Using remote sensing to assess biodiversity

This review paper evaluates the potential of remote sensing for assessing species diversity, an increasingly urgent task. Existing studies of species distribution patterns using remote sensing can be essentially categorized into three types. The first involves direct mapping of individual plants or associations of single species in relatively large, spatially contiguous units. The second technique involves habitat mapping using remotely sensed data, and predictions of species distribution based on habitat requirements. Finally, establishment of direct relationships between spectral radiance values recorded from remote sensors and species distribution patterns recorded from field observations may assist in assessing species diversity. Direct mapping is applicable over smaller extents, for detailed information on the distribution of certain canopy tree species or associations. Estimations of relationships between spectral values and species distributions may be useful for the limited purpose of indicating areas with higher levels of species diversity, and can be applied over spatial extents of hundreds of square kilometres. Habitat maps appear most capable of providing information on the distributions of large numbers of species in a wider variety of habitat types. This is strongly limited by variation in species composition, and best applied over limited spatial extents of tens of square kilometres.     

Mapping lake CDOM by satellite remote sensing

Given the importance of coloured dissolved organic matter (CDOM) for the structure and function of lake ecosystems, a method to estimate the amount of CDOM in lake waters over large geographic areas would be highly desirable. Advanced Land Imager (ALI) images were acquired in southern Finland (in 2002) and southern Sweden (in 2003) together with in situ measurements of bio-optical properties of 34 lakes (39 measuring stations). Based on this dataset, a band-ratio type algorithm was developed using ALI band 2 and band 3 for estimating CDOM content (absorption of filtrated water at 420 nm) in lakes. Correlation between in situ measured CDOM and the remote sensing estimate of CDOM was high, r²=0.73. The CDOM retrieval algorithm obtained on the basis of two images and in situ data was validated on a third ALI image (eastern Finland, 2002) that was available in the ALI image archive. In situ water-colour monitoring data from 22 lakes (27 measuring stations) in the third image were available in a database of the Finnish Environment Administration. The water-colour data were converted to CDOM absorption values, which were then compared to the results from a third ALI image. The correlation between remotely estimated and in situ CDOM values in the algorithm validation image was high, r²=0.83. These results support the conclusion that CDOM content in lakes over a wide range of concentrations (a_CDOM(420) between 0.68 and 11.13 m⁻¹) can be mapped using Advanced Land Imager data.     

Barriers to adopting satellite remote sensing for water quality management

Sustainable practices require a long-term commitment to creating solutions to environmental, social, and economic issues. The most direct way to ensure that management practices achieve sustainability is to monitor the environment. Remote sensing technology has the potential to accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long time periods, and is now proving useful in coastal waters, estuaries, lakes, and reservoirs, which are relevant to water quality managers. Comprehensive water quality climate data records have the potential to provide rapid water quality assessments, thus providing new and enhanced decision analysis methodologies and improved temporal/spatial diagnostics. To best realize the full application potential of these emerging technologies an open and effective dialogue is needed between scientists, policy makers, environmental managers, and stakeholders at the federal, state, and local levels. Results from an internal US Environmental Protection Agency qualitative survey were used to determine perceptions regarding the use of satellite remote sensing for monitoring water quality. The goal of the survey was to begin understanding why management decisions do not typically rely on satellite-derived water quality products.     

Crop yield estimation by satellite remote sensing

Two methods for estimating the yield of different crops in Hungary from satellite remote sensing data are presented. The steps of preprocessing the remote sensing data (for geometric, radiometric, atmospheric and cloud scattering correction) are described. In the first method developed for field level estimation, reference crop fields were selected by using Landsat Thematic Mapper (TM) data for classification. A new vegetation index (General Yield Unified Reference Index (GYURI)) was deduced using a fitted double-Gaussian curve to the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data during the vegetation period. The correlation between GYURI and the field level yield data for corn for three years was R ²=0.75. The county-average yield data showed higher correlation (R ²=0.93). A significant distortion from the model gave information of the possible stress of the field. The second method presented uses only NOAA AVHRR and officially reported county-level yield data. The county-level yield data and the deduced vegetation index, GYURRI, were investigated for eight different crops for eight years. The obtained correlation was high (R ²=84.6–87.2). The developed robust method proved to be stable and accurate for operational use for county-, region- and country-level yield estimation. The method is simple and inexpensive for application in developing countries, too.     

