Investigating the performance of Random Forest and Support Vector Regression for generation of cloudfree NDVI using Sentinel-1 SAR data

Presenter(s): Jayantrao MOHITE

Jayantrao MOHITE

Investigating the performance of Random Forest and Support Vector Regression for generation of cloudfree NDVI using Sentinel-1 SAR data
Corresponding paper: INVESTIGATING THE PERFORMANCE OF RANDOM FOREST AND SUPPORT VECTOR REGRESSION FOR ESTIMATION OF CLOUD-FREE NDVI USING SENTINEL-1 SAR DATA
Auhor(s): J. D. Mohite, S. A. Sawant, A. Pandit, and S. Pappula
Volume: Archives XLIII-B3-2020 / 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1379-2020

The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.

Useful Links

Useful External Links

Our Contact

ISPRS
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org