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中国建设用地的坡谱演化规律与爬坡影响

本站小编 Free考研考试/2021-12-29
周亮,1,2, 党雪薇1,3, 周成虎2, 王波4, 魏伟51.兰州交通大学测绘与地理信息学院,兰州 730070
2.中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100049
3.地理国情监测技术应用国家地方联合工程研究中心,兰州730070
4.中山大学地理科学与规划学院,广州 510275
5.西北师范大学地理与环境科学学院,兰州 730070

Evolution characteristics of slope spectrum and slope-climbing effects of built-up land in China

ZHOU Liang,1,2, DANG Xuewei1,3, ZHOU Chenghu2, WANG Bo4, WEI Wei51. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
3. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China
4. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
5. College of Geography and Environment Sciences, Northwest Normal University, Lanzhou 730070, China

收稿日期:2020-08-3修回日期:2021-04-27网络出版日期:2021-07-25
基金资助:教育部人文社会科学研究青年基金项目.17YJCZH268
国家自然科学基金项目.41961027
兰州交通大学“百名青年优秀人才培养计划”基金项目.


Received:2020-08-3Revised:2021-04-27Online:2021-07-25
Fund supported: Science Foundation for the Excellent Youth Scholars of Ministry of Education of China.17YJCZH268
National Natural Science Foundation of China.41961027
Foundation of A Hundred Youth Talents Training Program of Lanzhou Jiaotong University.

作者简介 About authors
周亮(1983-), 男, 甘肃天水人, 博士, 教授, 硕士生导师, 主要从事城市与区域可持续发展、城市遥感研究。E-mail: zhougeo@126.com







摘要
城镇建设用地规模与结构变化是国土空间开发与规划研究的基础。以往相关研究更关注建设用地水平空间扩张格局特征与模式,极少关注建设用地三维梯度上的“爬坡”特征规律与影响。因此,本文基于Google Earth Engine（GEE）,并结合高精度地形数据与土地利用数据,在建设用地坡谱概念基础上,首次构建了平均建设用地爬坡指数（ABCI）,系统地分析了1990—2018年中国建设用地坡谱在国家、区域、省级和城市4个尺度上的变化特征与规律并深入剖析建设用地爬坡的空间影响。结果显示：① 1990—2018年中国坡度5°以上地区建设用地面积增长了1.43倍,比例由10.25%上升至14.81%。其中2010—2015年是建设用地爬坡发展最迅速与规模最大的时期,且中西部地区建设用地爬坡最为显著。② 依据平均建设用地爬坡指数与上限坡度变化,可将中国34个省（自治区、直辖市）划分为高爬坡型、低爬坡型和水平扩展型3类,其中高爬坡型省份占50%以上,水平扩展型省份仅有7个,在空间上呈现“东南—西北”的两极分布特征。③ 1990—2010年爬坡型城市以山地与丘陵地貌城市为主,2010年后少数民族聚居区及低丘缓坡开发试点城市成为建设用地爬坡的主力。④ 建设用地爬坡在一定程度上能够减少建设用地扩张对平原优质耕地与生态用地的胁迫和侵占,缓解建设用地供需矛盾,但是无规划约束的开发和房地产驱动的“削山造地”则会导致地质灾害和生态环境风险的增加。
关键词： 空间规划;坡谱;城市三维;城市扩张;GEE;中国

Abstract
The changes in the scale and structure of built-up land is the basis for spatial development and planning of the national territory. Previous studies mainly focused on the characteristics and patterns of the horizontal expansion of built-up land, but little attention has been given to the "three-dimensional" gradient characteristics and effects of built-up land (such as slope-climbing). Therefore, based on Google Earth Engine, this study, for the first time as far as we know, uses DEM and land use data to draw built-up land slope spectrums and calculates the average built-up land climbing index (ABCI). The gradient characteristics and laws of the slope climbing of China's built-up land from 1990 to 2018 at the national, regional, provincial, and urban scales are systematically analyzed and the various spatial effects are explored. The results show that: (1) From 1990 to 2018, the area of built-up land with slope angle above 5° in China increased by 1.43 times, and the proportion of the total built-up land area rose from 10.25% to 14.81%. Particularly, the 2010-2015 period witnessed the fastest and largest slope-climbing development of built-up land in China. Moreover, the slope-climbing intensities in the central and western regions are higher than that in other regions. (2) According to the average built-up land climbing index (ABCI) and the upper limited slope angle change (ULSC), the 34 provinces (autonomous regions and municipalities) in China can be divided into three types: high-climbing, low-climbing, and horizontally expanding. Among them, the number of high-climbing provinces accounts for more than 50% of the total. And seven horizontally-expanding provinces present the distribution characteristics of "southeast-northwest" in space. (3) Before 2010, the cities with slope-climbing phenomenon were mainly mountainous cities. However, ethnic minority settlements and low-hill and gentle slope development pilot cities became the main force for the slope-climbing of built-up land after 2010. (4) The slope-climbing of built-up land can reduce the occupation of plain arable land and ecological land by built-up land expansion to a certain extent, and thus alleviate the contradiction between supply and demand of build-up land. However, it is worth noting that development and construction without reasonable plans and bulldozing mountains to build cities driven by real estate can also lead to increased geological disasters and ecological risks.
Keywords：spatial planning;slope spectrum;three-dimensional city;urban expansion;GEE;China


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本文引用格式
周亮, 党雪薇, 周成虎, 王波, 魏伟. 中国建设用地的坡谱演化规律与爬坡影响. 地理学报[J], 2021, 76(7): 1747-1762 doi:10.11821/dlxb202107013
ZHOU Liang, DANG Xuewei, ZHOU Chenghu, WANG Bo, WEI Wei. Evolution characteristics of slope spectrum and slope-climbing effects of built-up land in China. Acta Geographica Sinice[J], 2021, 76(7): 1747-1762 doi:10.11821/dlxb202107013


