近30年秦淮河流域水面变化及其驱动因素分析

针对秦淮河流域城市化水文效应对水文水资源影响,分析秦淮河流域和城市区水面时空变化及其驱动因素,选取流域1985—2015年49景Landsat影像,采用基于K均值聚类水体指数法对比分析水体指数的性能。在探讨水面率与降雨量、温度、流量关系基础上,从自然和人为因素2方面分析水面变化的主要驱动因素。结果表明,流域水面率在2.42%(62.69km~2)~5.05%(130.56km~2)变化,水面增加了8.48km~2,增长8.12%;城市区水面率在2.76%(8.63km~2)~6.63%(20.73km~2)变化,水面减少了6.60km~2,缩减43.15%;流域年降雨量与流量变化态势相同,可知降雨量对水面贡献较小;1988—2015年转移矩阵表明,流域32.34%水面转为耕地,城市区27.90%和20.52%水面转为建设用地与耕地,其他地类转换为水面比重较小;人为因素是水面变化的主要驱动因素。本文对研究城市化水文效应具有一定的理论和实际意义。     

基于高分辨率遥感影像的不透水面信息提取方法研究

不透水面是城市地区的典型特征,它与城市总用地面积的比值--不透水率作为一个重要的城市生态指数常出现于城市水文、水质、面源污染以及城市植被制图等研究中。利用高分辨率遥感影像提取不透水面不仅可获得较高精度的不透水面信息,而且可为中低分辨率遥感影像的不透水面提取提供样本训练区并检验其提取精度。本文利用南京IKONOS影像,采用面向对象分类方法提取不透水面信息,初步解决了阴影归类和遮盖不透水面的植被剔除等问题,提高了不透水面信息提取精度。     

基于LightGBM和多光谱—SAR多特征综合的中亚干旱区城市不透水面提取

不透水面是评价城市化水平和城市生态环境的重要指标,是近年来城市遥感研究中的热点方向之一。与湿润、半湿润区相比,干旱区城市植被覆盖度较低,不透水面与裸土、荒漠之间相似的光谱特征导致传统基于光学影像的亚像元分解法与光谱指数法在干旱区不透水面提取的适用性降低。针对该问题,提出一种多光谱与合成孔径雷达（SAR）影像多特征综合的方法以增大不透水面与其他地物覆盖类型之间的特征差异,从而提取干旱区城市不透水面。以阿斯塔纳、塔什干和杜尚别3个中亚城市为研究区,哨兵2号和哨兵1号影像为数据源,通过LightGBM算法对多光谱和SAR图像的空间特征、SAR的极化特征进行分类并提取不透水面。研究对比了不同特征组合以及不同分类方法的不透水面提取结果,实验结果表明：多光谱与SAR影像多特征综合的方法能有效提高干旱区不透水面提取精度,明显改善干旱区其他土地覆盖类型错分为不透水面的问题;LightGBM算法与XGBoost、HistGBT等基于梯度提升决策树的算法和随机森林等方法相比能获取更高的精度,更适用于干旱区不透水面提取。这表明基于LightGBM以及多光谱和SAR多特征联合的方法能够有效提取中亚干旱区城市不...     

1985～2020年上海市不透水面时空特征演化分析

不透水地表的分布与变化是城市发展过程的直观标志和重要指示因子,在城市生态功能、城市规划和可持续发展研究等方面发挥着重要作用。利用中国科学院空天信息创新研究院研发的1985～2020年长时序30m不透水面动态数据集(GISD30),结合GIS空间统计方法,研究分析了过去35 a上海市不透水面时空特征演化。结果表明：(1)35 a来,上海市不透水面面积从878.07 km²增长至2 849.90 km²,面积扩张到原来的3.25倍,随着1990年浦东新区的开发开放,上海城市化进程明显加快,1990～2010年上海市不透水面扩张最为显著,2010年以后不透水面扩张速度和扩张强度开始显著下降。(2)从区位分异特征来看,不透水面迅速扩张的行政区主要位于城市郊区,其中,浦东新区在各个研究时段的扩张速度均大于其他区划。(3)基于紧凑度和分形维数发现,中心城区不透水面空间分布结构趋于疏散,上海市整体不透水面边界复杂程度降低,城市空间形态更加规则。(4)“南北两翼”的上海城市扩张特点较为明显,南部郊区的高强度扩张带动了不透水面空间重心的持续南移,发展至2010...     

