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Operational Remote sensing Applications

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Operational Remote sensing Applications- MVR sesha sai, NRSC Hydrabad

Operational Remote sensing Applications- MVR sesha sai, NRSC Hydrabad

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  • 1. Operational Remote SensingApplications MVR Sesha Sai Head, Agriculture Division (LRG) National Remote Sensing Centre (ISRO) Hyderabad – 500625 INDIA IIRS, June 16, 2010
  • 2. STRUCTURE OF THE PRESENTATION Our Vision Statement Institutional mechanism Natural Resources Census Operational Thematic Applications Agriculture, Soils / Land, Water Resources, Forestry, Geology, Urban Studies; Watershed mgt. Disasters: Drought, Flood Enhanced Outreach Ground / Field Data Collection Conclusion
  • 3. Our Vision Indian space programme driven by vision of Dr Vikram Sarabhai, the father of the Indian Space Programme“There are some who question the relevance of space activitiesin a developing nation. To us, there is no ambiguity of purpose.We do not have the fantasy of competing with the economicallyadvanced nations in the exploration of the moon or the planetsor manned space-flight. But we are convinced that if we are toplay a meaningful role nationally, and in the community ofnations, we must be second to none in the application ofadvanced technologies to the real problems of man andsociety.”
  • 4. Components of National Natural Resources Management System PC – NNRMS Chair : Member (Science), Planning Commission STANDING COMMITTEES Chair: Secretaries of GoI Department of SC-A : Agriculture & Soils Space (Nodal SC-B : Bio-resources & Department) Environment ISRO Centres and NE- SC-C : Cartography & Mapping SAC SC-G : Geology & Mineral Resources SC- OM: Ocean Resources & Meteorology SC- R: Rural Development SC-T : Training & Technology SC-U : Urban Development SC- W : Water ResourcesState Support for Natural Ministries /Departments / Resources DepartmentsDistrict Management
  • 5. NATURAL RESOURCE INVENTORY USING SATELLITE DNational level 180m 60m 24m 6m State level District level RICE Mandal level Village level Rice Cotton BANANA MAIZE TOBACCO CHILLIESIRS WIFS AWiFS IRS LISS-III LISS-IV data
  • 6. LULC-250K Land Degradation LULC-50K Geomorphology LAND DEGRADATION WastelandIRS Data Soils SOIL Ground water GROUND WATER Wetlands VEGETATION TYPE Biodiversity BIODIVERSITY Forest & Vegetation WASTELAND Land Use Land GEOMORPHOLOGY Cover Snow Cover /Glacier SNOW/GLACIERS • AWiFS –250 K WETLANDS • LISS III – 50 K BHOOSAMPADA
  • 7. National Land use Land cover Map using Multi-temporal AWiFS data LULC 2007-08 2004-05 2005-06 2006-07 2007-08All interim Kharif and integrated LULC assessments were completed as per theschedule and reports were submitted by 31st December of each year
  • 8. BHOOSAMPADA 4 yearly Assessments:Released on 28th Jan 2004-082009 Maps, Reports Integrated queries with socio-economic data: Seasonal crop areas Seasonal water spread Seasonal snow cover Integrated LULC assessment
  • 9. APPLICATIONS IN AGRICULTURE• IDENTIFICATION AND ACREAGE ESTIMATION - MAJOR CROPS - MULTIPLE CROPS - HORTICULTURAL CROPS• AGRICULTURE DROUGHT ASSESSMENT• CROP PRODUCTION ESTIMATION• CROPPING SYSTEMS STUDIES
  • 10. recasting Agricultural Output using Space, Agrometeorology an Land based Observations (FASAL) na Re tio Land v en o Observation RS Se mot on l Agr ology s Re. , Mod. ns e C ete o r ing M T em por y al R metr Cropped Re S, H . no Sin i gh o Crop da Ec area condition t e gle Crop acreage Crop yield MULTIPLE IN-SEASON FORECASTS Pre- Early- Mid- Pre- Pre- Revised Season Season Season Harvest Harvest Incorporatin State State District g Damage
  • 11. Forecasting Agriculture output using Space, Agro- meteorology & Land based observations (FASAL) Nationwide Multiple Wheat & Rice Crop Forecasting o In-season Crop Forecasts Spectral, Agromet & Final Econometric Models o Impact of Drought & Flood Estimate o Integrated Yield Mode Assessment o Early Warning – Crop condition & Stress Scenario Spectral – Agromet Third Models o FASAL Centre /NCFC with Estimate oSpace Images Ministry of Agriculture oMeteorological data Forecasts oGround data Crop Year Acreage Production Agromet Models (mha) (mt) Second oSpace Images Rice 2009-10 31.31 64.55 Estimate oGround Data Wheat 2008-09 26.96 73.59 oTemp./Rainfall Wheat 2009-10 28.33 81.21* First Econometric Models*Delayed onset & extended monsoon , increased Estimateacreage & favourable met conditions enhanced Rabicrops productions Pre-harvest Production Forecast at National, State and District levels for Major Crops like Paddy, Wheat, Sorghum, Rapeseed, Mustard, ...
