World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Does Topographic Normalization of Landsat Images Improve Fractional Tree Cover Mapping in Tropical Mountains? : Volume Xl-7/W3, Issue 1 (29/04/2015)

By Adhikari, H.

Click here to view

Book Id: WPLBN0004015914
Format Type: PDF Article :
File Size: Pages 7
Reproduction Date: 2015

Title: Does Topographic Normalization of Landsat Images Improve Fractional Tree Cover Mapping in Tropical Mountains? : Volume Xl-7/W3, Issue 1 (29/04/2015)  
Author: Adhikari, H.
Volume: Vol. XL-7/W3, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus Publications
Historic
Publication Date:
2015
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Heiskanen, J., Maeda, E. E., E. Pellikk, P. K., & Adhikari, H. (2015). Does Topographic Normalization of Landsat Images Improve Fractional Tree Cover Mapping in Tropical Mountains? : Volume Xl-7/W3, Issue 1 (29/04/2015). Retrieved from http://members.worldlibrary.net/


Description
Description: University of Helsinki, Department of Geosciences and Geography,Helsinki, Finland. Fractional tree cover (Fcover) is an important biophysical variable for measuring forest degradation and characterizing land cover. Recently, atmospherically corrected Landsat data have become available, providing opportunities for high-resolution mapping of forest attributes at global-scale. However, topographic correction is a pre-processing step that remains to be addressed. While several methods have been introduced for topographic correction, it is uncertain whether Fcover models based on vegetation indices are sensitive to topographic effects. Our objective was to assess the effect of topographic correction on the accuracy of Fcover modelling. The study area was located in the Eastern Arc Mountains of Kenya. We used C-correction as a digital elevation model (DEM) based correction method. We examined if predictive models based on normalized difference vegetation index (NDVI), reduced simple ratio (RSR) and tasseled cap indices (Brightness, Greenness and Wetness) are improved if using topographically corrected data. Furthermore, we evaluated how the results depend on the DEM by correcting images using available global DEM (ASTER GDEM, SRTM) and a regional DEM. Reference Fcover was obtained from wall-to-wall airborne LiDAR data. Landsat images corresponding to minimum and maximum sun elevation were analyzed. We observed that topographic correction could only improve models based on Brightness and had very small effect on the other models. Cosine of the solar incidence angle (cos i) derived from SRTM DEM showed stronger relationship with spectral bands than other DEMs. In conclusion, our results suggest that, in tropical mountains, predictive models based on common vegetation indices are not sensitive to topographic effects.

Summary
Does topographic normalization of landsat images improve fractional tree cover mapping in tropical mountains?

 

Click To View

Additional Books


  • Micro Uav Based Georeferenced Orthophoto... (by )
  • Research on the Prototype of Rail Cleara... (by )
  • Gis Adoption and Diffusion Among Senior ... (by )
  • Three Pre-processing Steps to Increase t... (by )
  • New Instruments for Survey: on Line Soft... (by )
  • Extending a Mobile Device with Low-cost ... (by )
  • Fusing Passive and Active Sensed Images ... (by )
  • Performance Validation of High Resolutio... (by )
  • Project Archeye – the Quadrocopter as th... (by )
  • Dynamics and Forecasting of Population G... (by )
  • National Scale Monitoring Reporting and ... (by )
  • Exploring the Relationships of Between L... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.