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针对大熊猫栖息地近年来受逐渐频繁的人类活动和地震等自然灾害的影响,大熊猫的生存空间和活动范围呈现"破碎化""岛屿化"问题,该文提出了一种利用景观格局分析技术定量分析大熊猫栖息地的景观组分空间分布特征和景观功能的方法。通过采用景观生态学理论,选取四川喇叭河自然保护区为研究区域,基于2001、2007和2013年3期Landsat卫星影像,对研究区大熊猫栖息地景观类型开展动态监测;并通过选取计算景观指数,分析景观格局变化对大熊猫栖息地生态环境的影响。通过构建大熊猫运动阻力模型,利用GIS空间分析功能分析研究区自然生态对大熊猫物种基因交流的影响,从空间上对生态功能优化技术进行了初步探讨。 相似文献
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应用“3S”技术进行北京市森林立地分类和立地质量评价的研究 总被引：33，自引：0，他引：33
本文针对目的森林立地分类和立地质量评价研究中存在的问题。试图从立地分类和评价的方法进行技术上新的探讨。研究中以生态学和景观生态学理论为基础,以遥感（ＲＳ）、地理信息系统（ＧＩＳ）和专家系统（ＥＳ）作为主要的技术手段,借助相关数学分析,对北京市森林进行立地类型划分和在此基础上的立地质量评价及多目标动态决策。通过对北京地区景观特征及其气候、地貌、地形、土壤、植被等各种因子的定性分析,以及一、二类调查数据的定性定量分析,结合实际应用,确定分类原则和分类系统。应用ＧＩＳ建立各级分类的各因子专题数据库和图形库,通过各分类层次的主导因子及辅助因子的专题图叠加完成初分类。在此基础上,应用知识库中的专家知识及ＥＳ的推理机制对初分类结果进行综合,根据可信度理论,得出各级符合生产、造林规划和经营实际的立地类型图。对于最低一级的分类结果,采用专家打分的方法进行各类型立地质量的多因子综合评价,并编制立地质量评价图。在分类和评价的基础上,可以根据森林的生态效益、经济效益、环境效益和社会效益的综合考虑选择目标集,进行面向目标的动态决策。 相似文献
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遥感图像水体区域中因水体自身流动和波动等因素造成图像噪声,利用传统方法直接分割水体容易导致分割精度较低。为此,利用遥感图像中水体区域具有连通性强以及像素灰度值相近等特点,提出了一种利用多结构元素形态学重构边缘检测结合区域生长实现遥感图像水体分割的方法。首先将遥感图像转化为灰度图像,运用多结构元素形态学重构边缘检测,在去除噪声的同时增强水体边缘,保持水体区域边缘的较准确定位;然后利用灰度直方图自动选取种子点,确定水体区域灰度范围,利用该灰度范围内像素的均值和方差、种子点及已生长区域灰度特性作为生长准则,实现对水体区域的分割。实验结果表明,该方法能够对因水体扰动等因素导致的噪声图像进行有效分割,且水体区域分割精度较高。 相似文献
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遥感图像应用发展对图像质量的要求越来越高,不同质量的遥感图像往往需要不同的处理方法和参数。通过遥感图像质量等级分类研究,不仅能够为遥感图像的处理提供先验信息,还能够对遥感图像的客观质量评价和传感器的成像效果进行评估。为了克服现有的遥感图像质量等级分类方法计算参数获取困难、等级数量少的缺点,利用深度学习方法的分类机能,通过改进特征提取网络和等级分类设计,建立了一种基于深度卷积神经网络的遥感图像质量等级分类模型。通过质量等级分类预处理后,利用经典的深度学习方法进行目标检测实验。结果表明,所提方法在西北工业大学遥感图像数据集上质量等级分类的准确率、召回率、精确率和F1最高能达到0.976、0.972、0.974和0.973,优于传统算法。利用卷积神经网络实现遥感图像质量等级分类,既拓展了深度学习的应用领域,又为遥感图像质量评估提供了一个新方法。 相似文献
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本文针对合成孔径声呐图像线目标提取过程中,由于线目标宽度（直径）小且图像受相干斑噪声影响严重而导致的提取困难的问题,提出了基于霍夫直线检测和区域生长的线目标提取算法。首先利用Otsu算法计算区域生长终止阈值,并对噪声进行初步抑制;然后在对图像进行霍夫直线粗检测的基础上,对检测结果进行不均匀分割,再进行细检测,得到区域生长种子点;最后利用区域生长对线目标进行还原。试验结果表明,该算法能准确地提取线目标;与传统区域生长对比,该算法选取的种子点数量提升了5.37倍,且线目标提取结果具有更好的连续性和完整性。 相似文献
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地理国情外业调查是地理国情普查工作十分重要的工作内容,是保证地理国情普查数据质量的关键环节。外业调查是对采集的地理国情要素和解译的地表覆盖分类成果以及内业无法定性的类型、边界和属性进行实地调查,同时采集遥感影像样本数据,为最终形成地理国情要素数据、地表覆盖分类数据成果和遥感影像解译样本数据库提供基础。 相似文献
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Remote sensing has recently been used to map forage quality for rangeland management. However, the validity of the remotely sensed forage quality can best be assessed when it connects well with the animal unit. In this study we used the new WorldView-2 multispectral imagery to estimate and map forage quality (nitrogen concentration) as a step to explain GPS based cattle distribution in a rangeland of Southeastern Zimbabwe. Nitrogen concentration was successfully estimated and mapped (Rcv2 = 0.66, relative error = 0.13%) using partial least squares regression (PLSR). The integration of GPS based cattle distribution patterns with forage quality in a GIS showed that cattle locations significantly clustered in areas of high forage quality. The results of this study suggest that new multispectral data with unique band settings such as WorldView-2 improves the estimation and mapping of forage quality in rangelands at landscape level. In addition, our results indicate that remotely sensed forage quality can be used to explain herbivore distribution, particularly cattle grazing patterns in rangelands. 相似文献
