Agricultural Crop Monitoring Programme in India

Transcription

1 Agricultural Crop Monitoring Programme in India Dr. Jai Singh Parihar Dy. Director Remote Sensing Applications Area (RESA) Space Applications Centre (ISRO) Ahmedabad India Presentation in the Workshop to Develop a Strategy for Global Agricultural Monitoring in the framework of Group on Earth Observations, July 16-18, 2007, FAO Hq., Rome, Italy 1

2 Existing Indian Agricultural Statistics System Started as early as in the year 1883 Crop Acreage: Village-wise field level enumeration in most of the country Some states known as permanently settled states: 20% villages covered every year (Full coverage in 5 years Crop Yield: Crop cutting experiments based on randomly selected fields Strength: Very systematic and comprehensive coverage Weakness: Multi-level of aggregation and post harvest yield estimation requires time to prepare the data 2

3 Indian Agricultural Scenario Geo. Area : 329 mha Crop Productivity Net Area Sown : ~ 142 mha Food production : > 200 mt Agrl. Share of GDP(%): 22.2 Rice ~ 2.1 t/ha (China 5.8) Wheat ~ 2.9 t/ha (UK 6.9) Cropping Intensity: % Net Irrigated Area ~ 57 mha Fertiliser Consumption ~106 kg/ha Area under HYV : m ha Degraded Land as % Geo. Area India : 49.8 China : 30.0 Asia-Pacific: 31.3 Average Operational Holding Size: 1.57 ha Punjab: Uttar Pradesh : Kerala: 4.74 ha 0.83 ha ha

4 Indian Agriculture: Monsoon, Irrigation and Physiography Mean annual rainfall (cm) Monsoon onset normal dates Monsoon withdrawal normal dates Rainy days ( >= 2.5mm/day) Command Area Physiography 4 < ,000 > 1,001

5 CROP ACREAGE AND PRODUCTION ESTIMATION PROJECT SPONSORED BY Dept of Agri. & Cooperation, Govt. of India SCOPE OF WORK To provide pre-harvest district level acreage and production estimates Technology transfer to state for operational use CROPS AND STATES COVERED CROPS Wheat, rice, cotton, rapeseed/mustard, rabi sorghum, groundnut, sugarcane STATES Andhra Pradesh, Assam, Bihar, Chhattisgarh, Gujarat, Haryana, Himachal Pradesh, Karnataka, Madhya Pradesh, Maharashtra, Orissa, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh, West Bengal METHODOLOGY Sample segment Approach (5X5km, 15%) Stratified Random Sampling Single date multi-spectral remote sensing data with MXL classifier ACHIEVEMENTS Procedure and S/W developed, implemented it through participation of a team of >100 scientists from state agencies Pre-harvest forecast provided regularly 5

6 SUGGESTED SCHEDULE FOR FORECASTING Crop States Acreage Production K-rice Pun, JK, NE Jul. mid Sep. mid Har, UP, S-State Jul. mid Sep. end Asm, Bih,MP, WB.. Jul. end Oct. end All India Jul. end Oct. mid Wheat Guj, Mah, MP, Raj Dec. end Feb. end Other States Jan. end Mar. end All India Jan. end Mar. end 6

7 Forecasting Agricultural out put using Space, Agrometeorology and Land based observations(fasal) Conventional Econometry Agro Meteorology Cropped area Land Observations Crop condition RS, Mod. Re. Temporal Remote Sensing RS, High Re. Single date Crop acreage Crop yield MULTIPLE IN-SEASON FORECAST Pre- Season Early- Season Mid- Season 7 State Pre- Harvest State Pre- Harvest District

8 Crop Assessment and Monitoring Procedure for Temporal RS data analysis Multi-date RS Data (Current) Multi-date RS Data (Previous) National Wheat AWiFS Data Segment Types A B C D >75 % % % % Ancillary Data Data Pre-processing (Geo., Radio.) Land Based Observations Acreage Estimation Multi-date & year Analysis Sample Segment: 5 x 5 km Sampling Fraction (n): 15% of N Crop Yield Modelling Crop Production Forecasts Cropping Pattern, Crop Growth 8

9 Wheat Growth Characterization Using Multi- Year RS Data Cls_Alw - Non Wheat - 1 Yr Wheat Yr Wheat Yr Wheat Yr Wheat Yr Wheat 10.5 Mean_Alw Mad_Alw - Non Wheat - MAD: MAD: MAD: MAD: MAD : > Non Wheat - NDVI NDVI NDVI NDVI NDVI >

10 Transplantation Temporal backscattering profile of Rice & Non-Rice Area Backscatter co-efficient (db) Days ( July 1=1) Rice Water Urban Homestead Other Crops Pre-transplantation Tillering Vegetative Maturity Peak-vegetative Heading

11 Kharif Rice assessment using multidate SAR data NOV. 2,

12 FLOOD INUNDATION : ORISSA CYCLONE RADARSAT Nov 2, 1999 Nov 4,

13 Suitability for growing Rice June July 1-15 July August 1-15 August Sept % No estimation for white areas (msl height > 800 m) No NOAA CPC Data for parts of W Kachchh, W Sau., W Raj % % suitable days 0 %

