Evaluating the Robustness of NISAR's Cropland Product to Time of Observation, Observing Mode, and Dithering. Issue 8 (23rd August 2022)

• Record Type: Journal Article
• Authors: Kraatz, S.; Siqueira, P.; Kellndorfer, J.; Torbick, N.; Huang, X.; Cosh, M.
• Is Part Of: Earth and space science. Volume 9:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-23
• Subjects: UAVSAR -- NISAR -- cropland -- dithering; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2022EA002366
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: Cropland mapping is important for monitoring agricultural practices, cropland distribution and for supporting food security programs. Radar remote sensing will likely provide a means of cropland mapping, which can be efficient, accurate, and globally applied. Algorithms used for spaceborne radar cropland mapping are still undergoing calibration and validation efforts, necessitating ground and aircraft‐based campaigns ahead of launch. The upcoming NASA ISRO SAR (NISAR) mission will map croplands at 1 ha spatial resolution using a coefficient of variation approach. NASA Jet Propulsion Laboratory recently released simulated NISAR data over cropland calibration sites including morning (AM), evening (PM), and dithered with and without gaps. These freely available simulated data allow for making accurate a priori estimates of how NISAR's cropland science algorithm is impacted by factors such as orbit (i.e., the incidence angle, time of day), bandwidth (i.e., whether the 5, 20, or 40 MHz channels are used), and varying the system's pulse repetition frequency—a process known as dithering. This study investigates these science mission questions over agricultural regions in Mississippi and Arkansas, USA. Results show that compositing data from both orbits (AM + PM) yielded comparable classification accuracy to using only one of AM or PM data. The study also found that dithering only slightly decreased cropland mapping capability (<0.3% accuracy reduction). Key Points: Compositing AM and PM streamlines NASA ISRO SAR (NISAR) cropland product generation and allows for more robust coefficient of variation estimation (more data) Compositing slightly improved results at two sites (<1%), but performed 0.2% worse than the next poorest result at another Dithering had negligible impact (∼0.3% lower accuracy) on NISAR's cropland mapping, supporting the mission's decision to implement it