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本文利用国土卫星影像就京津唐地区的自然资源与环境调查进行了多学科综合应用和高层次专题制图的研究。在研究中,对影像的基本特性、质量和使用的技术指标作了较系统的分析,并按其精度、使用程度和效果等提出了评价。同时对国土卫星像片的几何配准,运用多项式与有限元法相结合的原理,进行了计算机和光学处理的对比研究。 本区资源与环境的遥感调查应用,主要是运用遥感地学原理,分析水文下垫面要素,划分水文环境类型,计算其产水量;分析非农业用地与总土地及其它用地的比例关系,探索土地利用类型结构的地域差异规律;农业低产地环境及其数量、质量特征的研究;综合调查森林资源,包括宜林地的生态环境、立地条件及宜林树种的生态与经济特性;以及以北京为中心的京津唐旅游圈及功能分区,矿产资源的赋存机制,区域地壳稳定性及区内近一万年来的自然环境的演化规律及其与国土整治、规划和城镇建设的关系等进行了多元综合研究。同时编制了一套高层次专题图件,并量算了各种资源数据。 相似文献
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This study employed image enhancement for LANDSAT TM and ALOS imagery to monitor the changing status of coastal resources from 2001 to 2011, object-based classification of high-resolution THEOS imagery to extract fish cage culture sites and interpolation methods to determine marine environmental quality in 2011 in the northern part of Phu Quoc Island. There were five classes in the study site: natural forest, Melaleuca forest, agriculture, peat and built-up areas. Agricultural land and Melaleuca forest changing into built-up areas constituted approximately 51.13% of the total area changing. The benthic seagrass habitat increased dramatically from 2001 to the end of 2010. Besides, marine culture has been concerned to cage culture which is one of the sources directly affecting aquatic life and water quality in coastal environment. Cage culture locations were detected using high-resolution imagery as THEOS data for image fusion and Object-based Image Analysis methods. Water quality criteria including nitrogen, phosphorus and chlorophyll-a concentrations were determined by interpolation method, and the spatial distribution of these parameters showed a concentration in the study area in the range from 0.17 to 0.49?mg/L, 0.012 to 0.073?mg/L and 0.26 to 1.046?μg/L, respectively. 相似文献
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The multispectral and multitemporal analysis of the spectral response of rice has made it possible to determine at which point in the vegetative cycle of rice it is best to make an inventory, together with the usefulness of the normalized‐difference vegetation index for such an inventory. The results could be usefully included in any classification procedure of the TM image in order to make the inventory in a systematic way. In this case a supervised classification of the image has been made which assumes a Gaussian behaviour for each spectral class. The results obtained are, for the most part, consistent with those obtained by using traditional methods. 相似文献
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Saygin Abdikan 《国际地球制图》2018,33(1):21-37
Remote sensing data utilize valuable information via various satellite sensors that have different specifications. Image fusion allows the user to combine different spatial and spectral resolutions to improve the information for purposes such as forest monitoring and land cover mapping. In this study, I assessed the contribution of dual-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar data to multispectral Landsat imagery. The research investigated the separability of forested areas using different image fusion techniques. Quality analysis of the fused images was conducted using qualitative and quantitative analyses. I applied the support vector machine image classification method for land cover mapping. Among all methods examined, the à trous wavelet transform method best differentiated the forested area with an overall accuracy (OA) of 94.316%, while Landsat had an OA of 92.626%. The findings of this study indicated that optical-SAR-fused images improve land cover classification, which results in higher quality forest inventory data and mapping. 相似文献
