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Journal of Geo-information Science >

2016 , Vol. 18 >Issue 10: 1352 - 1359

DOI: https://doi.org/10.3724/SP.J.1047.2016.01352

Orginal Article

Study on Urban Planning and Its Ecological Effect

  • LIU Zhicai ,
  • XU Hanqiu , * ,
  • LIN Zhongli ,
  • HUANG Shaolin
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  • 1. College of Environment and Resources, Fuzhou University, Fuzhou 350116, China
  • 2. Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou 350116, China
  • 3. Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou 350116, China
*Corresponding author: XU Hanqiu, E-mail:

Received date: 2015-12-01

  Request revised date: 2016-03-21

  Online published: 2016-10-25

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Abstract

In recent years, the urban built-up area continues to expand along with the continuous improvement of urbanization degree. Also, the property of urban land is changing. In various types of urban planning land, different urban construction plannings can cause different ecological effects. The study on the differences and the causes of their formations can provide a good decision support to urban planning managers, and it is of great significance for the construction of an ecological livable city. In this paper, two Landsat images of 2009 and 2013 were utilized to computer the Remote Sensing Ecological Index (RSEI). Combined with the newly approved Urban Master Planning of Fuzhou City by the State Council of China, five planning classes of the master planning, with 22 selected plots, were investigated to reveal their ecological changes before and after the implementation of construction planning. It is found that the ecological qualities of the five classes are all declining, which indicates an overall drop down in the RSEI value by 12%. Among them, the RSEI of the industrial class falls by 18% and the ecological degradation of the industrial class is the most sever one. At the same time, the ecological quality of the municipal utilities class falls by 14%, the ecological quality of the residential class falls by 11%, the ecological quality of the administration and public services class falls by 8%, and the ecological quality of the commercial and business facilities class falls by 6%. The main factors which lead to the degradation of ecological quality after the completion of urban planning are the significant decrease in vegetation and water, and the considerable increase in coverage for built-up impervious surface. Combining with the research results of this paper, we also put forward suggestions for the urban planning management department.

Key words： urban planning; ecological change; remote sensing; Fuzhou

Cite this article

LIU Zhicai , XU Hanqiu , LIN Zhongli , HUANG Shaolin . Study on Urban Planning and Its Ecological Effect[J]. Journal of Geo-information Science, 2016 , 18(10) : 1352 -1359 . DOI: 10.3724/SP.J.1047.2016.01352

1 引言

近年来,随着城市化带来的生态环境问题越来越突出,中国对生态城市的建设也格外重视。2012年11月8日,中国共产党第十八次全国代表大会在北京召开,会上提出“大力推进生态文明建设,把生态文明建设放在突出地位”。2014年3月10日,国务院发布了《国务院关于支持福建省深入实施生态省战略加快生态文明先行示范区建设的若干意见》,支持福建省深入实施生态省战略,加快生态文明先行示范区建设。以福建省福州市为例,研究城市规划用地中不同用地类型的生态效应对生态城市建设过程中,城市功能分区的优化以及政府有针对性的制定相应的城市规划管理策略具有重要 意义。
城市化引起的生态退化问题日益严重,得到国内外专家和学者的关注[1-7],并对此开展了一系列相关研究。其中,遥感技术也更多地应用到生态问题的研究中,早期的研究较多集中在利用单指标对整个城市或者城市中不同区域、不同用地类型之间的生态差异上[8-18]。近年来,除了运用单指标对城市生态进行研究以外,也出现了对城市生态评价指标体系的研究及应用,如国家环境保护部在2006年5月1日颁发了《生态环境状况评价技术规范(试行)》[19],推出了主要基于遥感技术的生态环境状况指数（EI）,旨在对中国县级以上的生态环境提供一种年度综合评价标准;黄蓓佳等从社会、经济、自然等方面构建了一套城市生态环境质量的指标体系,评价了上海市闵行区的生态环境质量[20];徐涵秋基于遥感技术提出了一个遥感生态指数（RSEI）,并利用该指数对福建省长汀水土流失区的生态变化进行了评价[21]。由于2006年试行的EI指数饱受诟病,2015年3月13日,环境保护部发布实施了修改后的《生态环境状况评价技术规范》,该规范确定了城市生态环境评价的指标及方法,并且首次将“城市热岛比例指数”作为评价因子[22]。
目前的研究主要利用单指标对城市不同土地利用类型的生态环境进行评价,这些土地利用类型与城市规划中的用地类型的分类不一致。而基于多指标的生态环境评价主要是针对整个城市区域,鲜有针对城市中不同规划用地生态环境的评价。因此,本文拟运用徐涵秋提出的遥感生态指数,首先反演出整个福州市的RSEI指数,在此基础上结合国务院最近审批通过的福州市城市总体规划方案中不同用地类型的布局情况[23],提取出各研究地块的RSEI指数,对福州城市建设过程中不同城市规划用地类型的生态变化差异进行研究,并为城 市规划管理部门的城市规划管理和决策提出相关 建议。

2 研究方法

2.1 研究区选取

福州市是福建省省会城市,也是“海峡西岸经济区”的核心城市。近30年来,福州城市的快速发展也使其生态环境遭到了一定的破坏,其高温天数一直位居全国第一。随着党的十八大 “大力推进生态文明建设”战略的制定以及福建省作为第一个生态文明先行示范区获批,福州市加强了生态文明建设。本文根据2012年1月1日实施的《城市用地分类与规划建设用地标准》[24],结合2015年获国务院审批通过的福州市城市总体规划方案,选取了城市规划用地中变化比较明显的5大类共22个地块,研究其建设前后的生态变化。图1为福州市总体规划及本文所选的22个研究地块的位置示意图,本文所选的5大类城市规划用地包括居住用地、公共管理与公共服务用地、商业服务业设施用地、工业用地、公用设施用地。
Fig. 1 The master planning map of Fuzhou (2011-2020) and the locations of the selected study plots

