All Stories

  1. Optimizing Cropping Intensity Through an Integrated MCDM Framework: a Step Toward Sustainable Agriculture
  2. Quantitative Analysis of Variance and Optimization of Coordinate Systems and Temporal Conditions for Minimizing GPS Measurement Errors
  3. Satellite-based Assessment of Phenological Informatics and Associated Drivers over a Biodiversity Hotspot in the North-Eastern Region of India
  4. Climate Change Impacts on Various Ecosystems: A Geospatial and AI Perspective
  5. Examining the Role of Geospatial Technologies and AI in Disaster Risk Management and Response, Including Hazard Mapping, Vulnerability Assessment, and Real-Time Monitoring
  6. Machine Learning Approach to Biomass Estimation: Integrating Satellite and Ground Data in Sal Forests of Jharkhand
  7. Enhancing Forest Canopy Height Mapping in Kaziranga National Park, Assam, by Integrating LISS IV and SAR data with GEDI LiDAR data Using Machine Learning
  8. Understanding and mitigating climate change impacts on ecosystem health and functionality
  9. Exploring the Integration AI and Geospatial Data for Natural Resources Monitoring: A Week Training at BIT Mesra
  10. Quantifying forest resilience post forest fire disturbances using time-series satellite data
  11. Estimation of natural vegetation phenology metrics using time series EVI over Jharkhand state, India
  12. Plugging the Gaps in the Global PhenoCam Monitoring of Forests—The Need for a PhenoCam Network across Indian Forests
  13. The relationship between central Indian terrestrial vegetation and monsoon rainfall distributions in different hydroclimatic extreme years using time-series satellite data
  14. Mapping Annual Cropping Pattern from Time-Series MODIS EVI Using Parameter-Tuned Random Forest Classifier
  15. Predicting the Forest Canopy Height from LiDAR and Multi-Sensor Data Using Machine Learning over India
  16. Analysing the spatio-temporal patterns of vegetation dynamics and their responses to climatic parameters in Meghalaya from 2001 to 2020
  17. Evaluating the climatic and socio-economic influences on the agricultural drought vulnerability in Jharkhand
  18. Effect of scale, landscape heterogeneity and terrain complexity on agriculture mapping accuracy from time-series NDVI in the Western-Himalaya region
  19. Sentinel 1 and Sentinel 2 for cropland mapping with special emphasis on the usability of textural and vegetation indices
  20. Multi-resolution analysis based data mining approach to assess vegetation dynamics in Jharkhand using time series MODIS products
  21. Resilience of the Central Indian Forest Ecosystem to Rainfall Variability in the Context of a Changing Climate
  22. Estimation and evaluation of high spatial resolution surface soil moisture using multi-sensor multi-resolution approach
  23. Improved NDVI based proxy leaf-fall indicator to assess rainfall sensitivity of deciduousness in the central Indian forests through remote sensing
  24. Segmentation-based approach for trend analysis and structural breaks in rainfall time series (1851–2006) over India
  25. Diagnostically counting palm date trees in Al-Ahssa Governorate of Saudi Arabia: an integrated GIS and remote sensing processing of IKONOS imagery
  26. Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India
  27. Development of a system for drought monitoring and assessment in South Asia
  28. Evaluating the Performance of Multi-Class and Single-Class Classification Approaches for Mountain Agriculture Extraction Using Time-Series NDVI
  29. Wavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data
  30. Mapping Agriculture Dynamics and Associated Flood Impacts in Bihar using Time-series Satellite Data
  31. George Joseph and C. Jeganathan: Fundamentals of Remote Sensing
  32. Fundamentals of Remote Sensing. Third Edition. By George Joseph and C. Jeganathan. Universities Press (India) Private Limited, Hyderabad, India. 2018. ISBN 978-93-86235-46-6. 606 pages with 20 in colour. Paperback, 180 mm x 240 mm.
  33. Extracting Agriculture Area from Coarse Resolution MODIS time-series data in the Mountainous Region
  34. Fractal-Based Pattern Extraction From Time-Series NDVI Data for Feature Identification
  35. MODIS-VCF Based Forest Change Analysis in the State of Jharkhand
  36. Multi-polarized Radarsat-2 satellite sensor in assessing forest vigor from above ground biomass
  37. Time-series cloud noise mapping and reduction algorithm for improved vegetation and drought monitoring
  38. Space-Time Integrated Landslide Hazard Zonation near Tehri Dam in Uttarakhand, India
  39. Monitoring Horizontal and Vertical Cropping Pattern and Dynamics in Bihar over a Decade (2001–2012) Based on Time-Series Satellite Data
  40. A survey of particle swarm optimization and random forest based land cover classification
  41. Spatio-Temporal Forest Change Assessment Using Time Series Satellite Data in Palamu District of Jharkhand, India
  42. A review of radar remote sensing for biomass estimation
  43. Extracting seasonal cropping patterns using multi-temporal vegetation indices from IRS LISS-III data in Muzaffarpur District of Bihar, India
  44. Remotely sensed trends in the phenology of northern high latitude terrestrial vegetation, controlling for land cover change and vegetation type
  45. Scrutinising MODIS and GIMMS Vegetation Indices for Extracting Growth Rhythm of Natural Vegetation in India
  46. Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology
  47. Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture
  48. Geoinformatics
  49. Multi-Objective Spatial Decision Model for Land Use Planning in a Tourism District of India
  50. Incorporating Spatial Variability Measures in Land-cover Classification using Random Forest
  51. Mapping the phenology of natural vegetation in India using a remote sensing-derived chlorophyll index
  52. The use of MERIS Terrestrial Chlorophyll Index to study spatio-temporal variation in vegetation phenology over India
  53. Terrestrial vegetation phenology from MODIS and MERIS
  54. Characterising the spatial pattern of phenology for the tropical vegetation of India using multi-temporal MERIS chlorophyll data
  55. Estimating the Local Small Support Semivariogram for Use in Super-Resolution Mapping
  56. Comparison of MODIS vegetation continuous field — based forest density maps with IRS-LISS III derived maps
  57. Discriminating the invasive species, ‘Lantana’ using vegetation indices
  58. Characterisation of malaria vector habitats using Remote sensing and GIS