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• Land use change detection along the Pravara River basin in Maharashtra, using remote sensing and GIS techniques

  71-86

  Veena Joshi

  Vikas Nagare

  Views:

  62

  In the past few decades there has been an increasing pressure of population all over the world, especially in India, resulting in the utilization of every available patch of available land from woodlands to badlands. The study area represents a basin which is economically growing fast by converting the fallow lands, badlands and woodlands to agricultural land for the past few decades. IRS (Indian Remote sensing Satellites) 1 C – LISS III and IRS 1 C PAN and IRS P6 – LISS III and IRS 1 D PAN Images were merged to generate imageries with resolution matching to the landscape processes operating in the area. The images of the year 1997, 2000, 2004 and 2007 were analyzed to detect the changes in the landuse and landcover in the past ten years. The analysis reveals that there has been 20% increase in the agricultural area over the past ten years. Built up area also has increased from 1.35% to 6.36% of the area and dense vegetation also has marginally increased. The remarkable increase in the agricultural area occurs owing to the reclaim of the natural ravines and fallow lands. Presently the area looks promising, but it is necessary to understand the sedimentological and geomorphological characteristics of the area before massive invasion on any such landscapes because the benefit may be short lived.

• UAS photogrammetry and object-based image analysis (GEOBIA): erosion monitoring at the Kazár badland, Hungary

  169-178

  László Bertalan

  Zoltán Túri

  Gergely Szabó

  Views:

  191

  A remarkable badland valley is situated near Kazár, NE-Hungary, where rhyolite tuff outcrops as greyish white cliffs and white barren patches. The landform is shaped by gully and rill erosion processes. We performed a preliminary state UAS survey and created a digital surface model and ortophotograph. The flight was operated with manual control in order to perform a more optimal coverage of the aerial images. The overhanging forests induced overexposed photographs due to the higher contrast with the bare tuff surface. The multiresolution segmentation method allowed us to classify the ortophotograph and separate the tuff surface and the vegetation. The applied methods and final datasets in combination with the subsequent surveys will be used for detecting the recent erosional processes of the Kazár badland.