2024/02/01 · This study aims to exploit multisource remotely sensed data to improve land cover classification of an area dominated by extensive wetlands.

Abstract: A decision-level fusion method was developed to classify eleven cover types in a sub-arctic ecosystem, including intertidal marsh, tundra heath, ...

Accurate land cover classifications and biophysical estimations derived from remotely sensed data are important to generate map products and provide ...

2024/03/15 · This study aims to exploit multisource remotely sensed data to improve land cover classification of an area dominated by extensive wetlands.

IMPROVING LAND COVER CLASSIFICATION IN SUBARCTIC WETLANDS USING MULTI-SOURCE REMOTELY SENSED DATA. Baoxin Hu, Yongjie Xia, York University, Canada; Glen ...

Thus, the full use of multitemporal and multisource satellite images exhibits promising potential for large-scale classification with detailed wetland types. In ...

Abstract: The goal of this research was to improve wetland classification by fully exploiting multi-source remotely sensed data.

This paper reviews the last 40 years of research and development on North American wetland classification through remote sensing methods.

Our aim is to review the key drivers of boreal forest productivity, assess the models used to estimate carbon dynamics and land cover change, and highlight ...

The blending of boundaries between wetlands and adjacent land covers does not necessarily improve when high spatial resolution remotely sensed data are used.