遥感与GIS支持下的城市绿地信息提取方法研究--以深圳市为例

城市绿地作为城市结构中的自然生产力主体，在城市系统中起着重要作用。传统的城市绿地调查多采用人工普查并结合统计学方法进行城市绿地调查，需要投入大量的人力和资金，但得到的数据精度和现时性都较差，而采用高分辨率遥感卫星数据与地理信息系统相结合的方法，可以达到对城市绿地遥感数据的快速特征提取和准确的空间统计分析。文章采用基于遥感和GIS相结合的方法，并以深圳市为例，进行了城市绿地特征提取方法的研究和应用分析。     

Predicting structural complexity of reefs and fish abundance using acoustic remote sensing (RoxAnn)

This study determined whether the acoustic roughness of Caribbean reef habitats is an accurate proxy for their topographic complexity and a significant predictor of their fish abundance. Fish abundance was measured in 25 sites along the forereef of Glovers Atoll (Belize). At each site, in situ rugosity (ISR) was estimated using the “chain and tape” method, and acoustic roughness (E1) was acquired using RoxAnn. The relationships between E1 and ISR, and between both E1 and ISR and the abundance of 17 common species and the presence of 10 uncommon species were tested. E1 was a significant predictor of the topographic complexity (r ² = 0.66), the abundance of 10 common species of surgeonfishes, pomacentrids, scarids, grunts and serranids and the presence of 4 uncommon species of pomacentrids and snappers. Small differences in E1 (i.e. ∆0.05–0.07) reflected in subtle but significant differences in fish abundance (~1 individual 200 m⁻² and 116 g 200 m⁻²) among sites. Although we required the use of IKONOS data to obtain a large number of echoes per site, future studies will be able to utilise RoxAnn data alone to detect spatial patterns in substrate complexity and fish abundance, provided that a minimum of 50 RoxAnn echoes are collected per site.     

遥感与GIS在蝗虫生境研究中的应用进展

蝗虫生境是蝗虫赖以生活、生存的环境。利用遥感技术获取与蝗虫密切相关的各种生境因子,并结合GIS技术研究和阐明蝗虫的生境因子对东亚飞蝗的产卵、孵化、成虫、迁飞等生育周期的影响机理,是实现对蝗虫监测、预测预警的基础。文章首先分析了各种蝗虫生境因子对蝗虫发生的影响机理,认为这些生境因子对蝗灾发生的影响不是孤立地起作用的,仅靠单个生境因子进行蝗灾的预测是不全面的,而遥感和GIS技术方便的获取、管理和分析多种生境因子数据,在大尺度蝗灾发生监测和预警中起到不可替代的作用。通过对遥感与GIS在蝗虫的不同发育阶段（蝗卵发育阶段、蝗蝻发育阶段和成虫阶段）的应用及其进展的分析,认为对蝗虫不同生育阶段的遥感监测需采用不同的参数和技术才能达到更好的效果,最后提出了遥感与GIS在蝗虫生境监测方面的未来发展方向。     

Mapping of the benthic communities in the Taranto seas using side-scan sonar and an underwater video camera

Side-scan sonar and underwater video camera records as well as dredging samples were used to map the bottom morphology and biocoenoses in the Taranto seas. A 1:20,000 scale chart has been produced with all the data recorded. Most of the study area consists of biocoenoses affected by the anthropogenic activities of the town of Taranto. Some native broadly tolerant species seem to benefit from these activities and become increasingly dominant. Environmental modifications also seem to favour the settlement of exotic species.     

Mapping of the benthic communities in the Taranto seas using side-scan sonar and an underwater video camera

Side-scan sonar and underwater video camera records as well as dredging samples were used to map the bottom morphology and biocoenoses in the Taranto seas. A 1:20,000 scale chart has been produced with all the data recorded. Most of the study area consists of biocoenoses affected by the anthropogenic activities of the town of Taranto. Some native broadly tolerant species seem to benefit from these activities and become increasingly dominant. Environmental modifications also seem to favour the settlement of exotic species.     