1 引言

建设用地扩张是人类主导的最迅速且不可逆转的土地利用变化过程[1],对工业化、城市化以及经济社会发展起到积极保障作用[2]。建设用地按用途可划分为居住用地、商服用地、工矿仓储用地、公共管理与公共服务用地、交通运输用地以及军事设施等特殊用地[3],从构成结构上可分为城市建设用地与农村居民点[4]。其中,城市建设用地扩张是城市化在地理空间上的直接体现[5]。目前,全球土地城镇化速度远高于人口城镇化速度,全球城市用地的平均扩张速度已达到其人口增长速度的2倍。2030年全球城市人口将超过50亿[6],城市土地面积将增加1.20×106 km2,近50%的新增城市用地集中在亚洲[7]。而快速城镇化引起的乡村人口减少[8],“空心村”等现象日益严重,农村宅基地“建新不拆旧”的思想导致新建住宅向外扩展,出现“外扩内空”的不良演化过程[9,10],对乡村生态景观造成一定的影响[11]。整体而言,城乡建设用地的剧烈变化直接和间接地驱动全球环境的变化[12],引发了不可持续的生产和消费方式,造成水资源浪费、高质量耕地流失、生境破坏、生物多样性丧失等生态问题[13,14,15,16]。因此,探究建设用地动态变化及其影响已成为当前国土空间规划与治理研究的重要课题[17],也是实现“包容、安全、有抵御灾害能力和可持续的城市和人类住区”的全球可持续发展目标的关键。

处于经济快速发展期和社会转型期的中国对建设用地的需求急剧增加[18]。中国建设用地面积由1984年的2.48×107 hm2增长至2015年的3.86×107 hm2,年均增长率达1.44%[2]。其中,城市建设用地面积扩张更为迅速,1981—2018年由6.72×103 km2增长至5.61×104 km2,年均增长率达5.90%[19]。第七次人口普查数据显示,中国人口已达14.11亿人,预计2030年将超过14.6亿[6]。随着人口城镇化的持续推进,未来很长一段时间内,中国建设用地的需求仍呈现一定的刚性增长趋势,生态用地、耕地和建设用地之间的矛盾将会更加剧烈。《2019年新型城镇化建设重点任务》指出要统筹优化国土空间布局,推动城镇高质量发展,强化三区三线管控,促进城市精明增长。目前,针对建设用地高度紧缺,以及建设用地侵占优质耕地问题,决策者先后采取了城乡建设用地增减挂钩、国土空间综合开发、城市增长边界与耕地保护红线划定、低丘缓坡荒滩等未利用土地开发利用试点等强有力的政策措施,力图在保障建设用地有效供给的同时,减少优质良田占用,缓解土地空间矛盾,从而实现国土空间的可持续发展。

建设用地爬坡是指通过平整和梯化改造坡地进行城乡建设,即主要在具有一定规模的、相对高差小于200 m、平均坡度小于25°以国有未利用土地为主的丘陵地,通过工程和生物措施进行综合建设的过程[20],在空间上表现为建设用地向坡度大的地区发展。建设用地爬坡现象在全球范围内普遍存在。例如,智利圣地亚哥的城市扩张从冲积平原扩展到安第斯山脉的山麓地带[21];2011年日本大地震之后,日本为避免海啸的侵袭,将易受灾地区的住宅搬迁至高地[22];中国陕西延安、湖北十堰、甘肃兰州等城市则通过开山填挖来弥补城市建设用地的短缺[23]。通过梳理已有文献可将建设用地扩张分为水平扩展和垂直爬升2个阶段：① 早期扩张多发生在平原地区,受地形约束较小,以“摊大饼”模式扩张。以城市建设用地或城市用地为主要分析对象的研究更倾向于探究城市形态的测度与演变[24,25,26],外延、内填、跳跃式等扩张变化规律[27,28,29],动力机制[30,31],模拟与预测[32,33]以及城市化与生态景观关系[34,35]。而有关农村建设用地（或农村居民点）的研究集中在时空变化及驱动力分析[36],乡村转型与空间重构[37]、乡村聚落整治[38]等方面。② 随着人口的快速增长、土地矛盾的加剧,建设用地的三维格局逐渐发生变化。建设用地发展的过程是垂直增长与水平扩张之间的持续交替相互作用[39],而有关建设用地三维扩张的研究主要集中在城市建设用地的垂直扩张,垂直城市发展（Vertical Urban Development）作为提高城市紧凑度的一种增长模式[40],逐渐引起各国****的关注。这类研究利用城市建筑高度变化反映城市垂直扩张的速度与强度,探究城市三维空间形态扩展机制及时空分异特征[41,42,43],分析城市用地与绿色空间在垂直维度上的演变特征[44],挖掘城市三维形态对城市热环境以及局部气候变化的影响[45]。然而,建筑高度的变化并非建设用地三维形态演变的唯一方式。受洪水、海啸等自然灾害的胁迫,水库工程建设以及建设用地供给不足、人地矛盾突出等社会因素的驱动,坡地已成为重要的土地资源被开发利用。因此,亟需转变现有二维平面研究模式,借助“第三维”视角从建设用地分布的高程梯度和坡度梯度等角度,采用建设用地坡谱[46]、地形位指数[47]、地形位置指数[48]、地形起伏度、坡度变率[49]等参数探寻城乡建设用地在坡度空间的分层模式及演变特征[50,51]。

