78 Comprehensive review on methods to extract, estimate and map impervious surfaces. 78 Discussions on the mapping requirements of urban impervious surfaces. 78 Problems and prospects in remote sensing of impervious surfaces in the urban areas. 78 Impact of new sensing systems on the models and algorithms in urban remote sensing. 78 First to discuss about research traditions in urban remote sensing.

不透水表面是城市中一种人工地表特征,隔离地表水下渗到土壤,割断了城市地表与地下水文联系,主要由城市中的道路、停车场、广场及屋顶等建筑物组成。不透水表面影响城市的地表径流、水文循环、水体质量、局部气候、生物多样性等生态环境要素,是监测城市生态系统及环境变化的重要指标,也是许多生态环境模型的主要输入参数。本文归纳了不透水表面提取技术及其对城市自然生态环境影响的研究进展。从遥感提取技术方面看,亚像元分解等新的运算方法提取中尺度分辨率遥感影像的不透水表面,将是未来遥感技术应用到城市自然资源环境研究的趋势。在数据源方面,中分辨率(10~100m)与高分辨率(0.3~5m)遥感数据为不透水表面指数在大范围、多时段的获取提供了可靠基础。在不透水表面指数应用方面,城市地表覆被监测与模拟可以为城市未来发展及规划管理提供基础。鉴于不透水表面决定了城市地区的地表水文循环、非点源污染、能量分布、植被变化及生物多样性等生态环境要素,因此搭起深入理解城市景观格局与生态过程相互关系的桥梁,是研究城市化的生态环境效应的最佳切入点。

Islands are hotspot areas with intensive interactions between land and ocean, and they are also the most vulnerable places to human activities and environmental change. As the frontier zone of oceanic economic development, coastal regions of China have undergone enhanced changes in land-cover change during recent decades. This study was conducted to investigate how land cover in Zhoushan Island and its surrounding islands, which are typical islands of China, has changed since the economic reform by using multisource remotely sensed imageries. The earliest land cover in 1970, 1976, and 1980 was interpreted and digitalized from CORONA and KH-9 photographs, respectively. For the period of 1986-2000, TM (Thematic Mapper) and ETM (Enhanced Thematic Mapper) imageries were classified to build land-cover maps with the supervised classification method. The most recent land-cover data in 2006 and 2011 were generated by inventory land-use vector map and SPOT5 imageries. The reconstructed land-cover time series indicate that Zhoushan Islands have involved substantial land-cover change since 1970. The arable land has changed into builtup types, mainly, and rate of change reached its peak in 2000, while the spatial distribution of transition was not uniform. Nevertheless, water bodies and woodlands have been well preserved during the past 40 years. During the urbanization process, the tidal zone of these islands shrank sharply, and some of them turned to built-up land-cover directly.

Vegetation cover, surface moisture availability (wetness) and radiant surface temperature constitute microclimatic variables derivable from multi-spectral satellite imagery. In addition, fraction impervious surface cover and urban-induced surface runoff (RO) are obtainable from such imagery when it is combined with a conventional image classification. Using AVHRR and Landsat TM data, we illustrate how these parameters respond to urbanization with a case study of Chester County, PA a region that has undergone rapid urban development over the past decade. Specific factors affecting the change in the surface microclimatic variables are discussed. Based on a statistical analysis of the Chester County data, future values of these microclimatic parameters can be predicted, given the characteristics of the initial land surface and an estimate of the change in vegetation and urban coverage.

Urban development has expanded rapidly in the Tampa Bay area of west-central Florida over the past century. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. This research utilizes an innovative approach for mapping urban extent and its changes through determining impervious surfaces from Landsat satellite remote sensing data. By 2002, areas with subpixel impervious surface greater than 10% accounted for approximately 1800 km 2, or 27 percent of the total watershed area. The impervious surface area increases approximately three-fold from 1991 to 2002. The resulting imperviousness data are used with a defined suite of geospatial data sets to simulate historical urban development and predict future urban and suburban extent, density, and growth patterns using SLEUTH model. Also examined is the increasingly important influence that urbanization and its associated imperviousness extent have on the individual drainage basins of the Tampa Bay watershed.