Crustacean habitat potential mapping in a tidal flat using remote sensing and GIS

To make a macrofaunal (crustacean) habitat potential map, the spatial distribution of ecological variables in the Hwangdo tidal flat, Korea, was explored. Spatial variables were mapped using remote sensing and a geographic information system (GIS) combined with field observations. A frequency ratio (FR) and logistic regression (LR) model were employed to map the macrofauna potential area for the Ilyoplax dentimerosa, a crustacean species. Spatial variables affecting the tidal macrofauna distribution were selected based on abundance and biomass and used within a spatial database derived from remotely sensed data of various types of sensors. The spatial variables included the intertidal digital elevation model (DEM), slope, distance from a tidal channel, tidal channel density, surface sediment facies, spectral reflectance of the near infrared (NIR) bands and the tidal exposure duration. The relation between the I. dentimerosa and each spatial variable was calculated using the FR and LR. The species was randomly divided into a training set (70%) to analyse habitat potential using FR and LR and a test set (30%) to validate the predicted habitat potential map. The relations were overlaid to produce a habitat potential map with the species potential index (SPI) value for each pixel. The potential habitat maps were compared with the surveyed habitat locations such as validation data set. The comparison results showed that the LR model (accuracy is 85.28%) is better in prediction than the FR (accuracy is 78.96%) model. The performance of models gave satisfactory accuracies. The LR provides the quantitative influence of variables on a potential habitat of species; otherwise, the FR shows the quantitative influence of a class in each variable. The combination of a GIS-based frequency ratio and logistic regression models and remote sensing with field observations is an effective method to determine locations favorable for macrofaunal species occurrences in a tidal flat.     

中国陆地植被生态系统生产有机物质价值遥感估算

可持续发展的战略要求推进生态资产研究,对生态系统生产有机物质功能价值的估算则是生态资产评估的重要组成部分。利用改进的CASA模型对中国陆地生态系统1995年NPP进行了估算,它与实测数据和国内其他研究成果的比较验证证明了该方法的可靠性;进而对1995年全国陆地生态系统生产有机物质的价值进行了估算,结果表明,1995年中国陆地生态系统净第一性生产力生产有机物质的总价值为1.902049×1012元.a-1,其空间分布是从东部向西北递减、由中部向东北和南部递增;从类型上看,常绿阔叶林的单位面积值最高,裸地和极稀疏植被的单位面积值最低。     

热岛效应季节动态随城市化进程演变的遥感监测

作为城市特有的一种环境问题,热岛效应动态发展变化的规律是城市热岛研究的基础工作.遥感技术在城市热岛动态变化监测方面的有用性已经得到了证实.然而当前城市热岛遥感研究基本都取少数几景进行对比分析,这使得遥感在城市热岛时空动态监测方面不能充分发挥作用.采用50景长时间序列Landsat TM和ETM+SLC-on/off影像,采取定性和定量分析相结合的方法,使用热岛强度、热岛范围等指标和热岛显著区的概念对厦门市1987-2008年20年间热岛季节动态随城市化进程演变的趋势进行分析,结果表明:厦门城市热岛在2003、2004年之后已由春夏秋扩展到冬季,且冬季热岛的高等级斑块在数量、个体面积和总面积上均有明显增长趋势.引起这种变化的原因还需要进一步研究和分析.     

