An improved method for estimating clumping index in mixed coniferous and broadleaved forests using BRDF shape of surface ecotype as constraints

XIE Rui; JIAO Ziti; DONG Yadong; CUI Lei; YIN Siyang; ZHANG Xiaoning; CHANG Yaxuan; GUO Jing

doi:10.11834/jrs.20211522

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An improved method for estimating clumping index in mixed coniferous and broadleaved forests using BRDF shape of surface ecotype as constraints
“New progress has been made in the study of vegetation canopy structure parameters. Researchers have proposed a method for dynamically selecting the end element CI components of mixed forest pixels to improve the accuracy of estimating vegetation aggregation index in coniferous and broad-leaved mixed forests, in response to the accuracy issues of existing methods for estimating CI products on satellite. This method utilizes the dual constraints of the International Geosphere Biosphere Programme's surface types and the surface anisotropic flatness index that describes the bidirectional reflectance distribution function, combined with high-resolution land cover classification data to determine the area ratio of end elements in pixels, in order to estimate the clustering index of MODIS coniferous and broad-leaved mixed forest pixels. The research results indicate that this method can significantly improve the estimation accuracy of pixel CI values in mixed coniferous and broad-leaved forests, providing a feasible solution for the production and accuracy improvement of CI products in mixed coniferous and broad-leaved forests. This research achievement is of great significance for global carbon, water cycle research, and vegetation ecology research.”
- role：First author第一作者
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
- Email：xierui@mail.bnu.edu.cn
- Introduction：谢蕊，研究方向为定量遥感，混交林植被聚集指数反演。E-mail： xierui@mail.bnu.edu.cn
XIE Rui
12 * ,
- role：Corresponding author通信作者
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
- Email：jiaozt@bnu.edu.cn
- Introduction：焦子锑，研究方向为多角度光学遥感的建模、反演与应用（土壤—植被—冰雪）。E-mail： jiaozt@bnu.edu.cn
JIAO Ziti
12 * ,
- Affiliation：
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
  Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
DONG Yadong
23 * ,
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
CUI Lei
12 * ,
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
YIN Siyang
12 * ,
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
ZHANG Xiaoning
12 * ,
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
CHANG Yaxuan
12 * ,
- Affiliation：
  Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  Skate Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
GUO Jing
12 *
Vol. 28, Issue 4, Pages: 995-1009(2024)
DOI：10.11834/jrs.20211522
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An improved method for estimating clumping index in mixed coniferous and broadleaved forests using BRDF shape of surface ecotype as constraints

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An improved method for estimating clumping index in mixed coniferous and broadleaved forests using BRDF shape of surface ecotype as constraints

XIE Rui

JIAO Ziti

DONG Yadong

CUI Lei

YIN Siyang

ZHANG Xiaoning

CHANG Yaxuan

GUO Jing

DOI：10.11834/jrs.20211522

AI Introduction

Full Text(HTML)

Figs( 17 ) Tabs( 3 )

References

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