Download
Cite as:
P&eacute;rez Postigo, I.; Silva, B. &amp; Bendix, J. (2015): <b>Potential of Remotely Sensed Image Textures for Predicting Herbivory in the Ecuadorian Andes</b> Fachbereich Philipps-Universit&auml;t Marburg, Geographie , <i>master thesis</i>

Resource Description

Title: Potential of Remotely Sensed Image Textures for Predicting Herbivory in the Ecuadorian Andes
FOR816dw ID: 1522
Publication Date: 2015-08-01
License and Usage Rights: PAK 823-825 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)
Resource Owner(s):
Individual: Isabel Pérez Postigo
Contact:
Individual: Brenner Silva
Contact:
Individual: Jörg Bendix
Contact:
Abstract:
The worldwide demand for large scale biodiversity monitoring systems is challenging for recent remote sensing techniques. For monitoring changes in species as well as functional diversity the consideration of ecosystem processes is crucial. Herbivory as a focal function in tropical forest ecosystems is therefore being investigated in this study. Aim of the study is to reveal the potential of remotely sensed image textures for predicting herbivory. For this leaf area loss (LAL) due to herbivory has been quantified in different vegetation layers of a tropical mountain forest in the Ecuadorian Andes. The study area is a structurally highly complex region along an elevation gradient from 1000 to 3000 m a.s.l. with undisturbed primary forest and disturbed forest fragments within agriculturally used land. It has been proven that LAL has similar patterns as herbivore abundance over the elevation gradient showing it to be a possible proxy for herbivore abundance. Further results show a correlation of LAL data and canopy cover thus local forest structure. Correlations between LAL and image textures as a proxy for vegetation structure were stronger than with pixel wise derived spectral values only. Unveiling the high potential of image textures as a surrogate for herbivory and ecosystem function.
Keywords:
| biodiversity | remote sensing | herbivory |
Literature type specific fields:
THESIS
Degree: master
Degree Institution: Fachbereich Philipps-Universität Marburg, Geographie
Total Pages: 27
Metadata Provider:
Individual: Christine Wallis
Contact:
Online Distribution:
Download File: http://www.tropicalmountainforest.org/publications.do?citid=1522


Quick search

  • Publications:
  • Datasets:



rnse logo

Radar Network Ecuador - Peru