Evaluating combinations of temporally aggregated Sentinel-1, Sentinel-2 and Landsat 8 for land cover mapping with Google Earth Engine
Land cover mapping of large areas is challenging due to the significant volume of satellite
data to acquire and process, as well as the lack of spatial continuity due to cloud cover …
data to acquire and process, as well as the lack of spatial continuity due to cloud cover …
[HTML][HTML] Predicting forest cover in distinct ecosystems: The potential of multi-source Sentinel-1 and-2 data fusion
The fusion of microwave and optical data sets is expected to provide great potential for the
derivation of forest cover around the globe. As Sentinel-1 and Sentinel-2 are now both …
derivation of forest cover around the globe. As Sentinel-1 and Sentinel-2 are now both …
Annual seasonality in Sentinel-1 signal for forest mapping and forest type classification
The Sentinel-1 satellites provide the formerly unprecedented combination of high spatial
and temporal resolution of dual polarization synthetic aperture radar data. The availability of …
and temporal resolution of dual polarization synthetic aperture radar data. The availability of …
Combined use of optical and synthetic aperture radar data for REDD+ applications in Malawi
M Hirschmugl, C Sobe, J Deutscher, M Schardt - Land, 2018 - mdpi.com
Recent developments in satellite data availability allow tropical forest monitoring to expand
in two ways:(1) dense time series foster the development of new methods for mapping and …
in two ways:(1) dense time series foster the development of new methods for mapping and …
[PDF][PDF] Towards the European-Wide Forest Mapping and Classification Using the Sentinel-1 C-Band Synthetic Aperture Radar Data
DIA Dostálová - scholar.archive.org
Forests cover around 38% of the European land surface and are of great economic and
ecological importance. Reliable and frequently updated information on forest resources is …
ecological importance. Reliable and frequently updated information on forest resources is …
Fine Classification Comparsion of GF-1 GF-5 and Landsat-8 Remote Sensing Data Based on Optimized Sample Selection Method
G Yang, L Jiao, W Sun, H Lu, X Meng… - IGARSS 2019-2019 …, 2019 - ieeexplore.ieee.org
This paper aims to compare the performance of GaoFen-1 (GF-1), GaoFen-5 (GF-5),
Landsat-8 data in fine classification. An optimized sample selection method (OSSM) is …
Landsat-8 data in fine classification. An optimized sample selection method (OSSM) is …