EMPIRICAL RELATIONSHIP BETWEEN LEAF BIOMASS OF RED PINE FORESTS AND ENHANCED VEGETATION INDEX IN SOUTH KOREA USING LANDSAT-5 TM

被引:2
作者
Gusso, A. [1 ]
Lee, J. [2 ]
Son, Y. [2 ]
Son, Y. M. [3 ]
机构
[1] Univ Vale Rio dos Sinos, Polytech Sch, Environm Engn, Sao Leopoldo, Brazil
[2] Korea Univ, Grad Sch, Dept Environm Sci & Ecol Engn, Seoul, South Korea
[3] Korea Forest Res Inst, Dept Forest Ind Res, Seoul, South Korea
来源
XXIII ISPRS CONGRESS, COMMISSION VIII | 2016年 / 3卷 / 08期
关键词
Vegetation Index Profile; Multi-temporal; Foliage Biomass; Tree Age; Red Pine Development; Carbon Storage; CLASSIFICATION;
D O I
10.5194/isprsannals-III-8-79-2016
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Research on forest carbon (C) dynamics has been undertaken due to the importance of forest ecosystems in national C inventories. Currently, the C sequestration of South Korean forests surpasses that of other countries. In South Korea, Pinus densiflora (red pine) is the most abundant tree species. Thus, understanding the growth rate and biomass evolution of red pine forest in South Korea is important for estimating the forest C dynamics. In this paper, we derived empirical relationship between foliage biomass and the no blue band enhanced vegetation index (EVI-2) profile using both field work and multi-temporal Landsat-5 TM remote sensing data to estimate the productivity of forest biomass in South Korea. Our analysis combined a set of 84 Landsat-5 TM images from 28 different dates between 1986 and 2008 to study red pine forest development over time. Field data were collected from 30 plots (0.04 ha) that were irregularly distributed over South Korea. Individual trees were harvested by destructive sampling, and the age of trees were determined by the number of tree rings. The results are realistic (R-2=0.81, p < 0.01) and suggest that the EVI-2 index is able to adequately represent the development profile of foliage biomass in red pine forest growth.
引用
收藏
页码:79 / 83
页数:5
相关论文
共 22 条
[1]  
[Anonymous], INT J ADV REMOTE SEN
[2]  
[Anonymous], 2001, KOREAN J AGR METEORO
[3]  
[Anonymous], CLIMATOLOGIA CON EST
[4]  
[Anonymous], SURV MAN BIOM SOIL C
[5]   Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors [J].
Chander, Gyanesh ;
Markham, Brian L. ;
Helder, Dennis L. .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (05) :893-903
[7]  
Chavez PS, 1996, PHOTOGRAMM ENG REM S, V62, P1025
[8]  
Didan K., 2006, TBRS LAB DOCUMENTS
[9]   CARBON POOLS AND FLUX OF GLOBAL FOREST ECOSYSTEMS [J].
DIXON, RK ;
BROWN, S ;
HOUGHTON, RA ;
SOLOMON, AM ;
TREXLER, MC ;
WISNIEWSKI, J .
SCIENCE, 1994, 263 (5144) :185-190
[10]   Algorithm for Soybean Classification Using Medium Resolution Satellite Images [J].
Gusso, Anibal ;
Ducati, Jorge Ricardo .
REMOTE SENSING, 2012, 4 (10) :3127-3142