基于深度学习的闽西森林覆盖时空变化特征及驱动因子

Characteristics and Driving Factors of Forest Coverage in Western Fujian Based on Deep Learning

  • 摘要: 森林是陆地生态系统的重要组成部分,探究区域森林覆盖时空变化特征及其驱动因子,可为区域森林资源保护和生态环境可持续发展提供重要指导作用。以福建省龙岩市为研究区域,借助GEE云平台,获取龙岩市2003、2013和2023年卫星遥感影像数据,运用Attention-UNet模型,结合PALSAR FNF标签层分割龙岩市森林与非森林地区,分析龙岩市近20 a森林覆盖时空变化特征,利用地理加权回归方法探讨龙岩市森林覆盖变化驱动因子。结果表明:(1) 采用深度学习Attention-UNet模型结合PALSAR FNF标签层分割龙岩市森林与非森林地区,取得良好的效果,准确率、精确率、召回率和F1分数分别为0.851、0.854、0.851和0.853。(2) 从时间变化来看,龙岩市森林覆盖面积从2003年的13 620.89 km2增至2023年的15 675.44 km2,增加2 054.55 km2。(3) 从空间变化来看,近20 a龙岩市森林覆盖增加的地区占27.5%,主要集中在长汀县中部、永定区南部以及武平县东部和上杭县西部的交界处;减少的地区占6.3%,主要集中在永定区西南部、东北部以及新罗区西南部;龙岩市森林覆盖在空间上呈显著正相关,且存在着空间异质性。(4) 地理加权回归(GWR)结果表明,2003—2023年夜间灯光指数(NL)、地表温度(LST)、降水量(PRE)和饱和蒸汽压差(VPD)对龙岩市森林覆盖产生负向影响,土壤湿度对森林覆盖的影响由2003和2013年的负向影响转为2023年的正向影响。5个驱动因子的回归系数在空间上呈现明显的分异特征,NL对森林覆盖的影响范围随时间推移而缩小,LST对森林覆盖具有显著负向影响的地区主要集中在龙岩市中西部地区。土壤湿度、NL、VPD和PRE是龙岩市森林覆盖增加的主要驱动因子;NL、PRE、LST和土壤湿度是龙岩市森林覆盖减少的主要驱动因子。

     

    Abstract: Forest is an essential component of terrestrial ecosystems. Investigating the spatiotemporal changes in regional forest cover, and the factors driving these changes, can provide critical guidance for the protection of forest resources and the sustainable development of the ecological environment. The research area in this study is Longyan City in Fujian Province. Using the GEE cloud platform, we obtained satellite remote sensing image data for Longyan City for the years 2003, 2013, and 2023. The Attention-UNet model, combined with the PALSAR FNF label layer, was used to segment Longyan City into forested and non-forested areas. We analyzed the spatiotemporal changes in forest cover over the past 20 years and used geographic weighted regression to explore the driving factors of changes in forest cover in Longyan City, resulting in the following conclusions. (1)The deep learning Attention-UNet model, combined with the PALSAR FNF label layer, effectively segmented forested and non-forested areas in Longyan City with accuracy, precision, recall rate, and F1 scores of 0.851, 0.854, 0.851, and 0.853, respectively. (2) Temporally, over the last 20 years, the forest cover area in Longyan City increased from 13 620.89 km2 in 2003 to 15 675.44 km2 in 2023, with an increase of 2 054.55 km2. (3) Spatially, 27.5% of the total area had increased forest cover which was mainly concentrated in the central part of Changting County, the southern part of Yongding District, and the border areas between the eastern part of Wuping County and the western part of Shanghang County. Areas with decreased forest cover accounted for 6.3% of the total area and were primarily located in the southwestern and northeastern parts of Yongding District and the southwestern part of Xinluo District. Forest cover in Longyan City exhibited significantly positive spatial correlation and spatial heterogeneity. (4) GWR results show that from 2003 to 2023, nighttime light (NL), land surface temperature (LST), precipitation (PRE), and vapor pressure deficit (VPD) had negative impacts on forest cover in Longyan City, while soil moisture shifted from a negative influence in 2003 and 2013 to a positive influence in 2023. The regression coefficients of the five driving factors displayed distinct spatial differentiation characteristics. For example, the impact of NL on forest cover decreased over time, and areas with significantly negative impacts of LST on forest cover were mainly concentrated in the central and western regions of Longyan City. Over the past 20 years, soil moisture, NL, VPD, and PRE were the primary drivers of increased forest cover, while NL, PRE, LST, and soil moisture were the main drivers of decreased forest cover. This study provides a scientific basis for achieving forest resource protection and sustainable development.

     

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