## Appendix A  
All the abbreviations in this paper are listed below, in Table A1.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Abbreviation** & **Full Term** & **Meaning** \\ \hline AWS & Amazon Web Services & The cloud platform that was developed by Amazon to handle remote-sensing big data. \\ CART & Classification and regression tree & One of the decision tree classification algorithms. \\ CCD & Charge coupled device & The optical sensors for remote-sensing image acquisition. \\ CHEOS & China’s High-Resolution Earth & A Chinese earth observation system for the acquisition of high-resolution remote-sensing images. \\ CODE-DE & Copernicus Data and Exploitation & The cloud platform that was developed by Germany to handle remote-sensing big data. \\ DEM & Digital elevation model & A model that demonstrates the elevation of the Earth’s surface. \\ DN & Digital number & The pixel value in a remote-sensing image. \\ DT & Decision tree & One of the machine-learning algorithms. \\ ENVI & Environment for visualizing images & The name of a type of software for remote-sensing image analysis, which was developed by Harris Corporation in Melbourne, Florida, USA. \\ EVI & Enhanced vegetation index & The index that demonstrates vegetation in optical remote-sensing images. \\ FLAASH & Fast Line-of-sight Atmospheric & The atmospheric correction algorithm \\ Analysis of Spectral Hypercubes & Analysis of Spectral Hypercubes & model. \\ GEE & Google Earth Engine & The platform used to process remote-sensing data online, which was developed by Google in the United States. \\ GF & GaoFen & The name of a Chinese high-resolution satellite. \\ GIS & geographic information system & The computer program used for the analysis of spatial information. \\ GPS & global navigation and positioning & The global navigation and positioning developed by the United States. \\ GTC & Geocoded terrain correction & One of the geo-correction methods for SAR remote-sensing images. \\ Kappa & Kappa coefficient & A value to quantitatively assess the accuracy of a classification. \\ MS & Multispectral & A type of optical remote-sensing image. \\ MVN & Mean value of NRCS & A statistic value that demonstrates the mean value of an NRCS. \\ NDMRI & Normalized difference metal rooftop & The index that demonstrates metal \\  & index & rootops in optical remote-sensing images. \\ NDVI & Normalized difference vegetation & The index that demonstrates vegetation \\  & index & in optical remote-sensing images. \\ NDWI & Normalized difference water index & The index that demonstrates water in optical remote-sensing images. \\ NEX & NASA Earth Exchange & The cloud platform that was developed by NASA in the United States to handle remote-sensing big data. \\ NIR & Near infrared & The name for a specific spectrum. \\ NRCS & Normalized radar cross section & The parameter that is used to depict the capability of a target on the Earth to reflect the incidence of electromagnetic waves of radar. \\ OA & Overall accuracy & The statistical parameter that is used to demonstrate classification accuracy. \\ PA & Producer’s accuracy & The statistical parameter that is used to demonstrate the classification accuracy. \\ PAN & Panchromatic & A type of optical remote-sensing image. \\ PIE & Pixel information expert & The cloud platform that was developed by PIESAT Group Inc. in China to handle remote-sensing big data. \\ \hline \hline \end{tabular}
\end{table}
Table A1: The meaning of abbreviations used in this investigation.