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author:

Cao, B. (Cao, B..) [1] | Du, Y. (Du, Y..) [2] | Li, J. (Li, J..) [3] | Li, H. (Li, H..) [4] | Li, L. (Li, L..) [5] | Zhang, Y. (Zhang, Y..) [6] | Zou, J. (Zou, J..) [7] | Liu, Q. (Liu, Q..) [8]

Indexed by:

Scopus

Abstract:

We compare five slope correction methods developed by Walter et al., Montes et al., Schleppi et al., España et al., and Gonsamo et al. (referred to as WAL, MON, SCH, ESP, and GON, respectively) using artificial fisheye pictures simulated by graphics software and a lookup table (LUT) retrieval method. The LUT is built by simulating the directional gap fraction as a function of leaf area index (LAI) and average leaf inclination angle (ALIA) using the Poisson law. LAI and ALIA estimates correspond to the case of the LUT that provides the lowest root-mean-square error between the observed gap fractions after slope correction and the simulated ones. Three LAI values (1.5, 3.5, and 5.5), four ALIA values (26.8°, 45°, 57.5°, and 63.2°), and three slope angles (0°, 20°, and 50°) constituted 36 samples of random scenes. ESP is recommended because its results are accurate and independent on the leaf angle distribution (LAD), while GON only performs well for spherical LAD. The three other methods present less good performances with underestimation or overestimation of LAI and/or ALIA depending on the LAD, and the recommended order for them is MON, SCH, and WAL. © 2004-2012 IEEE.

Keyword:

Average leaf inclination angle (ALIA); Digital hemispherical photography (DHP); Leaf area index (LAI); Slope correction; Topographic mask

Community:

  • [ 1 ] [Cao, B.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 2 ] [Cao, B.]Joint Center for Global Change Studies, Beijing, 100875, China
  • [ 3 ] [Du, Y.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 4 ] [Du, Y.]Joint Center for Global Change Studies, Beijing, 100875, China
  • [ 5 ] [Li, J.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 6 ] [Li, J.]Joint Center for Global Change Studies, Beijing, 100875, China
  • [ 7 ] [Li, H.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 8 ] [Li, H.]Joint Center for Global Change Studies, Beijing, 100875, China
  • [ 9 ] [Li, L.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 10 ] [Li, L.]Joint Center for Global Change Studies, Beijing, 100875, China
  • [ 11 ] [Zhang, Y.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 12 ] [Zhang, Y.]Joint Center for Global Change Studies, Beijing, 100875, China
  • [ 13 ] [Zou, J.]Key Laboratory of Data Mining and Information Sharing, Ministry of Education, Spatial Information Research Center of Fujian Province, Fuzhou University, Fuzhou, 350002, China
  • [ 14 ] [Liu, Q.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of Sciences, Beijing, 100101, China
  • [ 15 ] [Liu, Q.]Joint Center for Global Change Studies, Beijing, 100875, China

Reprint 's Address:

  • [Du, Y.]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing, Digital Earth of Chinese Academy of SciencesChina

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Source :

IEEE Geoscience and Remote Sensing Letters

ISSN: 1545-598X

Year: 2015

Issue: 9

Volume: 12

Page: 1958-1962

2 . 2 2 8

JCR@2015

4 . 0 0 0

JCR@2023

ESI HC Threshold:218

JCR Journal Grade:1

CAS Journal Grade:3

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: 3

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