  • 12. FASAL: Nationwide Crop Forecasting National / State level estimations Wheat (AWiFS) Rabi cropped area (RCA) by end of January First estimate of wheat acreage by end of February Final wheat acreage estimate by end of March Kharif Rice (Radarsat) • First estimate (F1) of rice acreages by Sept 30 • Second estimate (F2) by Oct 31 • Final rice acreage estimate by Jan 31 Winter Potato (AWiFS) o Haryana and Punjab by Dec 15 o Uttar Pradesh by Dec 31 o Bihar and West Bengal by Jan 15 1. National Wheat 2. National kharif RiceNov, Dec, Jan, Jul 13 (Date-1) Aug 06 (Date-2) 2 date FCC F-1 (33.7Mha) Aug 30 (Date-3) 3 date FCCRCA (32.0Mha) Feb- wheat-1 (26.6Mha)Mar- NDVI profile Wheat-2 (27.25Mha) Backscatter Profile F-2 (35.8 Mha) Wheat, Grams, Mustard, Potato, Early Mid Late Multi-date Resourcesat-1 AWiFS data Three date Radarsat SN2 data
  • 13. CHANGES IN DISTRIBUTION OF KHARIF RICE OF ANDHRA PRADESHRAW DATA 2000 2002 2004CLASSIFIED DATA RICE 2.64Mha 1.72Mha 2.36Mha
  • 14. CHANGES IN DISTRIBUTION OF KHARIF RICE OF ANDHRA PRADESHRAW DATA 2000 2002 2004CLASSIFIED DATA RICE 2.64Mha 1.72Mha 2.36Mha
  • 15. Changes in spatial distribution of rice and cotton in Karimnagar dist. A.P. 2006: Normal year 2002: Drought year Crop acreages (lakh hectares)CROPS 2006 2002RICE 1.44 1.11COTTON 1.14 0.45
  • 16. Inter seasonal changes in kharif rice & wheat cropped area (2007 vs. 2006) 2007 2006 2007 2006Part of Assam Part of RajasthanPart of Part of UPWest BengalPart of AP Part of Bihar
  • 17. Cropping Systems Analysis Post kharif rice fallow lands – Potential for pulse cultivationIRS-1C/1D WiFS DATA OF SOUTH ASIANS NATIONS Acreages of kharif rice & fallows Country Rice Fallows (Mha) (Mha) India 40.18 11.65 CLASSIFIED DATA OF SOUTH ASIAN NATIONS Bangladesh 6.36 2.11 Nepal 1.45 0.39 RICE Pakistan 2.45 0.14 WHEAT OTHER CROPS KHARIF RICE FALLOW LANDS
  • 18. Soils & Land
  • 19. Village Resources Maps Monitoing of Land Degradation Land productivity assessment 1997 2006 Action Plan Land capability 1992 2006 Watershed studies Land suitability SOIL MAP Land irrigabilty Micro-watershedCritical Areas Map Cotton Paddy S3 S1 S 3 Cotton N1 S1 N2 N2 Action plan map
  • 20. Types of Remote sensing data for Soil Mapping • purpose of the study, • scale of the study, • characteristics of targets • climatic condition of the study areaScale Sensors Level of Soil mapping Useful for planning at1: 250 000 LANDSAT - MSS Subgroups/ Soil Family National, State and IRS – LISS, WiFS and their association regional level1: 50000 IRS – LISS II, III Soil series and their District/ sub district LANDSAT- MSS association level SPOT1: 25000 IRS – LISS III +PAN Soil series and their Block / Taluk /Mandal merged data association level1: 12500 IRS – LISS III+PAN, Soil series, soil Phases Village level1: 8000 or LISS IV Association of soillarger IKONOS- MSS+PAN phases CARTOSAT-1/2
  • 21. METHODOLOGY FOR SOIL MAPPINGRS Satellite data Preliminary Visual Interpretation Ancillary data(summer season) SOI Topo maps Climatic data Published literature etcSoil Profile Study Ground truth collection Soil samples collection Soils -pH, Ece, ESP Soil Sample Analysis Soils Characterization Finalization of thematic map Soil / Land Degradation Map
  • 22. SOIL MAPPING AT VARIOUS SCALES Over the years, remotely sensed data like Landsat-MSS / TM , SPOT and IRS - LISS-I, II, III, IV etc., were employed to map soils at different scales ranging from 1:250,000 scale to 1:50,000 scale and even to 1: 12,500 scale.Small NBSS&LUP mapped soils of entire country using Less Landsat MSS / TM data on 1: 250,000 scale. Under IMSD Project, soils were mapped at 1:50,000 scale using IRS-LISS-II/ Landsat-TM data for various parts in Level of detail India covering an area of about 83.3 million hectares. Scale Under NATP soil maps at 1:12,500 scale were prepared for different micro-watersheds under different crop production systems /agro-climatic zones of the country. Under VRC programme, DOS is mapping soils on 1:10,000 or 1:8,000 scale using IRS-P6 LISS-IV and Cartosat data to provide soil resources information at village levelLarge More
  • 23. SOIL MAPPING USING SATELLTE DATASatellite data SOIL MAP IRS-LISS-II FCC SOIL MAP 1:250000 Scale 1:50,000 Scale IRS PAN + LISS-III IRS PAN + LISS-III IKONOS PAN +Multispect 1:25,000 Scale 1:12,500 Scale 1:8,000 Scale / 1:4,000
