基于遥感的湿地景观格局季相分析

以中国东北地区三江平原北部为研究区域,利用2012年多季相遥感影像作为数据源,结合野外调查数据,应用面向对象的分类方法,根据影像的物候、时相等特征,提取不同月份的湿地信息,进行景观格局季相分析。结果表明:(1)研究区湿地面积、类型格局在同一年不同季节不同月份会有不同幅度的变化,总体呈现缓增骤减的态势。湿地主要分布在低洼地区,主要湿地类型为草本沼泽,其次为河流,其他湿地占总面积比例较小。(2)研究区各阶段湿地都有转化,主要发生在湿地和非湿地之间,多数表现在草本沼泽和草地之间的转化。(3)湿地分布和湿地转化面积主要集中在低海拔区域和低坡度区域,其中海拔100 m和坡度5°以下范围内的湿地分布面积和湿地转化面积占湿地总面积及湿地转化面积的绝大部分。(4)年内季节性湿地转化与降水、温度和湿地植被物候关系密切。     

基于BP神经网络与ETM+遥感数据的盐城滨海自然湿地覆被分类

高效而精确的湿地遥感分类是大范围湿地资源动态监测与管理的必要保障。本研究使用ETM 遥感数据,借助Matlab神经网络工具箱,构建了基于BP神经网络的滨海湿地覆被分类模型,并将其应用于江苏盐城沿海湿地珍禽国家级自然保护区的核心区的自然湿地覆被分类研究中。本研究选择3、4、7、8波段作为输入层变量,单隐藏层设为10个节点,输出层变量对应待划分的8种覆被类型,构建三层式BP神经网络滨海湿地覆被分类模型。结果显示,BP分类总精度为85.91%,Kappa系数为0.8328,与最小距离法和极大似然法的分类总精度相比,分别提高了7.99%和6.08%,Kappa系数也相比提高。研究结果表明,BP神经网络分类法是一种较为有效的湿地遥感影像分类技术,能够提高分类精度。     

Wetland classification and inventory: A summary

Regional, national and local wetland classifications have been developed and successfully applied. These have invariably been orientated towards conservation and management goals, and the information used to assess wetland loss or to assign management priorities. Existing national and regional classification systems have not only been useful, but they provide an essential base for developing an international system. At the international level, differences among existing systems in the definition of a wetland and how wetland types are defined assume great importance and need to be resolved. Classification is an essential prerequisite for wetland inventory. A number of international inventories have been undertaken, although these have not generally utilized the available high technology and data storage systems available through remote sensing and geographic information systems. More extensive international inventories will require standardization of techniques for data collection, storage and dissemination. A minimum data set needs to be defined with standards for data accuracy. An international committee under the auspices of an international agency (e.g. IWRB, Ramsar Bureau, IUCN) needs to be established to develop an international classification system and guidelines for carrying out a complete inventory of the world's wetlands.     

环境灾害遥感小卫星在辽河三角洲湿地景观制图中的应用

及时、准确地获得湿地的空间分布,对湿地的动态监测、保护与可持续利用具有重要的意义.环境灾害遥感小卫星星座A、B星(HJ-1A/1B星)是我国自主发射的陆地资源监测卫星,可为湿地类型的提取提供新的遥感影像数据源.本文通过对比我国环境灾害遥感小卫星CCD相机影像（HJ CCD）数据与Landsat TM5影像数据获取的湿地景观类型图的分类精度和各景观类型面积,验证和探究了HJ CCD数据在湿地景观动态变化监测中的适用性和应用潜力.结果表明：HJ CCD数据在地物识别分类方面可完全替代Landsat TM5数据;在实时动态监测方面,HJ CCD数据获取周期仅为2 d,优于Landsat TM5数据（16 d）.     

