SRTM DEM Data Research Articles

Prioritization of Sub-Watersheds for Soil and Water Conservation in Parts of Narmada River through Morphometric Analysis Using Remote Sensing and GIS

ABSTRACT GIS-based prioritization of sub-watersheds of Hoshangabad and Budhni industrial area, Madhya Pradesh, India were carried out to describe the importance of morphometric parameters in the field of water and soil conservation. In the study, four subwatersheds were prioritized through geomorphologic analysis for soil and water conservation. Topographic maps 55 F/9, 55 F/10 and 55 F/13 on scale 1:50,000 were used to evaluate the drainage characteristics of watershed. SRTM DEM data has been processed for slope analysis and delineation of sub-watersheds. LISS-III, IRS data was processed for land use/ land cover analysis. Soil map has been generated by processing of NBSS & LUP soil map. The various morphometric parameters evaluated in each sub-watershed includes drainage network, drainage geometry and texture analysis and relief parameters in ArcGIS. Each sub-watershed has been prioritized by assigning ranks using compound parameter. After prioritization, land use, soil type and slope classes of each subwatershed were integrated to propose suitable soil and water conservation structures at appropriate places. It has been suggested that the proposed soil and water conservation structures must be executed on priority basis to reduce the adverse effect on the land and environment. The study shows that classification and prioritization of sub-watersheds are very relevant, supportive and useful in the watershed, where there is high diversity in agricultural practices, soil texture and land cover. Thus, priority wise execution of the proposed soil and water conservation structures will not only reduce the soil erosion but also increase the surface and groundwater availability in the area. Therefore, prioritization of these sub-watersheds is found very helpful for soil conservation and management of groundwater in the watershed.

Glacier elevation change in the Western Qilian mountains as observed by TerraSAR-X/TanDEM-X images

The glaciers in the Qilian mountains are a major water resource for the arid Hexi corridor and Qaidam basin. With the climate becoming warmer and wetter, it is essential to study the glacier elevation changes in this region. We used TerraSAR-X/TanDEM-X images, SRTM DEM data and differential synthetic aperture radar interferometry (DInSAR) technology to analyse the glacier elevation change. Results show that the glacier elevation is changing at the rate of –0.35 m yr−1 in the western Qilian mountains between 2000 and 2014. The glacier elevation thinning at –0.40 m yr−1 in the southern part of this region is more severe than that in the northern part (–0.29 m yr−1). The long-term equilibrium line altitude, calculated from glacier elevation change in each elevation bin, was at 5150 m, which is equal to that inferred from glacial area distribution in each elevation bin. Glacier shrinkage is related to air temperature increasing.

Demarcation of liquefaction zones and risk reduction in Fiji Islands from a geomatics perspective: a case study of Viti Levu Island

Liquefaction induced by tectonism is lethal which warrants up-front risks reduction planning. It is one of the geohazards associated with seismic ground shaking or tremor which result in collapse of buildings, loss of lives and environmental disturbances. Numerous procedures have been employed to identify potential liquefaction zones. The present study aims at assessing the site-soil-geology of Viti Levu Island using the GIS and remote sensing techniques. Site-soil-geology, geomorphology and SRTM DEM data were the main sources of layers used to carry out such analysis using the Saaty’s analytical hierarchical process and ArcGIS multi-criteria analysis. In the ArcGIS 10.5 spatial analyst tool, the raster calculator, reclassify and weightage overlay tools were chosen for this study. The final result of liquefaction potential zone indicates the ‘low’, ‘moderate’, ‘high’ and ‘very high’ zones for spatial planners and decision makers to formulate policies. Emphasizing the preventative measures as pro-active role rather than re-active role has been highlighted in this spatial physical planning exercise.

