Papers by Mritunjay Singh
m-hikari.com
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Arabian Journal of Geosciences, 2014
ABSTRACT Updated and Accurate Digital Elevation Model (DEM) of snow covered and glaciated mountai... more ABSTRACT Updated and Accurate Digital Elevation Model (DEM) of snow covered and glaciated mountainous area is essential for many applications such as avalanche hazard and numerical modeling of mass movements or mapping of terrain changes. The best high resolution terrain product available for Himalayan region is the DEM, with a spatial resolution of 10m, generated using Cartosat-1 stereo ortho-kit data. Even this spatial resolution is insufficient for many applications like avalanche hazard mapping or forecasting in complex mountainous terrain. This study reports the process of high spatial resolution (1m) DEM generation for Manali and nearby areas using digital aerial photogrammetric survey data of 40cm Ground Sampling Distance (GSD), captured through airborne ADS80 push-broom camera for the first time in Indian Himalayas. This DEM was also evaluated with Differential Global Positioning System (DGPS) points for accuracy assessment. The ADS80 DEM gave Root Mean Square Error (RMSE) of ~<1 m and Linear Error, at 90% confidence interval (LE 90) of 1.36 m in comparison with the DGPS points.
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Geocarto International, 2019
This research paper proposes a new five-step protocol to enhance the result of existing cloud rem... more This research paper proposes a new five-step protocol to enhance the result of existing cloud removal algorithms using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products (SCPs). The study has been carried out for the upper Bhagirathi basin (up to Maneri Hydropower Project) located in the Western Himalaya. Gafurov and Bárdossy test employed to validate the performance of the proposed method, followed by comparing with the field observed snow cover duration (SCD) data. The result shows that the mean overall accuracy of the proposed method for cloud removal is about ∼95%. However, the cloud removal method by Gafurov and Bardossy also achieved similar mean overall accuracy but with the higher variability within the individual images as compared with the variability within the results obtained by the proposed method. SCD computed from cloud removed SCPs matched significantly with the field observed SCD for a point location, supporting the accuracy achieved by the cloud removal method. This study also examines the spatiotemporal variability of the snow cover in the study area during the past 18 years (2000–2018). During the observation period, no specific trend was observed for annual maximum snow cover, while yearly minimum snow cover in the basin showed an increasing trend since 2010. Seasonally, December and June month witnessed significant changes. December experienced a declining trend in snow cover between 3000–6000 m a.s.l. covering 88% of the basin area, whereas, June showed an increasing trend between 4500 to 6000 m (a.s.l.). This elevation range covers 61% of the basin area, including core 86% of the glacier area within the basin. September and October experienced the highest inter-annual snow cover variability. Maximum snow cover month of February and minimum snow cover month of August experienced the least variability. The present study suggests significant elevation-dependent increasing as well as the decreasing trend in the snow cover with seasonal contrast, which may affect the glaciers as well as the hydrological behavior of the basin.
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The main objective of the study is Digital Terrain Model (DTM) generation from aerial photogramme... more The main objective of the study is Digital Terrain Model (DTM) generation from aerial photogrammetric data and identify and map the potential avalanche prone zones in Manali region. Avalanche is a dynamic hazardous phenomenon in the snow-bound mountainous terrain. Mapping of avalanche prone terrain is crucial to minimize the avalanche hazard. Nowadays, airborne data capturing technology, such as large-format Photogrammetry, has opened new vistas for the mapping of complex and inaccessible mountainous areas. In the present study, large format digital Photogrammetry data of 20 cm ground sample distance (GSD) have been used to generate high-resolution and accurate Digital Elevation Model and ortho-images. Digital terrain model along with its derivative terrain products and land cover map generated from land cover classification of derived ortho-photo is analyzed to locate the probable avalanche zone. The terrain characteristics, snow-pack condition and prevailing meteorological conditions are the groups of variables that influence the occurrence of avalanche. Amongst these, the terrain characteristics is the most influencing factor, and easier to map due to its stable nature along the time. Therefore advanced geo-informatics techniques have been used by mixing terrain property, Digital Elevation Model (DEM) and satellite imagery to determine the different geographical factors that affect the avalanche triggering. Also the derived information was combined in Analytic Hierarchy Process to extract a map of the avalanche prone zones in the study area standard mapping techniques as coarse-resolution data are not very appropriate for such studies.