  • 24. SOIL MAP AT PHASE LEVEL , ERRAMATTI TANDA VILLAGE, NALGONDA DISTRICT, A.P. SOIL LEGEND Map Soil- Description of Soil Phases Unit Physiography 1 Residual EMT-1, Very shallow, gravelly sandy Hill loam, steeply slopping, strongly stony + associated with rocks Erramatti Tanda Gently slopping upper pediplain 3 Moderately EMT-3, Mod. shallow, sandy loam, eroded gently slopping, mod erosion, mod stony 4 Moderarely EMT-3, Mod. shallow, loamy sand,PAN + MSS IKONOS DATA eroded gently slopping, mod erosion, strongly stony 5 Severely EMT-4, Shallow, loamy sand, gently eroded slopping, severe erosion, slightly stony Very gently slopping upper pediplain 6 Slightly EMT-5, Moderately deep, sandy clay eroded loam, very gently slopping, slight erosion, Erramatti Tanda slightly stony 7 Slightly EMT-6, Moderately deep, loamy sand, eroded very gently slopping, slight erosion, slightly stony 8 Moderately EMT-7, Moderately deep, sandy loam, eroded very gently slopping, moderate erosion, Settlement slightly stonySOIL MAP
  • 25. Evaluation of Soils Information Land irrigabiltyLand capability assessment Land productivity assessment
  • 26. Land evaluation for different crops Uppugunduru village, Prakasam district, Andhra Pradesh S3 Cotton N1 S1 N2 SOIL MAP Cotton S3S1 S1 S1 N2 N1S1 S1 N2 N2 Paddy Chillies
  • 27. Natural Resources Census: Land Degradation Mapping (1:50K) SALIENT FEATURES …. SALIENT FEATURES …. LD CLASSIFICATION SCHEME ….. LD CLASSIFICATION SCHEME ….. Land degradation processes (8) Land degradation processes (8)••Mapping and monitoring land Mapping and monitoring land Water erosion, Wind erosion, Waterlogging, Salinisation / /alkalization, Water erosion, Wind erosion, Waterlogging, Salinisation alkalization, degradation (1:50 K) of entire degradation (1:50 K) of entire Acidification, Glacial, Anthropogenic and Others. Acidification, Glacial, Anthropogenic and Others. country. country. Land degradation type (18) Land degradation type (18)••Use of multi-temporal IRS Use of multi-temporal IRS Sheet erosion, Rills, Gullies, Ravines, Stabilized/partially stabilized Sheet erosion, Rills, Gullies, Ravines, Stabilized/partially stabilized LISSS- III satellite data. LISSS- III satellite data. dunes, Un-stabilized dunes, Surface ponding, Saline soils, Sodic soils, dunes, Un-stabilized dunes, Surface ponding, Saline soils, Sodic soils, Saline-sodic soils, Acidic soils, Frost heaving, Mining, Brick kiln areas, Saline-sodic soils, Acidic soils, Frost heaving, Mining, Brick kiln areas,••Personal Geodatabase Personal Geodatabase Industrial effluent affected areas, Mass movement / /mass wastage, Barren Industrial effluent affected areas, Mass movement mass wastage, Barren (NNRMS standards) (NNRMS standards) rocky/stony waste and Miscellaneous. rocky/stony waste and Miscellaneous. Severity classes (5): Slight, Mod, Severe, Very severe & Extreme.••Land Degradation Information Land Degradation Information Severity classes (5): Slight, Mod, Severe, Very severe & Extreme. System for easy query & Landform classes (4): Hills, Undulating plains, Plains & Valley. Landform classes (4): Hills, Undulating plains, Plains & Valley. System for easy query & retrieval Land use classes (4): Agriculture, Forest, Plantation, Open scrub Land use classes (4): Agriculture, Forest, Plantation, Open scrub retrieval LAND DEGRADATION MAPPING – SALT AFFECTED SOILS Slight Saline-sodic JAN MAR FCC Feb, 06 Apr, 06 Nov, 06 Mod Saline-sodic APR Strong Saline-sodicDelivariables: Statewise seamless database Soils Division, ERG, RS&GIS AA, NRSA
  • 28. PARTICIPATING ORGANISATIONS : 33
  • 29. MAPPING METHODOLOGY Temporal IRS LISS III data Kharif, Rabi & Zaid Image Enhancements Data Processing Geo-rectification Ground truth Map legend On screen data interpretation Legacy data Soil sample Final thematic map analysisBase map & attribute data Accuracy assessment (Settlement, Drainage, Waterbodies …..) Geo-data base creationMap template Map outputs Report Area statistics State MosaicsColor / symbol scheme
  • 30. APPROACH Land Degradation Map 1:50K (Ancillary database: Admin boundary, Watershed boundaries …..)Area Statistics Projection Data Model LULC layer Geo-spatial Database State / district layerWasteland layer (metadata, spatial & attribute data) Digital vector layers - Forest layer SOI Different season theme layers Ground truth On-Screen Interpretation Satellite data Zaid Ortho-rectification Satellite data - Rabi Geo-rectification Satellite data - Kharif
  • 31. Land degradation in Devadurga Taluk, Raichur Dt., Karnataka Apr’06 Feb’06 Oct’06 Land degradation map Hemnur Saline-sodic Rill erosion Sheet erosion - water Barren rocky/ stony waste
