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Srivastava S.S.,Space Applications Center | Desai Y.,Space Applications Center | Desai Y.,Ahmedabad University | Sekhar K.S.S.,Space Applications Center | And 6 more authors.
Journal of the Indian Society of Remote Sensing | Year: 2016

The present study investigates two natural sites for calibration of IRS sensors, one at Thar Desert, Rajasthan and another at Rann of Kutch, Gujarat, India. The variance analysis of satellite data of different seasons over these sites and atmospheric characterization were carried out. Results of the study suggest that the sites identified are suitable and can be used for vicarious calibration of satellite sensors during the months of October to March as during this period the atmospheric loading of aerosols, water vapour and ozone are at minimum. Thar desert and Rann of Kutch sites show spatial uniformity of within ~0.78–2.0 % and 1.96–3.90 % respectively. Error budget is also estimated. If well calibrated instruments are used, the overall error should not exceed ~2 % for the reflectance based approach. © 2016 Indian Society of Remote Sensing Source

Surendran U.,Tamil Nadu Agricultural University | Rama Subramoniam S.,Regional Remote Sensing Center | Raja P.,Indian Central Arid Zone Research Institute | Raja P.,Center for Water Resource Development and Management | And 3 more authors.
Environmental Monitoring and Assessment | Year: 2016

Mining of nutrients from soil is a major problem in developing countries causing soil degradation and threaten long-term food production. The present study attempts to apply NUTrient MONitoring (NUTMON) model for carrying out nutrient budgeting to assess the stocks and flows of nitrogen (N), phosphorus (P), and potassium (K) in defined geographical unit based on the inputs, viz., mineral fertilizers, manures, atmospheric deposition, and sedimentation, and outputs, viz., harvested crop produces, residues, leaching, denitrification, and erosion losses. The study area covers Coimbatore and Erode Districts, which are potential agricultural areas in western agro-ecological zone of Tamil Nadu, India. The calculated nutrient balances for both the districts at district scale, using NUTMON methodology, were negative for nitrogen (N −3.3 and −10.1 kg ha−1) and potassium (K −58.6 and −9.8 kg ha−1) and positive for phosphorus (P +14.5 and 20.5 kg ha−1). Soil nutrient pool has to adjust the negative balance of N and K; there will be an expected mining of nutrient from the soil reserve. A strategy was attempted for deriving the fertilizer recommendation using Decision Support System for Integrated Fertilizer Recommendation (DSSIFER) to offset themining in selected farms. The results showed that when DSSIFER recommended fertilizers are applied to crops, the nutrient balance was positive. NUTMON-Toolbox with DSSIFER would serve the purpose on enhancing soil fertility, productivity, and sustainability. The management options to mitigate nutrient mining with an integrated system approach are also discussed. © Springer International Publishing Switzerland 2016. Source

Sharma R.,Regional Remote Sensing Center | Chaudhry S.,Kurukshetra University | Kudrat M.,Regional Remote Sensing Center | Tiwari A.K.,Regional Remote Sensing Center | And 2 more authors.
International Journal of Ecology and Development | Year: 2012

Vegetation and landuse mapping was carried out in the Kumaun Himalayan region, covering 21,034 km2 area, with the help of multi-season AWiFS data of IRS-P6. Different vegetation and landuse categories were identified using a hybrid approach of classification including unsupervised, supervised and contextual refinement techniques. 41% of the total area was occupied by vegetation with a dominance of pine forest spread in an area of 1982.74 km 2 (23% of total forest area). SRTM DEM was used for post classification refinements. Classified map was assessed for accuracy, and an overall accuracy of 92% was obtained. Distribution of different vegetation types was also analyzed with respect to different topographic variables in the study area. Maximum area with vegetation was observed in mid elevation zone in comparison to other altitude zones. In different categories maximum distribution of forest area was under low followed by mid and higher slope categories. Southern aspect was observed with maximum forest area. © 2012 IJED. Source

Bhadra B.K.,Regional Remote Sensing Center | Kumar S.,Krishi Vigyan Kendra | Paliwal R.,Regional Remote Sensing Center | Jeyaseelan A.T.,Indian National Remote Sensing Centre
Hydrogeology Journal | Year: 2016

Over-exploitation of groundwater for agricultural crops puts stress on the sustainability of natural resources in the arid region of Rajasthan state, India. Hydrogeological study of groundwater levels of the study area during the pre-monsoon (May to June), post-monsoon (October to November) and post-irrigation (February to March) seasons of 2004–2005 to 2011–2012 shows a steady decline of groundwater levels at the rate of 1.28–1.68 m/year, mainly due to excessive groundwater draft for irrigation. Due to the low density of the groundwater observation-well network in the study area, assessment of groundwater draft, and thus groundwater resource management, becomes a difficult task. To overcome the situation, a linear groundwater draft model (LGDM) has been developed based on the empirical relationship between satellite-derived crop acreage and the observed groundwater draft for the year 2003–2004. The model has been validated for a decade, during three year-long intervals (2005–2006, 2008–2009 and 2011–2012) using groundwater draft, estimated through a discharge factor method. Further, the estimated draft was validated through observed pumping data from random sampled villages (2011–2012). The results suggest that the developed LGDM model provides a good alternative to the estimation of groundwater draft based on satellite-based crop area in the absence of groundwater observation wells in arid regions of northwest India. © 2016 Springer-Verlag Berlin Heidelberg Source

Hebbar R.,Regional Remote Sensing Center | Ravishankar H.M.,Regional Remote Sensing Center | Trivedi S.,Regional Remote Sensing Center | Subramoniam S.R.,Regional Remote Sensing Center | And 2 more authors.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2014

High resolution satellite images are associated with large variance and thus, per pixel classifiers often result in poor accuracy especially in delineation of horticultural crops. In this context, object oriented techniques are powerful and promising methods for classification. In the present study, a semi-automatic object oriented feature extraction model has been used for delineation of horticultural fruit and plantation crops using Erdas Objective Imagine. Multi-resolution data from Resourcesat LISS-IV and Cartosat-1 have been used as source data in the feature extraction model. Spectral and textural information along with NDVI were used as inputs for generation of Spectral Feature Probability (SFP) layers using sample training pixels. The SFP layers were then converted into raster objects using threshold and clump function resulting in pixel probability layer. A set of raster and vector operators was employed in the subsequent steps for generating thematic layer in the vector format. This semi-automatic feature extraction model was employed for classification of major fruit and plantations crops viz., mango, banana, citrus, coffee and coconut grown under different agro-climatic conditions. In general, the classification accuracy of about 75-80 per cent was achieved for these crops using object based classification alone and the same was further improved using minimal visual editing of misclassified areas. A comparison of on-screen visual interpretation with object oriented approach showed good agreement. It was observed that old and mature plantations were classified more accurately while young and recently planted ones (3years or less) showed poor classification accuracy due to mixed spectral signature, wider spacing and poor stands of plantations. The results indicated the potential use of object oriented approach for classification of high resolution data for delineation of horticultural fruit and plantation crops. The present methodology is applicable at local levels and future development is focused on up-scaling the methodology for generation of fruit and plantation crop maps at regional and national level which is important for creation of database for overall horticultural crop development. Source

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