【摘要】：針對城鎮(zhèn)邊緣帶在空間上存在動(dòng)態(tài)的不確定性問題,該文提出以邊緣帶土地利用特征(主要指標(biāo)為建設(shè)用地土地利用率與墾殖率)為基礎(chǔ)的邊緣帶相對靜態(tài)定界體系。采用ArcGIS Python實(shí)現(xiàn)體系中的自然斷點(diǎn)分類法和空間篩選法,對特定時(shí)間節(jié)點(diǎn)的喀斯特山區(qū)城鎮(zhèn)邊緣帶分布格局進(jìn)行自動(dòng)識別。從統(tǒng)計(jì)學(xué)、景觀學(xué)探討靜態(tài)定界體系中網(wǎng)格參數(shù)設(shè)置,并從GIS統(tǒng)計(jì)分析山區(qū)城鎮(zhèn)邊緣帶分布特征。研究表明:研究區(qū)域內(nèi)邊緣帶約80%面積分布在0~15°坡度帶;它與到核心區(qū)距離中度相關(guān);山體和河道分布對城鎮(zhèn)空間發(fā)展的連續(xù)性有影響;在交通網(wǎng)絡(luò)影響下,地貌對邊緣帶界限的影響減弱,部分邊緣帶沒有與城鎮(zhèn)核心區(qū)相鄰。因此,喀斯特山區(qū)小城鎮(zhèn)邊緣帶分布在受地塊與核心區(qū)之間距離、地形地貌、交通網(wǎng)絡(luò)空間分布綜合影響下,呈"飛地"分布。
[Abstract]:In view of the dynamic uncertainty of the urban marginal zone in space, this paper proposes a relative static boundary system based on the land use characteristics of the marginal zone (the main indicators are the land use efficiency and reclamation rate of the construction land). The natural breakpoint classification method and spatial screening method are used to realize the automatic recognition of the distribution pattern of the urban edge zone in the karst mountain area with special time node by using ArcGIS Python. The grid parameter setting in static boundary system is discussed from statistics and landscape science, and the distribution characteristics of urban edge zone in mountainous area are analyzed statistically by GIS. The study shows that about 80% of the area of the marginal zone in the study area is distributed in the 0 ~ 15 擄slope zone, which is moderately related to the distance from the core area; the distribution of mountains and rivers has an effect on the continuity of urban spatial development; under the influence of traffic network, The influence of geomorphology on the boundary of the marginal zone is weakened, and some of the marginal zones are not adjacent to the urban core area. Therefore, the marginal zones of small towns in karst mountainous areas are distributed as "enclaves" under the influence of the distance between land blocks and core areas, topography and geomorphology, and the spatial distribution of traffic networks.
【作者單位】： 貴州師范大學(xué)喀斯特研究院;貴州省山地資源研究所;
【基金】：國家自然科學(xué)基金項(xiàng)目(41261038)
【分類號】：P208

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