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1.
Photogrammetry represents a non-destructive, cost-effective tool for coral reef monitoring, able to integrate traditional remote sensing techniques and support researchers’ work. However, its application to submerged habitats is still in early stage. We present new ways to employ Structure from Motion techniques to infer properties of reef habitats. In particular, we propose the use of Digital Surface Models and Digital Terrain Models for assessing coral colonies extension and height and discriminating between seabed and coral cover. Such information can be coupled with digital rugosity estimates to improve habitat characterization. DTM, DSM and orthophotos were derived and used to compute a series of metrics like coral morphologies, reef topography, coral cover and structural complexity. We show the potentialities offered by underwater photogrammetry and derived products to provide useful basic information for marine habitat mapping, opening the possibility to extend these methods for large-scale assessment and monitoring of coral reefs.  相似文献   

2.
Coral reefs are one of the most diverse of all marine ecosystems and are often referred to as the “rainforests of the sea”. Though they cover less than one per cent of Earth’s surface, they are home to one quarter of all ocean species by providing food and shelter to them. Optical remote sensing has been widely employed for mapping and monitoring coral reefs. But the application of microwave remote sensing has been an alternate domain in this area. This study explores the possibility of utilizing synthetic aperture radar (SAR) data of Radar Imaging Satellite-I, India’s first indigenous microwave satellite to delineate the coral reefs in Andaman and Lakshadweep Islands in the Indian Ocean. The dual polarized data, after reducing the speckle has been classified to delineate the coral reefs in the vicinity of both islands. SAR has a performance comparable with passive optical sensors under favourable conditions of imaging, viz. optimum tidal current and surface winds. The study results are compared with the international coral reef reference map and are found to be highly promising, with an overall accuracy of 98.3% and a Kappa coefficient of 0.944 for fringing reefs in Andaman region. For the atolls in Lakshadweep region, the overall accuracy is found to be 92.99% and the Kappa coefficient is estimated at 0.7377. This study tries to explore a different horizon for microwave remote sensing in coral reef studies. It is seen that, optical and microwave remote sensing can provide a mutually supporting platform in coral reef delineation, in terms of imaging depth as well as climatic conditions.  相似文献   

3.
This paper describes the application of high‐resolution SPOT data for the structural and thematic mapping of shallow coral reefs. Results are presented as structural and thematic maps of the main reef environment types. Different substrate themes including soft bottom, coral débris, coral rubble, and living coral have been identified. The separation of various living coral themes, as measured by differences in areal coral density, has also been achieved.  相似文献   

4.
Seagrasses ecosystems are fragile yet highly productive ecosystems of the world showing declining trend throughout the world due to natural and anthropogenic pressures. Effective conservation and management plan is thus required to protect these resources, to aid with conservation need mapping and monitoring of seagrasses using high resolution remote sensing data is very much required. Hence, the present study was made to record the seagrass aerial cover in the Lakshadweep islands using IRS P6 LISS IV satellite data. The suitability of LISS IV sensor for seagrass mapping was tested for the first time with an overall accuracy of 73.16%. The study found an area of 2590.2?ha of seagrasses in Lakshadweep islands with 1310.8?ha and 1279.4?ha dense and sparse seagrass cover respectively. The study recommends the use of LISS IV data for mapping the shallow water seagrasses, as mapping efficiency increases nearly 4 times more than the LISS III data, as the former (LISS IV) picks up the small patches of seagrasses and delineates the coral and reef vegetation patches from seagrass class.  相似文献   

5.
In this article, we present a satellite-based approach to gather information about the threat to coral reefs worldwide. Three chosen reef stressors – development, gas flaring and heavily lit fishing boat activity – are analysed using nighttime lights data derived from the Defense Meteorological Satellite Program (DMSP) produced at the National Oceanic & Atmospheric Administration, National Geophysical Data Center (NOAA/NGDC). Nighttime lights represent a direct threat to coral reef ecosystems and are an excellent proxy measure for associated human-caused stressors. A lights proximity index (LPI) is calculated, measuring the distance of coral reef sites to each of the stressors and incorporating the stressor's intensity. Colourized maps visualize the results on a global scale. Area rankings clarify the effects of artificial night lighting on coral reefs on a regional scale. The results should be very useful for reef managers and for state administrations to implement coral reef conservation projects and for the scientific world to conduct further research.  相似文献   