  • 32. Karnataka: Land Degradation Map and DatabaseLand Degradationmap of Karnataka F i e l Legend d Hmd p Nml h o Tbs t Wri2 o Wsh1 s Attributes of one mapping unitBidar district, KN Land degradation map database
  • 33. National Wastelands Monitoring ProjectUser: DoLR, Ministry of Rural Development, GOIObjective:To update spatial information on wastelands, identify and delineate areas where changes occurred lace
  • 34. National Land Use // Land Cover Mapping on 1:50.000 scale with Land Use Land Cover Mapping on 1:50.000 scale with multi-temporal IRS LISS III Data multi-temporal Objective Approach•Generate land use/ land •Use of multi temporal 7 geo-rectified LISS- IIIcover data base on data covering kharif, rabi, zaid seasons of1:50,000 scale using three 16 20 2005-06seasons (Kharif, Rabi & 4 3 •Creation of LULC:50 KZaid) LISS III satellite 17 19 3 13 integrated map baseddata for the period 2005- 2 18 8 12 on On-Screen Interpretation06 14 15 11 •GT , legacy and L-IV data used / consulted for interpretation. 1 6 10 Web-Enabled Information Syste Expected 9 14 Uses 14 5•Benchmark database for future Legend mapping cycles-2005-06•Digital LULC database for 2005-06 forvarious users at district level•Monitoring of dynamic features …•Identification of “hotspot” areas from 2nd
  • 35. Water Resources
  • 36. Snow Hydrology Snowmelt runoff forecast Forecast of seasonal snowmelt runoff inflows into Bhakra reservoir during April-May-June months in the first week of April every year to Bhakra Beas Management Board Snow Cover Depletion CurvesSnow Cover in Sutlej Basin as on 1stApril, 2005 Runoff (lakh cusec days) Year Forecast Actual % Variation 2000 14.0 13.21 -5.5% 2001 11.5 10.44 -10.1% 2002 21.0 19.90 -5.5% 2003 17.5 21.50 +18.6% 2004 9.5 9.24 -2.8% 2005 17.0 15.10 -12.6%
  • 37. Reservoir Sedimentation Temporal water spread26-Sep-94 map05-Feb-95 Reduction in04-May-95 18-May-95 reservoir capacity
  • 38. Irrigation Water Management Baseline inventory of command areas Cropping pattern, cropping pattern deviation and compliance monitoring Estimation of crop yield and crop cutting experiments design Irrigation system performance evaluation Through-the-years performance monitoring to assess impact of developmental programs Diagnostic evaluation of problem pockets Water logging and salinity problems Evapotranspiration studies Irrigation scheduling
  • 39. Irrigation Command Area MonitoringProgression of(19Crop Sowings using th Dec 2003 to 29 March 2004) th Performance indicatorsAWIFS data Cropping Pattern Area under crop Irrigation potential utilized Irrigation Intensity Crop Production Water Utilization Index Prior to Irrigation Irrigation Supplies Initiated Transplantation Transplantation, Emergence, Tillering Active Tillering, Heading
  • 40. Irrigation Water Management Near real time monitoring Progress of seasonal crop area, Rabi season
  • 41. Irrigation Water Management Through-the-years Rabi 2001-02 Rabi 1994-95 Rabi 1992-93 performance monitoring Rabi Crop Area (ha)Standard FCC 102591.81 100000 95269.32 97076.52 90000 H e ct a r e 80000 70000 60000 50000 1992-93 1994-95 2001-02Crop Map Paddy Non paddy Area Irrigated per unit of Water (ha/M.cu.m)Paddy Transplantation Variability 100 90 8 4 .3 5 Barpali 80 7 0 .8 8 7 4 .7 8 70 ha / M . cu.m 60 50 40 30 20 Early 10 Normal 0 1 9 9 2-9 3 1 9 9 4 -9 5 2 0 01 -0 2 Late Hirakud Command Area
  • 42. Ground Water Rajiv Gandhi National Drinking Water Mission Scientific database on ground water for identifying drinking water sourcesObjective to the NC/PC habitations on sustainable basis Ground Water Prospects Map (on 1:50,000 Scale) Potential zones Locations & Priority for Ground water areas for constructing occurrence Recharge structures Availability Quality Sustainability Potential zones Constituents distribution Site specific Recharge structures yield and depth BIS Standards Priority
  • 43. Mapping of Ground Water Prospects Validation results • Map Unit • Probable Depth Range Of WellsNo. of Wells Drilled 204923 • Rock Type & Geological • Expected Yield Range Of Wells Sequence Probable Success Rate Of Wells Success rate 94% • Geomorphic • Reference No. of Observation No of Recharge 9744 Unit/Landform WellsStructures Planned No of Recharge 7030 • Recharge Conditions • Ground Water Irrigated Area Structures • Nature Of The Unit • Recharge Structure Suitable Constructed • Type Of Wells Suitable