The spatial and spectral variability of urban environments present fundamental challenges to deriving accurate remote sensing products for urban areas. Multiple endmember spectral mixture analysis (MESMA) is a technique that potentially addresses both challenges. MESMA models spectra as the linear sum of spectrally pure endmembers that vary on a per-pixel basis. Spatial variability is addressed by mapping sub-pixel components of land cover as a combination of endmembers. Spectral variability is addressed by allowing the number and type of endmembers to vary from pixel to pixel. This paper presents an application of MESMA to map the physical components of urban land cover for the city of Manaus, Brazil, using Landsat Enhanced Thematic Mapper (ETM+) imagery. We present a methodology to build a regionally specific spectral library of urban materials based on generalized categories of urban land-cover components: vegetation, impervious surfaces, soil, and water. Using this library, we applied MESMA to generate a total of 1137 two-, three-, and four-endmember models for each pixel; the model with the lowest root-mean-squared (RMS) error and lowest complexity was selected on a per-pixel basis. Almost 97% of the pixels within the image were modeled within the 2.5% RMS error constraint. The modeled fractions were used to generate continuous maps of the per-pixel abundance of each generalized land-cover component. We provide an example to demonstrate that land-cover components have the potential to characterize trajectories of physical landscape change as urban neighborhoods develop through time. Accuracy of land-cover fractions was assessed using high-resolution, geocoded images mosaicked from digital aerial videography. Modeled vegetation and impervious fractions corresponded well with the reference fractions. Modeled soil fractions did not correspond as closely with the reference fractions, in part due to limitations of the reference data. This work demonstrates the potential of moderate-resolution, multispectral imagery to map and monitor the evolution of the physical urban environment.

位于福州盆地中心的福州市在城市化进程的推动下,城市空间快速扩展。利用多时相遥感影像和IBI建筑用地指数获得的建筑用地信息表明,福州市建成区在1976～2006年的30 a间面积增加了105 km2,增幅达到3.2倍。由于金山、快安等新城区的形成和马尾区的扩展,整个福州城区从西到东几乎连成一片,城市扩展经历了先慢后快,先北、后东、西的扩展历程。研究发现,福州城市的空间扩展并不属于工业主导型,而是第三产业推动型。城市空间的快速扩展已给福州带来了一定的环境资源问题,其中最突出的就是城市热岛效应与城市建筑用地总量控制问题。

Information on impervious surface distribution and dynamics is useful for understanding urbanization and its impacts on hydrological cycle, water management, surface energy balances, urban heat island, and biodiversity. Numerous methods have been developed and successfully applied to estimate impervious surfaces. Previous methods of impervious surface estimation mainly focused on the spectral differences between impervious surfaces and other land covers. Moreover, the accuracy of estimation from single or multi-temporal images was often limited by the mixed pixel problem in coarse- or medium-resolution imagery or by the intra-class spectral variability problem in high resolution imagery. Time series satellite imagery provides potential to resolve the above problems as well as the spectral confusion with similar surface characteristics due to phenological change, inter-annual climatic variability, and long-term changes of vegetation. Since Landsat time series has a long record with an effective spatial resolution, this study aimed at estimating and mapping impervious surfaces by analyzing temporal spectral differences between impervious and pervious surfaces that were extracted from dense time series Landsat imagery. Specifically, this study developed an efficient method to extract annual impervious surfaces from time series Landsat data and applied it to the Pearl River Delta, southern China, from 1988 to 2013. The annual classification accuracy yielded from 71% to 91% for all classes, while the mapping accuracy of impervious surfaces ranged from 80.5% to 94.5%. Furthermore, it is found that the use of more than 50% of Scan Line Corrector (SLC)-off images after 2003 did not substantially reduced annual classification accuracy, which ranged from 78% to 91%. It is also worthy to note that more than 80% of classification accuracies were achieved in both 2002 and 2010 despite of more than 40% of cloud cover detected in these two years. These results suggested that the proposed method was effective and efficient in mapping impervious surfaces and detecting impervious surface changes by using temporal spectral differences from dense time series Landsat imagery. The value of full sampling was revealed for enhancing temporal resolution and identifying temporal differences between impervious and pervious surfaces in time series analysis.

