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Kadam S.A.,Mahatma Phule Agricultural University | Gorantiwar S.D.,Mahatma Phule Agricultural University | Das S.N.,Maharashtra Remote Sensing Application Center | Joshi A.K.,Regional Remote Sensing Center Central
Journal of the Indian Society of Remote Sensing | Year: 2016

Penman–Monteith method adapted to satellite data was used for the estimation of wheat crop evapotranspiration during the entire growth period using satellite data together with ground meteorological measurements. The IRS-1D/IRS-P6 LISS-III sensor data at 23.5 m spatial resolution for path 096 and row 059 covering the study area were used to derive, albedo, normalized difference vegetation index, leaf area index and crop height and then to estimate wheat crop evapotranspiration referred to as actual evapotranspiration (ETact). The ETact varied from 0.86 to 3.41 mm/day during the crop growth period. These values are on an average 16.40 % lower than wheat crop potential evapotranspiration (ETc) estimated as product of reference crop evapotranspiration estimated by Penman–Monteith method and lysimetric crop coefficient (Kc). The deviation of ETact from ETc is significant, when both the values were compared with t test for paired two sample means. Though the observations on ETact were taken from well maintained unstressed experimental plot of 120 × 120 m size, there was significant deviation. This deviation could be attributed to, the satellite images representing the actual crop evapotranspiration as function crop canopy biophysical parameters, condition of the crop stand, climatic and soil conditions and the microclimate variation over area of one hectare. However, Penman–Monteith method represents a flat rate of specific growth stage of the crop. © 2016 Indian Society of Remote Sensing


Bhandari S.M.,Indian Center for Climate and Societal Impacts Research | Baba Shaeb K.H.,Regional Remote Sensing Center Central
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2014

We have examined, for the first time, the spatial coherence of oceanic parameters, namely, the ocean surface wind and significant wave height (SWH), using near-instantaneous along-track sampling over vast oceanic tracks provided by Poseidon-2 Radar Altimeter onboard Jason-1. The spatial coherence length scales over the Arabian Sea and the Bay of Bengal regions, derived using Auto correlation analysis, display interesting characteristics in relation to onset and evolution of SW Monsoon over India. The estimated spatial coherence scales are found to be of the order of 100-500 km. Generally, SWH coherence lengths over Arabian Sea are observed to increase from June to July during good monsoon year (2012). This trend is not followed for the poor monsoon year (2002). Similar trend is observed for spatial coherence scales for wind speed. The temporal evolution of analyzed spatial coherence scales of winds and waves over Arabian Sea clearly brings out the distinction between a 'good' (2012) and a 'poor' (2002) monsoon year. The spatial coherence lengths of these parameters over the Bay of Bengal are found to be shorter and do not show any systematic relation to onset and evolution of SW monsoon. Anisotropy in coherence lengths is also analyzed by treating ascending and descending tracks separately. Generally, the descending tracks measurements show higher spatial coherence lengths than the ascending ones. Like the spatial coherence scales, the anisotropy of the coherence scales over the Arabian Sea also mimics the behaviour of the strength of SW Monsoon.


Bothale R.V.,Regional Remote Sensing Center Central | Katpatal Y.B.,Visvesvaraya National Institute of Technology
Journal of Hydrologic Engineering | Year: 2014

Understanding the variability of rainfall with El Niño Southern Oscillation (ENSO) events at the watershed level is important for water resource managers to discern the pattern of water available for agricultural planning and water and soil conservation. This study was conducted to determine the responses of rainfall and vegetation to El Niño and La Niña events occurring between 2001 and 2011 in the Upper Wardha watershed in Maharashtra, India. Daily rainfall data pertaining to 14 stations in and around the study area were analyzed in conjunction with 16-day global 250-m Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor abroad the Terra (EOS AM) and Aqua (EOS PM) satellites. Results indicate correlations between ENSO events, rainfall, and vegetation. Both rainfall and vegetation show a positive anomaly during La Niña events and a negative anomaly during El Niño events, but the effects of all events are not the same. A low volume of rainfall with the early onset of monsoon, multimodal rainfall distribution over time, and intermittent rains are the effects of El Niño on rainfall. The effect of La Niña was to produce wetter conditions in the study area. The impacts of moderate to severe ENSO events (in 2009 and 2010) can be predominantly observed on rainfall and vegetation. © 2014 American Society of Civil Engineers.


Bothale R.V.,Regional Remote Sensing Center Central | Pandey B.,TERI University
Journal of the Indian Society of Remote Sensing | Year: 2013

The study evaluates and compares Digital Elevation Model (DEM) data of various grid spacing derived using high resolution Cartosat 1 stereo data for hydrologic applications. DEM is essential in modeling different environmental processes which depend on surface elevation. The accuracy of derived DEM varies with grid spacing and source. The CartoDEM is the photogrammetric DEM derived from stereo pairs. Damanganga basin lying in the Western Ghats was analysed using 11 Carto stereo pairs. The process of triangulation resulted in RMSE of 0.42. DEM was extracted at 10 m, 20 m, 30 m, 40 m, 50 m and 90 m grid spacing and compared with ASTER GDEM (30 m) and SRTM DEM (90 m). DEM accuracy was checked with Root Mean Square Error (RMSE) statistic for random points generated in different elevation zones. Extracted stream networks were compared based on Correctness Index and Figure of Merit index, calculated for all the Digital Elevation Models at varying cell sizes. In order to further evaluate the DEM's, a simple flood simulation with no water movement and no consideration of real time precipitation data was carried out and relationship between heights of flood stage and inundation area for each Digital Elevation Model was also established. © 2012 Indian Society of Remote Sensing.


Varghese A.O.,Regional Remote Sensing Center Central | Sawarkar V.B.,Wildlife Institute of India | Joshi A.K.,Regional Remote Sensing Center Central
Journal of the Indian Society of Remote Sensing | Year: 2015

Ardeotis nigriceps, commonly known as Great Indian Bustard (GIB), is a Critically Endangered, Evolutionary Distinct and Globally Threatened (EDGE) and endemic species to the Indian subcontinent. GIB is under tremendous threat in its last strongholds and sliding inextricably towards extinction. The GIB sanctuary in Maharashtra (India) is one of the last refuges of the bird constituting an area of 8496 km2 spread over in seven talukas of Solapur and Ahemednagar districts. Major portion of the sanctuary (94.3 %) consists of privately owned lands under a variety of economic vocations and large number of villages and townships. In view of the legal restrictions relating to Protected Area under the Wildlife (Protection) Act of India 1972, the inhabitants of villages and townships faced a very difficult situation regarding use of their lands, development of properties and deriving benefits from planned local and regional development. This created conflict between local people and the forest department over the use of land, which necessitated the rationalization of the sanctuary. The objective of the present study was to map the suitable habitat of GIB in GIB Wildlife Sanctuary as an input for the realignment of the GIB Sanctuary by identifying areas that are important for the GIB. Main parameters considered for the habitat suitability assessments are, habit and habitat of GIB, slope, minimum patch size and disturbance sources. Based on the criteria derived for the ecological and biological requirements of GIB, binary deductive habitat suitability modeling has been done using remote sensing and GIS and prioritized the potential habitats of GIB. The net area of important suitable habitat of GIB in GIB sanctuary is 2304.99 km2 out of 8496.44 km2. The output of the present study has been used as an input by the committee (set by Honorable Supreme court of India) on rationalization of the GIB Sanctuary and the sanctuary has been rationalized with an area of 1222 km2. © 2015 Indian Society of Remote Sensing

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