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The temporal monitoring of any glacier is important for observing the effects of changing climate... more The temporal monitoring of any glacier is important for observing the effects of changing climate. This study reports the decadal changes in Siachen glacier. Analysis was carried out on decadal basis by processing and analyzing Landsat images from 1978 to 2013. Images were co-registered within Root Mean Square Error (RMSE) limit of 0.5 pixel. An object based classification approach was adopted to perform temporal semi-automated areal change detection. The glacier inventory of 1978 showed around 74976 ha of glacier area which further decreased by around 1302 ha in 2013 with a shift of 1.5 km in the snout position.
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Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for ... more Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for heavy damage to the property. Avalanche susceptibility maps assist decision-makers and planners to execute suitable measures to reduce the avalanche risk. In the present study, a probabilistic data-driven geospatial fuzzy–frequency ratio (fuzzy–FR) model is proposed and developed for avalanche susceptibility mapping, especially for the large undocumented region. The fuzzy–FR model for avalanche susceptibility mapping is initially developed and applied for Lahaul-Spiti region. The fuzzy–FR model utilized the six avalanche occurrence factors (i.e. slope, aspect, curvature, elevation, terrain roughness and vegetation cover) and one referent avalanche inventory map to generate the avalanche susceptibility map. Amongst 292 documented avalanche locations from the avalanche inventory map,
233 (80%) were used for training the model and remaining 59 (20%) were used for validation of the map. The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve (ROC-AUC) technique. For validation of the results using ROC-AUC technique, the success rate and prediction rate were calculated. The values of success rate and prediction rate were 94.07% and 91.76%, respectively. The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping
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The accuracy of DEMs shows wide variations from one terrain to another and it needs to be determi... more The accuracy of DEMs shows wide variations from one terrain to another and it needs to be determined. This study evaluates NRSC (National Remote Sensing Centre, Hyderabad, India) CartoDEM V1 and V1.1R1 with respect to resampled ADS80 DEM for parts of the Himalayas. Both the test DEMs were properly registered with reference to resampled ADS80 DEM and then individually subtracted to get the difference DEMs. Visual and statistical analyses were performed to assess the quality of the tested DEMs in terms of visible terrain and vertical accuracy. For calculating the accuracies in different terrain classes, slope and aspect maps were generated from the ADS80 DEM. Properly registered Landsat5 TM data was used for the development of the land cover map with 4 classes. The overall vertical accuracy measured for CartoDEM V1 was 269.9m (LE90) while CartoDEM V1.1R1 showed huge improvement in the accuracy with 68.5m (LE90).
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The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used ... more The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.