图1 福州市城市总体规划(2011-2020年)及研究地块位置示意图

2.2 数据来源

本文采用福州市2009年6月6日的Landsat 5 TM影像和2013年8月4日的Landsat 8 OLI/TIRS影像为遥感数据,以下简称2009年和2013年数据。为了消除光照和大气等因素对地物反射的影响,利用Chander和Chavez的模型和参数[25-27]对影像进行大气校正,并将2009年和2013年的影像进行了配准,配准精度的RMSE小于0.5个像元。同时,还将福州市城市总体规划(2011-2020年)图与遥感影像进行配准,利用规划图中各用地的边界作为22个研究地块的划分依据。

2.3 生态指数选择与计算

目前,区域生态环境的评价大多采用单一的指标,基于多指标的综合评价很少,主要有国家环境保护部推出的EI指数[19,22]和徐涵秋提出的RSEI指数[21]。但EI指数主要用于大区域单元(县级以上)的评价,无法用于小面积地块的评价。另外,EI指数给出的只是一个单一的数值,无法可视化,无法揭示区域中不同生态环境的空间变化情况。而RSEI指数通过主成分分析集成了绿度、湿度、热度、干度4个与生态密切相关的指标,并且不受面积大小的限制,且可以对评价结果进行可视化,支持对研究区生态质量进行空间建模和时空变化分析等[21]。近年来,RSEI指数已在许多城市和地区的生态变化研究中得到广泛应用[28-30]。因此,本文选用由徐涵秋提出的RSEI指数[22]来揭示福州市不同城市规划用地类型的生态质量。
RSEI指数的4个分指标分别由以下遥感指数或参量进行求取[31-32]。
（1）湿度指标：用缨帽变换中的湿度分量Wet来计算,其公式为式（1）[31-32]。
Wet = C 1 B + C 2 G + C 3 R + C 4 N + C 5 M 1 + C 7 M 2 （1）
式中：对于Landsat 8 OLI影像,B、G、R、N、M1、M2分别代表第2、3、4、5、6、7波段的反射率,C1=0.1511、C2=0.1973、C3=0.3283、C4=0.3407、C5=-0.7117、C7 = -0.4559。对于Landsat 5 TM影像,B、G、R、N、M1、M2分别代表第1、2、3、4、5、7波段的反射率,C1=0.0315、C2=0.2021、C3=0.3102、C4=0.1594、C5=-0.6806、C7=-0.6109;
（2）绿度指标：用NDVI植被指数来代表 （式（2））。
NDVI = ( N - R ) ( N + R ) （2）
（3）热度指标：由经比辐射率校正的温度来代表。将Landsat热红外波段反演为亮温,再经过比辐射率校正可获取该指标,其公式为式（3）。
T = T b / [ 1 + ( λ T b / ρ lnε ] （3）
式中：T为经比辐射率校正后的温度（K）：Tb为亮 温（K）;ρ=h×c/σ=1.438×10-2 mK;λ为热红外波段的中心波长,对于Landsat 5 TM 6波段,λ = 11.45 µm;对于Landsat 8 TIRS 10波段,λ=10.9 µm;ε为比辐射率,Landsat 5和Landsat 8热红外波段的ε,可以分别通过Sobrino的模型和Nichol与MODIS的数值进行确定[33-35]。
（4）干度指标：城市中影响干度的主要因素是建筑用地,因此以建筑指数IBI[36]作为干度指标,其公式为式（4）。
IBI = [ 2 M 1 / ( M 1 + N ) - N / ( N + R ) - G / ( G + M 1 ) ] / [ 2 M 1 / ( M 1 + N ) + N / ( N + R ) + G / ( G + M 1 ) ] （4）
由于以上求出的4个指标的量纲不统一,需要分别进行归一化处理,后采用主成分分析中的第一主成分(PC1)来耦合。为使大的数值代表好的生态,可用1减去PC1来获得初始生态指数RSEI0（式（5））。
RSE I 0 = 1 - PC 1 （5）
然后,对RSEI0进行归一化处理,将它的值统一在0-1之间（式（7））。
RSEI = ( RSE I 0 - RSE I 0 _min ) ( RSE I 0 _max - RSE I 0 _min ) （6）
式中：RSEI即为所求的遥感生态指数,RSEI值越接近1,表示生态质量越好。

3 结果与分析

根据以上计算方法,先计算出整个福州市2个时相的RSEI（图2）,再将从福州市城市总体规划图选取的各地块的边界与2个时相的RSEI图进行叠加,统计出共22个地块在2009年和2013年的RSEI指数值（表1）,并据此分析城市建设活动引发的不同类型城市规划用地的生态变化差异。
Fig. 2 RSEI images of Fuzhou

图2 福州市遥感生态指数(RSEI)影像

Tab. 1 Ecological changes of the five urbanplanning classes in Fuzhou

表1 福州市主要城市规划用地类型生态变化表

用地类型 地块数
/个		 RSEI均值 变化情况/(%)
2009年 2013年
工业用地 3 0.627 0.514 -18.02
公用设施用地 3 0.516 0.441 -14.53
居住用地 5 0.483 0.430 -10.97
公共管理与公共服务用地 8 0.456 0.421 -7.68
商业服务业设施用地 3 0.360 0.340 -5.56
均值 0.488 0.429 -12.09
根据表1统计可以发现,随着规划用地的建成,本文研究的22个地块的RSEI指数均值从2009年的0.488下降到2013年的0.429,总体下降了12.09%,这意味着这5类城市规划用地所产生的生态效应为负效应,规划用地的建设导致了生态质量的明显下降。其中,生态质量退化最严重的是工业用地,下降幅度达18.02%。公用设施用地和居住用地的生态质量退化也比较严重,下降幅度均超过10%。而公共管理与公共服务用地和商业服务业设施用地的生态质量也都有一定程度的下降,下降幅度分别为7.68%和5.56%。
Fig. 3 Remote sensing images of the representative plots and their corresponding RSEI images before and after the construction