  • 44. Feedback (as on October-2009) 85 -95% No. of Success No. of Recharge State wells rate Structures 90%95% Drilled Planned Constructed 92.5% 92% Andhra Pradesh 25292 92% 2279 2279 Chhattisgarh 33413 92.5% 1155 327 92% Karnataka 47951 95% 2641 2589 95% Kerala 7979 92% 95 26 Madhya Pradesh 22006 90% 5190 3361 Rajasthan 98994 85 - 95% 320 320 92% CompletedGujarat 13380 95 % 848 155 Ongoing Orissa 292 92% Nil Nil Total 249307 12528 9057
  • 45. Forestry
  • 46. Forestry Applications Forest cover mapping Vegetation type mapping Preparation of the working plans Forest Bio-diversity at patch scale Forest fire mapping Protected area mapping
  • 47. Forestry Applications•Forest Cover•Biodiversity Characterisation• Trees Outside Forests•Environmental Impact: Vegetation and Land cover•Forestry Forest Fire monitoring Vegetation type•CDM – Afforestation and mapping Deforestation•Climate Change – NAPCC Working Plan Biodiversity characterization at landscape level Statistical tests Bootstrapping Statistical Graphs Charts Engine Design based Model based geostatistical Estimation GIS Engine Engine Database Web support Engine Spatial & Non-spatialData Sample Reports Maps Accuracy QueriesEntry Points Indian Forest Fire Response & Assessment System
  • 48. National Vegetation Type Map using IRS data Landscape level Biodiversity Characterisation : DOS – DBT Initiative Field Sample Locations 113 vegetation types and other land use classes, hierarchical classification scheme Forests, grasslands, scrub, plantations,orchards, agriculturePHASE 1 – 2000, PHASE 2 – 2003, PHASE 3 - 2006 Visual Interpretation of IRS LISSS III Data
  • 49. National Forest Cover AssessmentNational Forest cover assessment done on biannual basis, since two decadesState of Forest cover Report (SFR) placed in Indian Parliament Forest Cover of India 25 Closed forest cover 21.6 Total forest cover (State of the Forest Report , 2003) 19.47 20.55 19.52 19.44 19.47 19.27 19.39 19.45 20 Source : Forest Survey of India F or e st a r ea in p er c e n t Based on IRS LISS III data of 2002 14.12 15 12.68 11.71 11.72 11.73 11.48 11.51 11.17 10.88 10 Legend Very Dense Forest (>70 %)* Moderately dense forest(40 % - 70 %) 5 Open Forest(10 % - 40 %) Scrub Nonforest 0 1972- 1981- 1985- 1987- 1989- 1993- 1995- 1997- 2001- Waterbodies 75* 83* 87** 89** 91** 95** 97** 99** 2004 State boundaries Year Since 1997-98 cycle mapping carried out on 1:50,000 scale *% Crown density in parenthesisForest cover assessed in terms of Very Dense (> 70%), Moderately Dense (40 -70 %) and Open (10-40%)crown density classes using digital approachesForest Survey of India carries out the task with the technical know-how transferred in 1986 by Dept.Of Space
  • 50. Forest Cover Mapping – Large Scale 1 1 -20% 0% 2 20%-40% 3 40% -60% 4 60% -80% 5 > 80% 9 Scrub/Shrubland 10 Trees outside Forest
  • 51. Landscape level Biodiversity Characterization : DOS – DBT InitiativeProducts Vegetation Type Map Field sample Data Disturbance Index Map Biological Richness Map Eastern Ghats Bioprospecting area prioritization - SFDs, CIMAP, IIPM, RRL NTFPs surveys - SFDs, Tribal Ministry Conservation Prioritization - Wild life agencies, SFDs Biodiversity Registers - AP Biodiversity Board Climate Change studies - DOS, Around 350 patches of > MOEnF 200 sq km size which have varied potential for Eco-development - NGOs, bio-prospecting & SFDs conservation identified Working Circles - SFDs Impact Assessment - Pollution
  • 52. Forest Working Plans – Geospatial inputs Forest Inventory and Data Analysis System (FIDAS)DAS Ver 1.2 installed at Orissa Forest Dept Readily adoptable by other SFDs across n
  • 53. Protected Area Management Plans Spatial Inputs Forest Cover ,type ,water holes, tourism, wildlife habitat fire lines, eco- development Rehabilitation, conservation zoning Demonstrated and implemented in several protected areas by ISRO/WII WII working towards national effort under SC-B/MOEnF for all protected areas GB Pant Institute submitted a proposal for 15 Biosphere reserves to develop comprehensive management plans
  • 54. Fire Regimes across India Daily Fire Alerts of last 8 years
  • 55. Burnt area characteristics – Case study Western in ras ff Ghats False Colour Total Burnt area – 1,060 sq.km Composite Total Forest area – 7,1461 sq.km of entire Western Ghats : IRS AWIFS 400 90 data of 2007 350 80 Maharastra 70 300 60 250 % No of Burnt Patch Burnt Area (Sq.Km) 50 200 40 150 30Goa 100 20 50 10 Karnataka 0 0 ( <5 ha ) (5-40 ha) (40-100 ha) (100-1000 ha) (>1000 ha) Burnt Area % No of Patch 50% of the burnt area is composed of patches Kerala less than 100 ha (90% of the total patches) Tamilnadu 60% of the burnt areas are in deciduous forest and 20% on the scrub forest.
