Geographically Weighted Structural Equation Models: understanding the spatial variation of latent variables and drivers of environmental restoration effectiveness

B - Book chapters etc edited externally

Comber, A. J., Li, T., Lu, Y., Fu, B. and Harris, P. 2017. Geographically Weighted Structural Equation Models: understanding the spatial variation of latent variables and drivers of environmental restoration effectiveness. in: Bregt, A., Sarjakoski, T., Van Lammeren, R. and Rip, F. (ed.) Societal Geo-innovation: selected papers of the 20th Agile conference on geographic information science. (Lecture notes in geoinformation and cartography) Springer-Verlag Berlin.

AuthorsComber, A. J., Li, T., Lu, Y., Fu, B. and Harris, P.
EditorsBregt, A., Sarjakoski, T., Van Lammeren, R. and Rip, F.
Abstract

This paper describes a methodological extension to Geographically Weighted (GW) models. It develops and applies a GW structural equation model (SEM) to understand the observed and latent drivers associated with effective landscape restoration in Northern China. The paper reviews
recent landscape restoration activities in China, and describes the environmental context of these: soil loss, erosion and land degradation. Restoration effectiveness was described by changes in net primary production and fractional vegetation cover, as recorded in MODIS data for
the period 2000-2012. County level census data provided information on hypothesised latent variables of population pressure, off-farm economy and rural economy. The GW SEM analysis allows the spatial variation in the contributions made by different socio-economic factors to
restoration effectiveness to be evaluated. Although developed with ropey data – the County level population totals were perhaps unrealistically interpolated over a 2km grid and the MODIS data were aggregated over the same – the GW SEM allows the detail of the how what and where to be identified thus supporting local policy and planning. A number of future developments in refining this method are outlined.

KeywordsGWR; Soil erosion; Loess plateau; Critical zone
Year of Publication2017
Book titleSocietal Geo-innovation: selected papers of the 20th Agile conference on geographic information science. (Lecture notes in geoinformation and cartography)
PublisherSpringer-Verlag Berlin
ISBN978-3-319-56759-4
Digital Object Identifier (DOI)doi:10.1007/978-3-319-56759-4
Web address (URL)https://doi.org/10.1007/978-3-319-56759-4
FunderBiotechnology and Biological Sciences Research Council
Open accessPublished as non-open access
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Output statusPublished

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