A statistical model of land use/cover change integrating logistic and linear models: An application to agricultural abandonment
A statistical model of land use/cover change integrating logistic and linear models: An application to agricultural abandonment
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DOI：
10.1016/j.jag.2023.103339
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
I. Estacio;C. Sianipar;K. Onitsuka;Mrittika Basu;S. Hoshino
中科院分区：
文献类型：
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作者：
I. Estacio;C. Sianipar;K. Onitsuka;Mrittika Basu;S. Hoshino
几个土地利用/覆盖变化（LUCC）模型已经被开发出来模拟未来的土地利用/覆盖变化。然而，目前的模型假设输入的非空间变量对现有的土地利用变化具有重要意义，并且仍然缺乏能够识别哪些非空间变量是土地利用变化的重要驱动因素的模型。本文提出了基于空间驱动因素的logistic模型和基于非空间驱动因素的线性模型相结合的土地利用变化统计模型。逻辑模型产生一个概率图，表示土地覆盖变化的局部概率，而线性模型产生一个全局概率阈值，表示土地覆盖变化的全局概率，通过比较两个变量，可以映射土地覆盖变化。利用该统计模型对菲律宾伊富高梯田的农业撂荒进行了模拟。统计模型揭示了梯田农业撂撂撂撂的空间和非空间驱动因素。精度评估表明，模拟地图达到了适合土地利用/土地覆盖变化模拟的精度，表明统计模型可作为预测未来土地利用/土地覆盖变化的潜在工具。
Several land use/cover change (LUCC) models have been developed to simulate future LUCC. However, current models work with the assumption that the input non-spatial variables are significant to the LUCC in hand and there is still a lack of model that could identify which non-spatial variables are significant drivers of LUCC. This paper presents a statistical model of LUCC that integrates a logistic model based on spatial drivers and a linear model based on non-spatial drivers. The logistic model produces a probability map that represents local probabilities of LUCC while the linear model produces a global probability threshold that represents a global probability of LUCC, and by comparing the two variables, LUCC is mapped. The statistical model was utilized to model agricultural abandonment in the Ifugao rice terraces, Philippines. Statistical modeling identified the significant spatial and non-spatial drivers of agricultural abandonment in the terraces. Accuracy assessment showed that simulated maps achieved accuracies suitable for LUCC simulation, demonstrating that the statistical model can be a potential tool for prediction of future LUCC.