Remote sensing of upland vegetation: the potential of high spatial resolution satellite sensors

Aim Traditional methodologies of mapping vegetation, as carried out by ecologists, consist primarily of field surveying or mapping from aerial photography. Previous applications of satellite imagery for this task (e.g. Landsat TM and SPOT HRV) have been unsuccessful, as such imagery proved to have insufficient spatial resolution for mapping vegetation. This paper reports on a study to assess the capabilities of the recently launched remote sensing satellite sensor Ikonos, with improved capabilities, for mapping and monitoring upland vegetation using traditional image classification methods. Location The location is Northumberland National Park, UK. Methods Traditional remote sensing classification methodologies were applied to the Ikonos data and the outputs compared to ground data sets. This enabled an assessment of the value of the improved spatial resolution of satellite imagery for mapping upland vegetation. Post‐classification methods were applied to remove noise and misclassified pixels and to create maps that were more in keeping with the information requirements of the NNPA for current management processes. Results The approach adopted herein for quick and inexpensive land cover mapping was found to be capable of higher accuracy than achieved with previous approaches, highlighting the benefits of remote sensing for providing land cover maps. Main conclusions Ikonos imagery proved to be a useful tool for mapping upland vegetation across large areas and at fine spatial resolution, providing accuracies comparable to traditional mapping methods of ground surveys and aerial photography.     

高分辨率影像支持的群落尺度沼泽湿地分类制图

湿地作为众多野生动物和植物的栖息地,具有稳定环境及物种基因保护等重要功能.但是,湿地复杂的水陆交界生境特征及难以进入等客观条件限制给湿地研究造成了很大的困难.因此,遥感技术作为地表生态环境过程参量获取的重要工具,在当今湿地科学领域发挥着重要作用,特别是,当前高空间分辨率影像的性能与应用水平不断得到提高.以自然状态下的黑龙江三江平原洪河国家级自然保护区为研究对象,应用飞艇搭载的空间高分辨率摄像系统获取影像地面分辨率为0.13m的影像数据,主要结合面向对象分类方法,开展了基于湿地植物群落尺度的分类制图研究.结果表明:①因飞艇影像对植物形态、纹理等细致特征的刻画非常充分,沼泽植被型、草甸植被型和各种乔木、灌木植被型,都可以在合适的遥感分类方法下提取出来,总体分类精度能达到91.77％;②通过采用针对高分辨率影像面向对象的分类方法与传统的最大似然比遥感分类方法对比,前者达到很高的精度,而后者效果不理想,说明遥感分类方法的选择对于群落尺度湿地植物分类制图结果非常重要;③遥感分类制图的结果显示出研究区湿地植物群落分布格局受到水分环境梯度和微地貌的共同控制,呈现交替环带状分布规律.     

Land use and land cover change analysis in predominantly man-made coastal wetlands: towards a methodological framework

In areas with a long history of human occupation, coastal wetlands have undergone extensive modification to accommodate extractive activities as salt-extraction and aquaculture. These man-made wetlands maintain some of the ecological functions of natural wetlands in spite of their artificial character: their suitability as complimentary waterbird habitat is well documented. In cases of wetlands composed of mixed natural and man-made areas, similarities in substrate-vegetation-water compositions may pose challenges in the applicability of remote sensing and GIS techniques for the study of landscape changes, requiring tailor-made, case-specific methods. We explored this supposition by testing these techniques for the study of the Bahia de Cadiz Nature Park (Spain). Using Landsat imagery spanning the 1985–2011 period, natural and man-made marsh areas were classified separately and results merged to produce land cover classification maps. Different change dynamics were observed for the natural and man-made areas, the latter exhibiting prominent changes, including widespread vegetative succession. Further, through the overlay of ancillary land use data for 2011, an integrated land use and cover map was produced for this year. Different scenarios arising from the abandonment of extractive activity and structural negligence were highlighted. Furthermore, a methodological framework for the classification of predominantly man-made wetlands was designed. The method is cost-effective and open for integration of additional datasets, and is considered a beneficial input to conservation and land use management. Its applicability for monitoring of landscape change not only pertains to the study area, but also extends to other coastal wetland areas of a similar nature.     

