Generation and validation of DEM using SAR interferometry and differential GPS supported by multispectral optical data

Digital elevation model (DEM) and the derived terrain parameters e.g. contour, slope, aspect, drainage pattern, etc are required for natural resources management, infrastructure planning and disaster management. The present paper aims at generating DEM from ERS tandem pair using interferometric technique supported by differential GPS measurements (DGPS) and multispectral optical data. Validation of DEM has been carried out by DGPS measurements. Ground Control Points (GCP) established by DGPS measurements have been used to georeference the IRS-1D optical data that has finally been co-registered with SAR amplitude image. Optical data, co-registered with ERS - I SAR data has helped in locating the GCP’s and check points, precisely, for refinement of DEM and its validation.     

Siltation analysis in the Neyyar reservoir and forest degradation in its catchment: a study from Kerala state, India

 Impact of catchment erosion and the resultant reservoir siltation from a tropical environment is reported here to discuss the effect of a reservoir in the natural degradation of an evergreen-forested segment. While an area of 8.01 km² has been affected by direct inundation at the full reservoir level, another 2.6 km² area once under thick forest cover, had also lost its identity over the last 38 years by indirect degradation. This zone mainly falls in the confluence of tributaries, namely Neyyar and Mullayar, with the reservoir. The capacity of the reservoir was found to be reduced by 28.8 Mm³ during this period and the annual average loss is calculated as 0.75 Mm³ (0.71%), indicating the intensity of erosion from the catchment zone. In case the proposed upper dam in the reservoir comes into existence, an additional area of 2.4 km² from the virgin forest would be submerged and more area would face degradation around the inundated zone. Received: 29 July 1998 · Accepted: 16 November 1998     

Concurrent Use of OSCAT and AltiKa to Characterize Antarctic Ice Surface Features

Radar altimetry provides an important geophysical parameter, backscatter coefficient (σ₀), which is useful in studying target surface characteristics. Ku-band (Oceansat-2 scatterometer- OSCAT) and Ka-band (SARAL-AltiKa altimeter) data are concurrently used to characterize polar surface features over the Antarctic region. Maximum-likelihood classification has been employed to classify combined data set (AltiKa and OSCAT) for discrimination among sea ice, open water, and ice sheet (interior and exterior). The sea ice region obtained using the current approach has been compared with sea ice boundary derived from passive microwave data.     

Estimation of Sea Ice Freeboard from SARAL/AltiKa Data

An attempt has been made to derive sea ice freeboard from Ka-band Altimeter (SARAL/AltiKa) over Arctic region for 15 March–15 April 2013 (spring) and 15 September–15 October 2013 (autumn). A waveform template matching technique is employed for classification of leads and floe pixels. The estimated sea ice freeboards were found in close agreement with “Operation IceBridge quick look” freeboards (RMSD = 0.30 m). The differences between the two freeboards were largely due to snow layer over sea ice (R = 0.8). The estimated freeboards were of the order of 0.08–0.15 m during the two seasons.     

Extraction and validation of cartosat-1 DEM

CARTOSAT-1 satellite, launched in May, 2005 is a dedicated along track stereo mission providing high quality data for topographic and cartographic applications. The present paper describes the evaluation of the Cartosat-1 stereo data, mainly through the generation and validation of DEM for moderately undulating and hilly areas. Photogrammetric techniques have been used for generation of DEM and Orthoimage for two cases i.e. 1) using RPCs (Rational Polynomial Coefficients) and 2) using RPCs along with ground control points. Root Mean Square Error (RMSE) in elevation values for the moderately undulating (Dehradun) and hilly area (Shimla), are found to be 4.38 and 3.69m respectively.     

Estimation of sub-catchment area parameters for Storm Water Management Model (SWMM) using geo-informatics

This study presents a remote sensing and geographic information systems-based approach for using US EPA’s Storm Water Management Model (SWMM) in urban environment. Cartosat-1 PAN + IRS-P6 LISS-IV merged product was used to map land cover in part of Surat city at 1:10,000 scale. Cartosat-1 stereo pair was used for deriving digital elevation model of the study area. Geo-informatics-based methods were developed for delineation of sub-catchment areas, assignment of sub-catchment outlets and estimation of characteristic width. It was observed that 59% of the developed area in the study region was directly or indirectly connected to the storm water drainage network. Furthermore, dynamic rainfall-runoff simulation on three-day rainfall indicated that the average runoff coefficient on the urbanized sub-catchment areas which were directly connected to the drainage network was 0.92 as against 0.88 on those urbanized sub-catchments without having direct access to storm water drainage.