundaries and vicinity of lineaments for hydrothermal alteration zones under remote sensing and GIS environment

The applicability and significance of remote sensing images varies according to capability of synoptic view. These synoptic views of satellite images have tremendous utility to solve many geological enigmas due to constraints of limitations of investigations (manual/ mapping error) in the field of geology. To prepare more accurate remote locations, structural maps such as lineament, fold, faults, shear zone, geomorphology, lithology and mineralogy of remote sensing image helps to solve these problems. In the research work of the hydrothermal alteration minerals zoning and identification completed through spectroscopic and advanced visible-infrared imaging spectroscopy new generation (AVIRIS-NG) hyperspectral remote sensing data. To establish intercorrelation and implications of lineaments with hydrothermal alteration zone of the study area prepared lineament map through manual and auto extraction using Landsat 7 ETM+ and ASTER digital elevation model (DEM) remote sensing data with the applications of algorithms such as Sobels filtering and “LINE” tool of PCI Geomatica. The networks of lineaments have a significant role in demarcation of potential mineral zones. To get vicinity of lineaments, prepared a lineament density map through extracted lineaments. In the final output the vicinity of lineaments density, mineral sample locations, mineral map and regolith zones have shown strong correlation among each other. So, the conclusion is that there is a strong significance in intercorrelation of hydrothermal alteration zones, lineaments and litho-boundaries.

Evaluation of Shannon Entropy and Weights of Evidence Models in Landslide Susceptibility Mapping for the Pithoragarh District of Uttarakhand State, India

Landslide susceptibility mapping is considered a useful tool for planning, disaster management, and natural hazard mitigation of a region. Although there are different methods for predicting landslide susceptibility, the bivariate statistical analysis method is considered to be simple and popular. In this study, the main aim is to evaluate the performance of Shannon entropy (SE) and weights of evidence (WOE) statistical models in landslide susceptibility mapping of Pithoragarh district of Uttarakhand state, India. For this purpose, ten landslide affecting factors, namely, slope degree, aspect, curvature, elevation, land cover, slope forming materials, geomorphology (landforms), distance to rivers, distance to roads, and overburden depth were used for the development of landslide susceptibility maps using the SE and WOE methods. Data extracted from the Google Earth images, Aster Digital Elevation Model, and Geological Survey of India report were used for the construction and evaluation of landslide susceptibility models and maps. The landslide data of 91 locations were randomly divided into two parts in the ratio of 70 : 30 using GIS software that is 70% data was used for training the models and 30% data was used for testing and validating the models. Performance of the applied models was evaluated using area under the AUC (area under the curve) ROC (receiver operating characteristics) curve. Results indicated that the WOE model is having better accuracy (AUCWOE = 68.75%) than the SE model (AUCSE = 52.17%) in the development of landslide susceptibility maps. Hence, WOE model can be used for the development of accurate landslide susceptibility maps which can provide useful information to decision maker and policy planner in better development of landslide prone areas.