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Gonzales-Jaramillo, V.; Fries, A.; Zeilinger, J.; Homeier, J.; Paladines, J. &amp; Bendix, J. (2018): <b>Estimation of Above Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data</b>. <i>Remote Sensing</i> <b>10</b>, .

Resource Description
Title: Estimation of Above Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data
FOR816dw ID: 1708
Publication Date: 2018-04-24
License and Usage Rights:
Resource Owner(s):
Individual: Victor Gonzales-Jaramillo
Contact:
Individual: Andreas Fries
Contact:
Individual: Joerg Zeilinger
Contact:
Individual: Jürgen Homeier
Contact:
Individual: Jhoana Paladines
Contact:
Individual: Jörg Bendix
Contact:
Abstract:
A reliable estimation of Above Ground Biomass (AGB) in Tropical Mountain Forest (TMF)<br/> is still complicated, due to fast-changing climate and topographic conditions, which modifies the<br/> forest structure within fine scales. The variations in vertical and horizontal forest structure are hardly<br/> detectable by small field plots, especially in natural TMF due to the high tree diversity and the<br/> inaccessibility of remote areas. Therefore, the present approach used remotely sensed data from a<br/> Light Detection and Ranging (LiDAR) sensor in combination with field measurements to estimate<br/> AGB accurately for a catchment in the Andes of south-eastern Ecuador. From the LiDAR data,<br/> information about horizontal and vertical structure of the TMF could be derived and the vegetation at<br/> tree level classified, differentiated between the prevailing forest types (ravine forest, ridge forest and<br/> Elfin Forest). Furthermore, topographical variables (Topographic Position Index, TPI; Morphometric<br/> Protection Index, MPI) were calculated by means of the high-resolution LiDAR data to analyse the<br/> AGB distribution within the catchment. The field measurements included different tree parameters<br/> of the species present in the plots, which were used to determine the local mean Wood Density<br/> (WD) as well as the specific height-diameter relationship to calculate AGB, applying regional scale<br/> modelling at tree level. The results confirmed that field plot measurements alone cannot capture<br/> completely the forest structure in TMF but in combination with high resolution LiDAR data, applying<br/> a classification at tree level, the AGB amount (Mg ha??1) and its distribution in the entire catchment<br/> could be estimated adequately (model accuracy at tree level: R2 > 0.91). It was found that the AGB<br/> distribution is strongly related to ridges and depressions (TPI) and to the protection of the site (MPI),<br/> because high AGB was also detected at higher elevations (up to 196.6 Mg ha??1, above 2700 m), if the<br/> site is situated in depressions (ravine forest) and protected by the surrounding terrain. In general,<br/> highest AGB is stored in the protected ravine TMF parts, also at higher elevations, which could only<br/> be detected by means of the remote sensed data in high resolution, because most of these areas are<br/> inaccessible. Other vegetation units, present in the study catchment (pasture and subpáramo) do not<br/> contain large AGB stocks, which underlines the importance of intact natural forest stands.
Keywords:
| LiDAR | AGB estimation |
Literature type specific fields:
ARTICLE
Journal: Remote Sensing
Volume: 10
Page Range:
Metadata Provider:
Individual: Jörg Bendix
Contact:
Online Distribution:
Download File: http://www.tropicalmountainforest.org/publications.do?citid=1708


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