DSpace
 

Researchspace >
General science, engineering & technology >
General science, engineering & technology >
General science, engineering & technology >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5004

Title: Integrating environmental and in situ hyperspectral remote sensing variables for grass nitrogen estimation in savannah ecosystems
Authors: Ramoelo, A
Cho, M
Mathieu, R
Skidmore, AK
Schlerf, M
Heitkonig, IMA
Prins, HHT
Keywords: Hyperspectral
Savannah ecosystems
Foliar nitrogen concentration
Grass nitrogen (N)
Wildlife management
Livestock management
Kruger National Park
Environmental remote sensing
Remote sensing variables
Rangeland vitality
Issue Date: Apr-2011
Citation: Ramoelo, A, Cho, M, Mathieu, R et al. 2011. Integrating environmental and in situ hyperspectral remote sensing variables for grass nitrogen estimation in savannah ecosystems. The International Symposium on Remote Sensing of Environment (ISRSE 2011)-34th ISRSE, Sydney, Australia, 10-15 April 2011
Series/Report no.: Workflow request;6483
Abstract: Information about the distribution of grass nitrogen (N) concentration is crucial in understanding rangeland vitality and facilitates effective management of wildlife and livestock. A challenge in estimating grass N concentration using remote sensing in savannah ecosystems is that these areas are characterised by heterogeneity in edaphic, topographic and climatic factors. The objective is to test the utility of integrating environmental variables and in situ hyperspectral remote sensing variables for predicting grass N concentration along a land use gradient in the greater Kruger National Park. Data used include i) environmental variables, ii) measured grass N concentration and iii) in situ measured hyperspectral spectra. Non-linear partial least square regression was used. Results showed that several environmental variables were important for N estimation. Integrating environmental variables with in situ hyperspectral variables increased grass N estimation accuracy. The study demonstrated the importance of integrated modelling for savannah ecosystem state assessment.
Description: The International Symposium on Remote Sensing of Environment (ISRSE 2011)-34th ISRSE, Sydney, Australia, 10-15 April 2011
URI: http://hdl.handle.net/10204/5004
Appears in Collections:Earth observation
General science, engineering & technology

Files in This Item:

File Description SizeFormat
ramoelo1_2011.pdf214.45 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback