The Indian Remote sensing programme is driven by the user needs. In fact, the first remote sensing based pilot project was carried out to identify coconut root-wilt disease in Kerala way back in 1970. This pilot project led the development of Indian Remote Sensing (IRS) satellites. Varieties of instruments have been flown on-board the IRS satellites to provide necessary data in a diversified spatial, spectral and temporal resolutions to cater to different user requirements in the country and for global usage.
Advanced Research focuses on numerical and spatial modelling using image processing and GIS tools for applications like crop yield and weather forecasting, dynamics of atmosphere, oceans, coasts and ecosystem and use of microwave data for various applications.The EO applications developed at the centre are key ingredient in the programmes of the government at the Centre and State. The centre pursues R&D in various field application of which include:
Status of VRC Network in the NER (Assam)
The Project Manual with technical guidelines has been suitably modified based on the experience from the first phase of project implementation. The Manual has been simplified with step wise procedures to be followed while executing project in their respective states.
Mapping of potential areas for expansion of sericulture in 20 selected districts of NER is in final stage of completion. One week programme on quality check and database integration was organized during March 20-24, 2017 at NESAC for the Scientists from State Remote sensing Application Centres. For other states of India, first installment of funds has been transferred and work is progressing as per schedule.
Assessment of area under Mulberry in major sericulture districts of West Bengal
Mulberry (Morus sp.: Moraceae) thrives extensively in tropical and temperate countries its leaves are harvested during various phenophases in commensuration with the age of silkworm for its dietary gratification. Farmers of major sericulture districts in West Bengal take up five rearings per year on an average and accordingly mulberry leaves are harvested twice a day to feed the silkworm for a period of 18-27 days depending on season and silkworm breeds, preceded by pruning of the plants for required foliage-flush at desirable height. Mulberry undergoes 5-6 pruning/ year at the completion of silkworm larva-stage which feeds voraciously on mulberry gross primary production coupled with the fact that senescence is hindered. Traditional sericulture farmers uproot and replenish old plantation since the economic life of mulberry extends up to 20 years.
Considering the importance of proper assessment of acreage under mulberry in the major sericulture districts in West Bengal and for crop condition assessment, a project titled Assessment, Development and Management of area under Mulberry in major sericulture districts of West Bengal using geospatial techniques was formulated and are being implemented jointly by NESAC and Central Sericultural Research & Training Institute (CSRTI), Berhampore, West Bengal. .
The major objectives were defined a) To estimate the current spatial extent of mulberry cultivation in selected blocks of 4 major Mulberry growing districts of West Bengal using RS, GIS and GPS b) Leaf protein and moisture contents estimation using hyperspectral data and relation with the laboratory based analysis c) Make an attempt to estimate leaf protein and moisture contents using hyperspectral data with limited laboratory based analysis. d) To develop block specific MIS which can be integrated with SILKS portal for dynamic.
Satellite data classification utilizing Resourcesat-2 LISS III LISS IV, satellite data has been done for acreage estimation of mulberry in all the selected four districts. Classification results shows variation in the acreage estimates with the recorded estimates by government agencies. Additional points were supplied to CSRTI, Berhampore for ground truth collection so that accuracy of the estimates can be improved and finalise the mulberry acreage estimates Correlation of protein values with spectral reflectance across leaves and varieties has been studied. A number of indices viz., NDRE, CCCI, NDNI, NRI1510, TCARI, Red edge, OSAVI1510 were tried to correlate with mulberry protein content, out of which only OSAVI1510 (Optimal Soil Adjusted Vegetation Index) has been found to have significant correlation with mulberry protein content. For leaf moisture estimation, three indices viz., NDVI, NDWI and MSI have been explored. All the available layers with attribute information have been integrated in the MIS. All the spatial and non-spatial information supplied by CSRTI have been converted to vector layers. Mulberry filed plots have been digitized using GF2, Cartosat and google earth satellite images.
