Abstract
The spatial consistency of low-resolution multi-source remote sensing data is of great importance for their combination in global change research. Currently, many methods are developed for the precise geometric correction of single kind of low-resolution data. However, the spatial consistency correction method is still need to be developed when many different kinds of low-resolution sensors' data are taken into consideration altogether, which is aimed to make their spectral data become consistent in geo-location. MODIS surface reflectance products, as they are of high accuracy of geo-location and data quality among low-resolution data, the spectral data of the multi-source low-resolution sensors are corrected to be consistency with it, which contain the level 1B data of NOAA/AVHRR, FY-3/VIRR, FY-3/MERSI, FY-2/VISSR. The proposed method in this paper can conducted spatial consistency correction on multi-source low-resolution remote sensing data precisely, efficiently, and automatically, which is based on contour point coarse matching and contour precise matching.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.