Integrating Remote Sensing and Ancillary Data for Regional Ecosystem Assessment: Eucalyptus Grandis Agro-system in KwaZulu-Natal, South Africa

Abstract

The ability of various ecosystems to perform vital functions such as biodiversity production, and water, energy and nutrient cycling depends on the ecosystem state, i.e. health. Ecosystem state assessment has been a topic of intense research, but has reached a point at which accurate large scale (e.g. regional to global scale) modelling and monitoring are hindered by limitations in conventional assessment methods such as direct field sampling, modelling from environmental drivers such as temperature, precipitation and available nutrients, and modelling from remote sensing data. The Ecosystem-Earth Observation (Eco-EO) research group at the Council for Scientific and Industrial Research (CSIR), South Africa has highlighted the need in remote sensing research for an integrated sensing approach at the systems level. This perspective is based on the assumption that a modelling approach that exploits the strength of the various techniques (in situ environmental variables, direct field observation and remote sensing data) could potentially improve the assessment of ecosystem state at various geographic scales. In this light, the EcoEO research group has embarked on an agro-system state assessment project since 2007 as a first step towards the implementation of the integrated modelling approach for various ecosystems. The agro-system consists of a monoculture forest plantation of Eucalyptus grandis situated in KwaZulu-Natal, South Africa. This paper presents preliminary results from the KwaZuluNatal E. grandis experimental study.

DOI: 10.1109/IGARSS.2009.5417321

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@inproceedings{Cho2009IntegratingRS, title={Integrating Remote Sensing and Ancillary Data for Regional Ecosystem Assessment: Eucalyptus Grandis Agro-system in KwaZulu-Natal, South Africa}, author={Moses Azong Cho and Jan van Aardt and Bongani Majeke and Russell P Main and Abel Ramoelo and Renaud Mathieu and Mark Norris-Rogers and Marius Du Plessis}, booktitle={IGARSS}, year={2009} }