A multiscale analysis of LULC and NDVI variation in Nang Rong district, northeast Thailand

Walsh, Stephen J.; Crawford, Thomas W.; Welsh, William F.; Crews‐Meyer, Kelley A.

doi:10.1016/s0167-8809(01)00202-x

Cited by 115 publications

(48 citation statements)

References 5 publications

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“…Two different approaches of quantifying the multi-scale relations between land use and driving forces are known. The first is based on data that are artificially gridded at multiple resolutions; at each individual resolution the relations between land use and driving forces are statistically determined (Veldkamp and Fresco, 1997;de Koning et al, 1998;Walsh et al, 1999Walsh et al, , 2001Verburg and Chen, 2000). The second approach uses multi-level statistics (Goldstein, 1995).…”

Section: Implementation In Modelsmentioning

confidence: 99%

Land use change modelling: current practice and research priorities

et al. 2004

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Land use change models are tools to support the analysis of the causes and consequences of land use dynamics. Scenario analysis with land use models can support land use planning and policy. Numerous land use models are available, developed from different disciplinary backgrounds. This paper reviews current models to identify priority issues for future land use change modelling research. This discussion is based on six concepts important to land use modelling: (1) Level of analysis; (2) Cross-scale dynamics; (3) Driving forces; (4) Spatial interaction and neighbourhood effects; (5) Temporal dynamics; and (6) Level of integration. For each of these concepts an overview is given of the variety of methods used to implement these concepts in operational models. It is concluded that a lot of progress has been made in building land use change models. However, in order to incorporate more aspects important to land use modelling it is needed to develop a new generation of land use models that better address the multi-scale characteristics of the land use system, implement new techniques to quantify neighbourhood effects, explicitly deal with temporal dynamics and achieve a higher level of integration between disciplinary approaches and between models studying urban and rural land use changes. If these requirements are fulfilled models will better support the analysis of land use dynamics and land use policy formulation.

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Section: Implementation In Modelsmentioning

confidence: 99%

Land use change modelling: current practice and research priorities

et al. 2004

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“…For instance, landscape greenness has been linked to variables describing people and environment in Thailand measured at a range of spatial scales (72,73), and land use-preference weights of agents has been found to be scale dependent in spatial models of land-cover change in the Midwestern United States (66). The scales of social and biophysical inputs and model outcomes influence the patterns and processes of land-use and -cover change and the approaches used in model validation.…”

Section: Data Quality and Measurement Issuesmentioning

confidence: 99%

Developing a science of land change: Challenges and methodological issues

Rindfuss

Walsh

Turner

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

540

279

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Land-change science has emerged as a foundational element of global environment change and sustainability science. It seeks to understand the human and environment dynamics that give rise to changed land uses and covers, not only in terms of their type and magnitude but their location as well. This focus requires the integration of social, natural, and geographical information sciences. Each of these broad research communities has developed different ways to enter the land-change problem, each with different means of treating the locational specificity of the critical variables, such as linking the land manager to the parcel being managed. The resulting integration encounters various data, methodological, and analytical problems, especially those concerning aggregation and inference, land-use pixel links, data and measurement, and remote sensing analysis. Here, these integration problems, which hinder comprehensive understanding and theory development, are addressed. Their recognition and resolution are required for the sustained development of land-change science.

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“…Farajalla and Vieux, 1995;Western et al, 1998;Cosh and Brutsaert, 1999) and land use type (e.g. Moody and Woodcock, 1995;Walsh et al, 2001) vary considerably depending on geographical area (climate, vegetation), extent of the area and support scale of the data. For example, it is found that the scales for soil moisture determined by Farajalla and Vieux and Cosh and Brutsaert compare favourably (about 1000 m), in contrast to the 35-60 m estimated by Western et al This may be due to incorrect, large sampling distances in the former studies resulting in an overestimation of the 'true' appropriate scale.…”

Section: Introductionmentioning

confidence: 99%

Determination and integration of appropriate spatial scales for river basin modelling

Booij

2003

Hydrological Processes

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Abstract:Appropriate spatial scales of dominant variables are determined and integrated into an appropriate model scale. This is done in the context of the impact of climate change on flooding in the River Meuse in Western Europe. The objective is achieved by using observed elevation, soil type, land use type and daily precipitation data from several sources and employing different relationships between scales, variable statistics and outputs. The appropriate spatial scale of a key variable is assumed to be equal to a fraction of the spatial correlation length of that variable. This fraction was determined on the basis of relationships between statistics and scale and an accepted error in the estimation of the statistic of 10%. This procedure resulted in an appropriate spatial scale for precipitation of about 20 km in an earlier study. The application to river basin variables revealed appropriate spatial scales for elevation, soil and land use of respectively 0Ð1, 5Ð3 and 3Ð3 km. The appropriate model scale is determined by multiplying the appropriate variable scales with their associated weights. The weights are based on SCS curve number method relationships between the peak discharge and some specific parameters like slope and curve number. The values of these parameters are dependent on the scale of each key variable. The resulting appropriate model scale is about 10 km, implying 225-250 model cells in an appropriate model of the Meuse basin meant to assess the impact of climate change on river flooding. The usefulness of the appropriateness procedure is in its ability to assess the appropriate scales of the individual key variables before model construction and integrate them in a balanced way into an appropriate model scale. Another use of the procedure is that it provides a framework for decisions about the reduction or expansion of data networks and needs.

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A multiscale analysis of LULC and NDVI variation in Nang Rong district, northeast Thailand

Cited by 115 publications

References 5 publications

Land use change modelling: current practice and research priorities

Land use change modelling: current practice and research priorities

Developing a science of land change: Challenges and methodological issues

Determination and integration of appropriate spatial scales for river basin modelling

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