Abstract
Google Earth Engine (GEE) platform is an online tool, which generates fast solutions in terms of image classification and does not require high performance computers locally. We investigate several data input scenarios for mapping native-vegetation and non-native-vegetation in the Atlantic Forest region encompassed in a Landsat scene (224/076) acquired on November 28, 2019. The data input scenarios were: I- spectral bands (blue to shortwave infrared); II- NDVI (Normalized Difference Vegetation Index); III- mNDWI (modified Normalized Difference Water Index); IV- scenarios I and II; and V- scenarios I to III. Our results showed that the use of spectral bands added NDVI and mNDWI (scenario V) provided the best performance for the native-vegetation mapping, with accuracy of 96.64% and kappa index of 0.91.
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Estrabis, N. V., Osco, L., Ramos, A. P., Gonçalves, W. N., Liesenberg, V., Pistori, H., & Marcato Junior, J. (2020). Brazilian midwest native vegetation mapping based on google earth engine. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 42, pp. 303–308). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-303-2020
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