Impervious surface quantification is important for many planning and management applications because of the impacts that impervious surfaces have on a range of environmental resources such as groundwater. This research proposes an integrated method to quantify impervious surfaces at multiple spatial scales via a synthesis of several machine learning approaches. In this study, we 1) proposed a hierarchical classification method to detect impervious surfaces through a fusion of optimized artificial immune networks (OPTINC) and decision trees at high spatial resolution, 2) evaluated the method using multi-sensor data (i.e., high spatial resolution WorldView-2 and LiDAR data) to map impervious surfaces, 3) tested the applicability of the binary impervious surface maps to quantify sub-pixel imperviousness from Landsat TM data of a larger region using regression trees at moderate spatial resolution, and 4) examined the model sensitivity of regression trees to training sample size for impervious surface quantification. OPTINC and decision trees successfully identified impervious surfaces at high resolution (overall accuracy02>0290%). The regression tree predicted imperviousness from the TM data with a moderate success ( R 2 02=020.64 and MAE 02=0214.2%). Although the regression tree appeared robust when training sample size was sufficiently large, it was not stable with small sample size (e.g., <02100).

Buildings play an essential role in urban intra-construction, planning, and climate. The precise knowledge of building footprints not only serves as a primary source for interpreting complex urban characteristics, but also provides regional planners with more realistic and multidimensional scenarios for urban management. The recently developed airborne light detection and ranging (lidar) technology provides a very promising alternative for building-footprint measurement. In this study, lidar intensity data, a normalized digital surface model (nDSM) of the first and last returns, and the normalized difference tree index (NDTI) derived from the two returns are used to extract building footprints using rule-based object-oriented classification. The study area is chosen in London, Ontario, based on the various types of buildings surrounded by trees. An integrated segmentation approach and a hierarchical rule-based classification strategy are proposed during the process. The results indicate that the proposed object-based classification is a very effective semi-automatic method for building-footprint extraction, with buildings and trees successfully separated. An overall accuracy of 94.0% and a commission error of 6.3% with a kappa value of 0.84 are achieved. Lidar-derived NDTI and intensity data are of great importance in object-based building extraction, and the kappa value of the proposed method is double that of the object-based method without NDTI or intensity.

61We review the airborne LiDAR technology to aid in urban land cover classification.61The use of LiDAR height, intensity, waveform, and multi-sensor data is summarized.61The LiDAR data classification and radiometric calibration techniques are identified.61Five other relevant urban environmental applications are presented.61We finally point out five forthcoming research areas that require further efforts.

Impervious surface area (ISA) is an important parameter for many environmental or socioeconomic relevant studies. The unique characteristics of remote sensing data made it the primary data source for ISA mapping at various scales. This paper summarizes general ISA mapping procedure and major techniques and discusses impacts of scale issues on selection of remote sensing data and corresponding algorithms. Previous studies have indicated that ISA mapping remains a challenge, especially in urban rural frontiers and in covering a large area. Effectively employing rich spatial information in high spatial resolution imagery through texture and object-based methods is valuable. Data fusion of multi-resolution images and spectral mixture analysis are common approaches to reduce the mixed pixel problem in medium spatial resolution images such as Landsat. Coarse spatial resolution images such as MODIS and DMSP-OLS are valuable for national and global ISA mapping but more research is needed to effectively integrate multisource/scale data for improving mapping performance. Development of an optimal procedure corresponding to specific study areas and purposes is required to generate accurate ISA mapping results.

Chongming Island is the world's largest alluvial island. Its coastal wetland and tidal flats provide many important ecological services including buffers against tidal surges and staging areas for migratory birds. Due to its extraordinary resources, scenic qualities, and its proximity to the city of Shanghai 45 km away, the island is also an attractive tourist destination, and it supports important agricultural and fisheries economies. Yet, large-scale land reclamation projects that are severely affecting these ecosystems have been implemented. In this paper, we report an investigation of changes in land use and ecosystem services on Dongtan (East Beach of Chongming Island) between 1990 and 2000. We used three LANDSAT TM and/or ETM data sets to estimate changes in the size of five land-cover/land-use categories, and we also used previously published value coefficients to estimate changes in the value of ecosystem services delivered by each land category. Finally, we ranked the contribution of various ecosystem functions to the overall value of the ecosystem services. We determined that the total value of ecosystem services in Dongtan declined by 62% from $ 316.77 to 120.40 million per year between 1990 and 2000 (totaling $855.26鈥981.85 million over 10-years). This massive decrease is largely attributable to the 71% loss of wetlands/tidal flats. Our sensitivity analysis suggested that these estimates were relatively robust. We also found that the contribution of water regulation, water supply, waste treatment, and raw materials increased, while the contribution of nutrient cycling, food production, disturbance regulation, recreation, habitat/refugia, and biological control decreased during the 10-year time period. We conclude that future land-use policy formulation should give precedence to the conservation of these ecosystems over uncontrolled reclamation, and that further land reclamation should be based on rigorous environmental impact analyses.