目前有关建设用地扩张的研究仍主要集中探索城市二维水平扩张模式。尽管中国山区城镇高质量发展日渐受到关注[52],但是山地空间格局的探索仍未突破二维空间[53,54],对建设用地“三维”爬坡扩张的关注更显不足,且少有研究将农村居民点发展纳入分析。仅有的建设用地爬坡研究多集中于单个省或典型城市,小尺度研究所刻画的地区性问题不具有普遍性,对国家、世界层面等大尺度范围内建设用地爬坡的特征和影响分析较少。然而,建设用地爬坡必然会对生态、耕地和地质环境造成影响,其潜在风险不容忽视,因此综合系统地分析大区域大尺度城乡建设用地爬坡现象对可持续发展尤为重要。鉴于此,本文基于谷歌地球引擎（Google Earth Engine, GEE）平台,以1990—2018年中国土地利用数据为基础,系统的分析了国家、四大经济区域、省级以及城市4个尺度的地形坡谱和建设用地坡谱,构建平均建设用地爬坡指数,并根据建设用地分布的上限坡度对建设用地扩张模式进行分类,讨论建设用地爬坡对耕地、生态用地以及地质灾害造成的影响。研究首次从“第三维”视角全面地揭示中国城乡建设用地在坡度空间上的多尺度时空演化规律,系统分析建设用地爬坡扩张引起的主要影响,有助于解决国土规划“空间冲突”问题,为最大程度规避爬坡引发的地质灾害提供科学依据,促进城市和区域包容、绿色、协调、有序和高质量发展。

2 研究方法

2.1 数据来源

本文从国家、四大经济区域、省级与城市4个空间尺度进行研究,时间跨度为1990—2018年,其中1990—2015年以每5年为一个时间段,2015—2018年单独为一个时间段。国家、省、市边界矢量数据来自全国地理信息资源目录服务系统（http://www.webmap.cn）提供的中国1∶100万基础地理数据集。土地利用数据采用中国多时期土地利用土地覆被遥感监测数据集（CNLUCC）[55],空间分辨率为100 m×100 m,一级分类包括耕地、林地、草地、水域、建设用地和未利用土地共6类。本文所采用的建设用地的二级分类包括城镇用地、农村居民点和其他建设用地。其中,其他建设用地指厂矿、大型工业区、油田、盐场、采石场等用地以及交通道路、机场和特殊用地。研究采用的坡度数据来源于GEE平台上的SRTM（Shuttle Radar Topography Mission）数字高程数据集。该数据集空间分辨率为30 m,并使用开源数据ASTER GDEM2、GMTED2010和NED进行了空隙填充,可以完整覆盖整个研究区。2005—2018年地质灾害统计数据来源于中国地质环境监测院发布的《全国地质灾害通报》,其中由于2017年数据未公开发布,因此未计入统计。

2.2 研究方法

2.2.1 建设用地坡谱构建 为定量深入探究中国城乡建设用地在坡度空间上的演变特征,研究以坡度数据与7期土地利用数据为基础,基于国家、区域、省级和城市4个尺度单元,采用GEE平台的分区统计算法,以1°为间隔对区域内各坡度区间的栅格数量和区域建设用地栅格数量进行统计,并绘制地形坡谱曲线和建设用地坡谱曲线。坡谱曲线概念来源于汤国安等在研究黄土高原地形地貌时提出的坡谱地学分析方法[56]。本文所计算的坡谱包括地形坡谱（即土地面积频率坡谱）[57]和建设用地坡谱（即建设用地面积频率坡谱）[46]。具体计算公式如下：

Pt,i=Areat,iAreat×100%
Pcl,i=Areacl,iAreacl×100%
式中：Pt, i与Pcl, i分别指坡度为i的地区的土地面积频率与建设用地面积频率;Areat, i与Areacl, i分别指坡度为i的地区的土地面积和建设用地面积;Areat与Areacl分别指研究区（随研究尺度变化）内的土地总面积和建设用地总面积。坡谱是指以坡度（范围为0~90°）为横坐标,面积频率为纵坐标的曲线。当Pcl, i=Pt, i时,即坡度为i的地区建设用地面积占比与研究区建设用地面积占比相等时,建设用地坡谱与地形坡谱相交,将该坡度值定义为T。当Pcl, i>Pt, i时,即坡度低于T的地区的建设用地面积占比大于研究区总建设用地面积占比,表明该研究区建设用地主要分布在坡度低于T的地区,本文将其定义为建设用地分布的优势地区,反之,坡度高于T的地区为建设用地分布的劣势地区。为便于计算,本文以栅格数量代替面积进行计算。

2.2.2 平均建设用地爬坡指数与上限坡度 对建设用地坡谱的直观解读可以定性地反映建设用地分布的坡度梯度和时空变化特征,但仍需要根据定量的指数分析建设用地具体的爬坡程度。为此,本文通过计算一段时期内建设用地在坡度高于T的地区的面积占建设用地面积总量的比例的变化定义建设用地爬坡指数（Built-up land climbing index, BCI）。由于研究的6个时期时间跨度不同,为便于比较不同时期建设用地爬坡程度的变化,特别定义了平均建设用地爬坡指数（Average built-up land climbing index, ABCI）,其计算公式如下：

BCI=(lAreajAreaj-lAreaiAreai)×100%
ABCI=BCI/(j-i)
式中：BCI为i年至j年建设用地的爬坡指数;lAreai与lAreaj分别表示i年和j年统计区内坡度高于T的建设用地的面积;Areai与Areaj分别表示i年和j年统计区内建设用地总面积;ABCI为i年至j年建设用地的平均爬坡指数。ABCI > 0,表明建设用地在坡度高于T的地区的面积比例随时间增大,即建设用地表现为爬坡式发展,ABCI越大,表示建设用地爬坡程度越强烈。

坡地的地形坡度按是否适宜建设通常分为5个级别：≤ 3°、3°~8°、8°~15°、15°~25°和>25°。其中前3个等级分别表示适宜、较适宜和中等适宜城市建设。地形坡度>15°的地区已不适宜规模化的建设,坡度在15~25°的地区可以通过梯化改造坡地,安排适量的居住用地,而>25°的地区可安排少量居住用地[2]。为分析不同地区建设用地分布的坡度最大值随时间变化的差异,本文采用上限坡度（Upper limited slope, ULS）,即顺坡度由小到大的方向累加建设用地面积频率之和达95%时所对应的坡度值,通过分析上限坡度在不同适宜等级坡度区段内城市数量的变化,反映建设用地在坡度空间上分布的发展规模。为便于对比不同时期上限坡度的变化差异,特别计算上限坡度变化值（Upper limited slope angle change, ULSC）。当ULSC > 0时,表明该时期建设用地分布的上限坡度增大,即建设用地向高坡度地区发展,值越大,表示建设用地爬坡的幅度越大。ULSC ≤ 0则表明该时期建设用地分布的上限坡度减小,即建设用地主要在低坡度地区发展。

