Urban land classification and its uncertainties using principal component and cluster analyses: A case study for the UK West Midlands

Abstract

An urban land-cover classification of the 900 km 2 comprising the UK West Midland metropolitan area was generated for the purpose of facilitating stratified environmental survey and sampling. The classification grouped the 900 km 2 into eight urban land-cover classes. Input data to the classification algorithms were derived from spatial land-cover data obtained from the UK Centre for Ecology and Hydrology, and from the UK Ordnance Survey. These data provided a description of each km 2 in terms of the contributions to the land cover of 25 attributes (e.g. open land, urban, villages, motorway, etc.). The dimensionality of the land-cover dataset was reduced using principal component analysis, and eight urban classes were derived by cluster analysis using an agglomeration technique on the extracted components. The resulting urban land-cover classes reflected groupings of 1 km 2 pixels with similar urban land morphology. Uncertainties associated with this agglomerative classification were investigated in detail using fuzzy-type analyses. Our study is the first report of a quantitative investigation of uncertainty associated with a classification of this type. The resulting classification for the UK West Midland metropolitan area offers an impartial basis for a wide range of environmental and ecological surveys. The methods used can be adapted readily to other metropolitan areas where generic urban features (e.g. roads, housing density) are gridded.

Local and landscape scale determinants of macroinvertebrate assemblages and their conservation value in ponds across an urban land-use gradient

“…For this study, we selected 30 ponds that hold water for at least four consecutive months of the year, between 2 m 2 and Fig. 1 Geographic location of 30 study ponds (circles) in the West Midland conurbation, UK Sites are shown in relation to land-use within 1 km squares, using the classification of Owen et al (2006). Pond types were established using a Ward's hierarchical clustering procedure 20,000 m 2 (2 ha) in surface area (Pond Conservation Group 1993) from 1023 possible sites identified using a ArcGIS 9.3 Geographical Information System (GIS).…”

“…Pond types were established using a Ward's hierarchical clustering procedure 20,000 m 2 (2 ha) in surface area (Pond Conservation Group 1993) from 1023 possible sites identified using a ArcGIS 9.3 Geographical Information System (GIS). Site selection was stratified across a gradient of eight urban land-use classes from rural villages to heavily urbanised city centres, characteristic of the West Midlands (Owen et al 2006, Fig. 1).…”

Correlation between land-use change and greenhouse gas emissions in urban areas

“…Cluster analysis encompasses different algorithms and methods for grouping similar objects into respective categories (Owen et al 2006). In this study, the Euclidean distance (Eq.…”

Modelling the spatiotemporal change of canopy urban heat islands

“…It uses data from OS and the UK Center for Ecology and Hydrology (CEH) classified by a principle component analysis and cluster analysis [32]. The classification scheme was based on 27 different input attributes and the output spatial resolution is a 1 km 2 grid showing similar urban land morphology (for more details see [32]). The result map of this approach is shown in Fig.5, which consists of eight categories urban land use classification derived per pixel based on their common land use.…”