An Analysis of FASAL: The Operational
Crop Forecasting Programme of India
S. S. Ray1, K. R. Manjunath2, Neetu1, Sanjeev Gupta1, J. S. Parihar2
1Mahalanobis National Crop Forecast Centre (MNCFC), DAC, MoA, New Delhi
2Space Applications Centre, ISRO, Ahmedabad
Email: [email protected]
Conventional Crop Estimation in India
Area Statistics
Land Record States or temporarily settled states: 17 Major States, 4 UTs: 86% of reporting area, Timely Reporting Scheme (TRS), 20% villages are selected at random for
complete area remuneration.
States where area statistics are collected on the basis of sample surveys. Establishment of an Agency for Reporting of Agricultural Statistics (EARAS). 9% of reporting area. Sample
surveys of 20% villages/ investigator zones.
Hilly districts of Assam, rest of the states in NER, & other UTs. Area statistics based on impressionistic approach. 5% of the reporting area.
Yield Estimates
Crop Cutting Experiments (CCE) under scientifically designed General Crop Estimation Surveys (GCES).
Around 950 thousand CCEs. Stratified multi-stage random sampling: Tehsil / Taluk > Revenue Village> Survey Number /
Field> Experimental Plot (Specified size / shape)
80-120 CCEs for a crop in a major district
Advance Estimates
September (1st ), January (2nd ), March/April (3rd ), June/July (4th), January (Final)
S.N. Group Crop Type Crop Season Avg. Area
(M Ha)
Avg.
Production
(M Ton)
Status (RS
Assessment)
1
Food grains Cereals Rice Kharif + Rabi 39.1
4.3
85.3
13.6
1
1
2 Wheat Rabi 29.0 87.4 1
3
Coarse
Cereals
Maize Kharif + Rabi 7.2
1.3
15.1
5.3
4
3
4
Sorghum Kharif + Rabi 2.8
4.2
3.1
3.3
4
2
5 Bajra Kharif 8.7 9.0 4
7 Pulses Tur (Arhar) Kharif 3.8 2.6 3
8 Gram Rabi 8.4 7.8 3
9 Oilseeds Groundnut Kharif 4.6 4.9 4
10 R & M Rabi 6.2 7.3 1
11 Soybean Kharif 10.0 11.9 4
12 Fibre Crops Cotton Kharif 11.0 29.5* 2
13 Jute Kharif 0.8 10.4* 1
14 Sugarcane Sugarcane Long Durn 4.7 324.4 2
Major Crops of India
* Million bales
NASA-ISRO-MoA
1969 JEP 1978 CAPE 1988 FASAL Pilot
1997 FASAL 2007 NCFC 2012
45 Years of Use of Space Technology in Crop Forecasting
Coconut Root Wilt study in Kerala
Experimental Studies on Crop
Discrimination
Area & production Estimates of major
crops at State level.
National Wheat, FASAL-Odisha
District-State-National forecasts
using multiple approaches for
multiple forecasts
Institutionalisation of Space Technologies developed by ISRO
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/District forecasts: Kharif Rice (3 Forecasts, 14 states) Rabi Rice (1, 4) Wheat (3,6) Winter potato (2, 4) Rapeseed & Mustard (3,5) Jute (1,3) Cotton (2,8) Sugarcane (2,4) Rabi Sorghum (1,2)
Organisations Involved Department of Agriculture &
Cooperation Mahalanobis National Crop Forecast
Centre ISRO (SAC, NRSC, NESAC) State Agriculture Departments (19) State Remote Sensing Centres (14) India Meteorological Department &
46 Agro-Met Field Units Institute of Economic Growth
Salient Features for Crop Assessment using Remote Sensing
Multi-date Microwave (SAR) for Rice & Jute and Multi-date/Single-date Optical (AWiFS/ LISS III) for other crops
Data
Stratified Random Sampling
Approach
All those sates, which together contribute >85% of the Crops area in the Country
States Covered
Multiple, starting from 1 month of crop to pre-harvest
Periodicity
Hierarchical for Multi-date SAR; Hybrid (combination of supervised & unsup. for multi-date optical); MXL for single date optical
Classification Approach
FASALSoft, developed by ISRO
Software
Agro-meteorological, progressing towards spectral & simulation
Yield Forecast
DAC, MNCFC, State Agrl. Dept., IMD, SAC (ISRO), SRSC; IEG
Organisations Involved
Smartphone based Ground truth Collection
8997 points covering 17 states between August , 2013 to September, 2014
App by
NRSC
Agromet + Remote Sensing+ Field Observation
Simulation Models (Assimilation of RS data)
Empirical Models (Agromet + Remote Sensing)
Semi Physical Remote Sensing Models: Rice, Wheat
District Level Yield Models: IMD, SAUs
Meteorological Sub Division Level Yield Models: SAC, MNCFC
Crop Yield Forecasts
Remote Sensing Driven Crop Cutting Experiments
App by
NRSC
Estimates Rice Wheat
Remote Sensing DES Remote Sensing DES
1st Aug End Sep End Feb Mid Feb 1st Wk.
2nd Sep End Feb 1st Wk. Mar Mid April Last Wk.
3rd Jan End (Final) April Last Wk. Apr 1st Wk (Final) July Mid
4th --- July Mid --- ----
Final --- Feb 1st Wk. --- Feb 1st Wk.
Crop Estimate Satellite Data Area Production Date
Jute F1 RISAT-1 MRS 0.72 (0.77) 10.06* (10.98*) 24 Jul 2013
Rice F3 RISAT-1 MRS 37.47 (39.41) 86.87 (91.69) 22 Jan 2014
Cotton SDF LISS III/AWiFS 10.45 (11.69) 25.98* (36.59*) 18 Dec 2013
Sugarcane SDF LISS III/AWiFS 4.44 (5.01) 331.69 (350.02) 18 Dec 2013
Rapeseed & Mustard F3 LISS III 5.73 (6.70) 7.07 (7.96) 04 Mar 2014
Potato F2 (Total) AWiFS 1.91 39.75 28 Feb 2014
Rabi Sorghum SDF LISS III 4.23 (3.60) 3.88 (3.05) 15 Feb 2014
Wheat F3 LISS III 29.87 (31.19) 89.12 (95.91) 04 Apr 2014
Rabi Rice F1 RISAT-1 MRS 3.86 (4.54) 12.58 (14.84) 04 Apr 2014
Total Rice Final Estimated 41.34 (43.94) 99.45 (106.54) 04 Apr 2014
FASAL Forecasts, 2013-14
*Million Bales
Issues & Requirements
Minor and Scattered Crops
Non-Rice Kharif Crops
Accurate Yield Forecasts
Impact of Extreme Weathers
Higher Frequency of EO Data
Better Models for Yield
Satellite Derived Products
Geospatial Platforrms
www.ncfc.gov.in
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