High-Resolution Urban Land Mapping in China from Sentinel 1A/2 Imagery Based on Google Earth Engine

Accurate and timely urban land mapping is fundamental to supporting large area environmental and socio-economic research. Most of the available large-area urban land products are limited to a spatial resolution of 30 m. The fusion of optical and synthetic aperture radar (SAR) data for large-area high-resolution urban land mapping has not yet been widely explored. In this study, we propose a fast and effective urban land extraction method using ascending/descending orbits of Sentinel-1A SAR data and Sentinel-2 MSI (MultiSpectral Instrument, Level 1C) optical data acquired from 1 January 2015 to 30 June 2016. Potential urban land (PUL) was identified first through logical operations on yearly mean and standard deviation composites from a time series of ascending/descending orbits of SAR data. A Yearly Normalized Difference Vegetation Index (NDVI) maximum and modified Normalized Difference Water Index (MNDWI) mean composite were generated from Sentinel-2 imagery. The slope image derived from SRTM DEM data was used to mask mountain pixels and reduce the false positives in SAR data over these regions. We applied a region-specific threshold on PUL to extract the target urban land (TUL) and a global threshold on the MNDWI mean, and slope image to extract water bodies and high-slope regions. A majority filter with a three by three window was applied on previously extracted results and the main processing was carried out on the Google Earth Engine (GEE) platform. China was chosen as the testing region to validate the accuracy and robustness of our proposed method through 224,000 validation points randomly selected from high-resolution Google Earth imagery. Additionally, a total of 735 blocks with a size of 900 × 900 m were randomly selected and used to compare our product’s accuracy with the global human settlement layer (GHSL, 2014), GlobeLand30 (2010), and Liu (2015) products. Our method demonstrated the effectiveness of using a fusion of optical and SAR data for large area urban land extraction especially in areas where optical data fail to distinguish urban land from spectrally similar objects. Results show that the average overall, producer’s and user’s accuracies are 88.03%, 94.50% and 82.22%, respectively.

Land cover classification in the tropics, solving the problem of cloud covered areas using topographic parameters

Optical remote sensing data has been extensively used since early seventies for mapping and monitoring land cover. But, cloud cover has always been hindering the optimal use of the data, especially in the tropical and temperate regions. Because of cloud cover, researchers are forced to use only cloud free images or generate a composite using data from different dates to fill in the cloud and cloud-shadow areas. It is not a problem if the filling image is from the same season and from the same year. If there is large time gap between the acquisition date of image with the clouds and that of the filling image it will have an effect on classification accuracy. In this paper, we describe an approach in land cover classification of areas covered by cloud and cloud shadows. We use the synergy of optical image classification, processing of SAR data taking advantage of its ability of penetrating clouds, and decision rules using terrain parameters. We hypothesize that surface roughness of different land cover types derived from processing of SAR data and in combination with other topographic parameters (slope and elevation) can be applied to classify areas covered by clouds and cloud-shadows. The method was applied in a case study in Mts. Wayang-Windu and Patuha areas, near Bandung in West Java, Indonesia. Landsat 8 OLI-TIRS, Sentinel-1 A C band and SRTM DEM data of the study area were obtained. Initial classification of the optical data was carried out using training samples and fuzzy classification. Class labelling was done by applying fuzzy c-means algorithm. The Sentinel-1 A C band data was processed to get surface roughness. Decision boundaries for surface roughness, terrain slope and elevation were generated for each land cover type, which were implemented in the classification of the areas covered by cloud and cloud shadows. The result shows that it is possible to solve the problem of cloud cover using terrain parameters.