图3 代表性地块建设前后的遥感影像及所对应的遥感生态指数(RSEI)影像

为了分析不同类型城市规划用地的生态变化原因,本文选取工业用地、居住用地和公共管理与公共服务用地建设前后生态变化较明显的类别来做进一步分析,图3是这3类用地类型的代表性地块。从图3可看出：在2009-2013年,各地块均有不同程度的开发建设。图3（a）工业用地的遥感影像显示,该地块在2009年仅东侧有少量建筑,其余大部分为绿地,与RSEI影像中代表生态好的红色对应。到了2013年规划完成后,整个地块基本布满了工业厂房,大量绿地被破坏,RSEI影像中原来代表生态好的红色区域消失,被代表生态差的蓝色区域所替代。建筑不透水面覆盖比例增多、绿地面积减少导致了该地块生态质量急剧下降,RSEI指数从2009年的0.579降为2013年的0.46。图3（b）居住用地的遥感影像显示,在2009年该地块尚未被开发建设,地块中除了东南部为裸土外,其余大部分被绿地和水体覆盖。到了2013年该地块南部已经建成高楼林立的居住小区,北部也已开始建设,有10几栋楼在施工。整个地块的绿地基本被破坏,部分河道被填平。对应的RSEI图表现为,2009年RSEI影像中的大部分红色区域在2013年被蓝色区域代替。居住用地的建设使地块中原有的植被和水体被破坏,从而导致该地块生态质量的总体下降,RSEI指数从2009年的0.465降为2013年的0.402。从图3（c）公共管理与公共服务用地的遥感影像图可发现,该地块的大部分在2009年被植被和水体覆盖,只有少量建筑。到2013年,该地块上建成了一处体育馆,地块被体育馆及其附属建筑覆盖,植被和水体面积大量减少。在RSEI影像图上表现为,2009年的大片的红色区域（生态环境较好）在2013年基本消失,生态质量下降明显,RSEI指数从2009年的0.454降为2013年的0.346。
经统计以上3个代表性地块中构成RSEI指数的4个分指标值（表2）可发现,2009-2013年随着3个地块的开发建设,3个地块中对生态起负面影响的干度（IBI）、热度（LST）指标全部上升,而对生态呈正面影响的绿度（NDVI）和湿度（WET）指标全部降低,因此这3个地块的生态质量总体下降成为必然。
Tab. 2 Changes of the four sub-indicators of RSEI for the three representative plots

表2 代表性地块的各分指标变化统计

用地类型 各分指标 指标值 变化
2009年 2013年
工业用地 IBI 0.569 0.649 +
LST 0.385 0.518 +
NDVI 0.697 0.615 -
WET 0.772 0.752 -
居住用地 IBI 0.631 0.685 +
LST 0.415 0.575 +
NDVI 0.627 0.586 -
WET 0.749 0.744 -
公共管理与公共服务用地 IBI 0.637 0.700 +
LST 0.420 0.610 +
NDVI 0.600 0.520 -
WET 0.760 0.730 -

注：“+”代表指标上升,“-”代表指标下降

4 结论与讨论

随着城市的建设,规划用地类型发生了转变,城市的生态质量也发生了明显的变化。福州市的案例研究表明：
（1）2009-2013年,福州市建设活动比较明显的5大类城市规划用地的生态质量均呈下降趋势,RSEI指数总体下降了12%。其中,工业用地的生态质量退化最严重,RSEI指数下降多达18.02%,建成后的工业用地普遍建筑密度大、绿化率低,自然地表大量减少、地表蒸腾蒸散作用被严重破坏,从而导致了工业用地成为生态质量退化最严重的地块。
（2）公用设施用地、居住用地、公共管理与公共服务用地、商业服务业设施用地的生态质量也呈下降态势,其RSEI指数分别下降了14.53%、10.97%、7.68%和5.56%。与工业用地相比,这些用地类型的规划建筑密度较低,自然地表相对保存较好,因此这些地块的生态退化程度低于工业用地。
（3）导致各类型城市规划用地生态质量下降的主要因素是在规划完成的地块中,代表自然地面的植被、水体被破坏,而人工建筑不透水地表被建成。
由于不同的用地类型承担不同的城市功能,其在生态质量上存在差异有其一定的客观原因,但是在城市规划和建设中,如何最大限度地保护原有生态,已成为城市规划和建设者们必须认真考虑的重要问题。对于城市规划管理部门的城市规划管理和决策,建议如下：
（1）在满足国家规范要求的基础上适当提高建设项目绿地率下限（25%）的控制要求;
（2）对建设项目的建筑布局进行控制,避免建筑对夏季风通过造成阻挡;
（3）采取一定的措施,鼓励建设项目进行屋顶绿化与垂直绿化;
（4）鼓励建设项目道路和广场铺设使用透水性材料,并对道路、广场用地透水性铺设的比例进行下限控制。

The authors have declared that no competing interests exist.

