Digital Image Processing Group
The group is involved in areas such as Image Classification, Image Segmentation, Pattern Recognition, Multi Resolution Signal Analysis, Neural Networks, Wavelets.
Global Positioning System (GPS) and Photogrammetry Group
The group is working on following research areas: Global Positioning System: Precision Geo-location, Modeling of Ionospheric and Tropospheric effects on GPS signals, Rapid Geo-tagging, Stereo Image Processing and Analysis: Feature Extraction and Matching, Multimodal Stereo Image Analysis, Remote sensing and GIS applications: Surface Hydrology, Landuse Planning (AM/FM)
GeoSysIoT group is working on the areas of Image Information Mining (IIM) of petabyte-scale remote sensing image archives in a cloud computing environment, OGC standards-driven geospatial sensor webs, Geosemantics, Knowledge-based systems, Biophysical variables retrieval from Remote Sensing data, Data mining and Machine learning, Spatial Data Infrastructures, Critical Infrastructure Protection.
Microwave Remote Sensing Lab
Microwave remote sensing group of CSRE is working on both active and passive microwave remote sensing data for land based applications such as soil moisture retrieval, land use/land cover mapping and SAR (Synthetic Aperture Radar) interferometry for DEM generation and surface change studies. The group has also analysed SSM/I and AMSR-E data for soil moisture mapping over India. Active microwave sensing was started in CSRE in 1989 with Canadian Intera airborne X-SAR data acquired over Rajahmundry and Andamann and Nicolbar Islands. As part the project, various SAR filters and classification techniques were implemented. The data were also used for land use/land cover analysis. With the Announcement of opportunity given by ESA and Jaxa, CSRE got several SAR images from ERS-1/2 and JERS-1 satellites over India and anlysed the data for various applications such as backscattering properties of different objects, classification of agriculture fields, soil moisture mapping, etc.. The group also actively participated with Shuttle Imaging Radar (SIR-C) mission flights in 1994 and collected filed data synchronous with SIR-C passes over Gujarat, India. Several tandem data sets were acquired over India and used them for DEM generation. Differential InSAR technique was demonstrated using ERS-1/2 SAR images acquired over Indian glaciers and Chmoli earthquake affected areas. Several workshop/conferences/training programmes were conducted in CSRE with available data. The group is presently working on AMSR-E and SMOS satellite data for soil moisture mapping over large area and also polarimetric SAR data from ALOS-PALSAR and Radarsat-2 for soil moisture retrieval and classification of various land features. The group is involved in collecting ground truth synchronous with TanDEM-X mission and generating high resolution DEM.
Research is ongoing in the field of statistical analysis of SAR image which aims to describe SAR images through statistical methods and reveal the characteristics of these images. The group research interests also focuses on the theory and applications of SAR polarimetric decompositions and information theoretic methods for optimum polarimetric feature subset selection and machine learning methods for classification. The group also focuses on the aspects of statistical analysis of SAR speckle filtering methodologies.
Snow and Glacier Studies Group
The current research of the Snow and Glacier Studies group pertains to the study of cryosphere (glacier and snow) through remote sensing. Optical remote sensing data is being used to monitor the retreat of glaciers and mapping of glaciers. Techniques like NDSI are being used to map snow cover. Remote sensing based techniques are evolved to estimate mass balance of different glaciers. For this purpose, AAR and ELA based methods, DEM derived from stereo optical data, SAR interferometry techniques and also from cryosat-2, tandem-x are exploited to evaluate mass balance of various glaciers involving limited field based mass balance measurement values. Algorithms are also being developed based on SAR polarimetry for estimating snow pack characteristics like snow wetness, density, grain size, snow water equivalent etc. Innovative snow cover mapping technique based on polarisation fraction and λ3 (eigen value of coherency matrix) known as radar snow index has also been developed. Differential InSAR techniques are being attempted to estimate the glacier movement. Intensity tracking techniques have been successfully used to understand the glacier movement. A new technique combining ascending and descending track InSAR and multi aperture interferometry together (3D-DInSAR) has been developed to estimate the glacier dynamics.
The flagship project of the Agro-Informatics group is Indo (IITB) - Japan (The University of Tokyo and National Agricultural Research Center/Tsukuba) Bilateral (DST/JST) Project, and the main objective is to develop a real to near-real time DSS, called GeoSense, in precision agriculture (crop yield modelling, precision irrigation and pest/disease forewarning modelling) aspects. Geo-ICT concepts from GramyaVikas model, and distributed wireless sensing devices (Agrisens from the SPANN Lab, IITB and FieldServer from the NARC, Japan) are being integrated to develop the GeoSense. Experiments are also being carried out with wireless sensor network-based Flux Towers to study the energy balance under various irrigation conditions for climate change adaptation strategies. In addition, for the first time in India, FieldTwitter, with an Open hardware system with cloud computing technology, has been deployed for cost effectiveness. The Wireless Sensor Network is deployed in a Research Farm of Agro-met Cell, Agricultural Research Institute, ANGRAU/Hyderabad, and test crops are rice, groundnut and maize. Other important attempts of the group are to (1) develop a viable and generic toolkit for integrated watershed planning and management of its natural resources, called “WATMIS: Watershed Management Information System” using multiple technologies like GIS, Remote Sensing (RS), GPS, hydrological modelling, etc.; (2) study the temporal distribution of dynamic CBL height using LiDAR laser based remote sensing instrument for monitoring temporal distribution of particle movement along with thermal or convective cells due to solar heating in the day time over a Southern Tropical region in India (in collaboration with the NARL-ISRO/Tirupati); and (3) understand the soil-water-vegetation dynamics in watersheds with reference to climate change scenarios (in collaboration with CS&WCR&TI/ICAR).
Geology and Mineral Resources Group
The mineral systems studies and mineral exploration group focuses on understanding deep-seated mineral systems using a variety of remotely sensed data including ground and air/space-borne geophysics such as gravity, magnetic, seismic data; multispectral and hyperspectral optical and thermal remote sensing; and microwave remote sensing. The high goal of the research is to translate mineral systems understanding into a set of spatial proxies and, subsequently, model them using GIS-based spatial information integration techniques for predicting mineral potential areas. The group also carries out 3D and 4D crustal modelling studies for understanding the tectonic and metallogenetic evolution of geological provinces. The group is currently working on uranium, gold, and base-metal mineral systems of the Aravalli Region of Western Rajasthan and is also involved in a collaborative research project with the University of Western Australia and Geological Survey of Western Australia for mineral prospectivity analysis of various geological regions of Western Australia.
Water resources and ecosystem services are two of the essential drivers for the sustenance of life on the Earth. Remote sensing information helps monitor these processes at global as well as regional scales. The eco-hydrology group at CSRE focuses on two aspects. First is the development perspective, wherein we develop algorithms to estimate hydrological variables from satellite information. Currently, the emphasis is laid on passive microwave remote sensing of soil moisture, which quantifies the water content in the unsaturated soil. We are also trying to understand the ability of passive microwave sensors to assess the vegetation dynamics, which can be useful for monitoring droughts and agriculture, among other applications. Dedicated operational soil moisture missions, NASA's SMAP, and ESA's SMOS are the primary sources of information for our research. The overarching goal of our attempts is to improve the accuracy of products over data-sparse countries like India.
Updated on July 28, 2023