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WRI/Google DeepMind、Global Drivers of Forest Loss 2001-2022 v1.0
このデータセットは、2001 ~ 2022 年の樹木被覆喪失の主な要因を 1 km の解像度で世界地図上に示しています。World Resources Institute(WRI)と Google DeepMind が作成したこのデータは、収集された一連のサンプルでトレーニングされたグローバル ニューラル ネットワーク モデル(ResNet)を使用して開発されました。 agriculture deforestation forest forest-biomass google landandcarbon -
WRI/Google DeepMind グローバル ドライバ オブ フォレスト ロス 2001-2023 v1.1
このデータセットは、2001 ~ 2023 年の樹木被覆喪失の主な要因を 1 km の解像度で世界地図上に示しています。World Resources Institute(WRI)と Google DeepMind が作成したこのデータは、収集された一連のサンプルでトレーニングされたグローバル ニューラル ネットワーク モデル(ResNet)を使用して開発されました。 agriculture deforestation forest forest-biomass google landandcarbon -
WRI/Google DeepMind、Global Drivers of Forest Loss 2001-2024 v1.2
このデータセットは、2001 ~ 2024 年の樹木被覆喪失の主な要因を 1 km の解像度で世界地図上に示しています。World Resources Institute(WRI)と Google DeepMind が作成したこのデータは、収集された一連のサンプルでトレーニングされたグローバル ニューラル ネットワーク モデル(ResNet)を使用して開発されました。 agriculture deforestation forest forest-biomass google landandcarbon
Datasets tagged landandcarbon in Earth Engine
[null,null,[],[],[],null,["# Datasets tagged landandcarbon in Earth Engine\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2022 v1.0](/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2001_2022) |\n | This dataset maps the dominant driver of tree cover loss from 2001-2022 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... |\n | [agriculture](/earth-engine/datasets/tags/agriculture) [deforestation](/earth-engine/datasets/tags/deforestation) [forest](/earth-engine/datasets/tags/forest) [forest-biomass](/earth-engine/datasets/tags/forest-biomass) [google](/earth-engine/datasets/tags/google) [landandcarbon](/earth-engine/datasets/tags/landandcarbon) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2023 v1.1](/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_1_2001_2023) |\n | This dataset maps the dominant driver of tree cover loss from 2001-2023 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... |\n | [agriculture](/earth-engine/datasets/tags/agriculture) [deforestation](/earth-engine/datasets/tags/deforestation) [forest](/earth-engine/datasets/tags/forest) [forest-biomass](/earth-engine/datasets/tags/forest-biomass) [google](/earth-engine/datasets/tags/google) [landandcarbon](/earth-engine/datasets/tags/landandcarbon) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### WRI/Google DeepMind Global Drivers of Forest Loss 2001-2024 v1.2](/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2_2001_2024) |\n | This dataset maps the dominant driver of tree cover loss from 2001-2024 globally at 1 km resolution. Produced by the World Resources Institute (WRI) and Google DeepMind, the data were developed using a global neural network model (ResNet) trained on a set of samples collected ... |\n | [agriculture](/earth-engine/datasets/tags/agriculture) [deforestation](/earth-engine/datasets/tags/deforestation) [forest](/earth-engine/datasets/tags/forest) [forest-biomass](/earth-engine/datasets/tags/forest-biomass) [google](/earth-engine/datasets/tags/google) [landandcarbon](/earth-engine/datasets/tags/landandcarbon) |"]]