Location: Hydrology and Remote Sensing LaboratoryTitle: High resolution land surface geophysical parameters estimation from ALOS PALSAR data
|NARVEKAR, P. - Collaborator|
|TOMER, S.K. - Collaborator|
|SEKHAR, M. - Collaborator|
|MOHAN, S. - Collaborator|
|BANDYOPADHYAY, S. - Collaborator|
|ENTEKHABI, DARA - Collaborator|
Submitted to: Journal of Remote Sensing Society of Japan
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/30/2016
Publication Date: 11/1/2017
Citation: Narvekar, P., Tomer, S., Sekhar, M., Mohan, S., Bandyopadhyay, S., Jackson, T.J., Entekhabi, D. 2017. High resolution land surface geophysical parameters estimation from ALOS PALSAR data. Journal of Remote Sensing Society of Japan. 37(2):105-111.
Interpretive Summary: The potential of a radar-only algorithm (which does not need ancillary data on soil surface roughness and vegetation) is demonstrated over a study site in India. Retrievals used high resolution data from a recently launched Japanese radar instrument. The estimated soil moisture was compared with low resolution soil moisture estimates from the Aquarius and the Soil Moisture Ocean Salinity satellites and field based soil moisture measurements. These results showed the potential of the radar instrument and the algorithm in providing high resolution soil moisture, surface roughness and vegetation information. The products can be used to address hydrological and agricultural applications that demand higher resolution information.
Technical Abstract: High resolution land surface geophysical products, such as soil moisture, surface roughness and vegetation water content, are essential for a variety of applications ranging from water management to regional climate predictions. In India high resolution geophysical products, in particular soil moisture, could form a critical source of information from sowing of seeds to scheduling irrigation activities during the critical phenophases of the crops leading to optimal water management in farming activities. In this work we used a recently developed radar algorithm that was formulated for near real-time soil moisture mapping from satellite data. This algorithm also provides roughness and vegetation information as byproducts and, therefore, is independent of ancillary information about these parameters. The algorithm was tested earlier using airborne and satellite radar observations. Present study provides a preliminary analysis of ALOS PALSAR datasets available over a well monitored watershed, “Berambadi” in Karnataka, in Southern India. Results showed the potential of ALOS PALSAR data in mapping high resolution geophysical products towards highly awaited hydrological and agricultural applications in India.