多时相影像福州市不透水面对城市地表温度的空间分布研究

随着城市化进程的加快,城市热力场也随之发生变化,从而影响着城市区域环境、社会经济以及社会环境。由于NDVI具有季相变化的不稳定性,本研究采用两个时相TM/ETM+影像分析福州市及其周边地区不透水面对热力场的时空分布变化状况。为了获取精确的城市不透水面信息,本实验采用NDVI二元法结合2000年同区域的IKONOS影像提取不透水面信息。通过定量分析不透水面百分比、NDVI与地表温度的关系,得出不透水面百分比与城市地表温度呈线性相关,其相关系数在0.7左右;尤其30%以上的不透水面对地表热环境的空间分布影响最为突出,因此,相对于不稳定的NDVI而言,不透水面信息能更好地反映城市热环境的空间分布状况。     

哈尔滨城乡梯度建设用地结构变化及不透水面遥感监测分析

在快速城镇化背景下,客观掌握城市扩张进程中的城乡建设用地及内部不透水面变化特征,有利于优化大都市城乡用地结构及空间融合发展。基于城乡建设用地及不透水面遥感监测数据集,应用空间分析模型,对哈尔滨2000~2015年城乡建设用地规模、结构及内部不透水面时空演变特征进行分析,探究城市扩张格局、区位差异、建设用地利用强度及城乡之间的差异。结果表明：①2000年以来城乡建设用地快速扩张了158.32 km²,年变化率和动态度均呈先增大后减小趋势;从城市核心区至远郊区方向其扩张规模依次增大,建设重点不断向城市周边推移,呈现出较明显的空间异质性;②城镇建设用地和独立工矿用地面积及占比逐年增加,扩张来源均以耕地为主;农村居民点占比降低了13.14%,城乡建设用地结构特征发生了较明显变化;③2000~2015年城乡建设用地内部不透水面面积和比例分别增加了145.32 km²和10.04%,城镇建设用地利用强度已达到较高水平,农村居民点用地利用强度快速提高,城市和农村之间的差距不断缩小;自城市核心区至远郊区方向不透水面比例不断降低,可利用潜力越大,不透水面面积增量、比例增量、比例增长率及扩张强度大体呈增加趋势,不透水面与城乡建设用地规模变化趋势相近,可在一定程度上揭示城市扩张轨迹。     

通过不透水面聚集密度法提取城市建成区

针对已有基于不透水面提取城市建成区的方法无法保证建成区连续性的问题,提出了一种基于对象不透水面聚集密度的城市建成区提取方法。该方法计算了不透水面聚集密度并进行分级,提取聚集程度高的区域为输入对象,并将被建成区完全包围的绿地水体也包含在内;利用长时序遥感影像建成区提取结果,使用城市空间形态扩展指标对济南市1997—2017年城市时空演化特征进行分析。结果表明,该方法提取精度达到93.5%,能准确刻画出城市形态,保持建成区的完整性;1997—2017年间,济南市建成区面积不断扩张,扩张速度与强度分别达到10.48km~2/a、0.32%,呈现带状轴向扩展模式;1997—2013年,建成区扩展的不规则程度在逐年减少,2013年以后建成区形状变得复杂。     

1992~2013我国干旱区城市不透水遥感制图与扩张过程分析

城市不透水地表作为城市建成区的重要环境指标和物理参数,在城市管理规划、环境评估、灾害预测、城市热岛以及气候变化等领域具有重要价值。及时准确地获取区域尺度城市不透水地表信息,对于城市发展综合规划、科学研究等具有重要意义。以DMSP（Defense Meteorological Satellite Program）和MODIS（Moderate Resolution Imaging Spectroradiometer）为主要数据,通过构建植被调节型不透水指数（Vegetation-Adjusted Impervious Surface Index, VAISI）和非线性机器学习模型支持向量回归（Support Vector Regression, SVR）,完成了1992~2013年我国干旱区主要城市不透水面的22期遥感制图与变化过程聚类分析。研究结果表明：近20 a来我国干旱区城市不透水面总体上扩张幅度较大;时间变化过程上呈现显著扩张的趋势,且这一扩张在过程在2000年前后出现了提速;空间上,干旱区城市扩展的区域异质性显著,各城市不透水面扩张速度不均衡,不同等级规模城市扩张的速度差异明显。结合城市扩张动态度和城市面积聚类分析,我国干旱区主要城市的扩张过程可分为：高速扩张型、快速扩张型、中速扩张型和低速扩张型。     

城市不透水面及其与城市热岛的关系研究-以泉州市区为例

利用Landsat TM卫星影像提取了泉州市1989到1996年的城市建成区不透水面,并研究了其与城市热岛之间的关系。根据Ridd(1995)提出的城市建成区不透水面与植被覆盖度有很强的负相关关系的思想,先利用归一化植被指数求出泉州市建成区的植被覆盖度,进而提取了泉州市建成区的不透水面。通过比较所提取的两个时相不透水面信息,可以看出泉州市区不透水面的面积在7年里有了明显的增加,并主要沿研究区东南部扩展。通过将所提取的不透水面信息与利用TM6波段反演的地表温度进行相关分析,可发现二者之间存在着明显的正相关关系。     

