Use of Remote Sensing Technology in Crop Monitoring and Assessment of Impact of Natural Disaster

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1 Use of Remote Sensing Technology in Crop Monitoring and Assessment of Impact of Natural Disaster Shibendu S. Ray Mahalanobis National Crop Forecast Centre Department of Agriculture & Cooperation Government of India Mahalanobis National Crop Forecast Centre Mahalanobis National Crop Forecast Centre was established under Ministry of Agriculture with technical and human resources support from Indian Space Research Organization. Centre was inaugurated on 23 rd April, Named after great Indian Statistician P. C. Mahalanobis. Located in New Delhi, India. An initiative towards institutionalization of Remote Sensing Applications in Agriculture in the country. A state-of-the art RS&GIS lab The Mandate of the Centre is to use geospatial technology for agricultural assessment. Responsible for all operational crop forecasting and drought assessment in the country using Remote Sensing Data. Jointly works in collaboration with 18 state agriculture departments. Web:

2 FASAL (Forecasting Agriculture using Space, Agrometeorology and Land based observations) Aims at providing multiple pre-harvest production forecasts of crops at National/State/ District level National/State forecasts: Kharif Rice (3 Forecasts, 13 states) Rabi Rice (1, 4) Wheat (3,6) Winter potato (2, 4) Rapeseed & Mustard (3,5) Jute (1,3) State/District forecasts: Cotton (1,7) Sugarcane (1,3) Rabi Sorghum (1,2) Salient Features for Crop Assessment using Remote Sensing Data Multi-date Microwave (SAR) for Rice & Jute and Multi-date/Single-date Optical (AWiFS/ LISS III) for other crops Approach Stratified Random Sampling States Covered All those sates, which together contribute >85% of the Crop s area in the Country Periodicity Multiple, starting from 1 month of crop to pre-harvest Classification Approach Hierarchical for Multi-date SAR; Hybrid (combination of supervised & unsup. for multi-date optical); MXL for single date optical Software FASALSoft, developed by ISRO Yield Forecast Agro-meteorological, progressing towards spectral & simulation Organisations Involved MNCFC, State Agrl. Dept., IMD, SAC (ISRO)

3 Use of Multi-date Optical Data for Crop Classification Use of Indian SAR (RISAT) Data for Rice & Jute Indian SAR satellite RISAT-1 was launched in April 26, 2012 and data was available for user from November, Crop (Rice & Jute) assessment is the major use of RISAT-1 data (MRS mode). Multi (3) date data is used for crop assessment. MRS Data Coverage in Kharif Rice

4 Smartphone based Ground truth Collection 5680 points covering 16 states between August to January ( ) Crop Forecast Schedule and Variation Estimates Rice Wheat Remote Sensing DES Remote Sensing DES 1 st Aug End Sep End Jan End Feb 1 st Wk. 2 nd Sep End Feb 1 st Wk. Feb End April Last Wk. 3 rd Jan, 1 st Wk. (Final) April Last Wk. Mar End (Final) July Mid 4 th --- July Mid Final --- Sep End --- Sep End FASAL Forecasts Crop Year Area (Million Hectares) Production (Million Tonnes) MNCFC DES % Diff. MNCFC DES % Diff. Jute (F1) * * -5.1 Rice (F2) Rapeseed& Mustard (F3) Winter Potato (F2) NA NA Wheat (F3) Rabi Rice (F1) Forecasts in 20 Months *Million Bales (180 kg)

5 Remote Sensing driven Crop Cutting Experiments in Bihar Rice Crop Map was generated using such as RISAT-1 MRS data Resourcesat-2 AWiFS time composite NDVI during Sep 2 nd FN to Oct 1 st FN was extracted for rice. Three classes (A, B, C) were defined based on frequency distribution of NDVI Values. 37 points were randomly selected in 22 districts of Bihar Crop cutting experiment was carried out under the supervision of MNCFC. Yield models were developed between NDVI and yield and yield map generated Efficiency of stratification was very high. Use of Indigenous Software Operational use of indigenously developed software for Crop Forecasting (FASALSoft, developed by SAC/ISRO) and Drought Assessment (NAS, developed by NRSC/ISRO)