Hyperspectral Analysis of Columbia Spotted Frog Habitat

Abstract: Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96% (44 wetlands) correctly classified with the 2002 data and 89% (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74% (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72% (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats.     

Quantifying Tropical Dry Forest Type and Succession: Substantial Improvement with LiDAR

Improved technologies are needed to advance our knowledge of the biophysical and human factors influencing tropical dry forests, one of the world's most threatened ecosystems. We evaluated the use of light detection and ranging (LiDAR) data to address two major needs in remote sensing of tropical dry forests, i.e., classification of forest types and delineation of forest successional status. We evaluated LiDAR‐derived measures of three‐dimensional canopy structure and subcanopy topography using classification‐tree techniques to separate different dry forest types and successional stages in the Guánica Biosphere Reserve in Puerto Rico. We compared the LiDAR‐based results with classifications made from commonly used remote sensing data, including Landsat satellite imagery and radar‐based topographic data. The accuracy of the LiDAR‐based forest type classification (including native‐ and exotic‐dominated forest classes) was substantially higher than those from previously available data (kappa = 0.90 and 0.63, respectively). The best result was obtained when combining LiDAR‐derived metrics of canopy structure and topography, and adding Landsat spectral data did not improve the classification. For the second objective, we observed that LiDAR‐derived variables of vegetation structure were better predictors of forest successional status (i.e., mid‐secondary, late‐secondary, and primary forests) than was spectral information from Landsat. Importantly, the key LiDAR predictors identified within each classification‐tree model agreed with previous ecological knowledge of these forests. Our study highlights the value of LiDAR remote sensing for assessing tropical dry forests, reinforcing the potential for this novel technology to advance research and management of tropical forests in general.     

The US Fish and Wildlife Service's National Wetlands Inventory Project

In 1974, the US Fish and Wildlife Service directed its Office of Biological Services to design and conduct an inventory of the Nation's wetlands. The mandate was to develop and disseminate a technically sound, comprehensive data base concerning the characteristics and extent of the Nation's wetlands. The purpose of this data base is to foster wise use of the Nation's wetlands and to expedite decisions that may affect this important resource. To accomplish this, state-of-the-art principles and methodologies pertaining to all aspects of wetland inventory were assimilated and developed by the newly formed project. By 1979, when the National Wetlands Inventory (NWI) Project became operational, it was clear that two very different kinds of information were needed. First, detailed wetland maps were needed for site-specific decisions. Second, national statistics developed through statistical sampling on the current status and trends of wetlands were needed in order to provide information to support the development or alteration of Federal programs and policies. The NWI has produced wetland maps (scale=1:24 000) for 74% of the conterminous United States. It has also produced wetland maps (scale=1:63 360) for 24% of Alaska. Nearly 9000 of these wetland maps, representing 16.7% of the continental United States, have been computerized (digitized). In addition to maps, the NWI has produced other valuable wetland products. These include a statistically-based report on the status and trends of wetlands that details gains and losses in United States wetlands that have occurred from the mid-1970's to the mid-1980's. Other wetland products include a list of wetland (hydric) soils, a national list of wetland plant species, wetland reports for certain individual States such as New Jersey and Florida, and a wetland values data base.     

基于中分辨率TM数据的湿地水生植被提取

利用湿地水生植被生长旺盛、光谱反射较强、光谱信息比较丰富的8月份中分辨率Landsat TM和ETM+多光谱遥感影像,采用面向对象的分类方法,进行野鸭湖湿地水生植被的提取。研究表明:在提取过程中,通过对原始影像进行主成分变换和穗帽变换,将主要信息与噪声分离,不仅减小了数据冗余和波段间的相关性,而且增大了影像上湿地水生植被与其他地物类型光谱和空间信息的差异性,并结合野外水生植被光谱特征分析,选择归一化植被指数NDVI与归一化水体指数NDWI辅助分类,构建特征波段或波段组合,然后,确定适当的隶属度函数和阈值范围,构建分类决策树,完成湿地水生植被的自动分类,提高了影像分割与面向对象分类的精度,取得了较为理想的湿地水生植被提取结果。2002年和2008年两景影像的总体分类精度分别达到86.5%和85.44%,表明中分辨率TM影像可以满足湿地水生植被提取的需要,又因为其具有较高的波谱分辨率、极为丰富的信息量、相对较低的价格、长时间序列,可以作为近20a湿地水生植被提取和动态变化监测的主要数据源。     

