Geoinformatics in Agriculture: IARI Research Initiatives

1. Symposium on Geo-spatial for Rural Development Geoinformatics in Agriculture: IARI Research Initiatives Prof Vinay Sehgal Division of Agricultural Physics Indian Agricultural Research Institute New Delhi- 110012 INDIA 12 February 2009, Hyderabad

2. About IARI • 104 years old national institute of excellence in agricultural research & teaching in the country • Having 22 disciplines and 8 regional centres • Deemed to be a university for post-graduate studies • Crucible of “Green revolution” in the country

3. About Agricultural Physics @IARI • Associated with the first remote sensing experiment in country (1960’s) on coconut wilt disease. • ISRO –IARI Joint experimental programmes (JEP) since 1980’s on Optical and Microwave RS • Partnered in IRS-UP Programmes, CAPE& FASAL on crop production forecasting. • Conducted 15 ISRO sponsored Winter Schools on Remote Sensing since 1992. • First to introduce RS GIS courses (1980’s) in Post Graduate Programmes. (Principles of Remote Sensing, Remote Sensing in Agriculture, Satellite Agro-meteorology, GIS & GPS : Fundamentals and Applications). • More than 100 M.Sc. And Ph.D. students passed out in the Discipline of Agricultural Physics.

4. Agricultural System Soil texture, salinity, sodicity, fertility Soil texture, salinity, sodicity, fertility Weather Rainfall, temperature, solar radiation Land use Area under agriculture and other activities Weather Rainfall, temperature, solar radiation Land use Area under agriculture and other activities Plant & pests Crops/ varieties, crop x pest interactions G x E Animals Cows/ buffaloes/ hybrids Agricultural Production Agricultural Production Plant Crops/ varieties, G x E Animals Cows/ buffaloes/ hybrids Socio-economic labour, machinery, capital, markets, costs and returns Production technology irrigated, rainfed, mechanized/ organic Socio-economic labour, machinery, capital, markets, costs and returns Production technology irrigated, rainfed, mechanized/ organic Agronomic inputs seeds,FYM, irrigation, fertilizers, biocides Agronomic inputs seeds,FYM, irrigation, fertilizers, biocides

5. Indian Agriculture Issues • Characterization • Monitoring • Trends • Alternate strategies • Productivity / Food security • Sustainability • Vulnerability • Equity • Diversification • Infrastructure • Globalization • Climate Change

6. Forest Rice –Wheat Cotton-Wheat Maize –Wheat S.cane –wheat Fallow-Mustard Pearl millet –Mustard Pearl millet- wheat Sorghum –wheat Fallow- other pulses Rice-Fallow Others NDVI profile corrected using FASIR Technique NDVI Profile of Endmembers Cropping System

7. CT RCT Target spectra Reference /end member spectra ө Band 2 Band 1 Mapping Conservation tillage area Conservation (RCT) & conventional tillage(CT) areas of Karnal district, using Spectral Angle Mapper technique

8. Potential zones for resources conservation technologies Zero Tillage : Turn around time, High Initial Moisture Conditions Reduced Tillage : When ZT is not effective for weed control Surface Seeding: Excess Moisture conditions Furrow Irrigated Raised Bed (FIRB): Salt affected conditions, waterlogging Laser Land Leveling: Undulating Topography Potential Zones for Furrow Irrigates Raised Bed system (Area :17,170 ha) Cropping Sequence of Mau district (U.P.) derived from temporal satellite data Potential Zones for Zero Tillage (Area :41,432 ha) Potential zones of surface seeding Total Excessive Moisture (Area: 987 ha)

9. Crop Biophysical Parameters Retrieval Sampling sites in the study area

10. Crop Biophysical Parameters Retrieval Cab EWT Chlorophyll content Leaf Area Index Leaf Wetness

11. Potential Yields for Gap Analysis Grain yield kg/ha Grain yield kg/ha WHEAT RICE

12. Resource Characterization Soil Texture Land Unit Rainfall Organic Carbon Non-Agric. Areas Salinity Irrigation Sodicity District map

13. Optimal Agricultural Land Use in Haryana Kharif Rabi Dominant crop Rice Sugarcane Cotton Maize Millet Fallow Goal: Maximization of regional income with targets of agricultural production

