A higher accuracy forest cover product of China by fusing heterogeneous forest-related datasets using Dempster-Shafer theory

IF 3.7 1区地球科学 Q1 GEOGRAPHY, PHYSICAL

International Journal of Digital Earth Pub Date : 2024-06-25 DOI:10.1080/17538947.2024.2368706

Xueli Peng, Guojin He, Tengfei Long, Ranyu Yin, Guizhou Wang, Jianping Wang

引用次数: 0

Abstract

Forests are of vital importance in maintaining the balance of ecosystems, and accurate forest cover maps provide basic data for research. Existing forest cover products suffer from substantial disc...

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利用 Dempster-Shafer 理论融合异构森林相关数据集，获得精度更高的中国森林覆盖率产品

森林对维持生态系统的平衡至关重要，准确的森林覆盖图为研究提供了基础数据。现有的森林植被产品存在大量不一致的地方......

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Digital Earth 地学-遥感

CiteScore

6.50

自引率

3.90%

发文量

审稿时长

3 months

期刊介绍： The International Journal of Digital Earth is a response to this initiative. This peer-reviewed academic journal (SCI-E) focuses on the theories, technologies, applications, and societal implications of Digital Earth and those visionary concepts that will enable a modeled virtual world. The journal encourages papers that: Progress visions for Digital Earth frameworks, policies, and standards; Explore geographically referenced 3D, 4D, or 5D models to represent the real planet, and geo-data-intensive science and discovery; Develop methods that turn all forms of geo-referenced data, from scientific to social, into useful information that can be analyzed, visualized, and shared; Present innovative, operational applications and pilots of Digital Earth technologies at a local, national, regional, and global level; Expand the role of Digital Earth in the fields of Earth science, including climate change, adaptation and health related issues,natural disasters, new energy sources, agricultural and food security, and urban planning; Foster the use of web-based public-domain platforms, social networks, and location-based services for the sharing of digital data, models, and information about the virtual Earth; and Explore the role of social media and citizen-provided data in generating geo-referenced information in the spatial sciences and technologies.