Multi Scale Correlations between Topography and Vegetation in a Hillside Catchment of Honduras

All systems have causes and effects that can be appreciated at different spatial scales. Understanding and representing the complexity of multi scale patterns in maps and spatial models is a key research objective. We describe the use of three types of correlation analyses: (i) a standard Pearsons Correlation Coefficient, (ii) a 'global' multi scale correlation, and (iii) local Geographically Weighted Correlation. These methods were applied to topographic and vegetation indices in a small catchment in Honduras that is representative of the countr's hillsides agro-ecosystem which suffers from severe environmental degradation due to land use decisions that lead to deforestation, overgrazing, and unsustainable agricultural. If the geographical scale at which topography matters for land use allocation can be determined then integration of knowledge systems can be focused. Our preliminary results show that: (i) single scale correlations do not adequately represent the relationship between NDVI and topographic indices, (ii) peaks in the global multi scale correlations in agricultural areas coincided with the median farm size but there was no evidence of any community or larger scale land use planning or optimisation, and (iii) local multi scale correlations varied considerably from the global results at all scales, and these variations have strong spatial structure which may indicate local optimisation of land use.

NELSON Andrew;  OBERTHUR Thomas;  COOK Simon; 

2007-12-04

TAYLOR & FRANCIS LTD

JRC33680

1365-8816,   

https://publications.jrc.ec.europa.eu/repository/handle/JRC33680,   

10.1080/13658810600852263,