基于遥感-过程耦合模型的地表蒸散量应用研究

作为陆面过程中地气相互作用的重要过程之一,蒸散发(Evapotranspiration,ET)在地球的大气圈-水圈-生物圈中发挥着重要作用。利用遥感-过程耦合模型BEPS,以中分辨率成像光谱仪(MODIS)数据和NCEP/NCAR再分析资料为主要输入,模拟分析了2007-2009年美国区域的地表ET,同时利用通量观测网AmeriFlux的站点观测数据验证该模型在ET模拟研究中的可靠性与适应。结果表明：12个站点通量实测值与BEPS模型模拟的ET值的相关系数为0.7297(P<0.05),表明BEPS模型能够较好的模拟研究区的地表ET。ET在1年内呈现明显的单峰趋势,5-9月ET值较高,可达60 mm·mon-1以上,最小值在1月份,值为8.39 mm·mon-1,最大值在7月份,值为118.04 mm·mon-1。该区域ET的平均年总量为505 mm·a-1。受地形、气候的影响,ET最高值对应于南部区域,这些地区ET的年总量普遍在600 mm·a-1以上,最高值为1667 mm·a-1,对应的主要覆被类型为草地和农田;中北部和东部的大部分区域ET年总量为400~600 mm·a-1;ET最小值在西部区域,年总量小于400 mm·a-1,对应覆被类型为疏林地和混交林。降水量与ET差值呈现从东向西逐渐递减的趋势,最小值主要分布在西部沙漠。整个研究区域ET与降水量之比的平均值为0.72,由东向西基本呈现增加趋势,在西部以及中北部的部分地区比值达到最大。     

Development of a framework for fire risk assessment using remote sensing and geographic information system technologies

Forest fires play a critical role in landscape transformation, vegetation succession, soil degradation and air quality. Improvements in fire risk estimation are vital to reduce the negative impacts of fire, either by lessen burn severity or intensity through fuel management, or by aiding the natural vegetation recovery using post-fire treatments. This paper presents the methods to generate the input variables and the risk integration developed within the Firemap project (funded under the Spanish Ministry of Science and Technology) to map wildland fire risk for several regions of Spain. After defining the conceptual scheme for fire risk assessment, the paper describes the methods used to generate the risk parameters, and presents proposals for their integration into synthetic risk indices. The generation of the input variables was based on an extensive use of geographic information system and remote sensing technologies, since the project was intended to provide a spatial and temporal assessment of risk conditions. All variables were mapped at 1 km² spatial resolution, and were integrated into a web-mapping service system. This service was active in the summer of 2007 for semi-operational testing of end-users. The paper also presents the first validation results of the danger index, by comparing temporal trends of different danger components and fire occurrence in the different study regions.     

Study of the dynamics of estuarine and coastal waters using remote sensing: the Tinto-Odiel estuary,SW Spain

This paper deals with the application of satellite images to characterize some aspects of the circulation dynamics of the Tinto-Odiel estuary using turbidity patterns as ‘natural tracers’. 15 images (Landsat TM and Spot HRV) were processed to provide synoptic, instantaneous views of the circulation patterns under different environmental conditions. In addition, a comparison was made between results of oceanographic field work, using biplanes and fluorescent tracers, and satellite image turbidity patterns used as ‘ground truth’ data for specific hydroclimatic situations. This approach allowed (1) the identification and mapping of dynamic processes of interest during a theoretical tidal cycle, (2) the elaboration of additional information on the ‘flow schemes’ at the mouth of the estuary with improved spatial and temporal resolution, and (3) the supply of basic data to improve the knowledge of exchange processes between estuarine and coastal waters. The results of this study are considered to be useful for the management of the estuarine system.     

Assessment of the state of agroecosystem sustainability using landscape indicators: a comparative study of three rural areas in Greece

The research was based on a comparative study of three representative rural areas (Dovras, Larissa, and Messapia) in Greece. Remote sensing data were collected (maps, aerial photographs) for the landscape analysis and elaborated using GIS linked with economic and social parameters regarding land use. By using a selected core set of landscape indicators, this research aims at providing a useful tool for assessing agroecosystem management at territorial level and hopefully assist decision-making for the promotion of sustainability. The selected tool showed that the study area of Messapia presented the highest level of environmental sustainability, while the area of Dovras showed the best combination of agricultural productivity and landscape management. Results showed that the ecoregions of Dovras, Larissa, and Messapia presented a landscape composed of important ecological function areas in the percentages of 40%, 15%, and 70%, respectively, and of cultivated areas in the percentages of 55%, 71.19%, and 19.75%, respectively.     

Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque continental shelf (Bay of Biscay), using Ecological-Niche Factor Analysis

Predicting species distribution and habitat suitability (HS) modelling, across broad spatial scales, is now a major challenge in marine ecology. The resulting knowledge is of considerable use in supporting the implementation of environmental legislation, integrated coastal zone management and ecosystem-based fisheries management. This contribution considers the identification of seafloor morphological characteristics, together with wave energy conditions, that determine the presence of European lobster (Homarus gammarus); and it predicts suitable habitats over the Basque continental shelf (Bay of Biscay), in summer. The results obtained, by applying Ecological-Niche Factor Analysis (ENFA), indicate that lobster habitat differs considerably from the mean environmental condition over the study area; likewise, that it is restrictive in terms of the range of conditions in which they dwell. The best of the environmental predictors found to be: distance to the rock substrate; Benthic Position Index; wave flux over the seafloor; and the underlying bathymetry. A habitat suitability map was produced, with a high model quality (Boyce index: 0.98 ± 0.06). The most suitable habitat for European lobster are locations at the boundary between sedimentary- and rocky-bottoms, coincident with seafloor depressions with a steep slope, with medium to high wave energy conditions, and located within a range of water depths of 35–40 m. This approach demonstrates the applicability of the method in case studies where only presence data are available, together with the inclusion of environmental variables obtained from different sources.     

PyLUR: Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

• PyLUR comprises four modules for developing and applying a LUR model. • It considers both conventional and novel potential predictor variables. • GDAL/OGR libraries are used to do spatial analysis in the modeling and prediction. • Developed on Python platform, PyLUR is rather efficient in data processing. Land use regression (LUR) models have been widely used in air pollution modeling. This regression-based approach estimates the ambient pollutant concentrations at un-sampled points of interest by considering the relationship between ambient concentrations and several predictor variables selected from the surrounding environment. Although conceptually quite simple, its successful implementation requires detailed knowledge of the area, expertise in GIS, statistics, and programming skills, which makes this modeling approach relatively inaccessible to novice users. In this contribution, we present a LUR modeling and pollution-mapping software named PyLUR. It uses GDAL/OGR libraries based on the Python platform and can build a LUR model and generate pollutant concentration maps efficiently. This self-developed software comprises four modules: a potential predictor variable generation module, a regression modeling module, a model validation module, and a prediction and mapping module. The performance of the newly developed PyLUR is compared to an existing LUR modeling software called RLUR (with similar functions implemented on R language platform) in terms of model accuracy, processing efficiency and software stability. The results show that PyLUR out-performs RLUR for modeling in the Bradford and Auckland case studies examined. Furthermore, PyLUR is much more efficient in data processing and it has a capability to handle detailed GIS input data.     

Feasibility of using high‐resolution satellite imagery to assess vertebrate wildlife populations

Although remote sensing has been used for >40 years to learn about Earth, use of very high‐resolution satellite imagery (VHR) (<1‐m resolution) has become more widespread over the past decade for studying wildlife. As image resolution increases, there is a need to understand the capabilities and limitations of this exciting new path in wildlife research. We reviewed studies that used VHR to examine remote populations of wildlife. We then determined characteristics of the landscape and the life history of species that made the studies amenable to use of satellite imagery and developed a list of criteria necessary for appropriate use of VHR in wildlife research. From 14 representative articles, we determined 3 primary criteria that must be met for a system and species to be appropriately studied with VHR: open landscape, target organism's color contrasts with the landscape, and target organism is of detectable size. Habitat association, temporal exclusivity, coloniality, landscape differentiation, and ground truthing increase the utility of VHR for wildlife research. There is an immediate need for VHR imagery in conservation research, particularly in remote areas of developing countries, where research can be difficult. For wildlife researchers interested in but unfamiliar with remote sensing resources and tools, understanding capabilities and current limitations of VHR imagery is critical to its use as a conservation and wildlife research tool.