Monitoring coastal wetland communities in north-eastern NSW using ASTER and Landsat satellite data

The coastal wetland communities of north-eastern New South Wales (NSW) Australia exist in a subtropical climate with high biodiversity and are affected by anthropogenic and natural stressors such as urbanization and climate change. The aim of the research is to map and monitor the coastal wetland communities in north eastern NSW using satellite data. Advanced Spaceborne Thermal Emission and Reflectance Radiometer, Landsat ETM+ and Landsat TM satellite imagery of November 2003, June 2001 and September 1989 respectively were used to identify and monitor the wetland communities. Supervised classification was performed using the maximum likelihood standard algorithm. Normalized Difference Vegetation Index was produced and the health of the wetland vegetation was evaluated. The wetland maps present significant changes in the coastal wetland communities in the months of September 1989, June 2001 and November 2003. This information could be used by coastal wetland managers in order to enhance the management of these ecosystems.     

Applying remote sensing techniques to monitor shifting wetland vegetation: A case study of Danshui River estuary mangrove communities,Taiwan

The purpose of this study is to apply different remote sensing techniques to monitor shifting mangrove vegetation in the Danshui River estuary in Taipei, Taiwan, in order to evaluate a long-term wetland conservation strategy compromising between comprehensive wetland ecosystem management and urban development. In the Danshui estuary, mangrove dominated by Kandelia candel is the major vegetation, and a large area of marsh with freshwater grasses has been protected in three reserves along the river shore. This study applied satellite imagery from different remote sensors of various resolutions for spectral analysis in order to compare shifting wetland vegetation communities at different times. A two-stage analytical process was used for extracting vegetation area and types. In the first-stage, a normalized difference vegetation index (NDVI) was adopted to analyze SPOT, Landsat, and QuickBird imagery to obtain the spatial distribution of vegetation covers. In the second stage, a maximum likelihood classification (MLC) program was used to classify mangrove and non-mangrove areas. The results indicated that the spatial distribution of mangroves expanded 15.18 and 40 ha in two monitoring sites in 10 years, demonstrating the success of establishing reserves for protecting mangrove habitats. The analytical results also indicated that satellite imagery can easily discern the difference in characteristics between imagery of mangrove and other vegetation types, and that the logistical disadvantages of monitoring long-term vegetation community changes as well as evaluating an inaccessible area may be overcome by applying remote sensing techniques.     

Evaluation of a wetland classification system devised for management in a region with a high cover of peatlands: an example from the Cook Inlet Basin,Alaska

Several wetland classification schemes are now commonly used to describe wetlands in the contiguous United States to meet local, regional, and national regulatory requirements. However, these established systems have proven to be insufficient to meet the needs of land managers in Alaska. The wetlands of this northern region are predominantly peatlands, which are not adequately treated by the nationally-used systems, which have few, if any, peatland classes. A new system was therefore devised to classify wetlands in the rapidly urbanizing Cook Inlet Basin of southcentral Alaska, USA. The Cook Inlet Classification (CIC) is based on seven geomorphic and six hydrologic components that incorporate the environmental gradients responsible for the primary sources of variation in peatland ecosystems. The geomorphic and hydrologic components have the added advantage of being detectable on remote sensing imagery, which facilitates regional mapping across large tracts of inaccessible terrain. Three different quantitative measures were used to evaluate the robustness and performance of the CIC classes relative to that of other commonly used systems in the contiguous United States. The high within-group similarity of the classes identified by the CIC was clearly superior to that of the other systems, demonstrating the need for improved wetland classification systems specifically devised for regions with a high cover of peatlands.     

