Biodiversity mapping by remote sensing based method and ecological stratification

Hieu Cong Nguyen, Doyeon Kim, Joon Heo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Using spaceborne remote sensing data to measure biodiversity has been considerable to recent interest. This paper proposes a modeling approach for quantifying spatial distribution of plant species using decision tree algorithm and incorporation of climatic, topographic data and Moderate Resolution Imaging Spectroradiometer producing 16 dependent variables. The plant species richness derived from Korean National Forest Inventory (NFI) plots is used as the ground truth data as well as an independent variable in modeling process. Moreover, Genetic Algorithm was used to select optimal variables among 16 predictor variables; and in order to improve accuracy of the model, ecological stratification was conducted. As the result, the model applied for Kangwon province, South Korea shows that overall accuracies were consistently over 80% in all cases including the original, variables survived selection and ecological stratification. More interestingly, ecological stratifications with soil and bedrock type presented in the study were the most effective criterions than others.

Original languageEnglish
Title of host publication34th Asian Conference on Remote Sensing 2013, ACRS 2013
PublisherAsian Association on Remote Sensing
Pages3087-3090
Number of pages4
ISBN (Print)9781629939100
Publication statusPublished - 2013 Jan 1
Event34th Asian Conference on Remote Sensing 2013, ACRS 2013 - Bali, Indonesia
Duration: 2013 Oct 202013 Oct 24

Publication series

Name34th Asian Conference on Remote Sensing 2013, ACRS 2013
Volume4

Other

Other34th Asian Conference on Remote Sensing 2013, ACRS 2013
CountryIndonesia
CityBali
Period13/10/2013/10/24

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Nguyen, H. C., Kim, D., & Heo, J. (2013). Biodiversity mapping by remote sensing based method and ecological stratification. In 34th Asian Conference on Remote Sensing 2013, ACRS 2013 (pp. 3087-3090). (34th Asian Conference on Remote Sensing 2013, ACRS 2013; Vol. 4). Asian Association on Remote Sensing.