Spatio-temporal variability of lightning activity over J&K region and its relationship with topography, vegetation cover, and absorbing aerosol index (AAI)

Spatio-temporal variation of lightning activity over the Jammu and Kashmir province has been studied in the present research using LIS data for the period of 12 years (2001–2013). In addition, the association of lightning activity with the elevation range, vegetation cover, and absorbing aerosol index (AAI) has been studied using the LULC data of MODIS, elevation data of SRTM DEM and multi-sensor AAI data (GOME-1, SCIAMACHY, GOME-2 and OMI). It was observed through the analysis of data sets that the J&K region which lies in the Himalayan range experiences very high frequency of lightning occurrences in entire India. The lightning frequency is much higher towards the south-western side of J&K region at an altitude range of 300–1600 m. It was observed that the mixed forests and croplands contribute more towards the higher occurrence of the lightning activity. Furthermore, it has been discerned that there is a positive correlation between the Mean Monthly flash density (FD) and Mean Monthly Absorbing aerosol index (AAI) with a correlation coefficient of 0.61 and an increase in FD and AAI was observed in summer months and decreases towards the onset of spring to winter. The comparison between the AAI and FD indicates that the spatial distribution of the two components has alike features over southwestern portion, with maximum values in the summer months and decrease upto the winter season. The findings of the present study suggest that the elevation range, Absorbing Aerosol Index along with the type of LULC plays an important role in a linkage with the occurrence of higher lightning activities in J&K region.

Based on GIS Technology, the Heihe River Drainage Network is Extracted from Srtm-dem Data

For instance objects based on the HeiHe river basin and its water system, based on the space shuttle radar topography production of 90m high-resolution SRTM-DEM data, using the Hydrology ArcGIS10.2 hydrological analysis module of HeiHe river basin drainage network extraction and related analysis, verified the SRTM-DEM data application in hydrological analysis, also objectively shows the SRTM-DEM data the prospect of application in hydrological aspects is very objective.

Overflow probability of the Salt Lake in Hoh Xil Region

After the bursting of Huiten Nor in Hoh Xil Region in September, 2011, the topic on whether the water overflowed from the Salt Lake would enter into the Chumaer River and become the northernmost source of the Yangtze River has aroused wide concern from public and academic field. Based on Landsat TM/ETM+/OLI remote sensing images during 2010–2015, SRTM 1 arc-second data, Google Earth elevation data and the observation data from the Wudaoliang meteorological station, the study initially analyzed the variations of the Salt Lake and its overflowing condition and probability. The results showed that the area of the Salt Lake expanded sharply from October 2011 to April 2013, and then it stepped into a stable expansion period. On October 27, 2015, the area of the Salt Lake had arrived at 151.38 km2, which was about 3.35 times the area of the lake on March 3, 2010. The Salt Lake will overflow when its area reaches the range from 218.90 km2 to 220.63 km2. Due to the differences between SRTM DEM and Google Earth elevation data, the water level of the Salt Lake simulated would be 12 m or 9.6 m higher than the current level when the lake overflowed, and its reservoir capacity would increase by 23.71 km3 or 17.27 km3, respectively. Meanwhile, the overflowed water of the Salt Lake would run into the Qingshui River basin from its eastern part. Although the Salt Lake does not overflow in the coming decade, with watershed expansion of the Salt Lake and the projected precipitation increase in Hoh Xil region, the probability of water overflow from the Salt Lake and becoming a tributary of the Yangtze River will exist in the long term.

Extraction and Validation of Geomorphological Features from EU-DEM in The Vicinity of the Mygdonia Basin, Northern Greece

The European Union Digital Elevation Model (EU-DEM) is a relatively new, hybrid elevation product, principally based on SRTM DEM and ASTER GDEM data, but also on publically available Russian topographic maps for regions north of 60° N. More specifically, EU-DEM is a Digital Surface Model (DSM) over Europe from the Global Monitoring for Environment and Security (GMES) Reference Data Access (RDA) project - a realisation of the Copernicus (former GMES) programme, managed by the European Commission/DG Enterprise and Industry. Even if EU-DEM is indeed more reliable in terms of elevation accuracy than its constituents, it ought to be noted that it is not representative of the original elevation measurements, but is rather a secondary (mathematical) product. Therefore, for specific applications, such as those of geomorphological interest, artefacts may be induced. To this end, the purpose of this paper is to investigate the performance of EU-DEM for geomorphological applications and compare it against other available datasets, i.e. topographic maps and (almost) global DEMs such as SRTM, ASTER-GDEM and WorldDEM™. This initial investigation is carried out in Central Macedonia, Northern Greece, in the vicinity of the Mygdonia basin, which corresponds to an area of particular interest for several geoscience applications. This area has also been serving as a test site for the systematic validation of DEMs for more than a decade. Consequently, extensive elevation datasets and experience have been accumulated over the years, rendering the evaluation of new elevation products a coherent and useful exercise on a local to regional scale. In this context, relief classification, drainage basin delineation, slope and slope aspect, as well as extraction and classification of drainage network are performed and validated among the aforementioned elevation sources. The achieved results focus on qualitative and quantitative aspects of automatic geomorphological feature extraction from EU-DEM at a water basin level, with the use of Geographical Information Systems (GIS).

