Comparing the input, output, and validation maps for several models of land change

  title={Comparing the input, output, and validation maps for several models of land change},
  author={Robert Gilmore Pontius and Wideke Boersma and Jean-Christophe Castella and Keith C. Clarke and Ton C. M. de Nijs and Charles Dietzel and Zengqiang Duan and {\'E}ric Fotsing and Noah Charles Goldstein and Kasper Kok and Eric Koomen and Christopher D. Lippitt and William J. Mcconnell and Alias Mohd Sood and Bryan C. Pijanowski and Snehal Pithadia and Sean Sweeney and Tran Ngoc Trung and A. Veldkamp and Peter H. Verburg},
  journal={The Annals of Regional Science},
This paper applies methods of multiple resolution map comparison to quantify characteristics for 13 applications of 9 different popular peer-reviewed land change models. Each modeling application simulates change of land categories in raster maps from an initial time to a subsequent time. For each modeling application, the statistical methods compare: (1) a reference map of the initial time, (2) a reference map of the subsequent time, and (3) a prediction map of the subsequent time. The three… 
Validating models of one-way land change: an example case of forest insect disturbance
The objective is to develop a method for validation of one-way land change models, such that the method provides objective information about the spatial distribution of errors, and to reveal that the simulations underestimated change near initial points of spread.
Assessment of Land-Use Scenarios at a National Scale Using Intensity Analysis and Figure of Merit Components
The results revealed the cause of the low accuracy of the national scale land-use scenarios as well as priority solutions, such as aligning the underlying spatial vegetation maps and improving the model to reduce two types of disagreement between the simulation and reference maps.
Assessing the Accuracy of Changes in Spatial Explicit Land Use Change Models
Results of land use change models are often assessed by comparing simulation results with actual land use data. For this the Kappa coefficient of agreement is a common algorithm for map comparison;
Diagnostic tools to evaluate a spatial land change projection along a gradient of an explanatory variable
A method to quantify the goodness-of-fit of a land change projection along a gradient of an explanatory variable, by classifying pixels as one of four types: null successes, false alarms, hits, and misses is proposed.
Uncertainty in the difference between maps of future land change scenarios
Comparing the output maps of different scenarios of future land change in a manner that contrasts two different approaches to account for the uncertainty of the simulated projections shows that a productive approach is to use the simpler method to distinguish clearly between variations in the scenario maps that are due to scenario assumptions versus variations due to the simulation model.
Comparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change Models
Compared the quantity, allocation, and configuration accuracy of four inductive pattern-based spatial allocation land change models (SLEUTH, GEOMOD, Land Change Modeler (LCM), and FUTURES), which suggest some models may better simulate quantity and allocation at the trade-off of configuration accuracy, and vice versa.
Evaluation of Model Validation Techniques in Land Cover Dynamics
It is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research.


Uncertainty in Extrapolations of Predictive Land-Change Models
A technique to extrapolate the anticipated accuracy of a prediction of land-use and land-cover change (LUCC) to any point in the future and estimates how fast the decay in accuracy will occur based on prior model performance is given.
Visualizing certainty of extrapolations from models of land change
A method to estimate and to visualize the certainty of land change models as they extrapolate beyond the time interval for which empirical data exist and on the assumption that the model’s accuracy approaches randomness as it predicts farther into the future.
Evaluating impact of spatial scales on land use pattern analysis in Central America
Constructing land-use maps of the Netherlands in 2030.