14 Microwave Radiometry for Soil moisture Assessment HARYANA Analysis Duration: April 23 (Week 17) to Aug. 27 (Week 35) Week Number NA May June July NA =volumetric soil moisture has not crossed 0.25 level before July SSM/I Wetness Index derived from 19, 37 and 85 GHz channels at 0.33 degree grid size

15 Crop Parameter Retrieval- Leaf Area Index FCC image over Punjab on 03 Mar05 NDVI Wheat mask Ranges of LAI > Jan Mar LAI map

16 Rice Crop Phenology 13.4 GHz Ku-band QuikSCAT ; 4.45 km enhanced resolution 4-day composite Sigma-0 images-11-8 West Bengal Rice Crop Dense Forest Sigma-0 (db) Lake Water DOY (2004) Wheat Sigma-0 (db) Punjab Rice (Punjab) Rice Crop Rice (WB) Aug. 15 Oct DOY (2004) Sigma-0 (db) Rice Wheat Rice Days from sowing/tranplanting (Punjab ) 16 DOY Jul.29

17 Crop Phenology Progress of Sowing Aug 01-10, 04 Sept 01-10, 04 Oct 01-10, 04 Nov 01-10, 04 High 255 Rice Planting Pattern Map Early Normal Mod. Late Late Non-Rice Indo-Gangetic Plains Wheat Sowing Pattern Map Early Normal Late Non-Wheat Area Non-Agriculture Low:0 Non-ag 17

18 Estimation of Agromet, Crop Parameters & AET lnsolation Land surface temp. Albedo NDVI MJm -2 RET NDWI < NDVI 18

19 CROP GROWTH MONITORING SYSTEM Database WEATHER SOIL MGMT Remote Sensing ACREAGE Leaf Area Index PHENOLOGY Simulation Model SIMPLIFICATION VALIDATION CORRECTION GIS BOUNDARIES CROP DISTRIBUTION FRONT END TO LINK DATABASE, RS AND MODEL Outputs CROP GROWTH/ YIELD MAPS EVAPO-TRANSPIRATION, 19 LAI, BIOMASS MAPS SPATIAL QUERIES FOR POLICY

20 National Agricultural Drought Assessment and Monitoring (NADAMS) 20

21 Overland flow modelling Soil Textural Map Hydrological Land cover Soil Type Clay Clay Loam Loam Loamy Sandy Sandy loam Sandy Mountains Sand Forest Sandy Water body Legend Basin Boundary CROP CLASS Fair Crop Water body Not cultivable Poor Crop Double Crop Good Crop Forest Fallow Other Uncultivable mm ,200 1,201-1,500 1,501-2,000 2,001-2,500 2,501-3,000 3,001-4,000 4,001-5,000 5,001-8,200 Soil Texture Map Hydrological Soil Group HSCC SPOT- S10 Land Cover Classification CPC Rainfall (R) AMC Condition CN map for AMC II CN modified for AMC I & III Maximum Potential Retention (S) Initial Abstractions or losses (I a ) 21 Runoff mm ,000 1,001-1,500 1,501-2,000 2,001-2,500 2,501-3,000 3,001-4,000 4,001-5,000 5,001-7,700

22 Crop rotation Mapping (RS) SPOT VGT: Regional level Rice-Wheat Cotton-Wheat Maize Based Vegetable Based Others Non-Agriculture Road Network District Boundary AWiFS: State Level Rice-Wheat Sugarcane Based Cotton-Wheat Rice-Potato Maize-Wheat Pearlmillet-Wheat Rice-Fallow-Rice Rice-Fallow-Fallow Rice-Fallow-Jute Rice-Wheat-Other Fallow-Pulse Fallow-Wheat Minor Crop Rotations Fallow Non-Arable Village level LISS IV Rice-Wheat Sugarcane Fallow-Other crop Sugarcane-Wheat Other crop-other crop Rice-Fallow Other crop-fallow Fallow 22 LISS III: District level

23 Upscaling of Methane from Rice-Ecosystem using Remote Sensing & GIS Field Samples collected : Emission (Tg) from Indian Rice-ecosystem Max:5.01 Mean:3.43 Min:1.85 Rice Growth Profile PERSPECTIVE VIEW OF METHANE EMISSION PUNJAB JAMMU & KASHMIR UTTARA HP NCHAL Methane Emission Pattern GUJARAT HARYANA RAJASTHAN MADHYA PRADESH BIHAR UTTAR PRADESH JARKHANDWEST BENGAL CHHATIS GARH ORISSA ASSAM MAHARASHTRA Rice Cultural Types Rice Cropping Pattern ANDHRA PRADESH Emission kg/ha/year KARNATAKA K E R A L A TAMILNADU 23 Irrigated intermittent Irrigated Continuous Rainfed Flood Prone Rainfed Drought Prone

24 THANK YOU WE DO HAVE TRADITION OF PRECISION DESIGNING 24