This paper describes the feasibility of rice growth monitoring using the Fine Beam Dual polarization (FBD) mode data of Phased Array type L-band Synthetic Aperture Radar onboard Advanced Land Observing Satellite (ALOS/PALSAR). The relationship between the rice parameters acquired by ground truth and those acquired by HH-HV polarimetric correlation coefficients is investigated. The scattering mechanism with air/rice canopy/ground interaction is considered and compared with ground truth measurements. We found that the contribution to backscatter from the paddy rice canopy is larger than that from ground surfaces. The dominant scattering component is double bounce scattering from the interaction between paddy rice and water in the vegetative growth and reproductive growth periods. On the other hand, in the grain filling period it changes to a direct scattering component from paddy rice. The HH/HV correlation coefficient was also examined to confirm the change in the scattering mechanism between the reproductive growth and grain filling periods. Thus, the estimation of optimal harvest timing can be predicted by monitoring the cumulative change rate of the HH/HV polarimetric correlation coefficient.
High resolution land surface geophysical products, such as soil moisture, surface roughness and vegetation water content, are essential for 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 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 potential of ALOS PALSAR data in mapping high resolution geophysical products towards highly awaited hydrological and agricultural applications in India.
Low-altitude remote sensing, using an infrared camera suspended from a vessel-towed balloon, was adopted to map sea surface temperature (SST) around coastal oceanic fronts. Two field experiments were conducted in August 2013 and September 2014 to examine the capability of monitoring a fine oceanic structure typically revealed in coastal waters. The SST pattern visualized on infrared images was converted to that on a ground coordinate for geo-referencing conducted in two ways: one used buoys with the GPS receiver as reference points on the images, while the other used a wireless motion sensor attached to the infrared camera. The geo-referencing was successfully conducted in both cases, but the observation time was economized in the latter case. The fine coastal oceanic features such as frontal meander and eddies on the spatial scale of O(10) m were clearly detected by using this balloon infrared photography.
We developed a prototype system to generate PM2.5 concentration maps using GOSAT/CAI L1B products. The AOT (Aerosol Optical Thickness) retrieving process at 380 nm was reimplemented. We developed a formula to calculate PM2.5 concentrations by comparing satellite images and ground measurement data. Estimated PM2.5 concentrations showed good correlation with ground data (r=0.713 RMSE=22.4 μg/m3). Finally, PM2.5 concentrations maps were generated. In addition, an empirical cloud-screening method using CAI band1 images (SCUV) was also developed.