Using functional classifications from remote sensing data for assessing ecosystem spatial heterogeneity

Abstract

Fernández, N., Piñeiro, G. (2008). Using functional classifications from remote sensing data for assessing ecosystem spatial heterogeneity. Ecosistemas 17(3):64-78.

Most  remote  sensing  approaches  to  ecosystem  classification  continue  to  rely  on  structural  attributes  like  vegetation  physiognomy  and landform,  failing  to  incorporate  key  functional  properties  of  energy  and  matter  exchange.  Here  we  show  an  application  of  functional classifications for ecosystem characterization using the Normalized Difference Vegetation Index (NDVI), albedo and surface temperature as estimated from remote sensing data. We illustrate the development of ecosystem functional classifications in Cabo de Gata and Doñana, two Mediterranean  regions  of  high  conservation  concern  under  different  environmental  conditions.  Both  regions  displayed  a  complex  spatial pattern  in  functional  class  distributions  only  partly  related  to  vegetation  structure  and  landform.  We  identified  10  ecosystem  functional classes in Cabo de Gata, with only two closely associated to specific vegetation units. In addition, seven different landform units present in the region included a variety of ecosystem classes. Out of eight different functional classes recognized in Doñana, only two were closely associated to particular landform units within the highest protected area, whereas a combination of landform and land use intensity explained the distribution of other four functional classes. We propose that ecosystem functional classifications based on remote sensing data are of key  importance  for  ecosystem  characterization  and  management,  therefore  complementing  more  traditional  approaches  solely  based  on
structural attributes.