ESTIMATION OF MIXED FORESTS CLUMPING INDEX AND ITS SPATIAL HETEROGENEITY STUDY

Rui Xie, Ziti Jiao*, Yadong Dong, Xiaoning Zhang, Siyang Yin, Lei Cui, Jing Guo, Sijie Li, Zidong Zhu, Yidong Tong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Foliage Clumping Index (CI) is an important structural parameter within vegetation canopy, and current satellite-borne CI products mainly retrieved by using the linear relationship between the CI and the normalized difference between hotspot and dark spot (NDHD), while there is no directly model to calculate the CI of mixed forest. The objective of this paper is to propose a new method to calculate the mixed forest CI (MFCI) and access the ability to response the spatial heterogeneity of mixed forest pixels. The results show that: (1) The accuracy of MFCI is significantly higher than that of existing MODIS CI products, the average error can be reduced by 6.3% (2) the total sensitivity of MFCI to spatial heterogeneity is high(>0.6), and with the highest sensitivity to bare soil.

Original languageEnglish
Title of host publicationIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3701-3704
Number of pages4
ISBN (Electronic)9781665403696
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium
Duration: 12 Jul 202116 Jul 2021

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2021-July

Conference

Conference2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Country/TerritoryBelgium
CityBrussels
Period12/07/2116/07/21

Keywords

  • Clumping index
  • Mixed forest
  • Sensitivity analysist
  • Spatial heterogeneity

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