土地利用变化研究经历了近30年的快速发展,学者基于不同建模目标构建出多种土地利用变化模型,实现了从数量模拟到时空格局模拟,从单一模型向多种模型耦合的跨越。当前研究主要在元胞自动机(Cellular Automata, CA)模型和CLUE-S(Conversi...土地利用变化研究经历了近30年的快速发展,学者基于不同建模目标构建出多种土地利用变化模型,实现了从数量模拟到时空格局模拟,从单一模型向多种模型耦合的跨越。当前研究主要在元胞自动机(Cellular Automata, CA)模型和CLUE-S(Conversion of Land Use and its Effects at Small region extent)模型的基础上进行改进,马尔科夫模型、系统动力学(System Dynamics, SD)模型、Logistic回归和随机森林等均可计算CA模型和CLUE-S模型中所需的土地利用需求,多标准评价、地理加权回归、多主体模型以及人工神经网络等方法也多被用于CA模型的扩展,而CLUE-S的改进则存在模型本身系列的升级。这些模型广泛应用于各种区域和尺度土地利用变化预测实例研究并研发软件系统和数据集。驱动力分析主要从自然因素与人文因素两方面进行,人文因素是引发土地利用变化的主要因素。在目前的研究中,由于技术手段的限制,仍然存在时空尺度、数据误差、数据整合的不确定性等问题。未来土地利用变化模拟研究应进一步发挥大数据技术优势,推动土地利用变化模拟研究朝向精细化、多元化方向发展。结合生态环境领域实际问题,深挖土地利用变化与其生态环境效应之间的互馈机制,将研究视角从探究人类活动对土地利用变化的影响逐渐转向二者相互作用,最终促进人地关系协调发展。展开更多
There are significant differences between urban and rural bed-and-breakfasts(B&Bs)in terms of customer positioning,economic strength and spatial carrier.Accurately identifying the differences in spatial characteri...There are significant differences between urban and rural bed-and-breakfasts(B&Bs)in terms of customer positioning,economic strength and spatial carrier.Accurately identifying the differences in spatial characteristics and influencing factors of each type,is essential for creating urban and rural B&B agglomeration areas.This study used density-based spatial clustering of applications with noise(DBSCAN)and the multi-scale geographically weighted regression(MGWR)model to explore similarities and differences in the spatial distribution patterns and influencing factors for urban and rural B&Bs on the Jiaodong Peninsula of China from 2010 to 2022.The results showed that:1)both urban and rural B&Bs in Jiaodong Peninsula went through three stages:a slow start from 2010 to 2015,rapid development from 2015 to 2019,and hindered development from 2019 to 2022.However,urban B&Bs demonstrated a higher development speed and agglomeration intensity,leading to an increasingly evident trend of uneven development between the two sectors.2)The clustering scale of both urban and rural B&Bs continued to expand in terms of quantity and volume.Urban B&B clusters characterized by a limited number,but a higher likelihood of transitioning from low-level to high-level clusters.While the number of rural B&B clusters steadily increased over time,their clustering scale was comparatively lower than that of urban B&Bs,and they lacked the presence of high-level clustering.3)In terms of development direction,urban B&B clusters exhibited a relatively stable pattern and evolved into high-level clustering centers within the main urban areas.Conversely,rural B&Bs exhibited a more pronounced spatial diffusion effect,with clusters showing a trend of multi-center development along the coastline.4)Transport emerged as a common influencing factor for both urban and rural B&Bs,with the density of road network having the strongest explanatory power for their spatial distribution.In terms of differences,population agglomeration had a positive impact on the di展开更多
文摘土地利用变化研究经历了近30年的快速发展,学者基于不同建模目标构建出多种土地利用变化模型,实现了从数量模拟到时空格局模拟,从单一模型向多种模型耦合的跨越。当前研究主要在元胞自动机(Cellular Automata, CA)模型和CLUE-S(Conversion of Land Use and its Effects at Small region extent)模型的基础上进行改进,马尔科夫模型、系统动力学(System Dynamics, SD)模型、Logistic回归和随机森林等均可计算CA模型和CLUE-S模型中所需的土地利用需求,多标准评价、地理加权回归、多主体模型以及人工神经网络等方法也多被用于CA模型的扩展,而CLUE-S的改进则存在模型本身系列的升级。这些模型广泛应用于各种区域和尺度土地利用变化预测实例研究并研发软件系统和数据集。驱动力分析主要从自然因素与人文因素两方面进行,人文因素是引发土地利用变化的主要因素。在目前的研究中,由于技术手段的限制,仍然存在时空尺度、数据误差、数据整合的不确定性等问题。未来土地利用变化模拟研究应进一步发挥大数据技术优势,推动土地利用变化模拟研究朝向精细化、多元化方向发展。结合生态环境领域实际问题,深挖土地利用变化与其生态环境效应之间的互馈机制,将研究视角从探究人类活动对土地利用变化的影响逐渐转向二者相互作用,最终促进人地关系协调发展。
基金Under the auspices of National Social Science Foundation of China (No.21BJY202)。
文摘There are significant differences between urban and rural bed-and-breakfasts(B&Bs)in terms of customer positioning,economic strength and spatial carrier.Accurately identifying the differences in spatial characteristics and influencing factors of each type,is essential for creating urban and rural B&B agglomeration areas.This study used density-based spatial clustering of applications with noise(DBSCAN)and the multi-scale geographically weighted regression(MGWR)model to explore similarities and differences in the spatial distribution patterns and influencing factors for urban and rural B&Bs on the Jiaodong Peninsula of China from 2010 to 2022.The results showed that:1)both urban and rural B&Bs in Jiaodong Peninsula went through three stages:a slow start from 2010 to 2015,rapid development from 2015 to 2019,and hindered development from 2019 to 2022.However,urban B&Bs demonstrated a higher development speed and agglomeration intensity,leading to an increasingly evident trend of uneven development between the two sectors.2)The clustering scale of both urban and rural B&Bs continued to expand in terms of quantity and volume.Urban B&B clusters characterized by a limited number,but a higher likelihood of transitioning from low-level to high-level clusters.While the number of rural B&B clusters steadily increased over time,their clustering scale was comparatively lower than that of urban B&Bs,and they lacked the presence of high-level clustering.3)In terms of development direction,urban B&B clusters exhibited a relatively stable pattern and evolved into high-level clustering centers within the main urban areas.Conversely,rural B&Bs exhibited a more pronounced spatial diffusion effect,with clusters showing a trend of multi-center development along the coastline.4)Transport emerged as a common influencing factor for both urban and rural B&Bs,with the density of road network having the strongest explanatory power for their spatial distribution.In terms of differences,population agglomeration had a positive impact on the di