厦门市不透水面的时空演变

针对关于不透水面时空演变研究还缺乏有效的定量方法的问题,以厦门市为研究区,引入不透水面变化轨迹、不透水面重心及其迁移路径,定量剖析不透水面时空演变过程。结果表明,研究时段内不透水面持续扩张,研究区21%和35.32%的面积最终分别转化为高覆盖和中覆盖不透水面类型。转化为高覆盖类型的轨迹分布在各个行政区的建成区及其周边,另外3种类型的变化轨迹以圈层结构的形式,随着时间的推进在空间上不断远离原城区。20年来厦门本岛不透水面重心稳定在湖里区与思明区的交界地带,受岛内用地条件和自然条件的限制,重心迁移距离较小,岛外4个区不透水面重心迁移距离大于厦门岛,尤其是集美区4个时段内的迁移距离均较大。     

Application of a normalized difference impervious index (NDII) to extract urban impervious surface features based on Landsat TM images

The ecological conditions of urban areas have been deteriorating in some aspects due to population growth and increasing expansion, with significant effects on human health. Impervious surface areas are an important indicator of urban ecological environmental change, therefore quickly and accurately estimating impervious surface areas is essential to monitoring the urban dynamics of change and human activities and their effects on urban environmental quality. Currently, few methods that are applied in estimating urban impervious surfaces are capable of providing results quickly and accurately. Accordingly, this study proposes a new index, named the normalized difference impervious index (NDII), based on Landsat TM images, which uses the visible (red, green, and blue) and thermal bands. The index was used to extract the impervious surface areas of Nanjing city, Jiangsu Province, China, and we assume that the average value of five times strict supervised classification is the true value of impervious surfaces. A combination of red and thermal bands extracted the impervious surfaces with a producer’s accuracy of 86.9%, a user’s accuracy of 84.6%, an overall accuracy of 91.4%, and a kappa coefficient of 0.8. The accuracy is 87.7% validated by high-resolution images. This method can rapidly extract urban impervious surface areas with promising accuracy.     

基于线性光谱混合分析的乌鲁木齐不透水层提取及其时空变化分析

利用Landsat TM、OLI多光谱卫星遥感数据,采用VIS（植被－不透水层－土壤）模型和线性光谱混合分析法对丝绸之路经济带核心区乌鲁木齐建城区及其周边进行丰度估算,并针对红色彩钢板屋顶在不透水层丰度图像上低亮度特点,进行改进处理,提高了不透水层丰度估算精度。研究结果表明：1994~2018年的24年间乌鲁木齐市不透水层呈现出显著扩展的特点,其面积从140.41 km²扩大到462.62 km²;扩展速率在1994~2005年间缓慢上升,2005年之后迅速上升;扩展强度先上升,2010~2015年达到最大,之后出现下降;同时,城市不透水层的空间扩展具有明显差异,向西和东北方向扩展最为显著。综合分析指出：乌鲁木齐城市不透水层的空间扩展受到周边山体地形和煤矿开采等因素的限制,而“乌昌一体化”政策是城市扩展的主要助力因素。     

一种不透水面精细制图新方法及其在城市SDGs指标评估上的应用

城市不透水面是城市化程度的重要指示器,也是城市环境的重要敏感因子.联合国提出的城市可持续发展SDG11.3.1指标——城市土地使用率与人口增长率之比(LCRPGR)需要有效监测土地城镇化与人口城镇化关系.针对其监测与评估中高分辨率和高精度城市用地产品缺失,以及低纬度地区城市可持续发展研究较少的问题.基于Google E...     

Analyzing Temporal-spatial Change of Urumqi Impervious Surface using Linear Spectral Mixture Analysis

The method of linear spectral mixture analysis combined with V-I-S model(Vegetation-Imperious surface-Soil) is used to estimate the impervious surface abundance of Urumqi city, which is in the core area of the Silk Road Economic Belt, using Landsat OLI and TM multi-spectral data. Because the red color steel shed has low brightness on the impervious surface brightness image, an improvement was proposed, and then verify the accuracy through the interpretation of high-resolution satellite imagery. The results show that: the impervious surface area in Urumqi displayed a significant expansion from 140.41 km² to 462.62 km² during past 24 years (1994 to 2018). It expanded slowly during 1994 to 2005, and increased rapidly since 2005. The expansion intensity increased during 1994~2015 and decreased after 2015; and the spatial expansion of urban impervious surface is significantly different, with the largest expansion area in the west and northeast direction. The comprehensive analyses suggested that the expansion of the impervious surface of Urumqi city is limited by the surrounding mountain topography and coal mining, and the “Urumqi-Changji integration” policy is the major driving factor for urban expansion in the past 24 years.     