三江平原流域湿地景观破碎化过程研究

以流域为研究单元,利用历史图件和遥感数据资料及GIS技术,系统分析了该区典型流域50年来湿地景观的破碎化过程.结果表明,该区湿地景观破碎化在斑块个体和空间结构两方面变化极大.景观斑块个体变化主要表现为最大斑块、平均斑块面积不断缩小,斑块密度不断增大,斑块形状破碎化指数不断增大,景观内部生境面积破碎化指数不断上升;空间结构变化主要表现为湿地景观由初始基质景观逐渐变为河岸带景观;同时,随着农田面积逐渐扩大,隔离湿地斑体数量不断上升,隔离度不断增大;景观空间分布模式由“大陆-岛屿模式”向“卫星型模式”转变,最后变化为“完全隔离型模式”.导致该区湿地景观破碎化的主导因素是大规模的农业开发,反映了人类活动对湿地景观的巨大影响.     

Differentiating geological fertility derived vegetation zones in Kruger National Park,South Africa,using Landsat and MODIS imagery

Spatial technologies present possibilities for producing frequently updated and accurate habitat maps, which are important in biodiversity conservation. Assemblages of vegetation are equivalent to habitats. This study examined the use of satellite imagery in vegetation differentiation in South Africa's Kruger National Park (KNP). A vegetation classification scheme based on dominant tree species but also related to the park's geology was tested, the geology generally consisting of high and low fertility lithology. Currently available multispectral satellite imagery is broadly either of high spatial but low temporal resolution or low spatial but high temporal resolution. Landsat TM/ETM+ and MODIS images were used to represent these broad categories. Rain season dates were selected as the period when discrimination between key habitats in KNP is most likely to be successful. Principal Component Analysis enhanced vegetated areas on the Landsat images, while NDVI vegetation enhancement was employed on the MODIS image. The images were classified into six field sampling derived classes depicting a vegetation density and phenology gradient, with high (about 89%) indicative classification accuracy. The results indicate that, using image processing procedures that enhance vegetation density, image classification can be used to map the park's vegetation at the high versus low geological fertility zone level, to accuracies above 80% on high spatial resolution imagery and slightly lower accuracy on lower spatial resolution imagery. Rainfall just prior to the image date influences herbaceous vegetation and, therefore, success at image scene vegetation mapping, while cloud cover limits image availability. Small scale habitat differentiation using multispectral satellite imagery for large protected savanna areas appears feasible, indicating the potential for use of remote sensing in savanna habitat monitoring. However, factors affecting successful habitat mapping need to be considered. Therefore, adoption of remote sensing in vegetation mapping and monitoring for large protected savanna areas merits consideration by conservation agencies.     

The missing wetlands: using local ecological knowledge to find cryptic ecosystems

Small, temporally dynamic, biologically diverse isolated wetlands are among the most imperiled ecosystems, yet their conservation is hindered by lack of protective legislation and mapping. As part of an effort to better understand isolated wetland ecology in an area undergoing dramatic land use change, we mapped isolated wetlands in South Carolina’s Piedmont and Blue Ridge regions using remote sensing and local ecological knowledge (LEK). Remote detection of isolated wetlands was limited by digital resource resolution, topography, and wetland size. LEK was the most useful tool for locating small isolated wetlands. We sampled 10% of the study area using LEK and discovered 44 wetlands with “isolated” characteristics, none of which had been identified by remote sensing. Only 8 of 44 wetlands found through LEK could be identified using remote sensing after their discovery. LEK fills a gap in cryptic ecosystem detection when adequate remotely sensed data are not available. Though effective, using LEK is neither as rapid nor as repeatable as remote sensing. We suggest a two-pronged approach for finding cryptic ecosystems: remote sensing coupled with LEK where data resolution is inadequate. For remote detection of isolated wetlands, we suggest a minimum resolution of 0.33 m for Color Infrared, leaf-off, high-water photography. Despite great advances in remote sensing, data are not uniformly available worldwide and LEK may serve as an effective tool for locating cryptic resources for biodiversity conservation. Mapping cryptic resources will allow for more accurate resource and biodiversity conservation planning under current and future climate scenarios.     

