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GHSL: Tinggi bangunan global 2018 (P2023A)
Set data raster spasial ini menggambarkan distribusi global tinggi bangunan pada resolusi 100 m, yang merujuk pada tahun 2018. Data input yang digunakan untuk memprediksi ketinggian bangunan adalah ALOS Global Digital Surface Model (30 m), NASA Shuttle Radar Topographic Mission … alos building built built-environment builtup copernicus -
GHSL: Permukaan bangunan global 10 m (P2023A)
Set data raster ini menggambarkan distribusi permukaan bangunan, yang dinyatakan dalam meter persegi per sel petak 10 m, untuk tahun 2018 seperti yang diamati dari data gambar S2. Set data mengukur: a) total permukaan bangunan, dan b) permukaan bangunan yang dialokasikan ke sel petak … built built-environment builtup copernicus ghsl jrc -
GHSL: Permukaan bangunan global 1975-2030 (P2023A)
Set data raster ini menggambarkan distribusi permukaan bangunan, yang dinyatakan dalam meter persegi per sel petak 100 m. Set data ini mengukur: a) total permukaan bangunan, dan b) permukaan bangunan yang dialokasikan ke sel petak dengan penggunaan non-perumahan (NRES) yang dominan. Data diinterpolasi secara spasial-temporal atau … built built-environment builtup copernicus ghsl jrc -
GHSL: Karakteristik penyelesaian global (10 m) 2018 (P2023A)
Set data raster spasial ini menggambarkan pemukiman manusia dengan resolusi 10 m, dan menjelaskan karakteristik dalamnya dalam hal komponen fungsional dan terkait ketinggian dari lingkungan buatan. Informasi selengkapnya tentang produk data GHSL dapat ditemukan dalam laporan Paket Data GHSL 2023 … building built builtup copernicus ghsl height -
Tsinghua FROM-GLC Tahun Perubahan ke Permukaan yang Tidak Tembus Air
Set data ini berisi informasi perubahan tahunan area permukaan kedap air global dari tahun 1985 hingga 2018 pada resolusi 30 m. Perubahan dari pervious menjadi impervious ditentukan menggunakan pendekatan gabungan dari klasifikasi tersupervisi dan pemeriksaan konsistensi temporal. Piksel kedap air didefinisikan sebagai lebih dari 50% kedap air. … built population tsinghua urban
Datasets tagged built in Earth Engine
[null,null,[],[[["\u003cp\u003eThe Global Human Settlement Layer (GHSL) provides datasets characterizing human settlements, including building heights and built-up surfaces, at resolutions ranging from 10m to 100m.\u003c/p\u003e\n"],["\u003cp\u003eGHSL data utilizes various sources like ALOS, SRTM, and Sentinel-2 imagery to model built environments and their functional components.\u003c/p\u003e\n"],["\u003cp\u003eBuilt-up surface datasets within GHSL offer insights into total and non-residential built areas, spanning multiple years and resolutions.\u003c/p\u003e\n"],["\u003cp\u003eThe Tsinghua FROM-GLC dataset provides insights into annual impervious surface changes globally from 1985 to 2018 at a 30m resolution.\u003c/p\u003e\n"]]],[],null,["# Datasets tagged built in Earth Engine\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global building height 2018 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_H) |\n | This spatial raster dataset depicts the global distribution of building heights at a resolution of 100 m, referred to the year 2018. The input data used to predict building heights are the ALOS Global Digital Surface Model (30 m), the NASA Shuttle Radar Topographic Mission ... |\n | [alos](/earth-engine/datasets/tags/alos) [building](/earth-engine/datasets/tags/building) [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) |\n\n-\n\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global built-up surface 10m (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S_10m) |\n | This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 10 m grid cell, for 2018 as observed from the S2 image data. The datasets measure: a) the total built-up surface, and b) the built-up surface allocated to grid cells of ... |\n | [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) |\n\n-\n\n |--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global built-up surface 1975-2030 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S) |\n | This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 100 m grid cell. The dataset measures: a) the total built-up surface, and b) the built-up surface allocated to grid cells of predominant non-residential (NRES) use. Data are spatially-temporally interpolated or ... |\n | [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) |\n\n-\n\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global settlement characteristics (10 m) 2018 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_C) |\n | This spatial raster dataset delineates human settlements at 10 m resolution, and describes their inner characteristics in terms of the functional and height-related components of the built environment. More information about the GHSL data products can be found in the GHSL Data Package 2023 report ... |\n | [building](/earth-engine/datasets/tags/building) [built](/earth-engine/datasets/tags/built) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [ghsl](/earth-engine/datasets/tags/ghsl) [height](/earth-engine/datasets/tags/height) |\n\n-\n\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### Tsinghua FROM-GLC Year of Change to Impervious Surface](/earth-engine/datasets/catalog/Tsinghua_FROM-GLC_GAIA_v10) |\n | This dataset contains annual change information of global impervious surface area from 1985 to 2018 at a 30m resolution. Change from pervious to impervious was determined using a combined approach of supervised classification and temporal consistency checking. Impervious pixels are defined as above 50% impervious. ... |\n | [built](/earth-engine/datasets/tags/built) [population](/earth-engine/datasets/tags/population) [tsinghua](/earth-engine/datasets/tags/tsinghua) [urban](/earth-engine/datasets/tags/urban) |"]]