基于不透水地表比例的城市扩展研究

不透水地表比例是衡量城市化水平的一个重要指标,采用不透水地表比例可以研究城市的空间变化和扩展并定量化城市空间变化和扩展的强度。使用多端元光谱混合分析方法可以从TM影像中提取亚像元尺度的不透水地表比例,用该方法从两个时相的TM影像中提取南京都市发展区不透水地表比例,在此基础上定性和定量地分析该区域的空间变化和扩展。     

Evaluation of Urban Expansion in Chongqing City based on the Nighttime Light Data

Urbanization is an important embodiment of regional economic development.Its progress reflects the level of economic development in the region.Since Chongqing being directly under the Central Government in 1997,it has enjoyed rapid economic growth and rapid urbanization.Looking for an intuitive and efficient method of urbanization is of great practical significance to correctly grasp the achievements of urbanization in Chongqing from the overall situation.Through the comparison of statistical data on night lighting data,we can extract the built-up area of Chongqing year after year.The city gravity model is based on the results.A night light index is established and used to calculate the speed of urban expansion.The result indicates that the urban distributions in Chongqing is spatially distributed and expanded in all directions.There are great differences between urban areas and rural areas and urban area urbanization level is higher.The city gravity gradually shifted from Yuzhong district to Yubei district.The speed of city expansion maintains high.Our study can afford refers for the planning and construction of the Chongqing city.     

Annual dynamics of impervious surfaces at city level of Pearl River Delta metropolitan

Human activities have transformed natural land surface to artificial constructions, which causes the urban regions increasingly expanding. Urban development can be reflected by the dynamic changes of impervious surfaces, which can be assessed using time-series satellite data. The Pearl River Delta (PRD) metropolitan has witnessed fast urban development over past decades. Even though many studied have focused on monitoring the urbanization of megacities, there is still a lack of comprehensive understanding about the long-term annual dynamics of urban impervious surfaces at city level in PRD. In this study, MOD09A1 (MODIS Surface Reflectance 8 Day L3 Global 500 m) products were chosen to assess the annual dynamics of impervious surface at city level in PRD. Temporal filtering was utilized to improve the accuracy of the impervious surface estimation. Moreover, a new index, normalized difference urban development index (NDUDI) was proposed to investigate relative development of impervious surface in PRD. Additionally, the economy factor, Gross Domestic Product (GDP) was introduced to reveal the correlation with the impervious surfaces. Results demonstrated that the overall accuracy for impervious surface extraction was about 91.00–94.00%. The impervious surfaces area in PRD dramatically increased from 6000 km² to 115,840 km² in the past 16 years. Guangzhou and Foshan have the fastest developing speed, while Dongguan, Shenzhen and Foshan sacrificed much more lands to the construction of PRD than other cities. Besides, areas of impervious surface per city show very good correlations with GDP in city of Guangzhou, Huizhou, Foshan, Zhongshan, Hong Kong and Zhuhai-Macau. The scatter plot between NDUDI and GDP data display different clustering pattern between different cities.     

An integrated soft and hard classification approach for evaluating urban expansion from multisource remote sensing data: a case study of the Beijing–Tianjin–Tangshan metropolitan region,China

Integrating soft and hard classification to monitor urban expansion can effectively provide comprehensive urban growth information to urban planners. In this study, both the impervious surface coverage (as a soft classification result) and land cover (as a hard classification result) in the Beijing–Tianjin–Tangshan metropolitan region (BTTMR), China, were extracted from multisource remote sensing data from 1990 to 2015. Then, we evaluated urban expansion based on centre migration, standard deviation ellipse, and spatial autocorrelation metrics. Furthermore, the differences between the soft and hard classification results were analysed at the landscape scale. The results showed that (1) the impervious surface area increased considerably over the past 25 years. Notably, the areas of urban built-up land and industrial production land increased rapidly, while those of ecological land and agricultural production land seriously decreased. (2) The distribution of impervious surfaces was closely related to the regional economic development plan of ‘One Axis, Two Wing, and Multi-Node’ in the BTTMR. (3) The contributions of different land use types to impervious surface growth ranked from high to low as follows: urban built-up land, rural residential land, industrial production land, agricultural production land, and ecological land. (4) The landscape metrics varied considerably based on the hard and soft classification results and were sensitive to different factors.     

Mapping impervious surface expansion using medium-resolution satellite image time series: a case study in the Yangtze River Delta,China

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China–Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.