DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT – A LABORATORY EXPERIMENT

Dust pollution is serious in many areas of China. It is of great significance to estimate chlorophyll content of vegetation accurately by hyperspectral remote sensing for assessing the vegetation growth status and monitoring the ecological environment in dusty areas. By using selected vegetation ind...

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Main Authors: Y. Chen, B. Ma, X. Li, S. Zhang, L. Wu
Format: Article
Language:English
Published: Copernicus Publications 2018-04-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/65/2018/isprs-annals-IV-3-65-2018.pdf
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author Y. Chen
B. Ma
X. Li
S. Zhang
L. Wu
author_facet Y. Chen
B. Ma
X. Li
S. Zhang
L. Wu
author_sort Y. Chen
collection DOAJ
description Dust pollution is serious in many areas of China. It is of great significance to estimate chlorophyll content of vegetation accurately by hyperspectral remote sensing for assessing the vegetation growth status and monitoring the ecological environment in dusty areas. By using selected vegetation indices including Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI) ,Double Difference Index (DD) and Red Edge Position Index (REP), chlorophyll inversion models were built to study the accuracy of hyperspectral inversion of chlorophyll content based on a laboratory experiment. The results show that: (1) REP exponential model has the most stable accuracy for inversion of chlorophyll content in dusty environment. When dustfall amount is less than 80&thinsp;g/m<sup>2</sup>, the inversion accuracy based on REP is stable with the variation of dustfall amount. When dustfall amount is greater than 80&thinsp;g/m<sup>2</sup>, the inversion accuracy is slightly fluctuation. (2) Inversion accuracy of DD is worst among three models. (3) MTCI logarithm model has high inversion accuracy when dustfall amount is less than 80&thinsp;g/m<sup>2</sup>; When dustfall amount is greater than 80&thinsp;g/m<sup>2</sup>, inversion accuracy decreases regularly and inversion accuracy of modified MTCI (mMTCI) increases significantly. The results provide experimental basis and theoretical reference for hyperspectral remote sensing inversion of chlorophyll content.
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spelling doaj.art-17f0cc157f6f454cbcb14177148096da2022-12-22T01:22:49ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502018-04-01IV-3656910.5194/isprs-annals-IV-3-65-2018DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENTY. Chen0B. Ma1X. Li2S. Zhang3L. Wu4Department of Surveying and mapping engineering, Northeastern University, 110819, Shenyang, Liaoning, ChinaDepartment of Surveying and mapping engineering, Northeastern University, 110819, Shenyang, Liaoning, ChinaDepartment of Surveying and mapping engineering, Northeastern University, 110819, Shenyang, Liaoning, ChinaDepartment of Surveying and mapping engineering, Northeastern University, 110819, Shenyang, Liaoning, ChinaSchool of Geoscience and Info-Physics, Central South University, 410083, Changsha, Hunan, ChinaDust pollution is serious in many areas of China. It is of great significance to estimate chlorophyll content of vegetation accurately by hyperspectral remote sensing for assessing the vegetation growth status and monitoring the ecological environment in dusty areas. By using selected vegetation indices including Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI) ,Double Difference Index (DD) and Red Edge Position Index (REP), chlorophyll inversion models were built to study the accuracy of hyperspectral inversion of chlorophyll content based on a laboratory experiment. The results show that: (1) REP exponential model has the most stable accuracy for inversion of chlorophyll content in dusty environment. When dustfall amount is less than 80&thinsp;g/m<sup>2</sup>, the inversion accuracy based on REP is stable with the variation of dustfall amount. When dustfall amount is greater than 80&thinsp;g/m<sup>2</sup>, the inversion accuracy is slightly fluctuation. (2) Inversion accuracy of DD is worst among three models. (3) MTCI logarithm model has high inversion accuracy when dustfall amount is less than 80&thinsp;g/m<sup>2</sup>; When dustfall amount is greater than 80&thinsp;g/m<sup>2</sup>, inversion accuracy decreases regularly and inversion accuracy of modified MTCI (mMTCI) increases significantly. The results provide experimental basis and theoretical reference for hyperspectral remote sensing inversion of chlorophyll content.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/65/2018/isprs-annals-IV-3-65-2018.pdf
spellingShingle Y. Chen
B. Ma
X. Li
S. Zhang
L. Wu
DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENT
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENT
title_full DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENT
title_fullStr DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENT
title_full_unstemmed DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENT
title_short DUSTFALL EFFECT ON HYPERSPECTRAL INVERSION OF CHLOROPHYLL CONTENT &ndash; A LABORATORY EXPERIMENT
title_sort dustfall effect on hyperspectral inversion of chlorophyll content ndash a laboratory experiment
url https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/65/2018/isprs-annals-IV-3-65-2018.pdf
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AT xli dustfalleffectonhyperspectralinversionofchlorophyllcontentndashalaboratoryexperiment
AT szhang dustfalleffectonhyperspectralinversionofchlorophyllcontentndashalaboratoryexperiment
AT lwu dustfalleffectonhyperspectralinversionofchlorophyllcontentndashalaboratoryexperiment