Identifying potential sites for hydropower plant development in Busu catchment: Papua New Guinea

Identification of potential sites and then switching to hydro power saves the earth from the menace of emissions from fossil fuel, triggering climate change the world is currently agog with. Quantitative knowledge of the topographical setting along with the stream network within a river catchment is the key to identification of potential sites for hydropower plant development. For the present study, GIS and remote sensing technology were adopted for identifying potential sites for hydropower plant development in the Busu river catchment area. The river discharge was calculated with the help of average rainfall, soil texture, and the land use land cover data. The head was calculated using the SRTM DEM data utilizing focal statistical analysis tool in ArcGIS 10.2. Potential power output was calculated with the density of water and gravitational pull, and then through necessary integration the levels of power output at each site were indicated. Busu river catchment was found to be the most potential site for producing power up to 24 MegaWatt which was the maximum that was identified during evaluation and calculation. This method is suitable for initial screening only. Further in-depth feasibility study is needed to develop hydropower plant sites.

SURFACE DEFORMATION MONITORING IN PERMAFROST REGIONS OF TIBETAN PLATEAU BASED ON ALOS PALSAR DATA

Abstract. The permafrost region of Qinghai-Tibet Plateau is widely distributed with the freeze/thaw processes that cause surface structural damage. The differential interferometry synthetic aperture radar (DInSAR) can detect large scale surface deformation with high precision, thus can be used to monitor the freeze/thaw processes of frozen soil area. In this paper, the surface deformation pattern of Qinghai-Tibet railway was analyzed by using the PALSAR 1.0 raw data of the ALOS satellite (L band) and 90m resolution SRTM DEM data, with the help of two-pass DInSAR method in GAMMA software, and the differential interferograms and deformation maps were obtained accordingly. Besides, the influence of temperature, topography and other factors on deformation of frozen soil were also studied. The following conclusions were obtained: there is a negative correlation between deformation and temperature, and there is a delay between the deformation change and that of temperature; deformation and elevation are positively correlated; the permafrost deformation is also affected by solar radiation that could form variable amplitude variation.

A Study on Ortho-rectification of SPOT6 Image

Orthorectification of SPOT6 image based on Rational Function and Rigorous Orbit Model was conducted using the rational polynomial coefficient file (PRC), ASTER and SRTM DEM data and the field control point data in Huludao, Liaoning Province. The accuracy difference of orthorectify model and DEM was analyzed. The results showed that both orthorectification models based on the ASTER data and SRTM data can meet the 1: 10000 digital orthophoto mapping accuracy, different DEM has no influence on the accuracy of Rigorous Orbit Model without control points, The rational function model with control point correction method using SRTM data correction precision is higher. The correction accuracy of SRTM data in using 3-4 control points reached 2.85m, the application of ASTER data correction accuracy up to 3.30m.

