Radar Remote Sensing
Applications and Challenges
- 1st Edition - August 27, 2022
- Latest edition
- Editors: Prashant K. Srivastava, Dileep Kumar Gupta, Tanvir Islam, Dawei Han, Rajendra Prasad
- Language: English
Radar Remote Sensing: Applications and Challenges advances the scientific understanding, development, and application of radar remote sensing using monostatic, bistatic and multi… Read more
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Description
Description
Radar Remote Sensing: Applications and Challenges advances the scientific understanding, development, and application of radar remote sensing using monostatic, bistatic and multi-static radar geometry. This multidisciplinary reference pulls together a collection of the recent developments and applications of radar remote sensing using different radar geometry and platforms at local, regional and global levels.
Radar Remote Sensing is for researchers and practitioners with earth and environmental and meteorological sciences, who are interested in radar remote sensing in ground based scatterometer and SAR systems; air borne scatterometer and SAR systems; space borne scatterometer and SAR systems.
Key features
Key features
- Covers monostatic, bistatic and multi-static radar geometry
- Features case studies, including experimental investigations, for practical application
- Includes geophysical, oceanographical, and meteorological Synthetic Aperture Radar data
Readership
Readership
Postgraduates, PhD Research scholars, professors and scientists in the microwave remote sensing and space community. Hydrologists, modelers, agricultural scientists, ocean scientists, hydro-ecologists and meteorologists, environmental consultants, and oil and gas/mining industries
Table of contents
Table of contents
SECTION 1: Basis of Radar Remote sensing
1. Introduction to radar remote sensing
2. Microwave Component and Devices for Radar Systems
3. Theory of monostatic, and bistatic radar systems
4. Review of Microwave fundamentals and its applications
SECTION 2: Conventional methods for radar remote sensing
6. Identification of Sub-surface features using L-band SAR data in Jaisalmer, India
7. Terrestrial Water Budget Through Radar Remote Sensing
8. Application of SAR Remote Sensing in Forestry
9. Classification of Radar data using Bayesian optimized 2D-CNN
10. Modeling and Simulation of SAR Dataset for retrieval of soil surface parameters
11. Flood inundation mapping from SAR and optical data using support vector machine: a case study from kopili river basin during Amphan cyclone
12. Performance assessment of Phased Array type L-band Synthetic Aperture Radar and Landsat-8 used in image classification
13. Evaluation of Speckle Filtering Methods Using Polarimetric Sentinel-1A Data
SECTION 3: Advanced methods for radar remote sensing
15. Advanced Method for Radar Remote Sensing: Circularly Polarized Synthetic Aperture Radar
16. A processing chain for estimating crop biophysical parameters using multi-temporal Sentinel-1 SAR data in cloud computing framework
17. Fuzzy logic for the retrieval of kidney bean crop growth variables using ground based scatterometer measurements
18. Monitoring Tropical Peatlands Subsidence by Time-Series InSAR Technique
19. Towards a North American continental wetland map from space: Wetland classification using satellite imagery and machine learning algorithms on Google Earth Engine
SECTION 4: Future challenges in radar remote sensing
21. The Study of ISRO’s Ku-band based Scatterometer Satellite (SCATSAT-1) in Agriculture: Applications and Challenges
22. Radar Remote Sensing: Challenges and future prospect
Product details
Product details
- Edition: 1
- Latest edition
- Published: September 1, 2022
- Language: English
About the editors
About the editors
PS
Prashant K. Srivastava
DG
Dileep Kumar Gupta
Dileep Kumar Gupta received his doctoral degree from the Department of Physics, Indian Institute of Technology (Banaras Hindu University), Varanasi, India. He is currently working as Assistant Professor (Grade II) at Galgotias University, Greater Noida, India. His research expertise lies in microwave active and passive remote sensing, electronics and sensor systems, GNSS-based applications, and algorithm development for soil moisture and crop parameter retrieval using ground‑based and space‑borne platforms. His work closely integrates antenna‑enabled sensing systems with data processing methodologies. He has published extensively in peer‑reviewed journals, conference proceedings, and book chapters, and has also served as an editor for academic books with international publishers. His broader research interests include multi‑sensor remote sensing, microwave system applications, geoinformatics, and the use of artificial intelligence and machine learning techniques in remote sensing data analysis.
TI
Tanvir Islam
DH
Dawei Han
RP