Google Earth Engine ——美国LANDIFRE火灾数据集LANDFIRE MFRI (Mean Fire Return Interval) v1.2.0数据集内包含多种数据要素
LANDFIRE (LF), Landscape Fire and Resource Management Planning Tools, is a shared program between the wildland fire management programs of the U.S. Department of Agriculture's Forest Service, U.S. De....

Google Earth Engine ——美国LANDIFRE火灾数据集LANDFIRE/Fire/PLS/v1_2_0数据集内包含多种数据要素
LANDFIRE (LF), Landscape Fire and Resource Management Planning Tools, is a shared program between the wildland fire management programs of the U.S. Department of Agriculture's Forest Service, U.S. De....

Google Earth Engine ——2017-2018年伊朗土地覆盖/土地利用数据集KNTU/LiDARLab/IranLandCover/V1
The Iran-wide land cover map was generated by processing Sentinel imagery within the Google Earth Engine Cloud platform. For this purpose, over 2,500 Sentinel-1 and over 11,000 Sentinel-2 images were....

Google Earth Engine ——美国LANDIFRE植被数据集包括。生物物理设置(BPS)环境场地潜力(ESP)现有植被冠层(EVC)现有植被高度(EVH)现有植被类型(EVT)数据集
Google Earth Engine ——美国LANDIFRE植被数据集包括。生物物理设置(BPS)环境场地潜力(ESP)现有植被冠层(EVC)现有植被高度(EVH)现有植被类型(EVT)数据集

Google Earth Engine ——ALOS World 3D - 30m (AW3D30) 是一个全球数字表面模型 (DSM) 数据集
ALOS World 3D - 30m (AW3D30) is a global digital surface model (DSM) dataset with a horizontal resolution of approximately 30 meters (1 arcsec mesh). The dataset is based on the DSM dataset (5-meter ....

Google Earth Engine ——2001-2017年非洲土壤深度 0-20 厘米和 20-50 厘米的可提取铁,预测平均值和标准偏差数据集
iSDAsoil Extractable IronExtractable iron at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation.Pixel values must be back-transformed with exp(x/10)-1.In areas of dense jungle....

Google Earth Engine ——2001-2017年使用坡度、化学和物理土壤特性得出的土壤肥力能力分类,预测平均值和标准偏差数据集
iSDAsoil Fertility Capability ClassificationSoil fertility capability classification derived using slope, chemical, and physical soil properties. For more information about this layer, please visit t....

Google Earth Engine ——2001-2017年非洲土壤深度 0-20 厘米和 20-50 厘米的可提取粘土含量,预测平均值和标准偏差数据集
Clay content at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation.In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artefacts such....

Google Earth Engine ——2001-2017年非洲土壤深度 0-20 厘米和 20-50 厘米的可提取阳离子交换容量,预测平均值和标准偏差数据集
Effective Cation Exchange Capacity predicted mean and standard deviation at soil depths of 0-20 cm and 20-50 cm,Pixel values must be back-transformed with exp(x/10)-1.In areas of dense jungle (genera....

Google Earth Engine ——Gridded Surface Meteorological 数据集提供了 1979 年以来美国本土的温度、降水、风、湿度和辐射的高空间分辨率(~4 公里)
GRIDMET: University of Idaho Gridded Surface Meteorological DatasetThe Gridded Surface Meteorological dataset provides high spatial resolution (~4-km) daily surface fields of temperature, precipitati....

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