ENGLISH

Tectonism induced liquefaction can be a major disaster that warrants appropriate emphasis in any infrastructure development planning. Various procedures and methods are applied throughout the world to identify potential zones of liquefaction. The output results are used as tools for site selection and finding viability of funding in infrastructure development. Thus such measure is slated to preclude future loss of life and property owing to infrastructure collapse by earthquake induced liquefaction. Liquefaction is likely to occur due to saturated soils or unconsolidated sediments under the infrastructure basement that are subjected to give way due to ground shaking. Liquefaction is one of the main geohazards related to tremor. The present study aims at assessing different soil properties and geological structures of Morobe and Madang Province culminating in delineation of Liquefaction potential zones using multi-criteria evaluation and Analytical Hierarchy Process (AHP) appraisal using GIS and Remote sensing technologies. The main data layers that are chosen for carrying out the assessment consist in available geological, soil and SRTM DEM data. Several thematic layers are prepared from the data base as mentioned, followed by assigning weightage to each thematic layer generated. Weightages were further normalized using Saaty’s analytical hierarchy process. The final Liquefaction potential zone was prepared using the raster calculated from ArcGIS. The output liquefaction potential zone map was delineated and reclassified into five categories such as ‘very high', ‘high', ‘moderate', ‘low’ and ‘very low’ potential zones.

Effect Analysis of Statistical Unit on Relief Amplitude in Chongqing, China

This paper researches the influence rule of unit size on relief amplitude by analyzing relief amplitudes under various statistical units and determines the optimum statistical unit in study area-Chongqing using the correlation between different statistical data. The results show that relief amplitude increased with increasing area of statistical unit, but increasing rate finally becomes stable. When determining the optimum unit using artificial drawing method, the point maintains stable can be found. The optimum unit area is 4km2 of SRTM-DEM data in study area.

Seamless Synthetic Aperture Radar Archive for Interferometry Analysis

Abstract. The NASA Advancing Collaborative Connections for Earth System Science (ACCESS) seamless synthetic aperture radar (SAR) archive (SSARA) project is a collaboration between UNAVCO, the Alaska Satellite Facility (ASF), the Jet Propulsion Laboratory (JPL), and OpenTopography at the San Diego Supercomputer Center (SDSC) to design and implement a seamless distributed access system for SAR data and derived interferometric SAR (InSAR) data products. A unified application programming interface (API) has been created to search the SAR archives at ASF and UNAVCO, 30 and 90-m SRTM DEM data available through OpenTopography, and tropospheric data from the NASA OSCAR project at JPL. The federated query service provides users a single access point to search for SAR granules, InSAR pairs, and corresponding DEM and tropospheric data products from the four archives, as well as the ability to search and download pre-processed InSAR products from ASF and UNAVCO.

Analysis of lengths, water areas and volumes of the Three Gorges Reservoir at different water levels using Landsat images and SRTM DEM data

The impoundment and operation of the Three Gorges Reservoir (TGR) are geophysical “controlled experiments”. However, detailed procedures, data source and uncertainties on TGR's basic parameters, such as lengths, water areas and volumes, were not available to the science community, and are provided in this study by using Landsat images, SRTM DEM data and in situ measurements. Reservoir lengths are between 650 km and 700 km at the water level of 175 m above sea level (a.s.l.). The natural (but near maximum) water area of the Yangtze River within the reservoir (at the full range of 699 km) based on Landsat images was 489 km2 in August, 2002, before the impoundment. At 175 m a.s.l., the total water area mapped by Landsat images (929 km2) is ∼10% less than those derived from SRTM DEM data (1006 km2) and reported by Three Gorges Corporation (TGC) (1040 km2). SRTM DEM data could classify 90–92% of these areas as water areas, while the total areas from Landsat, SRTM and TGC have over 96% agreements at water levels ≤170 m. The larger estimate of water area by DEM data from both TGC and SRTM at 175 m could be partially explained by the construction of levees. The total static volumes derived from SRTM DEM data above 70 m have a linear relationship (R2 = 0.99, Mean Absolute Difference = 0.43 km3) with those reported by the Information Center of Water Resource (ICWR), Ministry of Water Resource, China. The analysis also suggests that the ICWR-reported water volumes in the reservoir neglect the wedge storage in a flooding peak.