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李双成,赵志强,王仰麟.中国城市化过程及其资源与生态环境效应机制[J].地理科学进展, 2009,28(1):63-70.<p>目前中国城市化进程表现为速度过快、地域差异显著以及城乡二元结构明显等特征。城市化带来了显著的 生态效应，使城市生态系统的结构、过程和功能受到影响或发生不可逆转的变化，出现了耕地资源流失、水资源稀 缺、能源压力、城市环境污染严重以及城市区域生态占用扩大等资源与生态环境问题。目前国内外学者研究了城市 热岛效应、城市地表覆被变化、城市生物多样性损失以及城市水土资源等问题，但多侧重单要素、单城市、单学科研 究，缺乏多尺度机理性的研究。鉴于此，提出若干未来城市化及其生态环境效应研究的方向与议题，归纳为：(1)中国 城市化过程多尺度定量模拟与监测研究；(2)阐明城市化影响下地表自然过程和人文过程相互作用的机理；(3)资源 与生态环境约束下中国未来城市化的可能情景及其风险评估等。</p>

DOI

[ Li S C, Zhao Z Q, Wang Y L. Urbanization process and effects of natural resource and environment in China: research trends and future directions[J]. Progress in Geography, 2009,28(1):63-70. ]

[4]
金贤锋,董锁成,周长进,等.中国城市的生态环境问题[J].城市问题,2009(9):5-11.在考察我国城市生态环境主要问题的基础上，从工业化、城镇化、环境治理和全球化等角度对其成 因进行了分析，并探讨了现有工业化和城市化发展态势下城市生态环境的发展趋势与压力，进而提出了合理确定城市环境保护目标、走新型工业化道路、积极建设生 态城镇、改革城市环境治理模式等对策建议。

[ Jin X F, Dong S C, Zhou C J, et al.The ecological environment problems of the city in China[J]. City Problems, 2009,9:5-11. ]

[5]
万本太,王文杰,崔书红,等.城市生态环境质量评价方法[J].生态学报,2009,29(3):1068-1073.城市生态环境质量评价是城市生态学研究的重要领域，是城市区域规划、生态管理的基础，研究从城市生态系统结构、城市生态效能与城市环境各个方面出发，基于科学性、目的性、系统性与可操作性原则，提出了生态服务用地指数、人均公共绿地指数、物种丰富指数、非工业用地指数等10类城市生态环境质量评价指数，根据专家经验赋权重方法，建立了城市生态环境质量评价指标。研究选择青岛、上海、长春等7个城市作为评价对象，进行了城市生态环境质量评价，结果表明，青岛城市生态环境质量优，昆明、上海、成都、长春、重庆城市生态环境质量较好，乌鲁木齐城市生态环境一般，生态环境质量评价结果与现状基本相符，可为城市规划、城市生态环境整治和城市生态环境管理提供重要基础。

[ Wan B T, Wang W J, Cui S H, et al.Research on the methods of urban ecological environmental quality assessment[J]. Acta Ecologica Sinica, 2009,29(3):1068-1073. ]

[6]
张理茜,蔡建明,王妍.城市化与生态环境响应研究综述[J].生态环境学报,2010,19(1):244-252.城市化是学者们一直比较关注的重点问题,他们从不同视角对城市化及其过程进行了大量而富有创新的研究,并取得了丰硕的成果。伴随着城市化进程的加快,人们对生态环境问题的关注,城市化与生态环境的响应关系是城市地理新的关注点。文章分别就国内外学者对城市化、城市生态环境、城市化与生态环境响应的研究进行了综述,认为国内外学者对城市化、城市生态环境的研究起步早,成果多,近年来研究范围日益拓展,研究程度日益加深,并加强了新技术新方法的应用。国内学者对城市化的研究集中于城市化道路选择问题的探讨、城市化水平测度以及城市化的动力机制三个方面。对城市生态环境的研究多集中于社会—经济—自然复合生态系统及生态城市的研究。对于城市化与生态环境响应关系的研究则多见于生态学家、经济学家及地理学家的成果中,主要集中在单方面的城市化对生态环境的影响研究,而对于生态环境是怎样反过来影响城市化进程的研究则比较少见。另外,学者们的研究以微观单个影响因子的研究居多,从宏观综合角度出发进行的研究较少。这将是今后研究的一个重点问题。

DOI

[ Zhang L Q, Cai J M, Wang Y.Advance in study on urbanization and urban eco-environment[J]. Ecology and Environmental Sciences, 2010,19(1):244-252. ]

[7]
吴永娇,马海州,董锁成,等.城市化进程中生态环境响应模型研究——以西安为例[J].地理科学,2011,29(1):64-70.

[ Wu Y J, Ma H C, Dong S C, et al.Advance in study on urbanization and urban eco-environment[J]. Scientia Geographic Sinica, 2011,29(1):64-70. ]

[8]
Wilson J S, Clay M, Martin E, et al.Evaluating environmental influence of zoning in urban ecosystems with remote sensing[J]. Remote Sensing of Environment, 2003,86:303-321.The influence of zoning on Normalized Difference Vegetation Index (NDVI) and radiant surface temperature (T) measurements is investigated in the City of Indianapolis, IN, USA using data collected by the Enhanced Thematic Mapper Plus (ETM+) remote sensing system. Analysis of variance indicates statistically significant differences in mean Tand NDVI values associated with different types of zoning. Multiple comparisons of mean Tand NDVI values associated with specific pairings of individual zoning categories are also shown to be significantly different. An inverse relationship between Tand NDVI was observed across the city as a whole and within all but one zoning category. A range of environmental influences on sensible heat flux and urban vegetation was detected both within and between individual zoning categories. Examples for implementing these findings in urban planning applications to find examples of high and low impact development are demonstrated.

DOI

[9]
William L S, Maik N.Assessment of ASTER land cover and MODIS NDVI data at multiplescales for ecological characterization of an arid urban center[J]. Remote Sensing of Environment, 2005,99:31-43.Study of the detailed structure and ecological functioning of urban and peri-urban systems is intensifying due to increasing concentration of the human population into urban centers. Much of this increase is expected to occur in semiarid to arid cites. Data from new high spatial, temporal, and spectral resolution satellite-based sensors promise to increase our understanding of global urban ecological and climatic processes and improve city and land planning capabilities. Two of these sensors, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Moderate Resolution Imaging Spectroradiometer (MODIS), provide an opportunity to compare urban spatial structure (distribution and configuration of discrete land cover/land use classes on the landscape) with contemporaneous measurements of surface biophysical composition at a variety of spatial and temporal scales. Such combined measurements are useful for modeling changes to urban climate, hydrology, and biogeochemical cycles caused by modification of the landscape. We compare gridded landscape metrics derived from expert system land cover classification of ASTER to corresponding MODIS NDVI data at scales of 250 m/pixel, 500 m/pixel, and 1 km/pixel in order to determine which of these scales is optimal for monitoring of urban biophysical processes and landscape structure change. Weak positive and negative correlations between NDVI and landscape structure were observed at all three spatial scales for the metrics Class Area, Mean Patch Size, Edge Density, and Interspersion/Juxtaposition Index.

