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Almengor Gonzalez, R. (2017): <b>OBIA: Automated delineation of Pine Plantations from Aerial Imagery in the southern Ecuadorian Paramos</b> Technische Universit&auml;t M&uuml;nchen, <i>master thesis</i>

Resource Description

Title: OBIA: Automated delineation of Pine Plantations from Aerial Imagery in the southern Ecuadorian Paramos
FOR816dw ID: 1657
Publication Date: 2017-08-13
License and Usage Rights: PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)
Resource Owner(s):
Individual: Roger Almengor Gonzalez
Contact:
Abstract:
Geographic Information Systems and Remote Sensing are important contributors to Sustainable<br/> Forestry Management Plans. Remote sensing techniques for image interpretation provides the<br/> means to extract valuable information that could be expensive and time-consuming to obtain<br/> through field observations (Franklin et al. 2001).<br/> Spatial Products derived from the interpretation of airborne and satellite borne images feed<br/> Geographic Information Systems to develop strategies and methodologies for resource<br/> management, harvest planning, fire management, map production, and model predictions.<br/> (Yusmah et al. 2015)<br/> This study has three important objectives: to test the feasibility of template matching for the<br/> identification of single pine tree crowns, to conduct a delineation of pine plantations using<br/> relational features and to evaluate how single tree crown size affects the accuracy of the<br/> proposed method.<br/> Templates of single trees were produced in the software eCognition Developer. The sampling<br/> process comprised the random selection of 3000 single pine trees in 7 different test sites (test sites were grouped in 3 categories according to the single tree sizes). A first rule set to detect<br/> single tree crowns was developed in eCognition Developer, using three different template groups (4, 8 and 16 templates). Through an analysis of variance, the number of single tree<br/> crowns detected was compared for the different template groups.<br/> Using a second rule set in eCognition, the template matching algorithm combined with<br/> relational, spectral and contextual information were applied to delineate pine plantation areas.<br/> An accuracy assessment was performed in the test sites for all thematic classes identified.<br/> Finally, an Analysis of Variance evaluated the influence of single tree crown size on the overall<br/> accuracy.<br/> Potential applications and improvements to the proposed methodology for single tree crown detection and plantation delineation are proposed at the end of the document.
Additional Infos:
Master Thesis jointly supervised by Thomas Schneider and Patrick Hildebrandt (Project B5 and B3)
Keywords:
| reforestation | remote sensing | pine forest | Paramo | Cajas National Park | orthophotos |
Literature type specific fields:
THESIS
Degree: master
Degree Institution: Technische Universität München
Total Pages: 86
Metadata Provider:
Individual: Carola Paul
Contact:
Online Distribution:
Download File: http://www.lcrs.de/publications.do?citid=1657


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