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author:

Jiang, H. (Jiang, H..) [1] | Wang, S. (Wang, S..) [2] | Cao, X. (Cao, X..) [3] | Yang, C. (Yang, C..) [4] | Zhang, Z. (Zhang, Z..) [5] | Wang, X. (Wang, X..) [6]

Indexed by:

Scopus

Abstract:

The effect of terrain shadow, including the self and cast shadows, is one of the main obstacles for accurate retrieval of vegetation parameters by remote sensing in rugged terrains. A shadow- eliminated vegetation index (SEVI) was developed, which was computed from only red and near-infrared top-of-atmosphere reflectance without other heterogeneous data and topographic correction. After introduction of the conceptual model and feature analysis of conventional wavebands, the SEVI was constructed by ratio vegetation index (RVI), shadow vegetation index (SVI) and adjustment factor (f (Δ)). Then three methods were used to validate the SEVI accuracy in elimination of terrain shadow effects, including relative error analysis, correlation analysis between the cosine of solar incidence angle (cosi) and vegetation indices, and comparison analysis between SEVI and conventional vegetation indices with topographic correction. The validation results based on 532 samples showed that the SEVI relative errors for self and cast shadows were 4.32% and 1.51% respectively. The coefficient of determination between cosi and SEVI was only 0.032 and the coefficient of variation (std/mean) for SEVI was 12.59%. The results indicate that the proposed SEVI effectively eliminated the effect of terrain shadows and achieved similar or better results than conventional vegetation indices with topographic correction. © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Keyword:

cast shadow; self shadow; shadow- eliminated vegetation index (SEVI); terrain shadow effect; Vegetation indices

Community:

  • [ 1 ] [Jiang, H.]Key Laboratory of Spatial Data Mining & Information Sharing of MOE, and Fujian Spatial Information Research Center, Fuzhou University, Fuzhou, China
  • [ 2 ] [Jiang, H.]Aerial Application Technology Research Unit, USDA-Agricultural Research Service, College Station, TX, United States
  • [ 3 ] [Wang, S.]Key Laboratory of Spatial Data Mining & Information Sharing of MOE, and Fujian Spatial Information Research Center, Fuzhou University, Fuzhou, China
  • [ 4 ] [Cao, X.]Key Laboratory of Spatial Data Mining & Information Sharing of MOE, and Fujian Spatial Information Research Center, Fuzhou University, Fuzhou, China
  • [ 5 ] [Cao, X.]Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China
  • [ 6 ] [Yang, C.]Aerial Application Technology Research Unit, USDA-Agricultural Research Service, College Station, TX, United States
  • [ 7 ] [Zhang, Z.]Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China
  • [ 8 ] [Wang, X.]Key Laboratory of Spatial Data Mining & Information Sharing of MOE, and Fujian Spatial Information Research Center, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • [Jiang, H.]Key Laboratory of Spatial Data Mining & Information Sharing of MOE, and Fujian Spatial Information Research Center, Fuzhou UniversityChina

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Source :

International Journal of Digital Earth

ISSN: 1753-8947

Year: 2019

Issue: 9

Volume: 12

Page: 1013-1029

3 . 0 9 7

JCR@2019

3 . 7 0 0

JCR@2023

ESI HC Threshold:137

JCR Journal Grade:2

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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