  • 56. ROLE OF REMOTE SENSING IN GEOLOGICAL THEMES THEMES ROLE OF REMOTE SENSING Lithological mapping Updating Of Existing Maps Geomorphological All the major landforms Mapping can be identified Structural Mapping Lineament Mapping, Trend lines, Strike Slip Fault, Structural Landforms Stratigraphic Mapping Difficult
  • 57. National Geomorphological andlineament mapping for the entirecountry on 1:50,000 scale under FireNRC in association with GSI dynamics inHyperspectral studies for Jharia coalmineralized belt in the country in fields usingassociation with GSI thermalLandslide Hazard Zonation studies datain association with ITC and GSI forvulnerable beltsSAR interferometry studies forunderstanding cosesimicdisplacement for earth quake CARTOSAT-1studies capturesAeromagnetic data and satellitedata integration for hydrocarbon landslideexplorations after the earthquake A in J&K GUD SIRISULT FA CH SEARIS Co-seismic A X displacem BAR EA R ent in FAU APUR LT Turkey earthquake using Aeromagnetic contour data DINSAR
  • 58. OVERVIEW OF NRC GEOMORPHOLOGICAL MAPPING ON 1:50,000 SCALE Groundwater Glacier Melting1 5 5 2 (Playa) (Outwash plain) Disasters Illegal Mining2 1 6 6 8 (Landslide) (Opencast mine)Mineral Exploration Coastal inundation3 7 • •Total 307 landforms in the country Total 307 landforms in the country are envisaged for mapping. are envisaged for mapping. 7 • •Project will be completed in 2013. (Beach ridge) Project will be completed in 2013. (Coastal bar) Building Material • •Quality of the maps will be checked Seismic Zonation Quality of the maps will be checked 4 by experts from ISRO and GSI.4 by experts from ISRO and GSI. 8 • •All state remote sensing centres 3 All state remote sensing centres and academics are involved. and academics are involved. (Inselberg) (Lineaments)
  • 59. National Urban Information System Executed by NRSC/ISRO,SOI/DST & MoUDProject Schedule: June 2008 – July 2010Scope : No. of Towns : 152Generation of Multi scale (10K,2K&1K)Hierarchical Urban Geospatial Database including Area : 55,755 sq.kmThematic data for various levels of UrbanPlanning, Infrastructure Development and e-governance using Satellite, Aerial and GPRtechniques.NRSC/ISRO Responsibility: Providing High Resolution Satellite Data of IRS P5 Cartosat-1(Stereo)& LISS-IV MX Data. Generation of Thematic Geospatial Database on Metro - 11 cities 1:10,000 scale with 16 Layers of Base, Urban Class I – 72 towns Landuse, Geology/Geomorphology, Soils themes Class II – 15 towns from IRS Satellite data and Administrative, Class III – 19 towns Municipal and Census data Class IV – 17 towns Class V – 6 towns Providing Aerial Photography on 1:10,000 Scale for Class VI – 12 towns generation of Geospatial Database at 1:2000 scale for Core City areas.
  • 60. Watershed Development
  • 61. APPROACHWatershed level NATURAL RESOURCES Identification of critical areas1: 50, 000 scale CHARACTERISATION Based on inherent soilIRS LISS III /IV problems Identification of a micro- watershed for detailed inventoryMicro-watershedlevel ASSESSMENT OF RESOURCES Action Plans1: 12, 500 scaleIRS LISS IV / POTENTIALS /CARTO 1& 2 CONSTRAINTS Water harvesting structures IMPLEMENTATION Soil conservation measuresField level Crop HYVs / improved practices / improved cropping intensity
  • 62. THEMATIC MAPS OF NIPANA MICRO WATERSHED SATELLITE DATA SOIL MAP LAND USE / LAND COVERGROUND WATER PROSPECTS CRITICAL AREAS MAP
  • 63. ACTION PLAN FOR RAINFED COTTON PRODUCTIONSYSTEM NIPANA MICROWATERSHED, AKOLA Dt, MAHARASHTRA Legend Improved hybrid cotton and intercropping with G.gram, B. Gram + Pigeon pea;CPGB, diversion ditches Broad bed and furrow; CPGB; Cotton(PKV-2) and intercropping with G.gram, B. Gram + Pigeon pea CPGB +Stone filter ; Improved Desi Cotton intercropping with pearl millet Cotton (Nanded 44)+Green gram (1:1)/Maize + Pigeon Pea (3:3/4:2) CPGB :Diversion ditches ICT + Teak/Bambaoo:Diversion Ditches ICT +Plantations – Dryland fruit crops Silvipastoral system of Ailanthes excelsa + Dinanath grass ; ICT Brush wood gully plugs:Gap Plantation with Hardy speciesFarm ponds Maintenance of Existing land use Nala bund Gully plug
  • 64. NIPANA MICRO WATERSHED AKOLA DISTRICT, MAHARASHTRAIntermittent contour trenches Satellite data Recharged well with high water level Action plan Good crop of cotton beside recharged wellConservation pit graded bund Cotton varietal trials Cement gully plug
  • 65. INTERMITTENT CONTOUR TRENCHES - VIEWED BY HIGH RESOLUTION SATELLITENIPANA MICRO WATERSHED, AKOLA DT. , MAHARASHTRA Quickbird MSS data after implementation Quickbird PAN data after implementation Intermittent contour trenches Farm pond
  • 66. Disasters