3 中国建设用地坡谱多尺度时空特征演变

3.1 国家尺度建设用地坡谱特征

1990—2018年中国建设用地在坡度梯度上呈规律分布（图1a）。经统计,1990年中国建设用地分布的平均坡度为2.92°,2018年平均坡度为3.53°,增长了0.61°。建设用地坡谱曲线与地形坡谱曲线走势相似,均呈偏态分布,谱峰位于1°~2°坡度区段内,2°之后随着坡度的增加,建设用地面积比例逐渐减少,最终趋于0。建设用地坡谱与地形坡谱在5°左右相交,即建设用地主要分布在5°以下地区。1990年,5°以下地区的建设用地面积占建设用地总面积的比例达89.75%,但随时间推移逐渐减小,至2018年面积比例已下降至85.19%,其中2010—2015年下降幅度最大,达1.48%。与1990年相比,2018年5°以上地区建设用地面积增长了143.05%。分析不同时期建设用地上限坡度变化值以及建设用地年均爬坡指数（图1b）发现,2010—2015年建设用地分布的上限坡度变化值最大,高达2°,建设用地平均爬坡指数由2005—2010年间的0.14%增加至2010—2015年间的0.30%,增长了一倍,2015—2018年间建设用地平均爬坡指数最高,达0.53%。结果表明,中国建设用地逐渐向高坡度地区发展,而且建设用地爬坡强度在2010年后显著增强,爬坡速度加快。

图1

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图11990—2018年中国地形与建设用地坡谱以及不同时期平均爬坡指数与上限坡度变化值

Fig. 1Terrain and built-up land slope spectrums, ABCI and ULSC of China from 1990 to 2018



3.2 区域尺度建设用地坡谱特征

受地理环境条件与城乡发展阶段差异的影响,中国东、中、西、东北四大经济区域建设用地在坡度梯度上的分布特征以及爬坡程度有所不同。2018年中国东北地区91.33%的建设用地分布在坡度为0~5°的地区,而西部地区仅有77%。自然地形的不同是导致不同区域建设用地在坡度梯度上的分布具有空间差异的主要原因。随着时间推移,各地区建设用地坡谱峰值均呈下降的趋势（图2）,其中,中部地区峰值下降幅度最大,达3.93%,其次为东部（2.39%）和西部地区（2.03%）,东北地区最小,为0.81%。该现象表明建设用地在坡度较高的地区的面积比例逐渐上升,在建设用地分布的劣势区段扩张的速度逐渐大于优势区段,即建设用地逐渐向高坡度地区发展。

图2

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图21990—2018年中国四大区域地形坡谱与建设用地坡谱

Fig. 2Terrain and built-up land slope spectrums of four regions of China from 1990 to 2018



图3反映了不同时期不同地区建设用地平均爬坡指数与上限坡度随时间的变化。东部地区ABCI指数随时间推移呈现出波动变化,ABCI较高的时期为2000—2005年与2015—2018年,分别为0.28%和0.44%。其建设用地上限坡度则呈现出逐年上升的趋势,由7°上升至10°。尽管东部地区平坦土地资源较丰富,但由于人口和经济的高速发展,快速的城市化已占用了大量平坦土地。同时,近年来出于对高质量耕地资源的保护,可用于建设的土地资源受限,然而土地的需求仍居高不下,因此东部地区的建设用地逐渐向坡度较高的地区发展,但爬坡程度并不强烈。受地形因素影响,中部地区建设用地爬坡程度最强,自1995年起,中部地区平均建设用地爬坡指数（ABCI）快速上升,在2015—2018年间达到峰值,超过0.8%。建设用地分布的上限坡度（ULS）从1990年的7°上升至2018年的12°,变化最大。西部地区地形复杂,建设用地爬坡程度逐渐增强,上限坡度最高,均为14°以上,但变化较小。大起伏的地势既是驱使建设用地向上爬坡的因素,也是限制城市发展规模的阻碍。东北地区由于地处平原,建设用地分布的上限坡度最低且变化最小。1990—2015年ABCI指数在0上下浮动,然而,2015—2018年间,ABCI指数大幅上升,爬坡程度剧烈增强。综合来看,2015—2018年是中国各地区建设用地爬坡程度最强烈的时期,表明建设用地爬坡这一新发展模式将逐渐成为缓解当前土地资源紧缺和供需矛盾的一项解决方案。

图3

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图31990—2018年中国四大经济区域平均建设用地爬坡指数与上限坡度

Fig. 3ABCI and ULS of China's four economic regions from 1990 to 2018.



