The impact of class resolution in land use change models

Conway, Tenley M.

doi:10.1016/j.compenvurbsys.2009.02.001

Cited by 25 publications

(17 citation statements)

References 42 publications

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“…It also strongly underlines that there may be serious implications of using different datasets to define urban in these types of models. There may also be variations in the processes that drive land conversion according to different urban land use/land cover types (Conway, 2009). In addition to different definitions of urban in the two datasets, there were differences in scale imposed during spatial aggregation by partial census block group versus the boundaries of the land use layers, and we asked how these differences in definition and scale would affect simulated development.…”

Section: Discussionmentioning

confidence: 99%

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

Syphard

Clarke

Franklin

et al. 2011

Journal of Environmental Management

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Section: Discussionmentioning

confidence: 99%

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

Syphard

Clarke

Franklin

et al. 2011

Journal of Environmental Management

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“…La definición de las clases de usos del suelo a utilizar tiene un efecto importante en el resultado del modelo, especialmente en modelos que intentan captar el proceso, no sólo el cambio. El uso de una sola clase puede derivar en que el modelo no esté bien calibrado, pero, por otra parte, tener numerosas clases puede reducir su precisión debido a la dificultad de capturar procesos que no son comunes (Conway, 2009). Del mismo modo, cuando se posee una única clase de uso del suelo, donde se estudia la presencia y ausencia de éste, y se desea predecir únicamente dicho cambio, el modelo puede generar menos error que si se estudian varias clases de usos del suelo conjuntamente, ya que hay menos posibilidades de que se convierta a una categoría errónea.…”

Section: Problemas O Dificultadesunclassified

Revisión y análisis de estudios de modelos de cambios de usos del suelo y de escenarios a futuro

Gallardo

2018

Geograph

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En las últimas décadas se ha producido un gran desarrollo de técnicas y modelos para la captura y el análisis de dinámicas de usos del suelo. Dicho interés se demuestra en los diversos programas institucionales y las numerosas investigaciones que se han llevado a cabo con el objeto principal de valorar y abordar un desarrollo sostenible del territorio. La sostenibilidad tiene implicaciones muy diversas, por lo que dichos estudios son también muy variados dependiendo del objetivo que se pretende alcanzar. Los modelos se han hecho cada vez más complejos, desde simples extrapolaciones a modelos estadísticos-matemáticos que compilan varias técnicas. Se presenta una revisión bibliográfica de trabajos sobre modelos de cambios de usos del suelo y de escenarios a futuro. Se definen las grandes tipologías de modelos que existen, las metodologías, factores explicativos, temáticas y modelos empleados, internacionalmente y en España. Se presentan también los grandes problemas y retos que afronta esta materia.

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“…Many researchers and professionals have used diverse land use change models to explore the drivers and patterns of land use change, to make possible future scenarios and to provide appropriate policies affecting the changes by analyzing the causes and consequences of land use changes [31][32][33][34][35]. Most existing land use change models, however, have been criticized for not being able to provide reliable accuracy assessment processes of the output effectively [36]. Since doubt and questions about the outputs still remain, the models can have difficulties adapting to local circumstances due to reliability and accuracy issues [37].…”

Section: Literature Gaps and Research Objectivesmentioning

confidence: 99%

“…Although LUCC models have risen in popularity, they can be criticized for not always being able to provide highly reliable accuracy outputs due to the ineffective use of upfront calibration methods [36]. Due to this issue, the models can have difficulty in adapting to local circumstances and communities [37].…”

Section: Accuracy and Reliabilitymentioning

confidence: 99%

Forecasting Urban Vacancy Dynamics in a Shrinking City: A Land Transformation Model

Lee

Newman

2017

IJGI

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Abstract:In the past two centuries, many American urban areas have experienced significant expansion in both populating and depopulating cities. The pursuit of bigger, faster, and more growth-oriented planning parallels a situation where municipal decline has also been recognized as a global epidemic. In recent decades many older industrial cities have experienced significant depopulation, job loss, economic decline, and massive increases in vacant and abandoned properties due primarily to losses in industry and relocating populations. Despite continuous economic decline and depopulation, many of these so-called 'shrinking cities' still chase growth-oriented planning policies, due partially to inabilities to accurately predict future urban growth/decline patterns. This capability is critical to understanding land use alternation patterns and predicting future possible scenarios for the development of more proactive land use policies dealing with urban decline and regeneration. In this research, the city of Chicago, Illinois, USA is used as a case site to test an urban land use change model that predicts urban decline in a shrinking city, using vacant land as a proxy. Our approach employs the Land Transformation Model (LTM), which combines Geographic Information Systems and artificial neural networks to forecast land use change. Results indicate that the LTM is a good resource to simulate urban vacant land changes. Mobility and housing market conditions seem to be the primary variables contributing to decline.

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The impact of class resolution in land use change models

Cited by 25 publications

References 42 publications

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

Revisión y análisis de estudios de modelos de cambios de usos del suelo y de escenarios a futuro

Forecasting Urban Vacancy Dynamics in a Shrinking City: A Land Transformation Model

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