Correlation of protein values with spectral reflectance is performed. The significant absorption bands were taken for comparison with the protein values. The absorption bands taken are in the range of 380nm -530 nm, 530nm -696 nm, 915 nm- 1030 nm, 1085 nm -1113 nm, 1113 nm -1252 nm, 1400 nm -1550 nm, 1635 nm -1810 nm and 1865 nm -1878 nm
Observation of Leaf protein vs reflectance analysis
The potential of using spectral characteristics for evaluating various biochemical parameter of mulberry has be examined from ground based remotely sensed hyperspectral data using spectroradiometer. Canopy reflectance spectra of mulberry has been collected for different varieties at three different leaves: namely glossy and 5th; 8th leaf. Spectral Range, No of Bands and Field of View of the sensors were 0.35-2.5 μm, 1024 bands and 4 ° respectively. Spectral measurements were taken at nadir looking position at a height of 10 cm(approx) over the canopy and timing close to solar noon (between 11:00 to 12:00 hrs) when changes in solar zenith angle is minimum. Acquisitions were obtained through a hand held PDA which gives reflectance values as the ratio of reflected radiance to incident radiance estimated by a calibrated white reference. All possible band combination has been trying to find the correlation with biochemical parameter (leaf protein and moisture). Best fit combination of indices will be worked out to assess individual parameter under study. Initial results shows out of six depth identified from the spectral curve, first depth and highest glossy leaf has shown significant correlation with the ground measured protein value. Several indices has been worked out and Optimized Soil-Adjusted Vegetation Index (OSAVI1510) has shown significant correlation with protein content of leaves of all varieties.
Crop condition assessment under abiotic stress of few selected crops of NER
Plant functions such as photosynthesis, transpiration, flower development and biomass production are sensitive to elevated CO2 and temperature and are expected to influence the future ecosystem functions and agricultural yield. High yields can only be obtained if plant stress is kept to a minimum. It is required to detect crop stress as early as possible so that management practices can be instigated to minimize its effect on the harvestable yield of the crop. Under an EOAM funded project, spectral signature of selected crops at different stress condition during crop growth stages are being generated. Common cultivars widely grown in this region were selected to study the crop performance under different stress condition. For two vegetable crop viz., Potato and Tomat data collection carried out for two years under different nitrogen fertilization and under elevated CO2 and Temperature conditions. Both morphological, biochemical and spectral data collection has been completed. Pooled data and ANOVA analysis for plant biophysical parameter is in progress. For upland rice (Ahu Rice), first year data collection is completed. Moisture stress has been induced at maximum tillering as well as at penicle initiation stage. For first year both morphological, biochemical and spectral data collection has been completed, data collection for the second year is in progress.
Land evaluation for organic crop planning in Assam using RS & GIS techniques
The Green revolution technology in India leads to many fold increase in food grains production. The effect of intensive cropping with high doses of agrochemicals has resulted in deteriorating soil properties and affecting animal and human health. Increasing consciousness about health hazards caused by agrochemicals has brought a major shift in consumer preference towards organic food which is considered safe and hazard-free. To meet the demand of organic food, there is a need to increase the area under organic farming for which land users and planners need basic soil information, problems and potential and suitability of soils for various crops for sustained agricultural production. This information can be obtained by using satellite images along with soil survey and land evaluation in GIS environment. Keeping in view that land evaluation for organic farming will help the planners and the farmers to expand the area under organic crop with sustainable production, the present study is proposed in Kamrup (Rural) district of Assam with following objectives: a) Preparation of soil, physiography and land use land cover map. b) Identification of potential areas for organic farming. c) Assessment of soil site suitability for organic crop planning in the potential area.
Soil map at large scale (1:25K) is being prepared by following the standard soil survey procedures. IRS P6 LISS-IV (MX) image is used for generation of landscape map, physiography and land use/land cover map by using visual image interpretation technique. Carto DEM is used to generate slope and aspect map. All theses maps are integrated and prepared physiography base map for the soil survey. Soil site information is recorded from each profile during the field survey. Horizon wise soil samples are collected from each profile for detailed physical and chemical analysis in the laboratory to incorporate the results with field observations and affirm soil taxonomy. The soil boundary will be delineated based on the boundary inferred by base layer in GIS environment.
