Estimation of aboveground carbon using KNN algorithm: A case study in Danyang, Korea

Jae Hoon Jung, Joon Hoe, Suhong Yoo, Kyung Hun Cho, Kyung Min Kim, Jungbin Lee

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

Abstract

Forest biomass stores a large amount of terrestrial carbon and the need of periodic monitoring forest biomass has increased. kNN algorithm is one of the common method to estimate forest biomass and has been widely used for a variety of biomass mapping and applications. The objective of this study is to estimate aboveground carbon stock of Danyang area in South Korea. Field data from NFI and Landsat ETM+ satellite image were used, and carbon stock were estimated at k = 1 to 10. As a result, the lowest RMSE was found at k = 5, and the mean and the total carbon stock of Danyang area were estimated to be 28.33 ton C/ha and 2209748.91 t respectively.

Original languageEnglish
Title of host publication31st Asian Conference on Remote Sensing 2010, ACRS 2010
Pages1008-1010
Number of pages3
Publication statusPublished - 2010
Event31st Asian Conference on Remote Sensing 2010, ACRS 2010 - Hanoi, Viet Nam
Duration: 2010 Nov 12010 Nov 5

Publication series

Name31st Asian Conference on Remote Sensing 2010, ACRS 2010
Volume2

Other

Other31st Asian Conference on Remote Sensing 2010, ACRS 2010
CountryViet Nam
CityHanoi
Period10/11/110/11/5

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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