DOI

[10]
Yuan F, Bauer M E.Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery[J]. Remote Sensing of Environment, 2007,106:375-386.This paper compares the normalized difference vegetation index (NDVI) and percent impervious surface as indicators of surface urban heat island effects in Landsat imagery by investigating the relationships between the land surface temperature (LST), percent impervious surface area (%ISA), and the NDVI. Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data were used to estimate the LST from four different seasons for the Twin Cities, Minnesota, metropolitan area. A map of percent impervious surface with a standard error of 7.95% was generated using a normalized spectral mixture analysis of July 2002 Landsat TM imagery. Our analysis indicates there is a strong linear relationship between LST and percent impervious surface for all seasons, whereas the relationship between LST and NDVI is much less strong and varies by season. This result suggests percent impervious surface provides a complementary metric to the traditionally applied NDVI for analyzing LST quantitatively over the seasons for surface urban heat island studies using thermal infrared remote sensing in an urbanized environment.

DOI

[11]
张新乐,张树文,李颖,等.土地利用类型及其格局变化的热环境效应——以哈尔滨市为例[J].中国科学院研究生院学报,2008,25(6):756-763.采用极差标准化方法消除由于时相差异造成遥感影像获取地表温度值 的不可比性;用2km格网内不同土地利用类型所占的面积比例表征土地利用格局,以中国哈尔滨市为例,研究城市热场分布的空间格局、时空变化规律,探讨不同 土地利用类型的空间格局对城市热环境的影响.结果表明:哈尔滨市建成区存在显著的热岛效应并呈增强态势、市区总体地表温度升高.各用地类型随面积比例的升 高平均地表温度相互间差异变小,建设用地对热岛效应的作用增强,水体缓解热岛效应的作用减弱,热环境的空间差异性变得不明显.

[ Zhang X L, Zhang S W, Li Y, et al.Study on the thermal environment effect of land use type and pattern changes: Harbin city[J]. Journal of the Graduate School of the Chinese Academy of Sciences, 2008,25(6):756-763. ]

[12]
Xu H Q, Ding F, Wen X L.Urban expansion and heat island dynamics in the Quanzhou region, China[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2009,2(2):74-79.Urban spatial expansion in the Quanzhou region of southeastern China has been accelerated over the past 20 years. This has caused land cover changes and, thus, has significant impacts on the local ecosystem and climate. To study the urban expansion and heat island dynamics of the region over the past 20 years, multitemporal Landsat TM images of 1987, 1996, and 2006 were used. The estimation of the urban expansion was assisted by the index-based built-up index (IBI) through enhancing built-up land features in the images. The urban-heat-island (UHI) effect was assessed using the urban-heat-island ratio index (URI). Multitemporal analysis indicates that the great increase in urban area has resulted in the development of UHIs in the region. Regression statistics reveal that built-up land has a positive exponential relationship with land surface temperature (LST). Therefore, the increase in built-up land percentage can exponentially accelerate the rise of LST.

DOI

[13]
Styers D M, Chappelka A H, Marzen L J, et al.Scale matters: indicators of ecological health along the urban-rural interface near Columbus, Georgia[J]. Ecological Indicators, 2010,10:224-233.lt;h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">Ecological data obtained from field plots can provide detailed information about ecosystem structure and function. However, this information typically reflects processes that occur over small spatial areas. Accordingly, it is difficult to extrapolate these data to patterns and processes that take place at regional scales. Satellite imagery can provide a means to explore environmental variables over a larger area. Therefore, our main objective was to examine the utility of a regional ecological assessment tool using landscape indicators of ecosystem health in a rapidly developing area of West Georgia near the city of Columbus. Indicator variables included in the assessment were: population density and change, road density, percent forest land-cover, forest patch density, landscape Shannon's Diversity Index, proportion of all streams with roads within 30&#xA0;m, proportion of area that has agriculture on slopes &gt;3%, proportion of all streams with adjacent agriculture, and proportion of all streams with adjacent forest cover. Cluster analysis was used to combine these variables into different groups, and resulting cluster means were used to rank regional areas according to degree of environmental impact. To assess the spatial accuracy of this tool results were compared to those obtained from a separate plot-level field-based forest condition study. Results derived using the landscape ecological assessment tool suggest that rural areas were the least environmentally impacted (or most healthy) of all areas in West Georgia, and support the findings from the field study. Results for developing areas were mixed between the two different studies and may be attributed to differences in scale. Overall, it appears that this tool is useful for broad generalizations about a given landscape, but is not detailed enough for site-specific management goals due to its inherent coarse spatial resolution (30&#xA0;m&#xA0;&times;&#xA0;30&#xA0;m). However, these site-specific goals may be achieved using higher resolution (1&#xA0;m&#xA0;&times;&#xA0;1&#xA0;m) satellite imagery and warrants further research. In any case, this tool is a useful asset for anyone needing a rapid diagnosis of ecosystem health in an inexpensive and timely manner.</p>

