您好，欢迎访问中国热带农业科学院 机构知识库！
中国热带农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Integrated Analyses of PALSAR and Landsat Imagery Reveal More Agroforests in a Typical Agricultural Production Region, North China Plain

文献类型： 外文期刊

作者： Yang, Zhiqi 1 ; Dong, Jinwei 1 ; Qin, Yuanwei 4 ; Ni, Wenjian 3 ; Zhao, Guosong 1 ; Chen, Wei 3 ; Chen, Bangqian 6 ; Kou, 1 ;

作者机构： 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China

2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China

3.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

4.Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA

5.Univ Oklahoma, Ctr Spatial Anal, Norman, OK 73019 USA

6.Chinese Acad Trop Agr Sci, Rubber Res Inst, Danzhou City 571737, Peoples R China

7.Minist Agr, Danzhou Invest & Expt Stn Trop Crops, Danzhou 571737, Peoples R China

8.Southwest Forestry Univ, Coll Big Data & Intelligence Engn, Kunming 650224, Yunnan, Peoples R China

9.Fudan Univ, Inst Biodivers Sci, Minist Educ, Key Lab Biodivers Sci & Ecol Engn, Shanghai 200438, Peoples R China

关键词： forest mapping; agroforests; Landsat; PALSAR; North China Plain

期刊名称：REMOTE SENSING （ 影响因子：4.848； 五年影响因子：5.353 ）

ISSN： 2072-4292

年卷期： 2018 年 10 卷 9 期

页码：

收录情况： SCI

摘要： As the largest among terrestrial ecosystems, forests are vital to maintaining ecosystem services and regulating regional climate. The area and spatial distribution of trees in densely forested areas have been focused on in the past few decades, while sparse forests in agricultural zones, so-called agroforests or trees outside forests (TOF), have usually been ignored or missed in existing forest mapping efforts, despite their important role in regulating agricultural ecosystems. We combined Landsat and PALSAR data to map forests in a typical agricultural zone in the North China Plain. The resultant map, based on PALSAR and Landsat (PL) data, was also compared with five existing medium resolution (30-100 m) forest maps from PALSAR (JAXA forest map) and Landsat: NLCD-China, GlobeLand30, ChinaCover, and FROM-GLC. The results show that the PL-based forest map has the highest accuracy (overall accuracy of 95 +/- 1% with a 95% confidence interval, and Kappa coefficient of 0.86) compared to those forest maps based on single Landsat or PALSAR data in the North China Plain (overall accuracy ranging from 85 +/- 2% to 92 +/- 1%). All forest maps revealed higher accuracy in densely forested mountainous areas, while the PL-based and JAXA forest maps showed higher accuracy in the plain, as the higher omission errors existed in only the Landsat-based forest maps. Moreover, we found that the PL-based forest map can capture more patched forest information in low forest density areas. This means that the radar data have advantages in capturing forests in the typical agricultural zones, which tend to be missing in published Landsat-based only forest maps. Given the significance of agroforests in regulating ecosystem services of the agricultural ecosystem and improving carbon stock estimation, this study implies that the integration of PALSAR and Landsat data can provide promising agroforest estimates in future forest inventory efforts, targeting a comprehensive understanding of ecosystem services of agroforests and a more accurate carbon budget inventory.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：中国热带农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台