Authors:
François-Rémi Mazy
1
and
Pierre-Yves Longaretti
1
;
2
Affiliations:
1
Université Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, 38000 Grenoble, France
;
2
Université Grenoble Alpes, CNRS-INSU, IPAG, CS 40700, 38052 Grenoble, France
Keyword(s):
Land Use Change, Land Cover Change, LULC, Model Development, Model Evaluation, Model Accuracy, Density Estimation, Calibration, Allocation, Map Simulation.
Abstract:
The use of spatially explicit land use and land cover (LULC) change models is widespread in environmental sciences and of interest in public decision-help. However, it appears that these models suffer from significant biases and shortcomings, the sources of which can be mathematical, conceptual or algorithmic. We formalize a modeling environment that distinguishes a calibration-estimation module and an allocation module. We propose an accurate calibration-estimation method based on kernel density estimation and detail an unbiased allocation algorithm. Moreover, a method of evaluation of LULC change models is presented and allows us to compare them on various fronts (accuracy, biases, computational efficiency). A case study based on a real land use map but with known (enforced) transition probabilities is used. It appears that the estimation error of the methods we propose is substantially improved over the best existing software. Moreover, these methods require the specification of v
ery few parameters by the user, and are numerically efficient. This article presents an overview of our LULC change modeling framework; its various formal and algorithmic constituents will be detailed in forthcoming papers.
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