Variations in reflectance with seasonality and viewing geometry: Implications for semi-arid vegetation mapping with MISR data

Lihong Su, Yuxia Huang, Mark Chopping, Albert Rango

Research output: Contribution to journalArticle

Abstract

The purpose of this article is to understand the effect of multi-temporalmulti-angle data on vegetation community type mapping in desert regions. Based on data from the multi-angle imaging spectroradiometer (MISR), a set of 46 multi-temporal classification experiments were carried out in the Jornada Experimental Range in New Mexico, USA. Besides multi-angle observations, bidirectional reflectance distribution function (BRDF) model parameters were also used as input data for the classifications. The experiments used two widely accepted BRDF models, the Rahman-Pinty-Verstraete (RPV) model and the Ross-thin Li-sparse reciprocal (RTnLS) model. The experiments show that multi-temporal multi-angle classifications can yield a more accurate mapping than multi-temporal nadir classifications, and multi-temporal BRDF model parameters combined with a single nadir image can provide an accuracy roughly the same as all multi-temporal multi-angle observations for the vegetation mapping. These findings opened not only a path of reducing data dimensionality for multi-temporal multi-angle classifications, but also a way of merging products of both MISR and moderate resolution imaging spectroradiometer (MODIS) to improve semi-arid vegetation mapping.

Original languageEnglish
Pages (from-to)8183-8193
Number of pages11
JournalInternational Journal of Remote Sensing
Volume32
Issue number23
DOIs
StatePublished - 1 Jan 2011

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MISR
vegetation mapping
seasonality
reflectance
bidirectional reflectance
geometry
nadir
experiment
MODIS
desert
vegetation
distribution

Cite this

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abstract = "The purpose of this article is to understand the effect of multi-temporalmulti-angle data on vegetation community type mapping in desert regions. Based on data from the multi-angle imaging spectroradiometer (MISR), a set of 46 multi-temporal classification experiments were carried out in the Jornada Experimental Range in New Mexico, USA. Besides multi-angle observations, bidirectional reflectance distribution function (BRDF) model parameters were also used as input data for the classifications. The experiments used two widely accepted BRDF models, the Rahman-Pinty-Verstraete (RPV) model and the Ross-thin Li-sparse reciprocal (RTnLS) model. The experiments show that multi-temporal multi-angle classifications can yield a more accurate mapping than multi-temporal nadir classifications, and multi-temporal BRDF model parameters combined with a single nadir image can provide an accuracy roughly the same as all multi-temporal multi-angle observations for the vegetation mapping. These findings opened not only a path of reducing data dimensionality for multi-temporal multi-angle classifications, but also a way of merging products of both MISR and moderate resolution imaging spectroradiometer (MODIS) to improve semi-arid vegetation mapping.",
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Variations in reflectance with seasonality and viewing geometry : Implications for semi-arid vegetation mapping with MISR data. / Su, Lihong; Huang, Yuxia; Chopping, Mark; Rango, Albert.

In: International Journal of Remote Sensing, Vol. 32, No. 23, 01.01.2011, p. 8183-8193.

Research output: Contribution to journalArticle

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