DOI

[14]
黄初冬,陈前虎,彭卫兵,等.杭州市“热岛效应”与城市功能布局的关联分析[J].规划师,2011,5(27):46-49.城市"热岛效应"与城市用地的 功能布局密切相关,运用Landsat TM/ETM+和Terra AS-TER时间序列遥感数据,对近年来杭州市"热岛效应"的空间分布、时间变化进行分析。将杭州市的地表温度数据与历年的城市用地状况进行关联分析可 知,从2000年开始,杭州市的"热岛效应"基本呈减弱的趋势,且与城市用地密切相关,因此,宜采用中心城区+外围组团的结构模式,保留足够的生态屏障, 加强对城市不可建设用地的保护,提升城市生态环境的质量。

DOI

[ Huang C D, Chen Q H, Peng W B, et al.Relevance analysis of Hangzhou hot island effect and urban functional layout[J]. Planners, 2011,5(27):46-49. ]

[15]
Gupta K, Kumar P, Pathan S K, et al.Urban neighborhood green index: a measure of green spaces in urban areas[J]. Landscape and Urban Planning, 2012,105(3):325-335.Urban green spaces (UGS) form an integral part of any urban area and quantity and quality of UGS is of prime concern for planners and city administrators. Objective measure of greenness using remote sensing images is percentage area of green, i.e., Green Index (GI), which is insensitive to spatial arrangement within the areal units. Measuring UGS at neighborhood level is important as neighborhood is the working level for application of greening strategies. Neighborhood (NH) is synonymous of nearness and can be defined as an area of homogeneous characteristics. The Urban Neighborhood Green Index (UNGI) aims to assess the greenness and can help in identifying the critical areas, which in turn can be used to identify action areas for improving the quality of green. For the development of UNGI, four parameters, i.e.. CI. proximity to green, built up density and height of structures were used and weighted using Saaty's pair wise comparison method. Four different types of NH were compared and it was found that mean CI (0.44) is equal for high-rise low density and low-rise low density NH, i.e., both areas have same quality of urban green based on CI. But mean UNGI is higher for low-rise low-density NH (0.62), as compared to high-rise low-density NH (0.54), hence, area of highrise NH requires more amounts of good quality properly distributed green as compared to low-rise NH. The input for UNGI is easily derivable from RS images, besides the developed method is simple, and easily comprehendible by city administrators and planners. (C) 2012 Elsevier B.V. All rights reserved.

DOI

[16]
祝善友,张桂欣,刘莹.苏州下垫面格局演变及其局地热环境效应[J].地理科学,2012,32(7):859-865.以苏州为研究区域,选择1986年Landsat TM、2006年Landsat ETM+遥感图像为主要数据源,分别提取下垫面类型和地表温度,研究景观格局指数的粒度效应,并在适宜粒度下分析景观格局的演变特征,进而研究其与热环境变化之间的关系。结果表明,研究区20多年来景观破碎化程度、斑块形状复杂程度与景观多样性变大,而聚集程度变低,热场变异指数增大区域的景观格局指数变化更为明显,这说明下垫面格局演变对热环境变化具有一定的影响作用。

[ Zhu, Y S, Zhang G X, Liu Y. Change of underlying surface pattern and its local thermal environment effect in Suzhou city[J]. Scientia Geographic Sinica, 2012,32(7):859-865. ]

[17]
Wu H, Ye L P, Shi W Z, et al.Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China[J]. International Journal of Applied Earth Observation and Geoinformation, 2014,32(1):67-78.Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.

DOI

[18]
Robert B, Mathias B, Saskia F, et al.Automated GIS-based derivation of urban ecological indicators using hyperspectral remote sensing and height information[J]. Ecological Indicators, 2015,48:218-234.Urban ecological indicators allow the objective and quantitative characterisation of ecological conditions in a spatially continuous way by evaluating the influence of urban surface types with respect to ecological functions and ecosystem services. Although the concept had already been developed in the 1980s, the variety of existing indicators had not been widely applied yet in urban planning practice, because of the high manual mapping effort that is required for spatially differentiated urban surface mapping. This paper presents a new automated remote sensing and GIS-based system for the flexible and user-defined derivation of urban ecological indicators. The system is based on automated surface material mapping using airborne hyperspectral image data and height information. Because the material classes obtained from remote sensing analysis differ in part from the surface types needed for the calculation of urban ecological indicators, they have been transformed into so-called linking categories representing the basis for the automated GIS-based derivation of urban ecological indicators. For this purpose, a computer-based system for flexible indicator derivation has been developed, allowing the user-defined integration of indicators based on the variable determination of mapping units, linking categories and respective weighting factors. Based on a comprehensive review of existing ecological indicators, 14 indicators have been selected and implemented in the system. To demonstrate the potential of the new system, a variety of indicators has been derived for two test sites situated in the German cities of Dresden and Potsdam, using city blocks defined by the municipal authorities as spatial mapping units. The initial mapping of surface materials was automatically performed on the basis of airborne hyperspectral image data acquired by the HyMAP system. The results of subsequent GIS-based indicator calculation were validated using results from field-based reference mapping that had been carried out for selected city blocks situated in both cities. An accuracy assessment for these reference city blocks has revealed mean errors of approximately 4%, confirming the suitability of the developed automated GIS-based system for flexible and efficient indicator calculation.

DOI

[19]
国家环保总局.中华人民共和国环境保护行业标准(试行)HJ/T192-2006[S].北京:中国环境科学出版社, 2006.

[ The State Environmental Protection Administration. The People's Republic of China environmental protection industry standards (trial) HJ/T192-2006[S]. Beijing: China Environmental Science Press, 2006. ]

[20]
黄蓓佳,王少平,杨海真.基于GIS和RS的城市生态环境质量评价[J].同济大学学报(自然科学版),2009,37(6):805-809.以上海市闵行区为例,从社会、 经济、自然等方面构建了一套城市生态环境质量的指标体系,结合专家咨询和层次分析法,确定了各指标的权重体系.结合反映城市生态环境质量的指标体系和权 重,采用基于矢量的空间叠加方法,对表征研究区域的城市生态环境质量的单因子和多因子的空间分异规律及其成因进行了探讨,为研究区域的城市生态化建设提供 了决策支持.

