Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kerala Environment...

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This presentation by Dr A R R Menon, Emeritus scientist, CED on Remote Sensing applications in agriculture and forestry was made at at the Kerala Environment Congress, Trivandrum organised by the Centre for Environment and Development

Transcript of Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kerala Environment...

  • Remote Sensing Application in Agriculture and Forestry Dr.A.R.R.Menon Scientist Emeritus Centre for Environment and Development Thiruvananthapuram
  • The toolsGeomatics1.GIS technology2.Remote Sensing Technology3.GPS Technology
  • 2. Remote Sensing as a toolfor baseline data gathering . ?
  • Information is gathered by instruments carriedon suitable platforms. The information is used tostudy targets of interest on the Earths surface Platform: Satellite Instrument: Scanner Target: Land-Water
  • Based on Reflected Energy SourceELECTROMAGNETIC SPECTRUM
  • Characteristic Features- Synoptic Nature- Repetitive Coverage of Large Area- Quantifiable Data Procurement
  • REGIONS OF ELECTROMAGNETIC SPECTRUM(covering entire spectrum using appropriate sensor)
  • Spectral reflectance of objects
  • Multistage Remote Sensing
  • SatellitesGeostationaryPolar
  • Satellite Paths and repetitivity
  • Sensor resolution1. Spatial resolution2. Spectral resolution3. Radiometric resolution4. Temporal resolution
  • SENSORS IN INDIAN REMOTE SENSING SATELLITES LISS II (36.5M) LISS III (23.5M) PAN (5.8M) WiFS (188.3M) Sensor Resolution - ? Spatial, spectral, radiometric, temporal
  • Pan image ofMoscow
  • Basics of Satellite Remote Sensing 3 3 1 2 2 1T C Composite (Normal) F C Composite
  • FCC of Shiwalik hills(Liss3 image)
  • 2. GPS technology as a tool for accuracy evaluation & mapping Geographical Position Fixing: -- using high altitude satellites GPS satellites using the principles of Trilateration
  • GPS satellites GPS satellite 24 numbers 6 orbits 22,200km altitude
  • Trilateration is a basic geometric principlethat allows you to find one location if youknow its distance from other, alreadyknown locations.
  • Trilateration: Receiver must track at least four satellites to calculate 3-D position3-D position is: Latitude, Longitude and AltitudeGPS receiver must solve for X,Y,Z and TimeIf GPS unit is only tracking 3SV, 2-D position willbe computed (XY).
  • 3. GIS as a tool for analysis & modeling
  • Agricultural application:The utilization of space-bourn multispectral datafor crop acreage and production estimationstarted in seventies with the launching of theLarge Area Crop Inventory Experiment (LACIE)jointly by NASA, USDA and NOAA (NationalOceanic and Atmospheric Administration) in1974.In India the satellite remote sensing is mainlyused for the crop acreage and productionestimation of agricultural crops.
  • The methodology for acreage andproduction estimation using Indian RemoteSensing Satellite (IRS1A/1B) has been inoperation for major crops, namely, wheat,paddy, sorghum, soybean, groundnut andcotton in the monocropped areas (SpaceApplication Centre, 1990).In 1970 ISRO carried out a very interesting andpromising experiment for IARI, in detectingcoconut root wilt disease in Kerala before itwas visible on ground.
  • 1. Identification, area estimation andmonitoring:The specific requirement of climate and soilconditions coupled with the specializedmanagement practices make the distribution ofplantation crops rather more localized in comparisonto other agricultural crops.The identification, estimation of growing stock,analysis of distribution and monitoring at regularintervals are major aspects in plantation crops.
  • 2.Crop nutrient deficiency detection:The nutrient deficiency in plants affectsthe color, moisture content and internalstructures of the leaves and as a resulttheir reflecting power changes.
  • 3.Soil mapping
  • 4.Vegetation indices: The green, red and NIR reflectance could beemployed as variables to estimate the Leaf Area Index(LAI).Many investigations have been conducted to assess cropcharacteristics, such as biomass, and LAI, by means ofcombinations of reflectance or digital pixel values invarious spectral bands.Such a combination of reflectance values, the vegetationindex, also serves to correct for undesirable influences ofvarying soil reflectance or atmosphere circumstances onthe result.
  • 5.Crop condition assessment: The physiological changes that occur in aplant due to stress may change the spectralreflectance/ emittance characteristics resultingin the detection of stress amenable to remotesensing techniques. Crop monitoring at regularintervals during the crop growth cycle is essentialto take appropriate measures and to assesinformation on probable loss of production.
  • 6.Phenological studies
  • 7.Spatial signature library:Spatial signature evaluation of thespecies and the reflectance properties ofdifferent species in different phonologicalstages and growth stages are yet to be explored.The work on this line on crop reflectance propertiesare conducted by organizations likeSpace Application Center, Ahemadabad.
  • 8.Crop yield modeling and production forecasting:The information on production of crops beforethe harvest is very vital to the national foodpolicy planning and economy of the country.Reliable crop yield estimate is one of the mostimportant components of crop production forecasting.
  • Crop evaluation
  • 9.Pest management:Integrated pest management isan important component of sustainableagriculture.Methodologies need to beperfected for identification of locustbreeding grounds based on vegetationor moisture status, thereby developingstrategies for preventing their spreadand effective control measures.
  • 10.Agricultural draught assessment:Draught assessment is yet anotherarea wherein remote sensing datahas been used at operational level.The district level drought assessmentand monitoring using NDVI generatedfrom NOAA-AVHRR data helps in takingtimely preventive and corrective measuresfor combating drought.
  • 11.Temporal data for irrigation studies
  • 12.Reflectance modeling:Physical reflectance modelsfor crops serve the importantpurpose of understanding thecomplex interaction betweensolar radiation and plant canopies.
  • In order to obtain a reliable yield prediction,growth of crops has to be modeled bymeans of crop growth models. Cropgrowth models describe the relationbetween physiological process in plantsand environmental factors such as solarirradiation, temperature, water andnutrient availability.
  • The solutionTo effectively utilize the informationon crops for improvement of economy,there is a need to develop state/ district levelinformation system based on availableinformation on various crops derived bothfrom conventional and remote sensingapproaches in GIS environment.
  • Forestry Applications