Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

Millington, James D.A.; Perry, George L.; Calcerrada, Raúl Romero

doi:10.1007/s10021-007-9020-4

Cited by 128 publications

(84 citation statements)

References 63 publications

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“…The proposed methods for mapping local accuracies in land cover change maps can be usefully explored in combination with work on landscape dynamics monitoring and modelling, such as that described by Millington et al [1] and Rutherford et al [2], and related research efforts [28,[30][31][32]. Firstly, results from maps of predicted changes using methods developed in [1,2] may well be evaluated with respect to their local accuracies by using the methods proposed in this paper.…”

Section: Discussionmentioning

confidence: 99%

“…For example, it is necessary to have accurate information about land cover dynamics in order to quantify the extent and rate of land cover change and develop models to relate change-driving processes to observed landscape changes. Relevant case studies from the northern Mediterranean Basin, the European Alps and Inner Mongolia can be found in Millington et al [1], Rutherford et al [2] and Wu et al [3], respectively.…”

Section: Introductionmentioning

confidence: 99%

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Integrating Logistic Regression and Geostatistics for User-Oriented and Uncertainty-Informed Accuracy Characterization in Remotely-Sensed Land Cover Change Information

Zhang

Mei

2016

IJGI

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Accuracy is increasingly recognized as an important dimension in geospatial information and analyses. A strategy well suited for map users who usually have limited information about map lineages is proposed for location-specific characterization of accuracy in land cover change maps. Logistic regression is used to predict the probabilities of correct change categorization based on local patterns of map classes in the focal three by three pixel neighborhood centered at individual pixels being analyzed, while kriging is performed to make corrections to regression predictions based on regression residuals at sample locations. To promote uncertainty-informed accuracy characterization and to facilitate adaptive sampling of validation data, standard errors in both regression predictions and kriging interpolation are quantified to derive error margins in the aforementioned accuracy predictions. It was found that the integration of logistic regression and kriging leads to more accurate predictions of local accuracies through proper handling of spatially-correlated binary data representing pixel-specific (in)correct classifications than kriging or logistic regression alone. Secondly, it was confirmed that pixel-specific class labels, focal dominances and focal class occurrences are significant covariates for regression predictions at individual pixels. Lastly, error measures computed of accuracy predictions can be used for adaptively and progressively locating samples to enhance sampling efficiency and to improve predictions. The proposed methods may be applied for characterizing the local accuracy of categorical maps concerned in spatial applications, either input or output.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrating Logistic Regression and Geostatistics for User-Oriented and Uncertainty-Informed Accuracy Characterization in Remotely-Sensed Land Cover Change Information

Zhang

Mei

2016

IJGI

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“…It is another thing to establish a causal linkage between population growth and deforestation. Unfortunately, the conflation of correlation and causation is an all-too-common problem in land -change studies generally (Kaimowitz 1997, Lambin 2000, Millington et al 2007). …”

Section: Temporal Dimensions and Causal Claims It Is Onementioning

confidence: 99%

Modeling human agency in land change in Madagascar: A review and prospectus

McConnell¹

2009

MCD

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Au fur et à mesure que les modélisations rendent mieux compte du rôle de tels facteurs, elles devraient alors permettre d'évaluer plus précisément la pertinence des efforts déployés pour protéger la biodiversité. Cet aspect peut être envisagé avec un certain espoir bien que de manière préliminaire ; la conversion des forêts à des usages agricoles dans les aires protégées semble être réduite par rapport à cette même dynamique

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“…This complex process is at the origin of the abandonment of remote rural areas with poor accessibility, which allows the expansion of wild low vegetation and forest (Antrop, 2004). Specifically, the abandonment of low-intensity agricultural lands and grazing practices has caused the increase in forest cover and scrubland vegetation (Poyatos et al, 2003;Millington et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Global assessment of rural–urban interface in Portugal related to land cover changes

Tonini

Parente

Pereira

2018

Nat. Hazards Earth Syst. Sci.

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Abstract. The rural-urban interface (RUI), known as the area where structures and other human developments meet or intermingle with wildland and rural area, is at present a central focus of wildfire policy and its mapping is crucial for wildfire management. In the Mediterranean Basin, humans cause the vast majority of fires and fire risk is particularly high in the proximity of infrastructure and of rural/wildland areas. RUI's extension changes under the pressure of environmental and anthropogenic factors, such as urban growth, fragmentation of rural areas, deforestation and, more in general, land use/land cover change (LULCC). As with other Mediterranean countries, Portugal has experienced significant LULCC in the last decades in response to migration, rural abandonment, ageing of population and trends associated with the high socioeconomic development. In the present study, we analyzed the LULCC occurring in this country in the 1990-2012 period with the main objective of investigating how these changes affected RUI's evolution. Moreover, we performed a qualitative and quantitative characterization of burnt areas within the RUI in relation to the observed changes. Obtained results disclose important LULCC and reveal their spatial distribution, which is far from uniform within the territory. A significant increase in artificial surfaces was registered near the main metropolitan communities of the northwest, littoral-central and southern regions, whilst the abandonment of agricultural land near the inland urban areas led to an increase in uncultivated semi-natural and forest areas. Within agricultural areas, heterogeneous patches suffered the greatest changes and were the main contributors to the increase in urban areas; moreover, this land cover class, together with forests, was highly affected by wildfires in terms of burnt area. Finally, from this analysis and during the investigated period, it appears that RUI increased in Portugal by more than two-thirds, while the total burnt area decreased by one-third; nevertheless, burnt area within RUI doubled, which emphasizes the significance of RUI monitoring for land and fire managers.

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Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

Cited by 128 publications

References 63 publications

Integrating Logistic Regression and Geostatistics for User-Oriented and Uncertainty-Informed Accuracy Characterization in Remotely-Sensed Land Cover Change Information

Integrating Logistic Regression and Geostatistics for User-Oriented and Uncertainty-Informed Accuracy Characterization in Remotely-Sensed Land Cover Change Information

Modeling human agency in land change in Madagascar: A review and prospectus

Global assessment of rural–urban interface in Portugal related to land cover changes

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