[ Huang B J, Wang S P, Yang H Z.City eco-environment quality assessment based on GIS and RS[J]. Journal of Tongji University (Natural Science), 2009,37(6):805-809. ]

[21]
徐涵秋. 区域生态环境变化的遥感评价指数[J].中国环境科学,2013,33(5):889-897.基于遥感信息技术提出一个新型的遥感生态指数(RSEI),以快速监测与评价区域生态质量.该指数耦合了植被指数、湿度分量、地表温度和土壤指数等4个评价指标,分别代表了绿度、湿度、热度和干度等4大生态要素.与常用的多指标加权集成法不同的是,本研究提出用主成分变换来集成各个指标,各指标对RSEI的影响是根据其数据本身的性质来决定,而不是由人为的加权来决定.因此,指标的集成更为客观合理.将RSEI应用于福建长汀水土流失区,并与国家环境保护部《生态环境状况评价技术规范》中的生态指数EI的计算结果相比较,发现二者的结果具有可比性.不同的是,RSEI不仅可以作为一个量化指标,而且还可以对区域生态环境变化进行可视化、时空分析、建模和预测.因此,可弥补EI指数在这些方面的不足.

[ Xu H Q.A remote sensing index for assessment of regional ecological changes[J]. China Environmental Science, 2013,33(5):889-897. ]

[22]
国家环保总局.中华人民共和国环境保护行业标准HJ192-2015[S].北京:中国环境科学出版社,2015.

[ The State Environmental Protection Administration. The People's Republic of China environmental protection industry standards HJ192-2015[S]. Beijing: China Environmental Science Press, 2015. ]

[23]
福州市人民政府. 福州市城市总体规划(2011-2020年)[EB/OL]. [2014-08-18]. [2015-08-05]. .

[The Government of Fuzhou. The master planning of Fuzhou (2011-2020)[EB/OL]. , 2014-08-18/2015-08-05.]

[24]
中华人民共和国国家标准. GB50137-2011, 城市用地分类与规划建设用地标准[S].2012.

[ GB50137-2011. Code for classification of urban land use and planning standards of development land[S].2012. ]

[25]
Chander G, Markham B L, Helder D L.Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors[J]. Remote Sensing of Environment, 2009,113(5):893-903.This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of-Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.

DOI

[26]
Chavez P S Jr. Image-based atmospheric corrections-revisited and revised[J]. Photogrammetric Engineering and Remote Sensing, 1996,62(9):1025-1036.

[27]
徐涵秋. 基于影像的Landsat TM/ETM+数据正规化技术[J].武汉大学学报·信息科学版,2007,32(1):62-66.阐述了基于影像的LandsatTM／ETM^＋的数据正规化技术及其发展。该技术通过将 Landsat影像的亮度值转换成传感器处的辐射值和反射率采对影像进行辐射校正。实例表明，使用正规化技术处理后的影像可以明显削弱日照和大气的影响， 去除它们产生的噪声；其所书的传感器处的反射率与地面实测反射率的RMS值非常小。

DOI

[ Xu H Q.Image-based normalization technique used for Landsat TM E/TM+ imagery[J]. Geomatics and Information Science of Wuhan University, 2007,32(1):62-66. ]

[28]
温小乐,林征峰,唐菲.新兴海岛型城市建设引发的生态变化的遥感分析——以福建平潭综合实验区为例[J].应用生态学报,2015,26(2):541-547.<div style="line-height: 150%">福建省平潭岛于2010年被正式确立为&ldquo;福建省平潭综合实验区&rdquo;，由此引发了新兴海岛型城市的建设高潮.本研究利用遥感生态指数(RSEI)，基于2007年Landsat-5影像和2013年Landsat-8影像，分析了平潭综合实验区建设初期的生态状况及其时空变化趋势和变化原因.结果表明： 研究期间，作为生态脆弱的海岛，平潭岛的生态状况整体处于中等水平，在综合实验区建设初期(2007&mdash;2013年)有进一步下降的态势，RSEI值从2007年的0.511下降至2013年的0.450，降幅达14%；占全岛面积约36.5%区域的生态状况趋于退化，且主要发生在中部和西南部地区.究其原因主要是由于综合实验区建设带来的大面积成片开发，使得岛内原本不多的植被遭到进一步破坏.平潭岛在综合试验区建设中应及时制定并落实科学有效的生态保护措施，以遏制其生态质量下滑的趋势.</div><div style="line-height: 150%">&nbsp;</div>

[ Wen X L, Lin Z F, Tang F.Remote sensing analysis of ecological change caused by construction of the new island city: Pingtan comprehensive experimental zone, Fujian Province[J]. Chinese Journal of Applied Ecology, 2015,26(2):541-547. ]

[29]
张灿,徐涵秋,张好,等.南方红壤典型水土流失区植被覆盖度变化及其生态效应评估——以福建省长汀县为例[J].自然资源学报,2015,30(6):917-928.南方红壤典型水土流失区——福建省长汀县曾因生态破坏导致严重的水土流失。经过多年以植树为主的生态修复,该县生态面貌有了明显的改观。论文首先采用线性光谱混合分析模型计算植被覆盖度,并在此原始模型的基础上提出了对地形阴影进行修正的方法来获取植被覆盖度。精度验证表明,在线性光谱混合分析模型中加入山地指数(NDMVI)波段能够削弱地形阴影问题,提高植被覆盖度反演精度。在此基础上利用多时相遥感影像分析了长汀2001—2013年植被覆盖度的时空变化,并利用遥感生态指数(RSEI)定量评价了长汀水土流失生态修复的效果。结果表明,经过13 a的水土流失治理,长汀的植被覆盖度有了明显的升高,从2001年的75.1%上升到2013年的86.5%。RSEI生态指数值也随之上升,生态等级为优良的面积比例从85.83%增加到90.59%,反映了长汀县生态质量整体有了明显的提高。植被的生态效应定量研究表明,长汀县的植被覆盖度每增加10%,RSEI生态指数值至少提高10%,植被覆盖度的生态提升效应显著。

