Synthetic aperture radar (SAR), with all-day and all-weather observation capabilities, can
capture the phenology of crops with short growth cycles to improve land cover classification …

Agriculture is an important sector in Canada, and annual crop inventories are required in
many agricultural applications. Multi-temporal polarimetric synthetic aperture radar (SAR) …

We have investigated multi-temporal polarimetric synthetic aperture radar (SAR) data for
urban land-cover classification using an object-based support vector machine (SVM) in …

Traditional pixel-based classification methods yield poor results when applied to synthetic
aperture radar (SAR) imagery because of the presence of the speckle and limited spectral …

Land cover classification is one of the most important applications of polarimetric SAR
images, especially in urban areas. There are numerous features that can be extracted from …

The main objective of this study was to explore the potential of the multi-temporal PolSAR
data in LULC mapping and to evaluate the accuracy of classification using single date and …

Regular land development detection on a short-term basis (monthly or multi-month) has
grown in importance with increasing concern over the impact of rapid urbanization on the …

This study proposes a new four-component algorithm for land use and land cover (LULC)
classification using RADARSAT-2 polarimetric SAR (PolSAR) data. These four components …

Polarimetric SAR (POLSAR) provides a rich set of information about objects on land
surfaces. However, not all information works on land surface classification. This study …

Incidence angle is one of the most important imaging parameters that affect polarimetric
SAR (PolSAR) image classification. Several studies have examined the land cover …