A mathematical programming approach for downscaling multi-layered multi-constraint land-use models

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2023-07-27 DOI:10.1080/13658816.2023.2241144

R. Ramos, M. Scarabello, Wanderson Costa, Pedro Ribeiro de Andrade Neto, A. Soterroni, F. Ramos

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引用次数: 0

Abstract

Abstract Land-use and land-cover change (LULCC) models are important tools for environmental policy planning. LULCC models are frequently constrained to the generation of projections at a specific resolution. However, subsequent studies or models may require finer resolutions. In this work, a downscaling method for LULCC models is proposed that uses a mathematical programming approach to disaggregate the multiple layers of the land-use change projections while respecting a series of constraints. The method is calibrated and validated with MapBiomas data for the years 2000 and 2018 converted for the GLOBIOM-Brazil model, successfully predicting land-use at a finer resolution. Also, as proof of concept, the calibrated model is also applied for GLOBIOM-Brazil projections for 2050. This paper advances the state-of-the-art by proposing and testing a downscaling method using a mathematical programming approach with spatial effects, that operates on multi-layered land-use projections with a range of constraints while allowing flexibility on the number and type of the specific layers and constraints.

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一种用于缩减多层多约束土地利用模型的数学规划方法

土地利用和土地覆盖变化(LULCC)模型是环境政策规划的重要工具。LULCC模型经常被限制在以特定分辨率生成预测。然而，后续的研究或模型可能需要更精细的分辨率。本文提出了一种LULCC模型的降尺度方法，该方法使用数学规划方法对土地利用变化预测的多层进行分解，同时尊重一系列约束条件。该方法使用MapBiomas 2000年和2018年的数据进行校准和验证，转换为globiomo - brazil模型，成功地以更精细的分辨率预测土地利用。此外，作为概念的证明，校正后的模型也应用于2050年的globiomo - brazil预测。本文通过使用具有空间效应的数学规划方法提出并测试了一种缩小比例的方法，该方法适用于具有一系列约束的多层土地利用预测，同时允许在特定层和约束的数量和类型上具有灵活性，从而推进了最先进的技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.