The Contribution of ALOS PALSAR Multipolarization and Polarimetric Data to Crop Classification

Abstract

(1) Agriculture and Agri-Food Canada, 960 Carling Ave., Ottawa (Canada) K1A 0C6, mcnairnh@agr.gc.ca Summary of originally proposed researchMapping and monitoring changes in the distribution of cropland provide information that aids sustainable approaches to agriculture and supports early warning of threats to global and regional food security. This project tested the capability of PALSAR multipolarization and polarimetric data for crop classification. L-band results were compared with those achieved with a C-band SAR data set (ASAR and RADARSAT-1), an integrated C-and L-band data set, and a multitemporal optical data set. Using all L-band linear polarizations, corn, soybeans, cereals, and hay-pasture were classified to an overall accuracy of 70%. A more temporally rich C-band data set provided an accuracy of 80%. Larger biomass crops were well classified using the PALSAR data. C-band data were needed to accurately classify low biomass crops. With a multifrequency data set, an overall accuracy of 88.7% was reached, and many individual crops were classified to accuracies better than 90%. These results were competitive with the overall accuracy achieved using three Landsat images (88.0%). L-band parameters derived from three decomposition approaches (Cloude-Pottier, FreemanDurden, and Krogager) produced superior crop classification accuracies relative to those achieved using the linear polarizations. Using the Krogager decomposition parameters from all three PALSAR acquisitions, an overall accuracy of 77.2% was achieved. These results emphasize the value of polarimetric, as well as multifrequency SAR, data for crop classification. With such a diverse capability, a SAR-only approach to crop classification becomes increasingly viable.

On the Added Value of Quad-Pol Data in a Multi-Temporal Crop Classification Framework Based on RADARSAT-2 Imagery

“…Although previous studies demonstrated the benefits of quad-pol data compared to single or dual-pol configurations for crop classification when just one acquisition date was available [22,42], when multi-temporal configurations were tested these differences were minor [8,43]. In fact, some studies [44,45] reported high classification accuracies with just three scenes acquired in key dates in dual-pol configurations, in coincidence with our results. Therefore, it seems that rather than a single-date quad-pol dataset, a multi-date dual-pol option provides enhanced crop classification accuracies.…”

A Framework for Defining Spatially Explicit Earth Observation Requirements for a Global Agricultural Monitoring Initiative (GEOGLAM)

“…In areas with persistent and pervasive cloud occultation, the costs may outweigh the benefits for monitoring with optical data. SAR data algorithms are currently being prototyped and analyzed for operational monitoring applications [57,64,[95][96][97].…”

Scattering Mechanism Extraction by a Modified Cloude-Pottier Decomposition for Dual Polarization SAR

“…Cloude and Pottier calculated an entropy H and an angle α and then linearly separated the H-α plane into nine zones within a feasible region to determine the basic scattering mechanisms. In recent years, Cloude-Pottier decomposition has been analyzed, improved, and widely applied in segmentation, classification, and detection applications [17][18][19][20][21][22][23][24][25][26][27][28][29][30].…”