摘要：We describe a new minimum extent, persistent surface water classification for reaches offour major rivers in the Peruvian Amazon (i.e., Amazon, Napo, Pastaza, Ucayali). These data weregenerated by the Peruvian Amazon Rural Livelihoods and Poverty (PARLAP) Project which aims tobetter understand the nexus between livelihoods (e.g., fishing, agriculture, forest use, trade), poverty,and conservation in the Peruvian Amazon over a 35,000 km river network. Previous surface waterdatasets do not adequately capture the temporal changes in the course of the rivers, nor discriminatebetween primary main channel and non-main channel (e.g., oxbow lakes) water. We generatedthe surface water classifications in Google Earth Engine from Landsat TM 5, 7 ETM+, and 8 OLIsatellite imagery for time periods from circa 1989, 2000, and 2015 using a hierarchical logical binaryclassification predominantly based on a modified Normalized Difference Water Index (mNDWI)and shortwave infrared surface reflectance. We included surface reflectance in the blue band andbrightness temperature to minimize misclassification. High accuracies were achieved for all timeperiods (>90%).