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Accuracy of the Digital Elevation Model (DEM) affects the accuracy of various geoscience and envi... more Accuracy of the Digital Elevation Model (DEM) affects the accuracy of various geoscience and environmental modelling results. This study evaluates accuracies of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM Version-2 (GDEM V2), the Shuttle Radar Topography Mission (SRTM) X-band DEM and the NRSC Cartosat-1 DEM V1 (CartoDEM). A high resolution (1 m) photogrammetric DEM (ADS80 DEM), having a high absolute accuracy [1.60 m linear error at 90 % confidence (LE90)], resampled at 30 m cell size was used as reference. The overall root mean square error (RMSE) in vertical accuracy was 23, 73, and 166 m and the LE90 was 36, 75, and 256 m for ASTER GDEM V2, SRTM X-band DEM and CartoDEM, respectively. A detailed error analysis was performed for individual as well as combinations of different classes of aspect, slope, land-cover and elevation zones for the study area. For the ASTER GDEM V2, forest areas with North facing slopes (0°–5°) in the 4th elevation zone (3773–4369 m) showed minimum LE90 of 0.99 m, and barren with East facing slopes (>60°) falling under the 2nd elevation zone (2581–3177 m) showed maximum LE90 of 166 m. For the SRTM DEM, pixels with South-East facing slopes of 0°–5° in the 4th elevation zone covered with forest showed least LE90 of 0.33 m and maximum LE90 of 521 m was observed in the barren area with North-East facing slope (>60°) in the 4th elevation zone. In case of the CartoDEM, the snow pixels in the 2nd elevation zone with South-East facing slopes of 5°–15° showed least LE90 of 0.71 m and maximum LE90 of 1266 m was observed for the snow pixels in the 3rd elevation zone (3177–3773 m) within the South facing slope of 45°–60°. These results can be highly useful for the researchers using DEM products in various modelling exercises.
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DOI: 10.1016/j.coldregions.2014.07.006., Jul 27, 2014
Supraglacial debris significantly hampers the mapping of glaciers using remote sensing data. A se... more Supraglacial debris significantly hampers the mapping of glaciers using remote sensing data. A semi-automated approach for the mapping of debris-covered glacier was applied, which combined the inputs from thermal and optical remote sensing data and the Digital Elevation Model (DEM) derived morphometric parameters.A thermal mask delineates the supraglacial debris extent was generated by thresholding of surface temperature layer obtained from Landsat TM/ETM + thermal band satellite data. The extent of clean glacier ice was identified by band ratioing and thresholding of TM/ETM + 4 and TM/ETM + 5 bands.Morphometric parameters like slope, plancurvature and profile curvature were rearranged insimilar surface groups using the technique of cluster analysis. All these masks were vectorised and final classification maps were generated using geographic information system (GIS) overlay operations. The areal extent of semi-automated outlines of Hamtah and Patsio Glaciers derived from cluster analysis varied from manually derived outline using pan-sharpened Landsat ETM + September 2000 image by -1.3% and -1.6%, respectively. Year 2011 classification map for Patsio Glacier was compared with the field observations and a high correlation and overall accuracy (~ 91%) was observed. The same classification methodology was adopted for images of years 2000 and 1989 for Patsio Glacier to observe the effects of varying snow cover patterns on adopted methodology. Also the methodology was adopted and verified for Hamtah Glacier, with different geometry and terrain conditions as compared to Patsio Glacier. Although the spatial resolution limitation of ASTER GDEM and Landsat TM/ETM + thermal band limits the automated mapping of small debris-covered glaciers, the outcomes are stillfavorable enough to apply such methodologies for mapping different types of debris - covered glaciers in the future.
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DOI:10.1080/14498596.2014.943310, Aug 5, 2014
This study established a decadal correlation between meteorological observations (temperature and... more This study established a decadal correlation between meteorological observations (temperature and snowfall) and satellite-derived seasonal snow cover for a glacier catchment. The study area was classified into 10 elevation zones. The time period for considering climatic variables was from the start of the significant fresh snowfall of the new season to the date of satellite image acquisition. The snowfall inputs from the five meteorological stations at different altitudes were interpolated for the entire catchment using a discretised thin-plate spline technique. A local temperature lapse rate for this specific time period was calculated. It was applied throughout the catchment for interpolating the temperature, which was further used to refine the interpolated snowfall. Such a hypsometric approach along with third-order polynomial curve fitting (R2 = 0.998) finally gave an equation for estimating percent snow-covered area for different elevation zones with a good accuracy and very low average RMSE (Root Mean Square Error) of 3.16 percent.