Oil spill detection by satellite remote sensing

This paper presents the state of the art for oil spill detection in the world oceans. We discuss different satellite sensors and oil spill detectability under varying conditions. In particular, we concentrate on the use of manual and automatic approaches to discriminate between oil slicks and look-alikes based on pattern recognition. We conclude with a discussion of suggestions for further research with respect to oil spill detection systems.     

遥感卫星图像自动导航方法研究

遥感卫星图像自动导航方法用来自动地确定遥感卫星图像中每一个像素的地理经纬度,目前已经在气象、海洋、资源、环境、军事等领域得到了广泛应用,并且产生了巨大的社会和经济效益。介绍了一种新的基于最大相关系数的遥感卫星图像自动导航方法。首先给出了问题的描述;其次介绍了图像自动导航数据流程;然后设计并实现了一种新的基于最大相关系数的自动图像导航方法,它是整个遥感卫星自动导航的关键部分;最后给出了实例,验证了方法的可行性以及高精度。     

Locating tuna forage ground through satellite remote sensing

A technique has been developed to assess tuna habitat using satellite derived ocean colour, water transparency and sea surface temperature. The scientific approach is based on the food and feeding habit and the preferential temperature range of tuna. Time series chlorophyll-a images of Indian Remote Sensing Satellite P4-Ocean Colour Monitor (IRS P4-OCM) have been analysed to define the critical phytoplankton patch size, its persistence and the optimal water transparency depth. Sea surface temperature (SST) data derived from National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) have been analysed to study the optimum temperature range in the surrounding waters. Results based on hindcasting indicate that the tuna forage ground derived from satellite data yielded high catch of tuna (>2% hooking rate). Study reveals that a minimum time delay of 5–7 days is required for a phytoplankton patch to mature to the forage ground. In addition, water transparency for facilitating sight feeding should be about 25–30 m depth. The thermal limit and preferential temperature range observed is 26–30°C and 26–28°C, respectively. Preliminary results based on limited validation are highly promising. However, an experimental forecast is being planned to validate this approach.     

面向存储资源优化的遥感卫星任务规划算法

针对遥感卫星的成像任务规划问题,按照任务重要性的不同,提出了两阶段调度策略,并设计了两个时间窗口选择规则。以星上存储资源优化为目标,利用地面站的下传活动将整个规划过程分为较小的调度区间,提出了可用存储空间上界估计算法计算每个调度区间的可调度存储资源容量,以此为基础对问题进行了简化,并给出了基于规则的启发式求解算法。实验结果表明,该算法是有效的。     

Attitude control system specifications for a remote sensing satellite

Abstract

Though the literature is replete with papers on remote sensing via space satellites, the specifications in terms of jitter and drift rate that have to be met by the specific mission, are often either over-specified or under-specified. In this paper the authors endeavour to present, through heuristic arguments, the effect of jitter and drift on picture quality, and to arrive at the proper specifications on attitude and orbit control systems for remote sensing satellites.     

Prospects for satellite remote sensing of Adelie penguin rookeries

Future conservation efforts are expected to require population statistics for Southern Ocean species, including penguins. Preliminary laboratory spectral reflectance measurements are presented of penguin plumage plus some of the major components of the Antarctic environment. A sketch is presented of the prospects for employing remote sensing systems for monitoring penguin populations on a regional scale.     