3.3 省级尺度建设用地坡谱特征

由于自然本底差异,不同省份建设用地坡谱形态不尽相同（图4）,建设用地在坡度空间上的分布差异显著。大部分省份建设用地坡谱呈现为较光滑的倒“V”型曲线,而且与地形坡谱形态相似性较高,例如天津市、新疆维吾尔自治区、安徽省等。这些省级地区在2018年5°以下的建设用地面积比例均超过全国平均值（85.19%）。然而部分省级地区建设用地坡谱尽管同样表现为先增加后减少的趋势,但存在多次轻微的波动变化,其中也有部分省份建设用地坡谱呈“几”字型,如福建省、广东省和台湾省。这些地区5°以下的建设用地面积比例均低于85%,表明建设用地分布的坡度范围较广。从建设用地坡谱曲线随时间变化来看,在建设用地分布的优势坡度区段内,大部分省级地区建设用地面积比例随时间推移呈逐渐减小的趋势,即建设用地逐渐向高坡度地区发展,变化较明显的省份包括山西省、福建省、湖北省、广东省等,均存在明显的建设用地爬坡现象。同时也存在部分省份的建设用地面积比例在优势坡度区段内呈上升的现象,例如青海省和香港特别行政区。

图4

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图41990—2018年中国各省份地形坡谱与建设用地坡谱

Fig. 4Terrain and built-up land slope spectrums of the provinces in China from 1990 to 2018



依据1990—2018年平均建设用地爬坡指数（ABCI）与上限坡度变化值（ULSC）综合分析发现（图5a）,中国34个省级地区大致可分为3类：高爬坡型（ABCI > 0且ULSC > 0）、低爬坡型（ABCI > 0且ULSC ≤ 0,或ABCI ≤ 0且ULSC > 0）以及水平扩展型（ABCI ≤ 0且ULSC ≤ 0）。其中,高爬坡型省份并非指建设用地爬坡的坡度大,而是指爬坡过程中上限坡度变化值以及爬坡程度均较大,最典型的省级地区包括西藏自治区、山西省、云南省和福建省,其中西藏自治区爬坡程度最强,1990—2018年ABCI指数高达1.28%,是山西省ABCI指数的3倍。低爬坡型省份包括陕西省、重庆市、四川省和宁夏回族自治区等,尽管建设用地分布的上限坡度呈现为不变甚至减少的趋势,但建设用地爬坡现象仍未停止,主要原因在于这些省份目前的上限坡度已达最高,如重庆市建设用地上限坡度已超过23°,若继续向高坡度地区发展,很有可能增加地质灾害的风险。水平扩展型省份的ABCI与ULSC指数均为负,即建设用地仍主要在平原地区进行扩张,主要包括青海省、甘肃省、新疆维吾尔自治区、上海市、台湾省、香港特别行政区以及澳门特别行政区,其空间分布呈现出明显的“东南—西北”两极分化趋势。

图5

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图51990—2018年中国各省与各城市平均建设用地爬坡指数与上限坡度变化值

Fig. 5ABCI and ULSC of the provinces and cities in China from 1990 to 2018



3.4 城市尺度建设用地坡谱特征

综合分析1990—2018年中国371个城市平均建设用地爬坡指数（ABCI）与上限坡度变化值（ULSC）（图5b）可知,爬坡型城市的数量（280个）占城市总数的3/4以上,其中68.93%为高爬坡型城市。从各个时期ABCI变化来看（图6）,建设用地爬坡的规模与程度均随时间推移逐渐增强。1990—1995年160个城市的建设用地发展模式表现为爬坡,其中云南省德宏傣族景颇族自治州建设用地爬坡程度最强,表现为中等爬坡程度的5个城市主要分布在云南省、河南省和甘肃省。然而,1995—2000年尽管爬坡的城市数量增加至169个,但爬坡程度在中等以上的城市减少至2个,分别为甘肃省甘南藏族自治州和浙江省丽水市。至2005年,胡焕庸线以东的大部分城市都表现出较明显的建设用地爬坡现象,其中爬坡程度在中等以上的城市集中分布在福建省。2005年之后,建设用地爬坡的城市数量大幅上升,湖北省十堰市建设用地表现出显著的爬坡现象,2010—2015年爬坡程度强的城市数量上升至15个,主要分布在云南、西藏、湖北、海南等省份,其中6个城市为藏族、苗族、黎族、壮族等少数民族聚居地。但是2015—2018年将近50%的建设用地爬坡程度强的城市集中分布在山西省和西藏自治区。其中爬坡程度最高的城市为西藏自治区的日喀则市,也是建设用地上限坡度变化最大的城市,从1990年的9°上升至2018年的32°。表1反映了建设用地分布的ULS在不同适宜等级坡度区段内城市数量的变化,其中ULS分布在3°~15°区间内城市数量最多,超过城市总数量的60%,但随着时间推移,该比例逐渐减小,从1990年的67.93%下降至2018年的61.92%,与此同时,ULS大于15°的城市数量逐渐上升,其占比从31.54%上升至38.81%。2010—2015年上限坡度大于25°的城市数量陡然上升,这段时期是中国建设用地爬坡发展最迅速,规模最大的时期,新增加的城市主要分布在云南、西藏、山西和贵州。2015—2018年虽然ULS大于25°的城市数量不增反降,但是15°~25°区间内的城市数量在3年间增长了14个,主要分布在山西、广西、吉林、安徽等省份。这一现象表明2015年后,建设用地爬坡现象仍在继续,但爬坡幅度相对放缓。

图6

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图61990—2018年中国各城市平均建设用地爬坡指数

注：基于自然资源部标准地图服务网站下载的审图号为GS(2019)1823号的标准地图制作,底图无修改。
Fig. 6ABCI of cities in China from 1990 to 2018



Table 1
表1
表11990—2018年上限坡度在不同适宜等级坡度区段内的城市数量及占比
Table 1The number and accounts of cities with ULS in different slope interval from 1990 to 2018
年份0~3°3°~8°8°~15°15°~25°≥ 25°
数量(个)占比(%)数量(个)占比(%)数量(个)占比(%)数量(个)占比(%)数量(个)占比(%)
199020.5414138.0111129.929024.26277.28
199520.5414138.0111230.198823.72287.55
200020.5414238.2711230.198923.99267.01
200510.2714338.5411029.658923.99287.55
201010.2714338.5410829.119124.53287.55
201510.2713335.8510628.579425.34379.97
201810.2712032.3510628.5710829.11369.7