  • 67. NATIONAL AGRICULTURAL DROUGHT ASSESSMENT AND MONITORING SYSTEM Coverage Satellite data analysis Drought assessment A N N N AWiFS N N N N N • AWiFS A • MODIS 250 m A • MODIS 1 km A A=AWiFS • AVHRR N N=NOAAIndicators/informationbeing used in Information reportingdrought assessment•NDVI•NDWI AVHRR•EVI•AMSR E soil moisture Integration with ground data•CPC rainfall forecast Rainfall deviations . . 300 Sowing progress•Rainfall 250 100 90 80•Sown area 200 70 % of normal % deviation 150 60•Soils 100 50 40 30 50•Cropping pattern 0 20 10 -50 . 0•Irrigation support 5 Jun 12 Jun 19 Jun 26 Jun 3 Jul 10 Jul 17 Jul 24 Jul 31 Jul 7 Aug 14 Aug 21 Aug 31 Aug 11 Sep 18 Sep 25 Sep 30 Sep -100 12/6 19/6 6/6 3/710/7 17/7 24/7 31/7 7/8 14/8 21/8 28/8 4/9 11/9 18/9 25/9
  • 68. Methodology for agricultural drought assessment Change in crop calendar Drought warning Lag between NDVI & (June, July, August) rainfall Normal Abnormal weather events Such as floodsNDVI anomaly WatchAssessment(1) Relative dev. Alert(2) VCI(3) In season transformation Extent of NDVI Drought declaration anomaly (Sep, Oct) Agricultural Extent of rainfall drought Mild deviation situation Moderate Extent of sown area deviation Severe
  • 69. Progression of NDVI : 2009 (nation)Jun 2009 Jul 2009 Aug 2009Sep 2009 Oct 2009 Nov 1fn 2009
  • 70. Monitoring Crop Condition – 2009, AVHRR NDVI July August June September October Agri. Drought Assessment
  • 71. Progression of NDWI : 2009 (nation)Jun 2009 Jul 2009 Aug 2009Sep 2009 Oct 2009 Nov 1fn 2009
  • 72. Agricultural drought assessment: Kharif 2009 June July August (part of the district) October SeptemberJune 215 distJuly 226 distAug 124 distSep 115 distOct 179 dist
  • 73. Agricultural Drought Assessment June 09 July 09 Aug 09 Sep 09 Oct 09 19 19 21 21 (602 1 Andhra Pradesh 7 (839 andals) (685 andals) (602 mandals) mandals) 2 Bihar 5 29 13 13 13 3 Chattisgarh 14 15 4 - - 4 Gujarat 25 17 17 13 19 2 (5 blocks) 5 Haryana 6 15 (64 blocks) 2 (5 blocks) 2 (5 blocks) 6 Orissa 14 1 - - - 7 Jharkhand 2 5 5 5 11 8 Karnataka 9 6 (14 Taluks) 8 (26 taluks) 3 3 (7 Taluks) 5 (20 Taluks) 9 Maharashtra 15 12 - 5 (20 Taluks)10 Madhya Pradesh 45 42 5 1 3211 Rajasthan 32 27 25 13 2312 Uttar Pradesh 41 38 (98 Taluks) 20 (53 Taluks) 23 (60 Taluks) 23 (60 Taluks)13 Tamil Nadu - - 6 16 27 215 226 124 115 179
  • 74. Agricultural Drought Assessment Drought impact assessment Vulnerability mapping Early warning systems NDVI Spatial Decision Support SystemsI anomaly Country wide monitoring with high resolution AWiFS dataN Support from geo-stationery systemsP Rainfall 2007+ Utilisation of microwave dataU deviation Process based indictors (energy balance)T Sown area • IRS AWiFS based sub-district level assessmentS deviation • AVHRR based regional/district level assessment O • Integration with ground data/multiple indices Drought warning: June, July, Aug. U • Decision rules for drought warning & declaration 2004 • Enhanced content & frequency of reporting * Normal T * Watch P • Institutional participation & Capacity building * Alert U • IRS WiFS based district / sub district level assessment Drought declaration: T • Supplementation of WiFS with MODIS Sept, Oct., Nov. 2002 • AVHRR based regional/district level assessment S * Mild • Agricultural area monitoring * Moderate * Severe • IRS WiFS based district / subdistrict level assessment 1998 • AVHRR based regional/district level assessment USER DEPARTMENTS • Participation of user departments (Union & State Govts.): • NOAA AVHRR1988 • Regional/district level assessment Agriculture Ministry Relief Commissioners
  • 75. Floods-2008 Introduction Kosi Breach • June-Sept, 8 states mapped • More than 400 flood maps 8 6 7 • State, district, detailed flood maps • MHA, CWC, IMD, State Govt • The breach in Kosi river embankment led to change in the river course, extensive flooding and reduction in the old river course.PRE FLOOD Monitoring POST FLOOD 11-Apr-08 20-Aug-08 23-Aug-08 27-Aug-08 2-Sep-08 7-Sep-08 18-Sep-08 20-Sept.-08 22-Sep-08 29-Sep-08 Detailed View Persistence of Flood Inundation • More than 130 villages are under submergence for more than a monthPRE BREACH: CARTOSAT & LISS IV MX MERGED IMAGE SHOWING BREACH LOCATION a a b b POST BREACH: CARTOSAT IMAGE SHOWING • Flood persistence map- Aug. 20th to Sep. 22nd, 2008-for part of Madhepura BREACH LOCATION • Detailed views of the embankment breach district
  • 76. August 20, 08 Flood Inundation r i ve s iR Ko Kosi River Breach mk 1.7Monitoring – every 2 days Info DisseminationImpact Assessment : • MHA, CWC, IMD, • 625 Villages Marooned •Govt. of Bihar • 0.12 Mha 95000 Sq Km ASAR data Cartosat-2 image collected in 3 resolutions 09 Sept. 08
  • 77. Impact of Orissa flood on kharif rice cropped areClassified data showing Rice Total Inundated area Inundated Ricecropped area14.0 Lakh ha 4.49 Lakh ha 1.83 Lakh ha Total Inundated Duration of Data used inundated rice area Flood area (ha) (ha) Scansar-N 01 day 18-09-08 204010 100135 Scansar-w 07 Days 24-09-08 73890 24806 Scansar-W 12 days 29-09-08 74305 21902
  • 78. CARTOSAT-1 DTM INDIAN COASTInput Data : Cartosat-1 data[Total No. of Scenes : 600 ( 270 East + 330 West)]Control Source : ETM (X,Y) and SRTM (Z)Output DTM (Bare earth): Upto 20km inland buffer Cartosat- 1 and LISS-IV MX Ortho ImagePILOT STUDIES Visakhapatnam and Nagappattinam Coast
