Faculty Publications
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Item Automated extraction of drainage network and watershed boundary from ASTER DEM and SRTM DEM and comparison with Topomap - A case study(2013) Megha, V.; Manju, P.; Ashitha, M.K.; Gopinath, G.For proper planning and management of water resources the adequate delimitation of watershed and its drainage is highly essential. This work deals with the evaluation of drainage network extracted automatically from Digital Elevation Models (DEM) obtained from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Shuttle Radar Topography Mission (SRTM) and watershed delineation. The comparison of drainage characteristics derived from satellite data with the topomap were analyzed. Bharathapuzha River basin is spreading its drainage network in Kerala and Tamilnadu. Arc Hydro tools (version 2.0) an application extension for Arc GIS 10 recently released by ESRI was used to extract drainage network. The threshold value for deciding on the required drainage density is arrived at by trial and error method where the watershed boundary derived from digital network matches the digitized boundary most accurately. The comparison of drainage network derived from ASTER and SRTM with the drainage from topomap is based on the stream length aspect. The length of the drainage network derived from the DEMs has a better resemblance with the topomap. © 2013 CAFET-INNOVA TECHNICAL SOCIETY.Item Age-based classification of arecanut crops: a case study of Channagiri, Karnataka, India(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2016) Bhojaraja, B.E.; Shetty, A.; Nagaraj, M.K.; Manju, P.Arecanut is one of the predominant plantation crop grown in India. Yield of this crop depends upon age of the crop and there is no information on the spectral behaviour of arecanut crops across its ages. In this study popular supervised classification algorithms were utilized for age discrimination of arecanut crops using Hyperion imagery. Arecanut plantations selected for the study are located in Channagiri Taluk, Davanagere district of Karnataka state, India. Ground truth information collected involves: (i) GPS coordinates of selected plots, (ii) spectral reflectance of arecanut crops with age ranging from 1 to 50 years, using handheld spectroradiometer with 1 nm spectral resolution. These spectral measurements were made close in time to the acquisition of Hyperion imagery to build age-based spectral library. It is observed from the analysis that crops of ages below 3, 3–7, 8–15 and above 15 years were showing distinct spectral behaviour. Accordingly, crops age ranging from 1 to 50 were grouped into four classes. Classification of arecanut crops based on age groups was performed using methods like spectral angle mapper, support vector machine and minimum distance classifier, and were compared to find the most suitable method. Among the classification methods adopted, support vector machine with linear kernel function resulted in most accurate classification method with overall accuracy of 72% for within class seperability. Individual age group classification producer’s accuracy varied minimum of 12.5% for 3–7 years age group and maximum of 86.25% for above 15 years age group. It may be concluded that, not only age- based arecanut crop classification is possible, but also it is possible to develop age-based spectral library for plantation crop like arecanut. © 2015 Taylor & Francis.