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综上,在市级尺度,不同时期中国建设用地的爬坡程度具有空间异质性。在城市发展建设的早期,仅有少数以山地、丘陵为主要地貌类型的城市表现出中强度的爬坡,如德宏傣族景颇族自治州（云南省）、甘南藏族自治州（甘肃省）、丽水市（浙江省）、漳州市（福建省）、十堰市（湖北省）等。2010年后建设用地爬坡程度明显增强,大量苗族、藏族、壮族等少数民族聚居区成为建设用地爬坡的主力,原因在于这些少数民族多以畜牧业、游耕游牧业为主,长期的生活和生产习惯使其多聚居在山地和高原地区,随着少数民族的建设发展,建设用地逐渐向坡度较大的地区扩张,在空间上表现为建设用地爬坡。此外,受政策影响,自2011年起,湖北十堰、贵州铜仁、浙江丽水、陕西延安以及山西省部分城市先后成为低丘缓坡荒滩等未利用土地开发试点地区,开展的“向山要地”“工业梯田”等工程是这些地区建设用地爬坡程度较强的重要原因。

4 建设用地爬坡影响

4.1 建设用地爬坡对耕地的影响

建设用地爬坡对保护平原地区优质耕地资源具有重要意义。依据《第三次全国土地调查技术规程》,将坡度≤ 2°的耕地视为平原耕地。1990—2018年各时期建设用地侵占平原耕地的面积占研究区建设用地侵占耕地总面积的比例变化见图7a。结果表明,1990—2018年,建设用地侵占平原耕地的面积比例在高爬坡地区呈下降的趋势,总下降幅度达8.62%,在低爬坡地区先减少后增加,整体仅下降了0.37%,而在水平扩展地区呈现明显的增长趋势,由1990—1995年的71.94%上升至2015—2018年的77.35%。尽管2015—2018年该比例在低爬坡地区略高于水平扩展地区,但整体而言,2005年后,爬坡型地区的建设用地侵占平原耕地的面积比例低于水平扩展地区。虽然自1998年,国家先后提出耕地占补平衡、基本农田保护、严守18亿亩耕地红线等耕地保护政策,但在以水平扩展为主要建设方式的地区,建设用地侵占平原耕地的趋势不降反升,而以建设用地爬坡为主要发展模式的地区建设用地对平原耕地的占用逐渐减少。由此可推断,建设用地爬坡在一定程度上确实有助于缓解平原耕地被侵占的问题。

图7

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图71990—2018年建设用地侵占平原耕地和生态用地的面积占比

Fig. 7The area proportion of cultivated land and ecological land (slope ≤ 2°) occupied by built-up land from 1990 to 2018



4.2 建设用地爬坡对生态用地的影响

低丘缓坡土地开发建设是协调城镇化和生态保护的重要途经[58]。1990—2018年各时期建设用地侵占平原生态用地（坡度≤ 2°的林地与草地）的面积占建设用地侵占生态用地总面积的比例变化见图7b。高爬坡地区平原生态用地被建设用地侵占的面积比例在所有时期均低于其他2类地区,由1990—1995年的40.56%下降至2015—2018年的31.10%,下降幅度达9.45%。1990—2018年建设用地侵占平原生态用地的比例在低爬坡地区先降后升,整体下降7.93%,而在水平扩展地区呈波动变化。与建设用地侵占平原耕地面积占比的变化规律相似,尽管2015—2018年建设用地侵占平原生态用地面积占比在低爬坡地区略高于水平扩展地区,但整体而言,2005年后爬坡型地区的建设用地侵占平原生态用地的面积比例低于水平扩展地区,表明建设用地爬坡能够有效缓解建设用地对平原生态用地的影响。与此同时,低丘缓坡开发过程中涉及的土地平整、城镇和道路建设等人类活动[59],极易造成坡地生态景观破碎,连通性降低等负面影响。建设用地占用平原生态用地的面积比例减少,也意味着坡地生态用地被侵占的比例增加,即建设用地爬坡可能会增大对高坡度地区生态环境的胁迫。

4.3 建设用地爬坡与地质灾害的关系

建设用地爬坡可能会诱发地质灾害。建设用地爬坡过程实质上是进行坡地的平整和改造,由于坡地易受水土流失的侵袭,且由于成土速率慢、土层薄、土壤贫瘠、土地植被生态系统脆弱敏感等特点,在建设用地开发利用过程中极易破坏土质结构,造成地质疏松,引发区域水土流失、山体滑坡、泥石流、地面沉降等地质灾害[60]。自2005年起,尽管全国地质灾害数量整体表现为减少的趋势,但是由人为因素,如采石、切坡、地产建设等引起的地质灾害数量占总数的比例呈上升趋势（图8）。据《全国地质灾害通报》统计,2005—2018年地质灾害事件主要发生在建设用地爬坡发展最为快速和剧烈的中西部地区。此外,2012年陕西延安、湖北十堰、甘肃兰州等城市先后实施规模巨大的削山造地工程[23]。这些大规模的极端建设用地爬坡建设极易破坏地区原有生态屏障及地质结构,导致地质灾害风险增加。2010—2019年兰州市境内各类地质灾害隐患点由863处上升至2470处,增长了近2倍[61]。2017年十堰市地质灾害共计发生552起,占全省全年灾害总数的64.94%,其中人为因素引起的地质灾害数量达107起,占全省人为因素引发的地质灾害数量的73.79%[62]。因此,为避免建设用地爬坡引起的山体滑坡、泥石流等地质灾害风险,必须基于灾害普查,落实“多规合一”绘制一张蓝图,综合考虑生态环境的脆弱性、地质地貌的复杂性以及地质灾害的易发性和高风险性,在减少地质灾害风险的基础上有效合理配置建设用地资源。

图8

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图82005—2018年中国地质灾害数量及人为因素引发的灾害数量占比

Fig. 8The number of geologic disasters and proportion of geologic disasters due to human activities from 2005 to 2018