sing Landsat TM data of 1988, 1998 and 2001, the dynamic process of the spatial-temporal characteristics of land use changes during 13 years from 1988 to 2001 in the special economic zone of Xiamen, China was analyzed to improve understanding and to find the driving forces of land use change so that sustainable land utilization could be practiced. During the 13 years cropland decreased remarkably by nearly 11304.95 ha. The areas of rural-urban construction and water body increased by 10 152.24 ha and 848.94 ha, respectively. From 1988 to 2001, 52.5% of the lost cropland was converted into rural-urban industrial land. Rapid urbanization contributed to a great change in the rate of cropland land use during these years. Land-reclamation also contributed to a decrease in water body area as well as marine ecological and environmental destruction. In the study area 1) urbanization and industrialization, 2) infrastructure and agricultural intensification, 3) increased affluence of the farming community, and 4) policy factors have driven the land use changes. Possible sustainable land use measures included construction of a land management system, land planning, development of potential land resources, new technology applications, and marine ecological and environmental protection.

Islands are an important part of the marine ecosystem. Increasing impervious surfaces in the Zhoushan Islands due to new development and increased population have an ecological impact on the runoff and water quality. Based on time-series classification and the complement of vegetation fraction in urban regions, Landsat thematic mapper and other high-resolution satellite images were applied to monitor the dynamics of impervious surface area (ISA) in the Zhoushan Islands from 1986 to 2011. Landsat-derived ISA results were validated by the high-resolution Worldview-2 and aerial photographs. The validation shows that mean relative errors of these ISA maps are <15 %. The results reveal that the ISA in the Zhoushan Islands increased from 19.2 kmin 1986 to 86.5 kmin 2011, and the period from 2006 to 2011 had the fastest expansion rate of 5.59 kmper year. The major land conversions to high densities of ISA were from the tidal zone and arable lands. The expansions of ISA were unevenly distributed and most of them were located along the periphery of these islands. Time-series maps revealed that ISA expansions happened continuously over the last 25 years. Our analysis indicated that the policy and the topography were the dominant factors controlling the spatial patterns of ISA and its expansions in the Zhoushan Islands. With continuous urbanization processes, the rapid ISA expansions may not be stopped in the near feature.

Impervious surface area (ISA) was derived for a period from 1979 to 1997 from Landsat MSS and TM data for the Line Creek watershed that lies to the south of the city of Atlanta, GA. The change in ISA is presented as an ecological indicator to examine the cumulative water resource impacts on mussel population in three sub-watersheds of Line Creek—namely, Line, Flat, and Whitewater creeks. The satellite analysis shows that ISA expansion occurred substantially from 1987 to 1997 and is predominantly in industrial, commercial, and shopping center (ICS) complexes but also in smaller lot-size residential development. Evidence of mussel habitat degradation is indicated and loss of species (in the region of 50 to 70%) is present in areas where ISA expansion is observed—specifically in ICS complex development in and around Peachtree City that drains directly into the Line and Flat creeks. This is in marked contrast to Whitewater Creek where overall development of ISA is less and no major loss of mussel species is observed.

We use a simple radiative transfer model with vegetation, soil, and atmospheric components to illustrate how the normalized difference vegetation index (NDVI), leaf area index (LAI), and fractional vegetation cover are dependent. In particular, we suggest that LAI and fractional vegetation cover may not be independent quantitities, at least when the former is defined without regard to the presence of bare patches between plants, and that the customary variation of LAI with NDVI can be explained as reuslting from a variation in fractional vegetation cover. The following points are made: i) Fractional vegetation cover and LAI are not entirely independnet quatities, depending on how LAI is defined. Care must be taken in using LAI and fractional vegetation cover independently in a model because the former may partially take account of the later; ii) A scaled NDVI taken between the limits of minimum (bare soil) and maximum fractional vegetation cover is insenstive to atmospheric correction for both clear and hazy conditions, at least for viewing angles less than about 20 degrees form nadir; iii) A simple relation between scaled NDVI and fractional vegetation cover, previously described in the literature, is further confirmed by the simulations; iv) The sensitive dependence of LAI and NDVI when the former is below a value of about 2-4 may be viewed as being due to the variation in the bare soil component.