Using active learning to adapt remote sensing image classifiers

The validity of training samples collected in field campaigns is crucial for the success of land use classification models. However, such samples often suffer from a sample selection bias and do not represent the variability of spectra that can be encountered in the entire image. Therefore, to maximize classification performance, one must perform adaptation of the first model to the new data distribution. In this paper, we propose to perform adaptation by sampling new training examples in unknown areas of the image. Our goal is to select these pixels in an intelligent fashion that minimizes their number and maximizes their information content. Two strategies based on uncertainty and clustering of the data space are considered to perform active selection. Experiments on urban and agricultural images show the great potential of the proposed strategy to perform model adaptation.     

容差粗糙集卫星遥感数据分类

结合粗糙集理论和遥感数据中地物光谱特征空间分布信息,提出了一种基于光谱特征邻域的容差粗糙集分类方法,用来处理卫星遥感数据分类中的不确定性问题。利用北京地区Landsat-5 TM数据进行分类试验,对算法分类过程进行讨论及其分类结果进行验证分析;结果表明：文中方法在可理解性和稳定性上体现出比较好的性质,能够有效处理卫星遥感数据分类中存在的不确定性因素,在具有复杂光谱特征地物分类方面具有发展潜力。     

卫星遥感及图像处理平台发展

航天科技是国家综合国力和科技实力的重要体现,而卫星遥感则是航天科技转化为生产力最直接、最现实的途径之一。遥感数据获取与分发、数据处理与信息提取是卫星遥感应用的两个基本步骤。随着国家民用空间基础设施规划中的遥感卫星体系稳步推进,以及商业卫星遥感的蓬勃发展,我国的卫星遥感数据获取能力呈现质量齐升之势。但同时,作为卫星遥感应用的基础设施和关键工具,遥感图像处理系统平台逐渐成为制约自主卫星数据应用和空间信息业务发展的重要因素之一。本文围绕卫星遥感对地观测主题,从卫星遥感数据获取能力、卫星遥感数据处理系统平台两方面,对国内外现状进行综述,在此基础上分析了卫星遥感的发展趋势。     

面向任意几何区域的遥感卫星对地覆盖法*

为了满足对任意几何区域进行覆盖特性分析的需要,本文在传统网格点覆盖法对矩形区域进行覆盖特性分析的基础上,对网格点构建、卫星过境覆盖分析等环节进行改进,使其适合对任意几何区域进行覆盖特性分析的需要,最后以中国行政区域为例进行实验并通过过境特性表、过境重绘图和覆盖重数图等进行覆盖特性的可视化。结果表明了本文研究的对地覆盖法在任意几何区域上能够准确的计算出其每次过境的覆盖区域及总覆盖区域,同时在实验分析中通过多种可视化方法展示目标区域的覆盖特性,使其更加直观。     

Reconciling the global terrestrial water budget using satellite remote sensing

Recent retrievals of multiple satellite products for each component of the terrestrial water cycle provide an opportunity to estimate the water budget globally. In this study, we estimate the water budget from satellite remote sensing over ten global river basins for 2003-2006. We use several satellite and non-satellite precipitation (P) and evapo-transpiration (ET) products in this study. The satellite precipitation products are the GPCP, TRMM, CMORPH and PERSIANN. For ET, we use four products generated from three retrieval models (Penman-Monteith (PM), Priestley-Taylor (PT) and the Surface Energy Balance System (SEBS)) with data inputs from the Earth Observing System (EOS) or the International Satellite Cloud Climatology Project (ISCCP) products. GPCP precipitation and PM (ISCCP) ET have less bias and errors over most of the river basins. To estimate the total water budget from satellite data for each basin, we generate merged products for P and ET by combining the four P and four ET products using weighted values based on their errors with respect to non-satellite merged product. The water storage change component is taken from GRACE satellite data, which are used directly with a single pre-specified error value. In the absence of satellite retrievals of river discharge, we use in-situ gauge measurements. Closure of the water budget over the river basins from the combined satellite and in-situ discharge products is not achievable with errors of the order of 5-25% of mean annual precipitation. A constrained ensemble Kalman filter is used to close the water budget and provide a constrained best-estimate of the water budget. The non-closure error from each water budget component is estimated and it is found that the merged satellite precipitation product carries most of the non-closure error.     