6.
珊瑚礁遥感研究进展   总被引:1,自引:0,他引:1  
珊瑚礁是生物多样性和初级生产力最高的海洋生态系统之一,对人类社会与海洋生态环境的健康和可持续发展有重要作用,而珊瑚礁又是中国南海主要的国土类型,国家因此越来越重视对南海珊瑚礁的规划、管理、建设与保护。珊瑚礁的调查与探测则是进行珊瑚礁活动的基础与依据,而遥感则在珊瑚礁的大范围探测方面具有很大的潜力,所以国内外已经存在很多利用遥感对珊瑚礁进行调查与探测的研究与应用。本文将按照被动遥感和主动遥感的顺序,客观地阐述国内外珊瑚礁遥感研究与应用的进展,探讨珊瑚礁遥感研究与应用的发展趋势,并尝试总结中国珊瑚礁遥感的机遇和挑战。其中被动遥感包括珊瑚礁地形与水深的遥感、珊瑚礁底质与地貌的遥感、珊瑚礁岸线变化与稳定性的遥感以及珊瑚礁环境的遥感等,而主动遥感则包括珊瑚礁水深的机载激光雷达遥感、珊瑚礁地貌的船载声学遥感和珊瑚礁地形的星载微波遥感等。结果发现,国内珊瑚礁遥感研究与应用的整体水平落后于国外:虽然在部分数据处理方面具有比国外更先进的技术,但相应的应用基础研究仍然达不到国外的广度与深度。因此,国内的珊瑚礁遥感研究仍需要鼓励珊瑚礁学者更多的参与与合作,以便在硬件设备和数据处理等方面加强针对珊瑚礁遥感的研究,进而融合多种手段而实现珊瑚礁遥感的工程化应用。  相似文献   

7.
Changes in shoreline, coral reef and seafloor have been mapped using remote sensing satellite data of IRS LISS-III (1998), IRS LISS-II (1988), Survey of India Topographic sheet (1969), Naval Hydrographic Chart (NHO) 1975 and bathymetry data (1999) with ARC-INFO and ARC-VIEW GIS. The analysis of multi-date shoreline maps showed that 4.34 and 23.49 km2 of the mainland coast and 4.14 and 3.31 km2 areas of island coast have been eroded and accreted, respectively, in the Gulf of Mannar. The analysis of multi-date coral reef maps showed that 25.52 km2 of reef area and 2.16 km2 of reef vegetation in Gulf of Mannar have been lost over a period of ten years. The analysis of multi-date bathymetry data indicates that the depth of seafloor has decreased along the coast and around the islands in the study area. The average reduction of depth in seafloor has been estimated as 0.51m over a period of twenty four years. The increased suspended sediment concentration due to coastal and island erosion, and raised reef due to emerging of coast by tectonic movement are responsible for coral reef degradation in the Gulf of Mannar. Validation by ground truth has confirmed these results.  相似文献   

8.
ABSTRACT

Researchers, policy makers, and farmers currently rely on remote sensing technology to monitor crops. Although data processing methods can be different among different remote sensing methods, little work has been done on studying these differences. In order for potential users to have confidence in remote sensing products, an analysis of mapping accuracies and their associated uncertainties with different data processing methods is required. This study used the MOD09A1 and MYD09A1 products of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, from which the Enhanced Vegetation Index (EVI) and the two-band EVI (EVI2) images were obtained. The objective of this study was to analyze the accuracy of different data processing combinations for multi-year rice area mapping. Sixteen combinations of EVI and EVI2 with two cloudy pixel removal methods (QA/BLUE) and four pixel replacement methods (MO/MY/MOY/MYO) were investigated over the Jiangsu Province of southeast China from 2006 to 2016. Different accuracy results were obtained with different data processing combinations for multi-year rice field mapping. Based on a comparison of the relative performance of different MODIS products and processing method combinations, EVI2_BLUE_MYO was proposed to be the optimal processing method, and was applied to forecasting the rice-planted area of 2017. Study results from 2006 to 2017 were validated against reference data and showed accuracies of rice area extraction of greater than 95%. The mean absolute error of transplanting, heading, and maturity dates were 11.55, 8.10, and 7.78 days, respectively. In 2017, two sample regions (A and B) were selected from places where rice fractional cover was greater than 75%. Rice area extraction accuracies of 85.0% (A) and 92.3% (B) were obtained. These results demonstrated the complementarity of MOD09A1 and MYD09A1 datasets in enhancing pixel spatial coverage and improving rice area mapping when atmospheric influences are significant. The optimal data processing combination indentified in this study is promising for accurate multi-year and large-area paddy rice information extraction and forecasting.  相似文献   

