Projects

Remote Sensing and GIS Based Projects

Remote Sensing and GIS Based Projects
Crop Identification and Area Estimation of Major Crops using Multi Temporal SAR data and Optical Imagery.
  • Used Time series Sentinel-1A SAR (VV, VH Polarization) data and Sentinel 2 data .
  • Study area was Veppanthattai taluk, Perambalur District, Tamil Nadu State, India.
  • Preprocessing of Images done using SNAP software.
  • ML Algorithms used for classification and compared their results – SVM, Neural Net, Max likelihood and Min Distance.
  • Identified the major crops and estimated their area.
  • Derived the temporal backscattering of all crops for VV, VH polarization.
  • Published Articles : Research Paper 1, Research Paper 2
Google Earth Engine
  • Land Use/ Land Cover Classification using machine learning algorithms ( such as Random Forest, SVM)
  • Extraction of Time Series values of NDVI for single point and multi point locations using sentinel 2 and MODIS imagery.
  • Extraction of Time series values of VV, VH and RVI for single point and multi point locations using sentinel 1A/1B SAR imagery.
  • Water area detection using sentinel 1A imagery.
  • Flood Mapping using Sentinel 1A imagery.
  • Mapping of Mangrove Forest.
  • DEM image downloading and creationg slope and aspect.
  • Google Earth Engine App Creation.
Google Earth Engine
Environmental Mapping of Kotturpuram, Chennai, Tamil Nadu, India
Environmental Mapping of Kotturpuram, Chennai, Tamil Nadu, India.
  • The study area was kotturpuram road and CLRI. We have taken 15 point samples from this surrounding location.
  • Data Collected for five days from 26th September to 30th september using mobile phone applications.
  • Data collected such as noise, air temperature, surface temperature, relative humidity using survey technique.
  • The Interpolation is done for each data in the period of four days.
  • The output is mapped and it shows the variation of temperature, noise and humidity for each location.
  • Each Results are compared with other parameters .
Digital Soil Mapping of Rasipuram Block, Tamil Nadu, India.
  • Soil Profiles have been taken from legacy data.
  • Study area was salem and namakal block of Tamil nadu state, India.
  • SCORPAN model was used for prediction.
  • Predicted the soil properties such as sand, clay, silt and Organic Carbon using Quantile Regression Forest (Machine Learning ) algorithm in R Studio.
  • Prediction of performance evaluated based on the R2, RMSE, ME and PICP.
  • Results has average accuracy. In order to improve results has to add more number of training points and high resolution of DEM imagery.
  • Published Article: Article 1
Other Projects
Other Projects :
  • Thematic map created using population data such as choropleth map, Dot Map, Located Pie chart and Located Bar chart.
  • Site Suitability analysis using model builder.
  • Hydrological modeling using HECRAS.
  • Least Cost Modeling using ArcGIS .
  • Calculated the LST ( Land Surface Temperature ) Using ArcGIS and QGIS.
  • Flood Inundation Mapping.
  • Morphometric Analysis.
  • Time Series earthquake analysis in Qgis.
  • Spatio Temporal variation of association between Sea surface Temperature and Chlorophyl in Indian Ocean.
  • Mangrove Forest Mapping and time series analysis of ndvi using GEE.
  • WebGIS app development for dashboard.
  • Change Detection and Prediction Of LULC using land change modeler ( Idrisi Taiga) .
  • Sowing Date identification for sugarcane farms using time series trends of vegetation indices.
  • Water, Built-up and Vegetation area extraction using indices in Google Earth Engine.