Research on and Application of SRTM DEM Data for Geological Mapping in China

Research on and Application of SRTM DEM Data for Geological Mapping in China

Geology and Geomorphology of the Manipur Valley Using Digitally Enhanced Satellite Image and SRTM DEM in the Eastern Himalaya, India

Landsat ETM+ data and SRTM DEM data were used to delineate the geological, structural and geomorphological features in the intermontane Imphal Valley in Manipur, India. This area has simple geology, structural features and there- fore provides an ideal site to test the utility of remote sensing and GIS techniques in geological studies. The various techniques such as band ratioing, Principal Component Analysis (PCA) and generation of FCC (False Colour Composite) were employed on ETM+ data. The SRTM DEM data is used in generating the west-east transects of altitude pro- files in the valley for characterization of altitude levels of the litho-units. DEM derived drainage network and relative drainage density in the basin were used in interpreting the location of fault plane in the valley. The slope and lineament maps were prepared using SRTM DEM. It suggests that entire valley is covered by very low slope (0? - 9?). Lineaments are oriented N-S, 180? while in south-east of valley the direction is largely NW-SE. The change in lineament direction suggests that the eastern side of the valley is controlled by Indonesian Island arc strike direction.

Auto-detection and integration of tectonically significant lineaments from SRTM DEM and remotely-sensed geophysical data

A set of techniques was developed for automatically detecting tectonic lineaments from multi-source remotely-sensed data at various scales. The techniques include adaptive shading of grid data to enhance linear features, a segment-tracing algorithm to extract line segments from the shaded grid data, grouping of the segments by concatenating short segments, and connecting them by proximity and co-linearity criteria to form a lineament that represents significant tectonic structure. B-spline smoothing was adopted for lineament representation. Finally, a technique for assessing the orientations and styles of faulting (normal, reverse, and strike-slip types) was developed for use in characterizing the extrapolated fracture planes. The applicability of the developed techniques was examined using 30 arc-second topography/bathymetry grids, 1-min gravity anomaly grids, and 2-min total field magnetic intensity grids covering Egypt and its surroundings. Lineaments derived from data types so diverse in composition and from various depths corresponded well with the referenced tectonic features over much of the region. Prominent trends and faulting styles of lineaments provided important clues as to the timing of their development as well as strong support for a structural inheritance model. Results demonstrated the effectiveness of the developed techniques combined with integration of remotely-sensed data in detecting regional fracture systems accurately and in characterizing geodynamics over a long timeframe.

Mapping of Lateritic Soils of Midlands in Kerala Using Resourcesat-1 LISS-III and SRTM DEM Data

Lateritic soils of Mathamangalam, Kannur District, located in midlands of Kerala, were morphologically studied, characterized, classified and mapped at 1:50,000 scale using remote sensing techniques. The terrain of the study area being hilly and covered with perennial vegetation, soil-landscape model was applied. For this purpose physiographic information was inferred from SRTM DEM, Resourcesat-1 LISS-III satellite image and topographical maps. The interpreted units were validated in the field and characterized through soil-site examination, soil profile study and soil analysis. The study indicated that the lateritic soils of midlands of Kerala vary in physical, chemical and morphological properties in relation to micro-relief. Soils developed on moderately steeply sloping side slopes (15–30% slope) are deep, moderately well drained with gravelly clay textured, where as the soils developed on moderately slopping side slope (10–15% slope) are very deep and well drained. The soils of valleys are very deep, moderately well drained with fine texture. Very gently sloping (1–3%) laterite plateau tops have extremely shallow soils associated with rock outcrops. These soils mainly belong to Order Ultisols followed by Inceptisols and Entisols. These were further grouped up to Family and Series level by tentatively establishing seven soil series. This study helps in understanding the behaviour of lateritic soils of midlands of Kerala, which can be useful in generation of interpretative maps and in optimizing the land use.