5 结论与讨论

5.1 结论

本文基于Google Earth Engine云平台,结合地形与1990—2018年土地利用等数据绘制中国全域、四大经济区域、省级和城市4个尺度的地形坡谱与建设用地坡谱,首次定义并构建了平均建设用地爬坡指数并计算建设用地分布的上限坡度,从“第三维”视角对不同尺度下建设用地在坡度空间上的时空变化规律进行系统全面的分析探究,并挖掘建设用地爬坡的主要影响,得出以下主要结论：

（1）中国85%以上的建设用地分布在坡度5°以下地区。1990—2018年建设用地分布的平均坡度增长了0.61°,上限坡度增加了4°,高坡度（5°以上）地区建设用地面积增长了1.43倍。2010年后,建设用地爬坡的程度明显增强,爬坡速度加快,2010—2015年平均建设用地爬坡指数超过2005—2010年的2倍。在区域尺度,地形较复杂的中西部地区爬坡指数和上限坡度变化最大,爬坡现象显著。地形平坦的东部和东北地区受耕地保护政策的约束,建设用地也存在爬坡现象,且人口稠密的东部地区爬坡程度比东北地区强。

（2）中国34个省级行政单元建设用地爬坡程度差异显著。高爬坡型省份占总数的 50%以上,其中西藏自治区爬坡程度最强。水平扩展型省份仅有7个,呈现出明显的“东南—西北”两极分化趋势。市级尺度分析发现,建设用地爬坡城市逐渐增多,范围逐渐扩大,爬坡程度逐渐增强。爬坡型城市的数量占城市总数的75%以上,其中68.93%为高爬坡型,且主要分布在西南民族聚居区、山地城市以及低丘缓坡开发利用试点地区。

（3）建设用地爬坡在充分利用坡地拓展建设空间的同时,也对周围基本农田、生态用地以及区域地质环境造成显著影响。一方面,爬坡型地区建设用地对耕地与生态用地的占用比例低于水平扩展地区,有效地缓解了平原优质耕地和生态用地被侵占的问题。另一方面,不合理的爬坡扩张、过度的削山造地也容易破坏山体地质结构,导致中西部生态和环境脆弱地区地质灾害和生态风险增加。

5.2 讨论

中国城乡建设用地空间差异性与内部不均衡性十分显著。当前,仅依靠城乡建设用地增减挂钩政策、城市增长边界山体、城市致密化、城市更新等规划手段,难以在短期内有效解决建设用地紧张的“人—地”关系矛盾。因此,在确保生态环境安全和空间规划合理的前提下,适度开发低丘缓坡,有序拓展建设用地资源仍是未来一段时间内,中国解决土地资源紧缺问题的有效手段之一。国家空间治理和国土空间规划编制应根据不同地区的自然资源禀赋、地质条件、灾害普查、未来人口城镇化趋势以及民族聚居特征,设定合理的土地开发限额并加强管制[63]。对于平地少,且建设用地开发强度低的中西部地区,可以通过合理开发低丘缓坡缓解土地短缺问题。但是必须提前从生态、环境、地质等多方面考虑低丘缓坡土地的开发适宜性,避免由于建设用地爬坡引发的区域生态问题、环境问题和地质灾害等问题。与已有研究相比,本文较好的实现了大尺度研究,从整个中国建设用地爬坡的多尺度规律探索,构建建设用地爬坡指数定量分析建设用地爬坡的演变特征规律,是对当前建设用地扩张研究的补充与扩展。本文也综合考虑时间分辨率与空间分辨率,采用了空间分辨率为100 m的CNLUCC数据集,与Global Land Cover 2000、MODIS 500 m Map of Global Urban Extent、GlobeLand30等数据集相比,本文采用的数据空间和时间分辨率更为精细,土地分类相对全面,满足在全国尺度的研究需求,但是如果尺度逐级下沉到省、市、县层面,数据的空间分辨率将对研究产生强烈的约束和限制。因此在未来研究中,可综合多种数据源,根据研究尺度和需求,选择或制备适宜时间分辨率和空间分辨率的数据,以便更加精确地描述和分析建设用地在坡度梯度上的扩张演变。此外,本文定性探索了爬坡式发展对耕地、生态用地的影响以及与地质灾害的关系,但对建设用地爬坡的动因和机理的挖掘还有待持续深入。因此,进一步厘清不同坡度区间内建设用地、耕地以及生态用地三者之间的转化关系及动力机制,综合考虑爬坡建设的生态风险至关重要[59]。在全球气候变化、未来地球计划（Future Earth）、全球可持续发展目标（SDGs）、城镇高质量发展的大背景下,如何定量解析建设用地爬坡对耕地、生态用地以及环境的影响,特别是如何结合国家多级空间治理体系,提出合理有效的建设用地开发方案,寻找对人类有利且对自然界损害最小的平衡点,减少和规避灾害风险,研究团队将持续跟进,也欢迎感兴趣的****共同展开探索和研究。

