2001—2023年华东地区森林损失的遥感监测与时空特征分析

doi:10.13466/j.cnki.lczyyj.2024.06.007

摘要/Abstract

摘要：

森林损失是当代社会发展的重大威胁之一,探讨华东地区长期的森林损失模式对于森林管理和保护具有重要意义。基于高分辨率森林变化数据集(GFC),采用趋势分析与新兴时空热点分析等空间分析技术,系统分析华东地区森林损失的时空动态特征。结果表明:1)2001—2023年,华东地区森林损失总面积约为382.82万hm²,其中2001—2008年森林损失面积与斑块数量均快速增长,此后则表现为波动性变化。2)将研究区细分为10 km网格统计发现,森林损失主要表现为轻度和中度2种类型,呈现出小规模破碎化的空间分布特征。3)华东地区大部分区域的森林损失整体呈上升趋势,其中安徽省新出现的森林损失热点区域尤为明显。2001—2023年,华东地区的森林面积显著减少,特别是在福建省、江西省和安徽省的部分区域,森林损失以小规模破碎化形式逐年增加,亟需加强森林监测和保护。

关键词: 森林损失, 趋势分析, 新兴时空热点分析, 华东地区

Abstract:

Forest loss is regarded as a significant impediment to contemporary social development.Understanding of the long-term patterns of forest loss in East China is essential for the forest management and conservation.By employing a high-resolution forest change dataset(GFC),this study examined the spatial and temporal dynamics of forest loss patterns in East China.This involved utilising spatial analysis techniques,including trend analysis and analysis of emerging spatiotemporal hotspots.1)From 2001 to 2023,the total area of forest loss in East China was approximately 3,828,200 hm².Both the area of forest loss and the number of patches demonstrated a rapid increase from 2001 to 2008,followed by fluctuating changes.2)Statistical analysis based on 10 km grid divisions revealed that the primary types of forest loss were mild and moderate,characterized by small-scale fragmentation.3)Most regions in East China exhibited an increasing trend in forest loss,with emerging hotspots of forest loss in Anhui Province.Over the past two decades,the forest area in East China has undergone a notable decline,particularly in regions of Fujian,Jiangxi,and Anhui provinces.The observed forest loss exhibits a pattern of small-scale fragmentation and an increasing trend on an annual basis,underscoring the need for enhanced monitoring and protection measures.

Key words: forest loss, tend analysis, analysis of emerging spatiotemporal hotspots, East China

中图分类号:

S718.55

王尚晓, 牛晓楠, 张明, 张洁, 宗乐丽, 周墨, 唐志敏. 2001—2023年华东地区森林损失的遥感监测与时空特征分析[J]. 林草资源研究, 2024,(6): 54-63.

WANG Shangxiao, NIU Xiaonan, ZHANG Ming, ZHANG Jie, ZONG Leli, ZHOU Mo, TANG Zhimin. Remote Sensing Monitoring and Spatiotemporal Characteristics Analysis of Forest Loss in East China from 2001 to 2023[J]. Forest and Grassland Resources Research, 2024,(6): 54-63.

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热点类别	定义
新增热点	最后1个时间步长统计上出现显著性的热点,且在其他时间步长从未出现过显著热点的位置
加强热点	在90%时间步长(包括最后的时间步长)上观察到显著的热点现象。各时间步长内的聚集强度显著增加。
连续热点	在最后一个连续时间步内,观察到2个具有统计显著性的热点,并且在此之前的所有热点运行均未达到统计显著性。
持续热点	在90%以上的时间步长中,具有统计显著性的热点,且在分析期间聚集强度没有明显增减
振荡热点	在最后1个时间步长统计显著的热点,同时在前1个时间步长中存在的显著冷点

区域	减少面积/ hm²	减少面积占比/%	平均减少面积/hm²	最小年份及面积/hm²		最大年份及面积/hm²
区域	减少面积/ hm²	减少面积占比/%	平均减少面积/hm²	年份	面积/hm²	年份	面积/hm²
上海	873.81	0.02	37.99	2002	1.71	2021	154.26
江苏	32 793.21	0.86	1 425.79	2003	124.20	2021	5 672.16
浙江	397 877.04	10.39	17 299.00	2001	4 349.70	2017	31 046.31
安徽	356 839.29	9.32	15 514.75	2003	3 236.04	2023	30 732.03
福建	1 556 672.13	40.33	67 681.40	2001	16 125.84	2011	108 245.16
江西	1 483 149.96	38.74	64 484.78	2001	8 243.37	2023	114 488.01
华东地区	3 828 205.44	100.00	166 443.71	2001	33 245.10	2017	268 153.29

区域	新增热点		震荡热点			持续热点		连续热点			加强热点
区域	面积/10⁴hm²	占比/%	面积/10⁴hm²		占比/%	面积/10⁴hm²	占比/%	面积/10⁴hm²	占比/%		面积/10⁴hm²	占比/%
上海	0	0	0			0	0	0		0	0
江苏	2	10	18	90.00		0	0	0		0	0
浙江	13	5.33	231	94.67		0	0	0		0	0
安徽	91	28	234	72.00		0	0	0		0	0
福建	0	0	788	65.07		184	15.19	28		2.31	211	17.42
江西	19	1.28	1 466	98.72		0	0	0		0	0
华东地区	125	3.81	2 737	83.32		184	5.60	28		0.85	211	6.42