Assessment of Multi-Frequency SAR for Crop Type Classification and Mapping
Annual and within-season crop type monitoring and mapping is an important ongoing consideration for governments, global agricultural monitoring organizations and private interests worldwide. Successful country-wide operational remote sensing-based inventories are well-established utilizing optical-only and optical/single frequency Synthetic Aperture Radar (SAR) combinations of data. However, the drawbacks of these data combinations are the requirement of multiple sources of imagery throughout the entire growing season, which impedes within-season analysis, and cloud cover effects on the optical data. Currently, C-band SAR data are available with continuous global coverage from Sentinel-1A and B, RADARSAT-2 and from the expected launch of the RADARSAT Constellation Mission (RCM). With current and expected launches of several other frequency (L-, P-, etc.) SAR missions over the next few years (SAOCOM, NISAR, etc.) the opportunity for continuous, multi-frequency SAR coverage edges toward reality. The JECAM SAR Inter-Comparison Experiment is a multi-year, multi-partner project that aims to compare global methods for SAR-based crop monitoring and inventory. The third component of this experiment is the assessment of multi-frequency SAR data for crop classification and mapping. Earth observation (EO) data acquisitions of Sentinel-1A and B, RADARSAT-2/RCM, ALOS-2, SAOCOM1 and TerraSAR-X/TanDEM-X have been planned and requested for the 2019 growing season to complement within field surveys being conducted across the globe. In preparation for these data, this research analyzed ALOS-2, TerraSAR-X and RADARSAT-2 data for crop mapping at the JECAM Canada-Carman site using two dates of multi-frequency SAR data, in comparison to a traditional full season optical/SAR dataset. The multi-frequency data had similar overall accuracies as the optical/SAR dataset, and improved on several individual agricultural class accuracies.
|agriculture, ALOS-2, multi-frequency SAR, RADARSAT-2, Random Forest, Sentinel-1, Terra-SAR-X|
|39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019|
Robertson, L.D. (Laura DIngle), Davidson, A. (Andrew), McNairn, H. (Heather), Hosseini, M. (Mehdi), & Mitchell, S. (2019). Assessment of Multi-Frequency SAR for Crop Type Classification and Mapping. In International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 489–492). doi:10.1109/IGARSS.2019.8898006