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China has undergone a rapid urbanization since the beginning of the 21st century. Urban expansion monitoring has become a hotspot in the field of geographical science. However, methods of urban boundary extraction were inconsistent, and the precision of previous urban boundary products is relatively low due to the coarse image resolution. In this paper, a method of high-precision and unified urban expansion monitoring and analysis of China's 31 provincial capitals was carried out based on high-resolution remote sensing images. First, the urban boundaries of 2000, 2005, 2010 and 2015 were extracted with a series of unified rules by urban landscape characteristics and geographical knowledge based on high-resolution images. Then, urban boundary result was compared with other urban boundary products based on low and mid-resolution images to assess the accuracy. Finally, urban size distribution and urban expansion were analyzed based on urban area and urban boundary results. Results showed that the proposed method of urban boundary extraction was superior to other researches. From 2000 to 2015, China's provincial capitals witnessed a rapid growth trend, and the total urban area increased by 90.15%; the provincial capitals system approximated size distribution of the rank-size law. Urban expansion had a significant regional difference. Urban expansion rate in the eastern region gradually slowed down, while that in the western and northeastern regions had an accelerating mode, and that in the central region expanded steadily. Beijing, Tianjin, Shanghai, Guangzhou and Chongqing, which were designated as the national central cities in 2010, ranked the top five of urban area size in 2015. The five cities increased by 82.45% during the 15 years, and the average annual urban expansion area was 30.66 km2. Urban area of Beijing, Tianjin, Shanghai, Guangzhou and Chongqing increased by about 30%, 100%, 100%, 60% and 200%, respectively. This research provides unified and high-precision spatial urban boundaries data and urban expansion results for local governments and the public, which are useful for scientific urban development and planning of China's urban system.
[ 张翰超, 宁晓刚, 王浩, 等. 基于高分辨率遥感影像的2000—2015年中国省会城市高精度扩张监测与分析
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Fang Chuanglin, Cui Xuegang, Liang Longwu. Theoretical analysis of urbanization and eco-environment coupling coil and coupler control
Acta Geographica Sinica, 2019,74(12):2529-2546.
DOI:10.11821/dlxb201912008 [本文引用: 1]
There is an extremely complex nonlinear coupling relationship between urbanization and eco-environment. How to coordinate this relationship has become a global strategic problem and a worldwide scientific problem. First, based on theoretical analysis, this paper revealed the coupling, coupling relationship, coupling degree and coupling tower of interaction between urbanization and eco-environment. Second, by analyzing the main controlling factors, ten kinds of interaction modes between urbanization and eco-environment are summarized. Third, according to the strength of coupling degree, we have identified six coupling types, including low coupling, slight coupling, moderate coupling, high coupling, excellent coupling, and full coupling, which correspond to the random coupling, indirect coupling, loose coupling, synergistic coupling, tight coupling and control coupling, respectively. Then, urbanization and eco-environment coupling tower was formed. Finally, the theory of urbanization and eco-environment coupling coil was established. Through rotating the graph by 10°, we built 45 kinds of coupled graphs, including linear graph, index curve graph, logarithmic curve graph, double index curve graph and S-shaped curve graph. Different graphs represent different urban development modes, stages and characteristics. Among them, S-shaped curve coupled graph is optimal, and it reflects the best state of urbanization and eco-environment coupling. After that, we amplified the S-shaped coupled graph, and then constructed a coupler (UEC) based on the SD model and the complex relationship between different variables. The coupler consists of 11 regulatory elements and 201 variables, and can control the coupling state between urbanization coil and eco-environment coil. In general, the above control types include static control of multiple cities at the same time, dynamic control of a single city at different times, and dynamic control of multiple cities at different times. Through coupler control, urbanization coil and eco-environment coil can keep the best dynamic and orderly state. In addition, if one variable changes, the structure, function and simulation results of the coupler will also be affected. Finally, with the increase of control intensity, the coupler will gradually improve the coupling degree between urbanization coil and ecological environment coil.
[ 方创琳, 崔学刚, 梁龙武. 城镇化与生态环境耦合圈理论及耦合器调控
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In order to explore the spatial structure of rural residential land transition and its relevance to economic development, the spatial layout and agglomeration characteristics of rural residential land transition in Shandong Province were studied by applying theoretical hypothesis on rural housing land transition and spatial correlation analysis methods, such as global spatial autocorrelation analysis and hot spot analysis. Economic growth stages at county scale were divided based on per capita GDP, and the coupling relationship between rural residential land transition and economic development were revealed from the integrated angle of global scale at the provincial level and "point-line-face" feature unit. The results showed that, the rural residential land transition index from 2005 to 2014 displayed a significantly increasing trend in the east-west direction and a gradually descending trend from south to north. Based on the global spatial autocorrelation analysis, Moran's index, which reached 0.6317, indicated that the rural residential land transition showed a significant pattern of high-high and low-low spatial clustering. Furthermore, by applying hot spot analysis, it was found that the hot spots and hot sub-spots were intensively distributed in the western inadated plain of the Yellow River, southwest Huaihe plain and central Yimeng Mountains of Shandong Province; the cold sub-spots were distributed in the periphery of the hot sub-spots, such as cities of Zaozhuang, Jinan, Zibo, Binzhou and Weifang; and the cold spots were mostly distributed in Jiaodong hilly region and the northern Yellow River Delta. Moreover, obvious correlation of mathematical statistics and spatial coupling between rural residential transition indices and economic development level were indicated. The decreasing tendency from low to high economic gradient at both global scale and provincial level and feature units of "Five counties - Three belts - Four regions" were revealed by all rural residential land transition characteristics, with the significant relationship of power exponent trend. This paper explored the spatial characteristics of rural residential land transition, and made up for the deficiency of the single non-spatial analysis of land use transition; and the results verified the previous theoretical hypothesis successfully.
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Low-slope hilly land is one of the most important construction and development resources in China, where hilly area is much more than the flat ground. The construction process can be very difficult as the complex terrain and sensitive eco-environment of the hilly land, where eco-environmental problems may take place due to unreasonable human development. An ecological risk assessment conceptual framework of low-slope hilly land has been built by taking account of natural ecological risk probability, development ecological risk probability as well as ecological importance. In detail, natural ecological risk probability contains geological disaster stress and soil erosion stress, while the development ecological risk consists of pollution accumulated stress, resource depletion stress and space occupation stress. Then a conceptual framework has been applied in the ecological risk assessment of Dali Bai Autonomous Prefecture, a representative region of low-slope hilly city construction areas in Yunnan Province, China. In this study, firstly, the quantitative and spatial patterns of the influence factors were analyzed separately and then the integrated ecological risk probability was graded into 5 degrees. Secondly, the spatial pattern of integrated ecological risk and its relationship with land use types has been analyzed. Finally, 383 watersheds were classified into four categories, namely development priority area, protection priority area, development balance area and protection balance area according to the grade of integrated ecological risk and grade of development status. The guidance and advice for future development has also been proposed for low-slope hilly construction in Dali Prefecture.
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