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Land management map of the Russian Federation (2020)

ロシア連邦の土地管理マップ（2020年） (AI 翻訳)

Shchepashchenko, Maria, Korotkov, Vladimir, Vladimirova, Nadezda, Shvidenko, Anatoly, Karminov, Viktor, Schepaschenko, Dmitry

Zenodoデータセット2026-08-10#炭素会計Origin: Global
DOI: 10.5281/zenodo.21872180
原典: https://zenodo.org/records/21872180

🤖 gxceed AI 要約

日本語

本データセットは、ロシアの管理地・非管理地を空間的に区分し、UNFCCCの国家GHGインベントリ報告とリモートセンシングデータの整合を支援する。ESA WorldCover等を基に、森林、草地、湿地、水域等を分類し、管理地は約9.4億ha（国土の56%）と推定。100m解像度のラスターデータを提供する。

English

This dataset spatially delineates managed and unmanaged land in Russia for 2020, supporting consistency between spatial datasets and national GHG inventory reporting under UNFCCC. Using ESA WorldCover and auxiliary data, it classifies land categories, estimating managed land at 940 million ha (56% of territory). Provided as a 100m resolution raster.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本ではSSBJ開示やGHGインベントリの精緻化が進む中、土地利用の空間的区分はScope 1排出量の算定精度向上に寄与する。本データセットの手法は、日本の森林・農地管理における排出量推定の参考となる。

In the global GX context

Globally, this dataset addresses the critical need for consistency between remote sensing and national GHG inventories, a key issue under UNFCCC and Paris Agreement transparency frameworks. Its methodology for classifying managed land can inform similar efforts in other countries, including those aligning with ISSB and CSRD disclosure requirements.

👥 読者別の含意

🔬研究者:Provides a replicable method for spatial delineation of managed land to improve GHG inventory accuracy.

🏢実務担当者:Useful for companies with Russian operations to understand land-use emissions and align with reporting standards.

🏛政策担当者:Highlights the importance of spatial data consistency for national GHG reporting and climate commitments.

📄 Abstract（原文）

Description The spatial delineation of managed and unmanaged land is essential for ensuring consistency between spatial datasets (e.g. remote sensing products and atmospheric greenhouse gas inversions) and national GHG inventory reporting under the UNFCCC. According to the recent National Inventory Document (NID, 2025), managed land in Russian Federation accounts for 940 million ha, or 56% of the total land area. This dataset provides a spatially explicit delineation of managed and unmanaged land across Russia for the year 2020. It is specifically designed to support comparison between spatial datasets and national inventory reporting. The classification is based on a combination of global land cover products and auxiliary datasets. The ESA WorldCover 2021 dataset (Zanaga et al., 2022) was used as the base land cover map.   Methodology Unmanaged land was identified based on the following criteria: Forests without management plans (155.5 million ha, NID, 2025) Delineated based on regional forest management plan data (HCVF, 2025). Natural grasslands (18.2 million ha) Derived from ESA WorldCover grassland class (class 20), excluding managed grasslands using Global Pasture Watch (Parente et al., 2025). Undisturbed wetlands (including inner waters: 226.5 million ha) Identified from ESA WorldCover wetland-related classes (class 90), as well as grasslands and shrublands (classes 20 and 30) consistent with national wetland map (Schepaschenko, Shvidenko, 2026). Managed and modified areas were excluded using WPC (2026). Natural water bodies Derived from ESA WorldCover (class 80), excluding reservoirs identified using the Global Dam Watch database (GDW, 2024). Other unmanaged land (359.5 million ha), Including: Bare land, snow, and ice (ESA WorldCover classes 60, 70) Tundra ecosystems (ESA WorldCover classes 20, 30, 100), excluding managed grasslands (Parente et al., 2025) Abandoned afforested land , defined as forest cover (class 10) on previously abandoned cropland (Lesiv et al., 2018) All remaining areas were classified as managed land . Additional adjustments were applied: Mining areas (Maus et al., 2020) were classified as managed land Bare land adjacent to built-up areas was also assigned to managed land Output Data The final product is land management classification and a binary raster mask of managed and unmanaged land in the Russian Federation for the year 2020. The dataset is provided at a spatial resolution of approximately 100 m (0.000833 degrees) in the WGS 84 geographic coordinate system.    References GDW (2024). Global Dam Watch Database. https://doi.org/10.6084/m9.figshare.25988293 HCVF (2025). High Conservation Value Forests. https://hcvf.ru/ru/documents_old Parente, L. et al. (2025). Global Pasture Watch – Annual grassland class and extent maps (2000–2024) (v2-beta). Zenodo. https://doi.org/10.5281/zenodo.15648551 Lesiv, M. et al. (2018). Spatial distribution of arable and abandoned land across former Soviet Union countries. Scientific Data , 5, e180056. https://doi.org/10.1038/sdata.2018.56 Maus, V., Giljum, S., Gutschlhofer, J. et al. A global-scale data set of mining areas. Sci Data 7 , 289 (2020). https://doi.org/10.1038/s41597-020-00624-w NID (2025). National Inventory Document. Russian Federation. https://unfccc.int/documents/646536 WPC (2026). Drained peatland dataset. NGO Wildfire Prevention Center https://peatfires.nextgis.com/resource/5/display Schepaschenko, D., & Shvidenko, A. (2026). Land cover for Russia 2010 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18630207 . Zanaga, D. et al. (2022). ESA WorldCover 10 m 2021 v200. https://doi.org/10.5281/zenodo.7254221

🔗 Provenance — このレコードを発見したソース

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。