9.
Abstract

Coastal Tropism is a worldwide phenomenon. It induces urgent needs for observation inventories and management of coastal environment, mainly in developing countries.

High resolution satellite data may solve some aspects of the problems. Three examples based upon the potential use of shrimp aquaculture sites in tropical salt marshes, the biotopes mapping in coral reef environments for biologic stock assessments and the characterization and quantification of evolutive stages of coral platforms, are developed. All three are relative to the same tropical Pacific Island with respect, for the first and second examples, to actual needs for the management of mangroves and coral reefs and for the third, to a scientific approach related to evolutive theory of reefs platforms in lagoons.

Methodology and results based upon digital image processing and computer assisted photointerpretation are exposed.

New trends in digital processing and associated digital cartography are listed.  相似文献   

10.
珊瑚礁对于海洋生态环境研究具有重要意义,通过分析珊瑚礁底栖物质的分布及健康状况,可以对珊瑚礁生态环境进行评估。本文提出了一种基于面向对象的图像分类方法,通过试验确定不同地貌的最优分割尺度,其中陆地和深海的最优分割尺度为150,各类底栖物质的最优分割尺度为30。以Sentinel-2A卫星遥感影像为例,提取海南三亚珊瑚礁自然保护区的珊瑚礁底栖物质,并使用混淆矩阵对提取结果进行精度评估。结果表明,底栖物质提取总体分类精度为87.91%,Kappa系数为0.83。面向对象分类方法可有效结合珊瑚礁底栖物质的纹理特征和光谱特征,并充分利用遥感影像不同波段的组合特性,可为三亚珊瑚礁保护管理提供方法支撑。  相似文献   

11.
Remote sensing measurements in coral reef environments commonly confront the problem of overlying atmosphere and modification of spectral signal due to water column over the bottom substrates. In order to correct these problems, hyperspectral observations offer an advantage over multispectral observations. Airborne hyperspectral remote sensing data from Airborne Visible Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) sensor was acquired during low tidal condition on 14 February 2016 at Pirotan reef, Gulf of Kachchh region, India. The objective of this study is to map benthic coverage and bottom topography over Pirotan reef. The methodology involved atmospheric correction, simultaneous retrieval of water parameters, bathymetry, water column correction and mapping. Atmospheric correction was performed by removing path radiance and aerosol contribution and dividing by atmospheric transmittance and incoming solar irradiance to obtain remote sensing reflectance. Model derived error minimization technique was used for simultaneous retrieval of water parameters and bathymetry. Derived water parameters were used to account for water column attenuation and retrieve concomitant true bottom signature.  相似文献   