Land evaluation for organic crop planning will be done as per FAO (1983) guidelines. This approach is based on the matching of qualities of different land units in a specific area, with the requirements of actual or potential land use.
Under this ongoing project updated lithology, physiography and LULC map of 1:50,000 scale to 1:25,000 scale based on LISS-IV images. Prepared slope map from Carto DEM. Updated road network map. All these maps are integrated and prepared physiography base map. Selected sample sites for profile study. Field survey is completed. During field survey studied morphological properties of soil and collected soil samples from each horizon from 60 soil profiles and started soil sample analysis in the soil testing laboratory.
Identification of suitable areas for expansion of Boro rice in Meghalaya
In Meghalaya the rice crop is distributed in three rice ecosystems. They are low altitude rice that covers 70% of total rice growing areas (TRGA), mid altitude rice covers 25% of TRGA and high altitude rice that covers 5% of TRGA. Area wise, Sali rice constitute about 63000 hectares with an average yield of 1.9 MT/Ha, Ahu about 33,000 hectares with an average yield of 1.3 MT/Ha and Boro about 13,000 hectares with an average yield of 3.7 MT/Ha. Considering the fact that Boro rice has high yield and there scope of expansion of Boro rice, Government of Meghalaya has requested NESAC to take up the project on identification of areas suitable for expansion of Boro rice cultivation in the state with the following objectives a) Preparation of soil map and soil fertility map at 1:50,000 scale. b) Mapping of areas suitable for expansion of areas under Boro rice. c) Acreage estimation of areas under Boro paddy at district/block levelThe project has been taken up in collaboration with Directorate of Agriculture (DoA), Govt. of Meghalaya, Shillong. Land evaluation for soil site suitability for Boro rice will be done as per FAO (1983) guidelines. Different thematic maps namely; soil depth, drainage, flooding, texture, gravel/stoniness, pH, organic matter, CEC, base saturation and slope will be prepared by the soil analysis and field data. All these thematic layers will be generated in GIS environment and analysed to find out suitability map for Boro rice. Then this suitability map will be used to identify suitable areas for expansion of Boro rice in the state.
Under this ongoing project prepared slope and elevation map from CartoDEM. The LULC map is updated by using LISS III images of 2015-2016. Selected sample sites for collection of soil samples. Maps showing sample sites along with road, LULC, slope and elevation have been prepared and submitted to DoA. Required training is provided to the collaborating agency on using of maps and GPS for soil sample collection. Completed collection of soil samples. Soil samples are analyzed and used for preparation of soil fertility map which will be used for mapping of suitable areas for expansion of Boro rice in the state.
Horticulture application in Remote Sensing
CHAMAN (Coordinated Horticulture Assessment and Management using geo-informatics) was initiated in September 2014 by Department of Agriculture, Cooperation & Farmers’ Welfare (DAC&FW), Ministry of Agriculture & farmers’ Welfare (MA&FW), Govt. of India under the Mission for Integrated Development of Horticulture (MIDH) as a Horticulture Assessment and Development project for better horticulture inventory and management using remote sensing, GIS and collateral field data. The major responsibility of project coordination and implementation has been assigned to Mahalanobis National Crop Forecast Centre (MNCFC), DAC&FW, New Delhi.NESAC organized four days training programme on Site Suitability Analysis in collaboration with MNCFC & SAC during 18-21 October, 2016 for the Scientists of the Remote Sensing Applications Centres of North-Eastern States. Terms of Reference (ToR) has also been signed between NESAC and respective SRSACs. The first installment (50% of total project cost) has been released to all the SRSACs after signing of ToR. NESAC purchased LISS-IV MX data of 2015-16 for all the 8 districts of NE states and provided to all the SRSACs for updating LULC-10K (SIS-DP data).
Updation of LULC using LISS-IV MX data has been completed for Meghalaya, Mizoram and Nagaland. Extraction of soil attributes from SOIl-50K/250K map prepared by NBSS&LUP/ SLUSI/ NESAC has been completed for the state of Meghalaya and Mizoram. Extraction of elevation, slope and aspect from Carto-Dem (10m) has been completed for the state of Arunachal Pradesh, Manipur, Meghalaya and Mizoram.