Application of Hyperion data for investigating agriculture field stress to drought conditions

EasyChair Preprint 2287

Abstract

Vegetation indices are the most popular satellite banding calculations. These are used to calculate the vegetation cover, to study vegetation types, and the vegetation of a region at different times. In this study, we combining these indices with water indices, crown cover and brightness of plant pigments using Hyperion data, to estimate areas of influenced by water stress. The results show that by combining various vegetation cover indices with different WBI and ARI indices different results are obtained. The two vegetation indices RENDVI and NDVI offer nearly close result, but the combination of the NDVI, WBI, and ARI indices seems closets to reality. The survey of observation data from the area of crops in 2010 and 2011 indicates that the area of agricultural farms is reduced by about 5000 hectares during this period [12]. To record and follow this ongoing trend, the combination of the NDVI index with the WBI and ARI indices is recommended instead of other GI indices.

Keyphrases: Agriculture, Greenness Index, Hyperspectral data, Normalize Difference Vegetation Index, remote sensing

@booklet{EasyChair:2287,
  author    = {Soghra Andaryani and Dennis Trolle and Abolfazl Mokhtari Asl},
  title     = {Application of Hyperion data for investigating agriculture field stress to drought conditions},
  howpublished = {EasyChair Preprint 2287},
  year      = {EasyChair, 2019}}