12.
Wetlands are the second-most valuable natural resource on Earth but have declined by approximately 70 % since 1900. Restoration and conservation efforts have succeeded in some areas through establishment of refuges where anthropogenic impacts are minimized. However, these areas are still prone to wetland damage caused by natural disasters. Severe storms such as Hurricane Irma, which made landfall as a Category 3 hurricane in southwest Florida (USA) on September 11, 2017, can cause the destruction of mangroves and other wetland habitat. Multispectral images from commercial satellites provide a means to assess the extent of the damage to different wetland habitat types with high spatial resolution (2 m pixels or finer) over large areas. Using such images presents a number of challenges, including deriving consistent and accurate classification of wetland and non-wetland vegetation. Machine learning methods have demonstrated high-accuracy mapping capabilities on small spatial scales, but require a large amount of robust training data. Meanwhile, ambitious efforts to map larger areas at finer resolutions may use hundreds of thousands of images, and therefore encounter Big-Data processing challenges. Large-scale efforts face the dilemma of adopting traditional mapping methods that may lend themselves to Big Data analytics but may result in accuracies that are inferior to new methods, or move to machine learning methods, which require robust training data. Given these considerations, we describe a version of the traditional Decision Tree (DT) approach and compare two common machine learning methods to derive land cover classes using a WorldView-2 image collected on November 12, 2018 to include one growing season after Hurricane Irma affected this area. Specifically, we compared the Support Vector Machine [SVM] and Neural Network [NN] methods, trained and validated with separate ground-truth datasets collected during a robust field campaign. Overall accuracies were only marginally different (85 % NN vs 83 % each DT and SVM), but healthy mangroves were more accurately identified with the DT (91 % vs 88 % NN and 86 % SVM), and degraded mangroves were more accurately identified with NN (62 % vs 57 % NN and 38 % DT). These results, combined with their respective training requirements, have implications for the direction with which large-scale high-resolution mapping of coastal habitats proceeds.  相似文献   

13.
Wetlands have been determined as one of the most valuable ecosystems on Earth and are currently being lost at alarming rates. Large-scale monitoring of wetlands is of high importance, but also challenging. The Sentinel-1 and -2 satellite missions for the first time provide radar and optical data at high spatial and temporal detail, and with this a unique opportunity for more accurate wetland mapping from space arises. Recent studies already used Sentinel-1 and -2 data to map specific wetland types or characteristics, but for comprehensive wetland characterisations the potential of the data has not been researched yet. The aim of our research was to study the use of the high-resolution and temporally dense Sentinel-1 and -2 data for wetland mapping in multiple levels of characterisation. The use of the data was assessed by applying Random Forests for multiple classification levels including general wetland delineation, wetland vegetation types and surface water dynamics. The results for the St. Lucia wetlands in South Africa showed that combining Sentinel-1 and -2 led to significantly higher classification accuracies than for using the systems separately. Accuracies were relatively poor for classifications in high-vegetated wetlands, as subcanopy flooding could not be detected with Sentinel-1’s C-band sensors operating in VV/VH mode. When excluding high-vegetated areas, overall accuracies were reached of 88.5% for general wetland delineation, 90.7% for mapping wetland vegetation types and 87.1% for mapping surface water dynamics. Sentinel-2 was particularly of value for general wetland delineation, while Sentinel-1 showed more value for mapping wetland vegetation types. Overlaid maps of all classification levels obtained overall accuracies of 69.1% and 76.4% for classifying ten and seven wetland classes respectively.  相似文献   

14.
Tsunami waves struck the Indian coast on 26th December 2004 affecting the Andaman and Nicobar group of islands. A quick assessment of the status of the vital coastal ecosystems has been made using pre- and post-tsunami Advance Wide Field Sensor (AWiFS) data of Indian satellite RESOURCESAT with an accuracy of 87–90% and the Kappa ranging from 0.8696 to 0.9053. Among the coastal ecosystems the coral reefs have suffered the maximum with the Nicobar reefs (69% eroded and 29% degraded) bearing the brunt more than the Andaman reefs (54% eroded and 22% degraded). Significant improvement to the condition of the reef damaged due to backwash has been noted. About 41% of the Sentinel reef area has undergone significant improvement. The continuance of the erosion of the southwestern Andaman reefs is due to the impact of recurring earthquakes. The impact on mangroves of both the groups of islands has been due to uprooting as well as inundation of seawater and resulting stagnation. Changes are expected in community structure of mangroves as a result of tsunami.  相似文献   

15.
张伟  赵理君  郑柯  唐娉 《测绘通报》2017,(10):34-38
快速、准确地从卫星遥感影像上获取水体信息已成为水资源调查及监测、湿地保护、洪涝灾害评估等领域的重要技术手段。本文以GF-4卫星的PMS传感器影像为数据源,提出了一种改进光谱角匹配(MSAM)的水体信息提取方法,以内蒙古中东部和长江中下游两个试验区为研究对象,对比分析了MSAM与单波段阈值法、NDWI阈值法、支持向量机和光谱角匹配等传统方法的水体信息提取结果,并进行了精度评价。试验结果表明,本文提出的MSAM方法不仅能准确地提取水体信息,而且能很好地区分水体与云阴影,对细小水体的提取也具有很好的效果。在内蒙古中部和长江中下游两个试验区的水体提取精度分别达到99.86%和98.37%,在5种水体提取方法中的精度最高,可以有效地提取水体信息。  相似文献   

