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

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Yuteng Chen^1¹  Baodong Ma^1² 

[1] Department of Surveying and mapping engineering, Northeastern University, 110819, Shenyang, Liaoning, China^1;School of Geoscience and Info-Physics, Central South University, 410083, Changsha, Hunan, China^2

关键词: Dustfall;    Hyperspectral;    Chlorophyll Content;    Vegetation Index;    Inversion Accuracy;   

DOI  :  10.5194/isprs-annals-IV-3-65-2018

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

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 g/m², the inversion accuracy based on REP is stable with the variation of dustfall amount. When dustfall amount is greater than 80 g/m², 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 g/m²; When dustfall amount is greater than 80 g/m², 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.

【 授权许可】

CC BY