DOI: 10.1016/j.jag.2014.03.016
Scopus记录号: 2-s2.0-84904463622
论文题名: Quantifying uncertainty in remote sensing-based urban land-use mapping
作者: Cockx K ; , Van de Voorde T ; , Canters F
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 31, 期: 1 起始页码: 154
结束页码: 166
语种: 英语
英文关键词: Image classification
; Land-use mapping
; Monte Carlo simulation
; Spectral unmixing
; Uncertainty
; Urban remote sensing
Scopus关键词: image classification
; land cover
; land use change
; mapping
; Monte Carlo analysis
; pixel
; remote sensing
; satellite data
; satellite imagery
; SPOT
; time series
; uncertainty analysis
; urban area
; Antwerp [Belgium]
; Belgium
; Brussels [Belgium]
; Flanders
英文摘要: Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface cover at subpixel level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty of the land-use mapping strategy is addressed by comparing the most likely land-use maps obtained from the simulation with the original land-use map, obtained without taking uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map - indicating absence of bias in the mapping process - it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modelling of urban growth. © 2014 Elsevier B.V. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79763
Appears in Collections: 气候变化事实与影响
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作者单位: Cartography and GIS Research Group, Department of Geography, Vrije Universiteit Brussel, Building F, Pleinlaan 2, B-1050 Brussel, Belgium
Recommended Citation:
Cockx K,, Van de Voorde T,, Canters F. Quantifying uncertainty in remote sensing-based urban land-use mapping[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,31(1)