16.
Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas.  相似文献   

17.
In this study, we create and critically analyse an automated decision tree classification approach for regional level land cover mapping in insular South-East Asian conditions, using a combination of 10–30 m resolution optical and radar data. The resulting map contains 11 land cover classes and reveals a great deal of contextual information due to high spatial resolution. A limited accuracy assessment indicates 59–97% class wise accuracies. The unprecedented spatial detail of closed canopy oil palm mapping (with user’s accuracy of 90%) is seen as the most promising feature of the mapping approach. The incapability of separating primary forests from other tree cover, and the large variety of different landscapes (e.g. home gardens and tea plantations) classified as shrubland, are considered the main areas for future improvement. Overall, the study demonstrates the great potential of multi-source 10–30 m resolution high data volume land cover mapping approaches in insular South-East Asian conditions.  相似文献   

18.
本文利用ADS40相机进行航空摄影,对海岛(礁)区域1∶2000比例尺成图精度进行了分析,比较了差分GPS与精密单点定位技术应用于ADS40航摄的精度。试验结果表明,ADS40相机可满足海岛(礁)大比例尺成图航摄的精度要求,缩短成图周期,精密单点定位技术的平面精度与差分GPS方法相当,高程精度较差,从工程角度考虑,海岛(礁)大比例尺成图时架设地面GPS基站比较稳妥。  相似文献   

19.
Most normal requirements of photocontrol for mapping are outlined in terms of accuracies, patterns and densities of points, and methods of identification. An established mapping organisation is well able to make the necessary allowances for particular local difficulties. Ground control remains an expensive, high risk and time consuming part of the map production process which should be kept to a minimum by using aerial triangulation and airborne control where appropriate. Once the GPS (global positioning system) satellites become fully operational, the approach to control will have to be reassessed.  相似文献   

20.
全球土地覆盖制图在过去的10年中取得重要进展,空间分辨率从300 m增加至30 m,分类详细程度也有所提高,从10余个一级类到包含29类的二级分类体系。然而,利用光学遥感数据在大空间范围制图方面仍有诸多挑战。本文主要介绍在农田、居住区、水体和湿地制图方面的挑战,讨论在使用多时相和多传感器遥感数据上的困难,这将是未来遥感应用的趋势。由于各种地表覆盖数据产品有自己定义的地表覆盖类型体系和处理流程,通过调和以及集成各种全球土地覆盖制图产品能够满足新的应用目的,并且可以最大程度地利用已有的土地覆盖数据。然而,未来全球土地覆盖制图需要能够按照新应用需求动态生成地表覆盖数据产品的能力。过去的研究表明有效地提高局部尺度制图的分类精度,更好的算法、更多种特征变量(新类型的数据或特征)以及更具代表性的训练样本都非常重要。我们却认为特征变量的使用更重要。本文提出了一个全球土地覆盖制图的新范式。在这个新范式中,地表覆盖类型的定义被分解为定性指标的类、定量指标的植被郁闭度和高度。非植被类型通过它们的光谱和纹理信息提取。复合考虑类、郁闭度和高度3种指标来定义和区别包含植被的地表覆盖类型。郁闭度和高度不能在分类算法中提取,需要借助其他直接测量或间接反演方法。新的范式还表明,一个普遍适用的训练样本集有效地提高了在非洲大陆尺度土地覆盖分类。为了确保更加容易地实现从传统的土地覆盖制图到全球土地覆盖制图新范式的转变,建议构建一体化的数据管理和分析系统。通过集成相关的观测数据、样本数据和分析算法,逐步建成全球土地覆盖制图在线系统,构建全球地表覆盖制图门户网站,为数据生产者、数据用户、专业研究人员、决策人员搭建合作互助的平台。  相似文献   

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