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DOI:10.1080/10106049.2014.925003, Jul 25, 2014
This study scrutinises the use of terrestrial laser scanning (TLS) to measure diameter at breast ... more This study scrutinises the use of terrestrial laser scanning (TLS) to measure diameter at breast height (DBH) and tree height at individual tree species level. LiDAR point cloud scans are collected from uniformly defined control points. The result of processed TLS data demonstrates the precise measurements of tree height and DBH by comparing it with field data (DBH, tree height, tree species and location). The average tree height and DBH obtained through TLS measurements were 9.44 m and 43.30 cm, respectively. A linear equation between TLS derived parameters and field measured values were established, which gave the coefficient of determination (r2) of 0.79 and 0.96 for tree height and DBH, respectively. Further, these parameters were used to calculate above ground biomass (AGB) for individual tree species by considering a non-destructive approach. The total AGB and carbon stock from 80 different trees are computed to be 49.601 and 22.320 tonnes, respectively.
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DOI: 10.5194/isprsarchives-XL-4-71-2014
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DOI:10.1080/10106049.2014.883434, Mar 31, 2014
This work provides an overview of various methods for estimating snow cover and properties in hig... more This work provides an overview of various methods for estimating snow cover and properties in high mountains using remote sensing techniques involving microwaves. Satellite based remote sensing with its characteristics such as synoptic view, repetitive coverage and uniformity over large areas, has great potential for identifying the temporal snow cover. Many sensors have been used in the past with various algorithms and accuracies for this purpose. These methods have been improving with the use of Synthetic Aperture Radar (SAR) sensors, working in different microwave frequencies, polarization and acquisition modes. The limitations, advantages and drawbacks are illustrated while error sources and strategies on how to ease their impacts are also reviewed. An extensive list of references, with an emphasis on studies since 1990s, allows the reader to delve into specific topics.
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DOI: 10.1007/s12517-014-1299-9, Feb 13, 2014
Updated and Accurate Digital Elevation Model (DEM) of snow covered and glaciated mountainous area... more Updated and Accurate Digital Elevation Model (DEM) of snow covered and glaciated mountainous area is essential for many applications such as avalanche hazard and numerical modeling of mass movements or mapping of terrain changes. The best high resolution terrain product available for Himalayan region is the DEM, with a spatial resolution of 10m, generated using Cartosat-1 stereo ortho-kit data. Even this spatial resolution is insufficient for many applications like avalanche hazard mapping or forecasting in complex mountainous terrain. This study reports the process of high spatial resolution (1m) DEM generation for Manali and nearby areas using digital aerial photogrammetric survey data of 40cm Ground Sampling Distance (GSD), captured through airborne ADS80 push-broom camera for the first time in Indian Himalayas. This DEM was also evaluated with Differential Global Positioning System (DGPS) points for accuracy assessment. The ADS80 DEM gave Root Mean Square Error (RMSE) of ~<1 m and Linear Error, at 90% confidence interval (LE 90) of 1.36 m in comparison with the DGPS points.
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This paper reports the experiments carried out for extraction of DEMs from Cartosat-1 stereo imag... more This paper reports the experiments carried out for extraction of DEMs from Cartosat-1 stereo imagery using stereo correlation technique for Manali region. The focus of this paper was to assess the accuracy of extracted DEM with respect to DGPS observations, DEM generated from digitized contours of Survey of India (SoI), 1:50,000 scale topographic map(converted to ellipsoidal height using egm2008 geoid model) as well as well-known freely available DEMs ASTER GDEM and SRTM. The vertical accuracy of Cartosat-1 DEMs was analysed with DGPS derived ground control points. The relative vertical accuracy (root mean square error; RMSE) of Cartosat-1 DEM with DGPS control points was ±9.6 m. The RMSE with the topographic DEM was found to be ±10.6 for 22 spot heights and ±10.8 m for 6,458,800 checkpoints. The relative vertical accuracy assessment is more important than the absolute vertical accuracy assessment. The result of relative accuracy assessment of DEMs with respect to field measurement of DGPS points and reference DEMs shows Cartosat-1 DEM is more accurate when compared to ASTER DEM, SoI Topographic DEM, and SRTM DEM for Manali region.