6 Crop Emergence Progression November 1-10 November November December 1-10 December December January January January January 31-feb > 0.7 Map of Rabi Season Emergence Area in 6 States Drought Assessment 'National Agricultural Drought Assessment and Monitoring System (NADAMS)' project, conceptualized and developed by ISRO, Department of Space Provides near real-time information on prevalence, severity level and persistence of agricultural drought at state/ district/sub-district level Currently, it covers 13 states of India, which are predominantly agriculture based and prone to drought situation. Agricultural conditions are monitored at state/district level using daily NOAA AVHRR and MODIS data for 13 states. AWiFS (Advanced Wide Field Sensor) of Resourcesat (56 m resolution) is used for detailed assessment of agricultural drought at district and sub district level in four states Monthly report of drought condition is provided to the all concerned agencies in Centre and State under NADAMS. From the year 2012, the NADAMS project is being implemented by the Mahalanobis National Crop Forecast Centre (MNCFC), Ministry of Agriculture

7 Methodology for Agricultural Drought Assessment Multi-satellite, Multi-date Data VI Time Composite NDVI/NDWI anomaly Assessment (1)Relative dev. (2)VCI (3)In season change Irrigation Percentage Ground Information Rainfall deviation Agricultural Drought Situation Sown area deviation Drought Warning (June, July, August) Normal Watch Alert Drought Declaration (Sep, Oct) Mild Moderate Severe Change in Crop Calendar Lag between VI & Rainfall Abnormal Weather Events (e.g. Floods) Additional Information Agricultural Drought Assessment for September 2013 (No. of Districts) State Normal Mild Moderate Andhra Pradesh Bihar Chhattisgarh Gujarat Haryana Jharkhand Karnataka Maharashtra Madhya Pradesh Odisha Rajasthan Tamil Nadu Uttar Pradesh Total

8 Agricultural Drought Assessment - Bihar AVHRR based Normalized Difference Vegetation index Seasonal Rainfall upto 30/09/13 (Source: September 2013 September 2011 Legend EXCESS (+20% OR MORE) NORMAL ( +19% TO -19%) DEFICIENT2 (-40% TO -59%) DEFICIENT1 (-20% TO -39%) MODIS based Normalized Difference Water index September 2013 September 2011 (upto 21 st ) SCANTY ( -60% TO -99%) NO RAIN (-100%) NO DATA Agricultural drought assessment September 2013 Odisha Rice-Flood Assessment (Rice Map of Odisha from RISAT Data) (Flood Map of Odisha, upto 17 th Oct., ISRO) An Estimate of District wise Rice Inundation Area (Assessment Upto 17 th October, 2013) (Rice Flooded Map of Odisha, upto 17 th Oct.)

9 Agricultural Condition (January 2014) Vegetation & Temperature Condition Index Vegetation Condition Index(NDVI) = 100*(NDVI-NDVI min )/(NDVI max -NDVI min ) Vegetation Condition Index(NDWI) = 100*(NDVI-NDVI min )/(NDVI max -NDVI min ) Temperature Condition Index = 100*(LST max - LST)/(LST max LST min ) VCI (NDVI) VCI (NDWI) TCI District-level Crop Alert VCI (NDVI) VCI (NDWI) TCI VCI > < VCI < 40 VCI < 20 VCI > < VCI < 40 VCI < 20 TCI > < TCI < 40 TCI < 20 Combined

10 Tasks Ahead More Crops and More Area Spectral Yield Mapping Biotic & Abiotic Disaster impact on Agriculture Agricultural Development Monitoring Crop Insurance Global Agricultural Monitoring Automatization, Web-GIS, Portals..

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