Unveiling spatiotemporal tree cover patterns in China: The first 30 m annual tree cover mapping from 1985 to 2023

IF 10.6 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL
Yaotong Cai , Xiaocong Xu , Peng Zhu , Sheng Nie , Cheng Wang , Yujiu Xiong , Xiaoping Liu
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引用次数: 0

Abstract

China leads in the greening of the world, with a nearly doubled increase in its forest area since the 1980 s revealed by the National Forest Inventory (NFI). However, a significant challenge persists in the absence of consistent and reliable remote sensing data that align with the NFI, hindering a comprehensive understanding of the spatiotemporal patterns of terrestrial ecosystem changes driven by afforestation and reforestation efforts over recent decades in China. Moreover, conventional binary thematic maps and land use and land cover (LULC) maps encounter difficulties in providing a thorough assessment of canopy cover at the subpixel level and trees extending beyond officially designated forest boundaries. This limitation creates substantial gaps in our comprehension of their invaluable contributions to ecosystem services. To confront these challenges, this study presents a systematic framework integrating time-series Landsat satellite imagery and random forest-based ensemble learning techniques. This framework aims to generate China’s inaugural annual tree cover dataset (CATCD) spanning from 1985 to 2023 at a 30 m spatial resolution. Evaluation against multisource reference data shown high correlations ranging from 0.70 to 0.96 and reasonable RMSE values ranging from 5.6 % to 25.2 %, highlighting the reliability and precision of our approach across different years and data collection methodologies. Our analysis reveals that China’s forested area has doubled, expanding from 1.04 million km2 in 1985 to 2.10 million km2 in 2023. Notably, 33 % of this growth can be attributed to a shift from non-forest to forest land categories, primarily observed in the three-north and southwest regions. However, the majority, contributing 67 %, results primarily from crown closure in central and southern China. This realization underscores the limitations of conventional binary thematic maps and LULC maps in accurately quantifying forest gain in China. Furthermore, China’s tree population structure has undergone a transformative shift from 83 % forest trees and 17 % non-forest trees in 1985 to 92 % forest trees and 8 % non-forest trees in 2023, signifying a transition from afforestation to established forests. Our study not only enhances the understanding of tree cover variations in China but also provides valuable data for ecological investigations, land management strategies, and assessments related to climate change.

揭示中国树木覆盖的时空格局:首次绘制1985-2023年30米年树木覆盖图
国家森林资源清查(NFI)显示,自 20 世纪 80 年代以来,中国的森林面积增加了近一倍,在世界绿化进程中居于领先地位。然而,由于缺乏与《国家森林资源清查》相一致的可靠遥感数据,全面了解中国近几十年来植树造林和重新造林所导致的陆地生态系统变化的时空模式成为一大挑战。此外,传统的二元专题地图和土地利用与土地覆盖(LULC)地图在提供亚像素级树冠覆盖和官方指定森林边界以外树木的全面评估方面也存在困难。这种局限性使我们在理解它们对生态系统服务的宝贵贡献方面存在巨大差距。为了应对这些挑战,本研究提出了一个整合时间序列大地卫星图像和基于随机森林的集合学习技术的系统框架。该框架旨在生成中国首个年度树木覆盖数据集(CATCD),时间跨度为 1985 年至 2023 年,空间分辨率为 30 米。根据多源参考数据进行的评估显示,相关性从 0.70 到 0.96 不等,均方根误差值从 5.6 % 到 25.2 % 不等,显示了我们的方法在不同年份和数据收集方法中的可靠性和精确性。我们的分析显示,中国的森林面积翻了一番,从 1985 年的 104 万平方公里扩大到 2023 年的 210 万平方公里。值得注意的是,33% 的增长可归因于非林地向林地类别的转变,这主要体现在三北和西南地区。不过,67%的增长主要来自华中和华南地区的树冠郁闭。这凸显了传统二元专题地图和 LULC 地图在准确量化中国森林增量方面的局限性。此外,中国的树木种群结构发生了转变,从 1985 年的 83% 林地和 17% 非林地树木转变为 2023 年的 92% 林地和 8% 非林地树木,这标志着从植树造林向人工林的过渡。我们的研究不仅加深了对中国林木覆盖率变化的理解,还为生态调查、土地管理策略和气候变化相关评估提供了宝贵数据。
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
ISPRS Journal of Photogrammetry and Remote Sensing
ISPRS Journal of Photogrammetry and Remote Sensing 工程技术-成像科学与照相技术
CiteScore
21.00
自引率
6.30%
发文量
273
审稿时长
40 days
期刊介绍: The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive. P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields. In particular, P&RS encourages the submission of papers that are of broad scientific interest, showcase innovative applications (especially in emerging fields), have an interdisciplinary focus, discuss topics that have received limited attention in P&RS or related journals, or explore new directions in scientific or professional realms. It is preferred that theoretical papers include practical applications, while papers focusing on systems and applications should include a theoretical background.
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