  • 79. Enhanced Outreach
  • 80. Village Resource Centres (VRCs) For Empowering Rural Community Components of VRC• Two way audio-video link via satellite• Advisory related to Agri., Fisheries, …• Natural Resources VRCs Information As on January 2010• Tele-Education, Tele- Healthcare, …• Disaster related• Skill Development• ……………. Natural Resource data at VRCs Set-up: ~ 45 partner agencies ~75 Expert Centres/ HospitalsSatellite data Road Network Geomorphology Landuse/cover are linked in the network Over 6000 programmes conducted, more than 4 lakh people benefited
  • 81. Space Based Information Support for Decentralized Planning: SIS-DP (2009 Road 2015) Telephone toBackground Canal Post Office Electricity Wells Taken up at the behest of Planning Market Commission’s and PC-NNRMS resolution to facilitate GIS enabled Resource Catalogue and make them School available to the people at grassroots College Internet Sanitation Dispensary level. Bore well Banks develop deploy Objectives • Spatial depiction of land & water resources with attribute information, by keeping cadastral data as base in seamless engage manner for entire country • Tools and utilities for providing user driven applications for speedy, accurate and transparent decision making; and empower • Capacity building in state departments with the training of advance manpower in spatial data analysis. Land Cover Settlement Well data Infrastructure Ex. Road widening
  • 82. Space Based Information Support for Decentralized Planning: SIS-DP ISRO Role Satellite Data NR Census layers • Land Use / Land Cover (Cartosat – 1, 2 / • Land Degradation LISS MX IV) • Forest & Vegetation MIS Periodic National Monitoring • Wetlands • Snow & Glacier Space Land cover, Road, • Geomorphology based Settlement, Drainage • Soil Monitoring & WB, Soil*, GWP* Periodicity (Revisit in 10 years) • Every 5 years Slope (DEM) • Every 20 years 1:10 K Customized State Data Repository Communication State Creation & Updating Dissemination Highway Cadastral User Projects (Digital Maps) • Ground Water Prospect District database (RGNDWM) District Usage and updating • Wastelands Resourcesat2, - Digital village cadastral • Irrigation Infrastructure Cartosat3 - maps, attribute linking (AIBP) …… (Existing digital maps if • Watershed ISRO EO • National Urban Information Missions available will be used) System Usage through Panchayat customized interface 4/5 states, NLRMP • Biodiversity • Watershed Prioritisation • Tribal Development Based upon Policy:* Soil & GWP in prioritized G2G, G2Careas only New Existing/ongoing Assured Continuity New (1:10K) (1:50K)
  • 83. Geospatial approach for Climate change studies• Long term historical •High resolution data satellite data •Field based• Long term climate data biophysical,• Vulnerability patterns meteorological data Process ModelsNational Spatial Database BAU + Dynamic •Crop growth•Projected climate Scenario Response •Dynamic growth•Socioeconomic vegetation/niche•Hydrology Functional •Hydrology•LULC Change Analysis •Urban heat and spread Drought response Water conservation • Degradation Urban energy Alternate cropping & balance systems • Species conservn zones conservation & • Eco corridors augmentation Food security Water security Ecological security Energy security
  • 84. Ground / Field Data Collection
  • 85. Mobile Device Based Solution for Field Data Collection Technology Cellular Photo Network GPS Receiver camera Field Internet Collecting GPS coordinates, photographs, field Mail parameters Server Database CentralGSM/GPRS Developed Server ApplicationObservation Transmission Information Decision Action Enables real time data collection & transmission GPS coordinates, Digital Photos, user specified parameters People affected: 354 People died: 40 Data can be organized into database, viewed in geo-spatial form Application demonstrated- Relief Shelters/Hospitals/Civil Godowns Customized applications can be developed for other applications
  • 86. Systems for Watch on Weather and Climate Automatic Space Observations Doppler Weather RadarWeather Station (AWS) (DWR) EO instrument capabilities • Radiometers & Satellite Spectrometers Transmitter • Atmospheric Sounders • Continuous monitoring of severe weather • Rain Radars events • High resolution imagers • Radar network for Met. Analysis Data • Polarimetric radiometersSensor Team/ User Processing entire coastal areas, NE Data Dept. Center • Altimeters/Scatterometers region, major cities, … Providing inputs for meso-scale modeling
  • 87. Indian EO Missions - The Near Future Resourcesat- Oceansat-3 Ku Band 3 Scatterometer LISS-3 WS 2012-13 DMSAR-1 C/X SAR INSAT-3D RISAT-1 2010-11 Geo HR VHRR, Sounder C-band SARCartosat- Imager2B Resourcesat – 2 50m resolution LISS III, LSS IV , AWiFS1 m res. IMS - AWiFS Cartosat- 2C/ 60m, 740 km 2D 80 cm res. Scan-SAT Ku Band Scatterometer SARAL Cartosat- 3 Ka band Altimeter 30 cm res. MEGHA- TROPIQUES
  • 88. o RSC st N nk A, ts ha A pu T IS in G he S & or tR f Thanks for your kind attention