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: shibendu.ncfc@nic.in

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

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