欢迎访问《生态学杂志》官方网站,今天是 分享到:

生态学杂志 ›› 2020, Vol. 39 ›› Issue (11): 3881-3889.doi: 10.13292/j.1000-4890.202011.020

• 技术与方法 • 上一篇    下一篇

多源土地覆被数据类别一致性及景观格局差异性——以京津冀区域为例

邵明超1,宋宏利1,2,3*,尚明1,3,何洪涛1,史宜梦1   

  1. (1河北工程大学地球科学与工程学院, 河北邯郸 056038;2河北省煤炭资源综合开发与利用协同创新中心, 河北邯郸 056038;3邯郸市自然资源空间信息重点实验室, 河北邯郸 056038)
  • 出版日期:2020-11-11 发布日期:2021-05-10

Multisource land-cover data category accuracy evaluation and the difference of landscape patterns: A case study of Beijing-Tianjin-Hebei region.

SHAO Ming-chao1, SONG Hong-li1,2,3*, SHANG Ming1,3, HE Hong-tao1, SHI Yi-meng1     

  1. (1College of Geosciences and Engineering, Hebei University of Engineering, Handan 056038, Hebei, China; 2Collaborative Innovation Center for Comprehensive Development and Utilization of Coal Resources in Hebei Province, Handan 056038, Hebei, China; 3Key Laboratory of Natural Resources and Spatial Information, Handan 056038, Hebei, China).
  • Online:2020-11-11 Published:2021-05-10

摘要: 土地覆被遥感数据是大尺度景观格局研究的基础信息。然而不同的土地覆被数据来自于不同的科研团队,采用不同的数据源及分类方法,导致其对于景观格局研究结果具有差异性,因此定量分析土地覆被数据一致性及其对景观格局研究的影响具有重要意义。本研究以当前2套全球尺度30 m分辨率的土地覆被遥感数据GlobeLand30和FROM-GLC为对象,从土地覆被类别及景观格局指数两个角度对比分析了二者在京津冀不同水土保持区的差异。结果表明:(1)在太行山东部山地丘陵水源涵养保土区,二者的面积一致性最大,一致性值为96.8%,在太行山西北部山地丘陵防沙水源涵养区二者的面积一致性最低,其数值仅为3.6%;(2)两数据集在津冀鲁渤海湾生态维护区空间的一致性最高,其空间一致性值为73.6%,在太行山西北部山地丘陵防沙水源涵养区空间的一致性最低,其值为25.17%;(3)在景观格局上,GlobeLand30数据集在京津冀6个生态功能区的复杂程度均小于FROM-GLC数据集,说明GlobeLand30数据景观多样性较低,地表景观类别均质性较强,而FROM-GLC数据的地表景观异质性较强,破碎化程度较高。

关键词: GlobeLand30数据, FROM-GLC数据, 一致性, 景观格局
 

Abstract: Remote sensing data of land cover is the basic information for largescale landscape pattern research. Land-cover data from different research teams adopt different data sources and classification methods, which leads to inconsistent results of landscape pattern research. Quantitative analysis of the consistency of land-cover data and its impacts on landscape pattern research is of great significance. Here, with two sets of global scale 30m resolution landcover remote sensing data GlobeLand30 and FROM-GLC as the research objects, we compared their differences in soil and water conservation areas in Beijing-Tianji-Hebei Region from two aspects of landcover type and landscape pattern index. The results showed that: (1) In the mountainous and hilly water conservation and soil conservation region in the eastern part of Taihang Mountains, theagreement in area size between the two datasets was the highest, with a consistency value of 96.8%. By contrast, the consistency was the lowest in the mountainous and hilly sand control and water conservation region in the northwestern Taihang Mountains, with a value of 3.6%; (2) The spatial consistency of those two datasets in the Jin-Yi-Lu Bohai Bay ecological maintenance area was the highest, with a spatial consistency value of 73.6%. In the mountainous and hilly area of the northwestern Taihang Mountains, the spatial consistency of sand control and water conservation area was the lowest, with a value of 25.17%; (3) In terms of landscape pattern, the complexity of GlobeLand30 dataset in the six ecological functional areas of BeijingTianjinHebei was lower than that of the FROM-GLC dataset, indicating that diversity of landscape in GlobeLand30 dataset was lower, and homogeneity of surface landscape categories was stronger, while surface landscape heterogeneity and fragmentation degree of FROM-GLC dataset were stronger.

Key words: GlobeLand30 data, FROM-GLC data, consistency, landscape pattern.