基于遥感技术的全国生态系统分类体系

随着遥感技术的发展,以遥感数据作为生态系统监测与评价的基础已成为宏观生态学研究的重要手段。遥感数据要求每一数据集都要有相应的地物分类体系与之匹配,这也造成不同遥感数据及分类体系之间相互独立。虽然体系间多有联系和相似之处,但不同数据集的分类体系难以直接使用或替换,制约了多元数据在生态系统评价中的使用效果。为尝试解决这一问题,提高多源遥感数据的使用效率,提出了一套基于中分辨率遥感数据的生态系统分类体系。这套体系共有9个一级类、21个二级类、46个三级类,该体系主要依据类别内生态系统特征的相似性,并考虑了气候、地形等因素。最后以海南岛、内蒙古和甘肃3个省为例,探讨了以遥感数据为基础的区域生态系统构成分析方法与应用效果。研究表明,该分类体系有较好的生态学依据,可以支持更加深入的生态系统评估。但分类体系中还存在遥感数据与生态因子数据尺度不匹配、不能满足小尺度研究中对三级类进一步细分的要求以及当前数据质量和模拟技术不足以完全支持植被覆盖率反演精度要求等问题。     

US Fish and Wildlife Service 1979 wetland classification: A review

In 1979 the US Fish and Wildlife Service published and adopted a classification of wetlands and deepwater habitats of the United States. The system was designed for use in a national inventory of wetlands. It was intended to be ecologically based, to furnish the mapping units needed for the inventory, and to provide national consistency in terminology and definition. We review the performance of the classification after 13 years of use. The definition of wetland is based on national lists of hydric soils and plants that occur in wetlands. Our experience suggests that wetland classifications must facilitate mapping and inventory because these data gathering functions are essential to management and preservation of the wetland resource, but the definitions and taxa must have ecological basis. The most serious problem faced in construction of the classification was lack of data for many of the diverse wetland types. Review of the performance of the classification suggests that, for the most part, it was successful in accomplishing its objectives, but that problem areas should be corrected and modification could strengthen its utility. The classification, at least in concept, could be applied outside the United States. Experience gained in use of the classification can furnish guidance as to pitfalls to be avoided in the wetland classification process.The US Government's right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

Long-term monitoring of wetlands along the Western-Greek Bird Migration Route using Landsat and ASTER satellite images: Amvrakikos Gulf (Greece)

The west coast of Greece is an important migration route for migratory waterbirds. The wetlands along this coast are important stopover sites during bird migration between wintering and breeding sites. The use of remote sensing methods for mapping bird migration habitats and for temporal monitoring of changes in these habitats was investigated. The Amvrakikos Gulf, a coastal wetland complex along the west coast of Greece, was selected as the study area. Landsat TM and ETM+ images and ASTER VNIR images were used to perform a post-classification change detection over a time period of 15 years (1989–2004). In order to assess the spatial quality of existing wetland patches, spatial metrics (such as patch area, distance between the patches, and proximity) were calculated. To study changes in the degree of fragmentation of the stopover area, a binary patch structure was used in which the focal patches were embedded in a neutral matrix. The results showed that Landsat and ASTER VNIR satellite images can be used to trace small wetlands of approximately 0.5 ha minimum. These data sources are suitable for monitoring changes in wetlands, in particular marshes and mudflats, which are important habitats for migratory waterbirds. In the 15-year period that has been studied there was an estimated 32% decrease in marsh and mudflat area. Among this decrease, 25% went to water surface and 7% to vegetation in the months of August and September. Within the same period of time, a higher degree of fragmentation of the potential bird migration habitat has also been recorded. For this purpose, the remote sensing approach used in this study where change detection is performed on freely available Landsat and ASTER satellite images could be an interesting tool for policy makers and managers, as they allow easy recognition and monitoring of changes in wetlands and therefore contribute to an evaluation of the efficiency of protection and management schemes applied by countries for their wetlands.