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The main objective of the study is Digital Terrain Model (DTM) generation from aerial photogramme... more The main objective of the study is Digital Terrain Model (DTM) generation from aerial photogrammetric data and identify and map the potential avalanche prone zones in Manali region. Avalanche is a dynamic hazardous phenomenon in the snow-bound mountainous terrain. Mapping of avalanche prone terrain is crucial to minimize the avalanche hazard. Nowadays, airborne data capturing technology, such as large-format Photogrammetry, has opened new vistas for the mapping of complex and inaccessible
mountainous areas. In the present study, large format digital Photogrammetry data of 20 cm ground sample distance (GSD) have been used to generate high-resolution and accurate Digital Elevation Model and ortho-images. Digital terrain model along with its derivative terrain products and land cover map generated from land cover classification of derived ortho-photo is analyzed to locate the probable avalanche zone. The terrain characteristics, snow-pack condition and prevailing meteorological conditions are the groups of variables that influence the occurrence of avalanche. Amongst these, the terrain characteristics is the most influencing factor, and easier to map due to its stable nature along the time. Therefore advanced geo-informatics techniques have been used by mixing terrain property, Digital Elevation Model (DEM) and satellite imagery to determine the different geographical factors that affect the avalanche triggering. Also the
derived information was combined in Analytic Hierarchy Process to extract a map of the avalanche prone zones in the study area standard mapping techniques as coarse-resolution data are not very appropriate for such studies.
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Papers by Mritunjay Singh
233 (80%) were used for training the model and remaining 59 (20%) were used for validation of the map. The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve (ROC-AUC) technique. For validation of the results using ROC-AUC technique, the success rate and prediction rate were calculated. The values of success rate and prediction rate were 94.07% and 91.76%, respectively. The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping
mountainous areas. In the present study, large format digital Photogrammetry data of 20 cm ground sample distance (GSD) have been used to generate high-resolution and accurate Digital Elevation Model and ortho-images. Digital terrain model along with its derivative terrain products and land cover map generated from land cover classification of derived ortho-photo is analyzed to locate the probable avalanche zone. The terrain characteristics, snow-pack condition and prevailing meteorological conditions are the groups of variables that influence the occurrence of avalanche. Amongst these, the terrain characteristics is the most influencing factor, and easier to map due to its stable nature along the time. Therefore advanced geo-informatics techniques have been used by mixing terrain property, Digital Elevation Model (DEM) and satellite imagery to determine the different geographical factors that affect the avalanche triggering. Also the
derived information was combined in Analytic Hierarchy Process to extract a map of the avalanche prone zones in the study area standard mapping techniques as coarse-resolution data are not very appropriate for such studies.
233 (80%) were used for training the model and remaining 59 (20%) were used for validation of the map. The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve (ROC-AUC) technique. For validation of the results using ROC-AUC technique, the success rate and prediction rate were calculated. The values of success rate and prediction rate were 94.07% and 91.76%, respectively. The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping
mountainous areas. In the present study, large format digital Photogrammetry data of 20 cm ground sample distance (GSD) have been used to generate high-resolution and accurate Digital Elevation Model and ortho-images. Digital terrain model along with its derivative terrain products and land cover map generated from land cover classification of derived ortho-photo is analyzed to locate the probable avalanche zone. The terrain characteristics, snow-pack condition and prevailing meteorological conditions are the groups of variables that influence the occurrence of avalanche. Amongst these, the terrain characteristics is the most influencing factor, and easier to map due to its stable nature along the time. Therefore advanced geo-informatics techniques have been used by mixing terrain property, Digital Elevation Model (DEM) and satellite imagery to determine the different geographical factors that affect the avalanche triggering. Also the
derived information was combined in Analytic Hierarchy Process to extract a map of the avalanche prone zones in the study area standard mapping techniques as coarse-resolution data are not very appropriate for such studies.