Investigation into lossless hyperspectral image compression for satellite remote sensing

Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-infrared (IR), mid-IR and thermal IR portions of the spectrum, thus requiring large data storage on board the satellite and high bandwidth of the downlink transmission channel to ground stations. Image compression techniques are required to compensate for the limitations in terms of on-board storage and communication link bandwidth. In most remote-sensing applications, preservation of the original information is important and urges studies on lossless compression techniques for on-board implementation. This article first reviews hyperspectral spaceborne missions and compression techniques for hyperspectral images used on board satellites. The rest of the article investigates the suitability of the integer Karhunen–Loève transform (KLT) for lossless inter-band compression in spaceborne hyperspectral imaging payloads. Clustering and tiling strategies are employed to reduce the computational complexity of the algorithm. The integer KLT performance is evaluated through a comprehensive numerical experimentation using four airborne and four spaceborne hyperspectral datasets. In addition, an implementation of the integer KLT algorithm is ported to an embedded platform including a digital signal processor (DSP). The DSP performance results are reported and compared with the desktop implementation. The effects of clustering and tiling techniques on the compression ratio and latency are assessed for both desktop and the DSP implementation.     

高分辨率遥感卫星影像的河流提取方法研究

为了克服单纯采用光谱信息提取河流的缺陷,利用高分辨率遥感影像突出的高分辨率的特性提出一种综合影像中光谱、纹理、几何特性等多特征联合提取河流的方法。该方法分别对河流水体的光谱特征、纹理特征及河流几何形状进行描述,选取特征参数,构造综合特征矩阵,利用均值聚类分割最终得到河流目标。通过对真实高分辨率遥感影像Worldview1影像进行的实验验证了该方法的高精准性及快速性。     

A satellite remote sensing technique for geological structure horizon mapping

A satellite remote sensing technique is demonstrated for generating near surface geological structure data. This technique enables the screening of large areas and targeting of seismic acquisition during hydrocarbon exploration. This is of particular advantage in terrains where surveying is logistically difficult. Landsat Thematic Mapper (TM) data and a high resolution digital elevation model (DEM), are used to identify the map outcropping horizons. These are used to reconstruct the near surface structure. The technique is applied in Central Yeman which is characterized by a 'layer-cake' stratigraphic section and low dipping terrain. The results are validated using two-dimensional seismic data. The near surface map images faults and structure not apparent in the raw data. Comparison with the structure map generated from two-dimensional seismic data indicates very good structural and fault correlation. The near surface map successfully highlights areas of potential closure at reservoir depths.     

基于FPGA的无线遥测颅内压监护仪的研制

本文从分析传统颅内压监护仪的特点出发.给出了一种新型无线遥测颅内压监护仪的实现方案,重点介绍了系统及各部分的硬件电路及上位机软件的设计思想与方法,并对整个系统工作性能做了简要分析.     

基于HJ-1星CCD数据的溢油遥感特性分析与信息提取

基于HJ-1星CCD多光谱数据,以2010年美国墨西哥湾深海油井溢油污染海域为研究区,对溢油迁移转化过程进行分析,认为油水混合物是该次事故的主要污染类型之一.研究HJ-1星CCD数据多种目标的影像特征与光谱响应特征,指出油水混合物能明显改变海水对入射光的后向散射性能,可以被有效地识别与判定.利用决策树分类方法能有效地提取墨西哥湾溢油污染中的油水混合物;对误判信息进行分块合并处理后,可进一步提高油水混合物的提取精度.研究表明,HJ-1星CCD多光谱数据能有效提取海洋溢油污染信息,具备了开展海洋溢油污染遥感监测的能力.