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1. chinaXiv:201911.00018 [pdf]

基于CA-Markov模型的多时间跨度土地利用变化模拟

靳含; 杨爱民; 夏鑫鑫; 朱磊; 张青青
Subjects: Geosciences >> Geography

土地利用/覆被变化(Land Use and Cover Change, LUCC)模拟是LUCC研究的主要内容和重要手段。时间间隔是模拟过程中的重要参数,对模拟结果精度有何影响,有待深入研究。以新疆玛纳斯河流域典型绿洲区四道河子镇为例,基于遥感影像提取1975、1985、1995、2000、2005、2010年和2015年的土地利用数据,分别以20 a、15 a、10 a和5 a为时间间隔构建CA-Markov模型,模拟2015年土地利用结构,定量探讨时间间隔对CA-Markov模型精度的影响。结果表明:1975—2015年,四道河子镇LUCC以耕地和草地为主,期间耕地、建设用地迅速扩张,林地、草地和未利用地大幅减少,水域在1985—2000年呈现小幅增长。耕地的增加和草地及林地的减少是研究区近40 a LUCC最显著的特征。对比模拟结果与实际结果,时间间隔为20 a、15 a、10 a、5 a的TFOM分别为70.35%,69.18%,76.32%和88.00%。基于2005—2010年转移概率的模拟结果更接近于2015年实际结果,适合模拟四道河子镇未来的土地利用变化。土地利用模拟应依据区域LUCC特征确定最佳的时间间隔,提高模拟精度。

submitted time 2019-11-15 From cooperative journals:《干旱区地理》 Hits6486Downloads428 Comment 0

2. chinaXiv:201810.00181 [pdf]

Evaluating and modeling the spatiotemporal pattern of regional-scale salinized land expansion in highly sensitive shoreline landscape of southeastern Iran

Mohammad, SHAFIEZADEH; Hossein, MORADI; Sima, FAKHERAN
Subjects: Geosciences >> History of Geosciences

Taking an area of about 2.3×104 km2 of southeastern Iran, this study aims to detect and predict regional-scale salt-affected lands. Three sets of Landsat images, each set containing 4 images for 1986, 2000, and 2015 were acquired as the main source of data. Radiometric, atmospheric and cutline blending methods were used to improve the quality of images and help better classify salinized land areas under the support vector machine method. A set of landscape metrics was also employed to detect the spatial pattern of salinized land expansion from 1986 to 2015. Four factors including distance to sea, distance to sea water channels, slope, and elevation were identified as the main contributing factors to land salinization. These factors were then integrated using the multi-criteria evaluation (MCE) procedure to generate land sensitivity map to salinization and also to calibrate the cellular-automata (CA) Markov chain (CA-Markov) model for simulation of salt-affected lands up to 2030, 2040 and 2050. The results of this study showed a dramatic dispersive expansion of salinized land from 7.7 % to 12.7% of the total study area from 1986 to 2015. The majority of areas prone to salinization and the highest sensitivity of land to salinization was found to be in the southeastern parts of the region. The result of the MCE-informed CA-Markov model revealed that 20.3% of the study area is likely to be converted to salinized lands by 2050. The findings of this research provided a view of the magnitude and direction of salinized land expansion in a past-to-future time period which should be considered in future land development strategies.

submitted time 2018-10-29 From cooperative journals:《Journal of Arid Land》 Hits3073Downloads650 Comment 0

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