14. ------ [INPUTS ] ------- --------- [GIS ] ---------- [CENTRAL RDBMS] [SIMULATION MODEL] GRID NUMBERS (GN) CENTRAL LAT/LONG GEOGRAPHIC AREA STUDY AREA BOUNDS,GRID SIZE MODEL GRID ADMINISTRATIVE BOUNDARY MAP STUDY AREA BOUNDARY VECTORS GN + DISTRICT CODE GN + FRACTION CROP AREA RS DATA CLASSIFIED CROP MASK CROP SIMULATION MODEL (WTGROWS) WEATHER SURFACES (POINT TO RASTER INTERPOLATION) DAILY WEATHER DATA (POINTS) GN + WEATHER FILE GN + WEATHER CONSTANTS CGMS SHELL ver 1.0 WEATHER CONSTANT THIESSEN POLYGONS PTF GN + SOIL WATER CONSTANTS SOIL TEXTURE CLASS SOIL MAP( NBSS&LUP) SOIL DEPTH CLASS GN + SOIL DEPTH SOIL OC SURFACE (INTERPOLATION) SOIL OC% (POINTS) GN + SOIL OC % DISTRICT-WISE CROP MANAGEMENT Cultivar, Sowing Date, Irrigation, Fertilizer GN + CULTIVAR, SOWING DATE, IRRIGATION, N FERT CROP YIELD MAP GN + CROP YIELD MODEL OUTPUT PTF – Pedo Transfer Functions Selection by SHELL as per run parameters DISTRICT-WISE AGGREGATED CROP YIELD CROP GROWTH MONITORING SYSTEM

15. CGMS: Spatial Inputs

16. Simulated Growth Parameters Leaf Area Index Above Ground Biomass (t/ha)

17. HARYANA (1996-97) Yield Simulation & Validation Grain Yield (t/ha)

18. Farmer’s Field Study

19. 220 210 200 190 SCALED NDVI 180 170 160 150 140 130 120 0 10 20 30 40 DEKAD Trends in Crop Phenology

20. 18-Sep-01 5-Nov-01 7-Dec-01 21-Jan-02 Rice Yield Modeling Using LAI Product LEAF AREA INDEX ORYZA MODEL % Deviation from Mean

21. TREND: TIME OF START OF SEASON Early Punjab, Haryana, UP showing early start of rice season whereas North Bihar and West Bengal showing delay Late During rabi, Punjab is showing early start of season whereas in rest of IGP a delay in start of season

22. TREND: DURATION OF SEASON The rice crop duration is showing a general increase throughout IGP. During rabi, duration is decreasing in most of IGP except Punjab.

23. Drought Monitoring NOAA CPC RAINFALL SPOT VGT NDVI OCT 2 Difference 2003 2004

24. EASTERN (MZ 18) & WESTERN RAJASTHAN (MZ 17)

25. Comparative study of effectiveness of NDVI and NDWI5 in monitoring drought 28 th July NDVI (2003-2002) NDWI5 (2003-2002) NDWI5 NDVI Rainfall(mm) Rainfall(mm)

26. Drought: Environmental Vulnerability Mapping Early season Mid season Late season

27. Soil Fertility Mapping OC Sample location K20 P205

28. 1 2 3 4 5 6 7 8 Fertilizer Recommendation Simulated recommended N:P:K dose for different crops through QUEFT Model

30. Hyperion Data for fertility mapping Hyperion data with 139 bands only FLAASH Corrected reflectance and radiance data profile Preliminary comparison of soil spectral data from ASDI FS3 and Hyperion image

31. Ground water quality for irrigation (Elec Conductivity) Low (C1) < 0.25 dS/m Medium (C2) 0.25 -- 0.75 dS/m Medium to high (C3)0.75 -- 2.25 dS/m High (C4) 2.25 -- 5.00 dS/m Very high (C5) > 5.00 dS/m

32. Criteria table Class C1: Can be used for most crops on most soils Class C2: Can be used for moderate salt tolerant crops with moderate leaching Class C3: Can be used for moderate salt tolerant crops with adequate leaching Class C4: Can be used for salt tolerant crops with special salinity management practices Class C5: Not suitable under normal condition but may be used occasionally with very special management practices

33. Ground water quality Class I (Good): 27.77% Class II (Moderate): 23.77% Class III (Poor): 48.46% Class I (Good): 38.43% Class II (Moderate): 26.01% Class III (Poor): 35.51%

34. Thank You vksehgal@gmail.com sehgal@iari.res.in Acknowledgements Dr R.N. Sahoo Dr D. Chakraborty Dr P.K. Aggarwal Dr V.K. Dadhwal

35. Residue Characterization Kumar, R, Sahoo RN , Tomar RK, 2008