DOI

[ Zhang C, Xu H Q, Zhang H, et al.Fractional vegetation cover change and its ecological effect assessment in a typical reddish soil region of southeastern China: Changting county, Fujian province[J]. Journal of Natural Resources, 2015,30(6):917-928. ]

[30]
罗春,刘辉,戚陆越.基于遥感指数的生态变化评估——以宁德市为例[J].国土资源遥感, 2014,26(4):145-150. ]利用遥感技术进行区域生态变化评估，能够得到周期长、现时性强的结果。以常宁市为例，采用遥感生态指数方法来监测水土流失区的生态变化，选取1990年，2002年及2009年的Landsat TM 遥感图像，分别提取绿度、湿度、热度和干度4个生态因子作为评估指标，结合主成分分析方法，定量、客观地评估研究区域20 a间生态变化。结果表明，遥感生态指数方法能够很好地评价水土流失区生态修复的效果，其中，遥感生态指数值上升了22.39%，生态为优良等级所占的面积比例先从1990年的13.086%下降到2002年的4.006%，再上升到了2009年16.699%，说明常宁市经过20 a的水土流失治理，该区域的生态质量先急剧下降再有了较大的改善。通过对常宁市调查分析，以植树造林和施工预防为主的措施对生态质量的改善有较好的效果。

DOI

[ Luo C, Liu H, Qi Y L. Ecological changes assessment based on remote sensing indices: a case study of Changning city[J]. Remote Sensing for Land & Resources, 2014,26(4):145-150. ]

[31]
Crist E P.A TM tasseled cap equivalent transformation for reflectance factor data[J]. Remote Sensing of Environment, 1985,17(3):301-306.A transformation of TM waveband reflectance factor data is presented which produces features analogous to TM Tasseled Cap brightness, greenness, and wetness. The approach to adjusting the transformation matrix to other types of reflectance factor data (different instrument or band response) is described in general terms.

DOI

[32]
Huang C, Wylie B, Yang L, et al.Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance[J]. International Journal of Remote Sensing, 2002,23(8):1741-1748.A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study.

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[33]
Sobrino J A, Jimenez-Munoz J C, Paolini L. Land surface temperature retrieval from Landsat TM5[J]. Remote Sensing of Environment, 2004,90(5):434-440.In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared data supplied by band 6 of the Thematic Mapper (TM) sensor onboard the Landsat 5 satellite are compared. The first of them lies on the estimation of the land surface temperature from the radiative transfer equation using in situ radiosounding data. The others two are the mono-window algorithm developed by Qin et al. [International Journal of Remote Sensing 22 (2001) 3719] and the single-channel algorithm developed by Jiménez-Mu09oz and Sobrino [Journal of Geophysical Research 108 (2003)]. The land surface emissivity (LSE) values needed in order to apply these methods have been estimated from a methodology that uses the visible and near infrared bands. Finally, we present a comparison between the LST measured in situ and the retrieved by the algorithms over an agricultural region of Spain (La Plana de Requena-Utiel). The results show a root mean square deviation (rmsd) of 0.009 for emissivity and lower than 1 K for land surface temperature when the Jiménez-Mu09oz algorithm is used.

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[34]
Nichol J.An emissivity modulation method for spatial enhancement of thermal satellite images in urban heat island analysis[J]. Photogrammetric Engineering and Remote Sensing, 2009,75(5):547-556.This study examines and validates a technique for spatial enhancement of thermal satellite images for urban heat island analysis, using a nighttime ASTER satellite image. The technique, termed Emissivity Modulation, enhances the spatial resolution while simultaneously correcting the image derived temperatures for emissivity differences of earth surface materials. A classified image derived from a higher resolution visible wavelength sensor is combined with a lower resolution thermal image in the emissivity correction equation in a procedure derived from the Stephan Bolzmann law. This has the effect of simultaneously correcting the image-derived "Brightness Temperature" (Tb) to the true Kinetic Tempera- ture (Ts), while enhancing the spatial resolution of the thermal data. Although the method has been used for studies of the urban heat island, it has not been validated by comparison with "in situ" derived surface or air temperatures, and researchers may be discouraged from its use due to the fact that it creates sharp boundaries in the image. The emissivity modulated image with 10 m pixel size was found to be highly correlated with 18 in situ surface and air temperature measurements and a low Mean Absolute Difference of 1 K was observed between image and in situ surface temperatures. Lower accuracies were obtained for the Ts and Tb images at 90 m resolution. The study demonstrates that the emissivity modulation method can increase accuracy in the computation of kinetic temperature, improve the relationship between image values and air temperature, and enable the observation of microscale temperature patterns.

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[35]
ICESS. MODIS UCSB emissivity library [EB/OL]. .

[36]
Xu H Q.A new index for delineating built-up land features in satellite imagery[J]. International Journal of Remote Sensing, 2008,29(14):4269-4276.A new index derived from existing indices - an index-based built-up index (IBI) - is proposed for the rapid extraction of built-up land features in satellite imagery. The IBI is distinguished from conventional indices by its first-time use of thematic index-derived bands to construct an index rather than by using original image bands. The three thematic indices used in constructing the IBI are the soil adjusted vegetation index (SAVI), the modified normalized difference water index (MNDWI) and the normalized difference built-up index (NDBI). Respectively, these represent the three major urban components of vegetation, water and built-up land. The new index has been verified using the Landsat ETM+ image of Fuzhou City in southeastern China. The result shows that the IBI can significantly enhance the built-up land feature while effectively suppressing background noise. A statistical analysis indicates that the IBI possesses a positive correlation with land surface temperature, but negative correlations with the NDVI and the MNDWI.

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