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S. Jonna K. V. S. Badarinath J. Saibaba 《Journal of the Indian Society of Remote Sensing》1989,17(2):59-64
Remotely sensed data has been found useful in various aspects of hydrology like sedimentation, water quality watershed management, flood and drought monitoring, ground water resources evaluation etc. With the fast development of computer applications to image processing and availability of low cost image processing systems, digital image processing methods supplemented by visual interp etation aids will be useful for effective utilization of Remote Sensing data. Application of various digital image processing along with using a low cost image processing system for detailed study of water quality parameters is discussed. Studies have been conducted in a sample revervoir to obtain suitable digital image processing techniques for achieving better visual separability within the reservoir water. An overview of semiquantification of sediment concentration in the reservoir water using computer aided processing methods is presented in this paper. 相似文献
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Steve Dury Brian Turner Bill Foley Ian Wallis 《International Journal of Applied Earth Observation and Geoinformation》2001,3(4):328
In this study we assess the feasibility of remotely measuring canopy biochemistry, and thus the potential for conducting large-scale mapping of habitat quality. A number of studies have found nutrient composition of eucalypt foliage to be a major determinant of the distribution of folivorous marsupials. More recently it has been demonstrated that a specific group of secondary plant chemicals, the diformylphloroglucinols (DFPs), are the most important feeding deterrents, and are thus vital determinants of habitat quality. We report on the use of laboratory spectroscopy to attempt to identify one such DFP, sideroxylonal-A, in the foliage of Eucalyptus melliodora, one of the few eucalypt species browsed by folivorous marsupials. Reflectance spectra were obtained for freeze-dried, ground leaves using near infrared spectroscopy (NIRS) and for both oven-dried and fresh whole leaves using a laboratory-based (FieldSpec) spectroradiometer. Modified partial least squares (MPLS) regression was used to develop calibration equations for sideroxylonal-A concentration based on the reflectance spectra transformed as both the first and second difference of absorbance (Log 1/R). The predictive ability of the calibration equations was assessed using the standard error of calibration statistic (SECV). Coefficients of determination (r2) were highest for the ground leaf spectra (0.98), followed by the fresh leaf and dry leaf spectra (0.94 and 0.87, respectively). When applied to independent validation sub-sets, sideroxylonal-A was most accurately predicted from the ground leaf spectra (r2 = 0.94), followed by the dry leaf and fresh leaf spectra (0.72 and 0.53, respectively). Two spectral regions, centred on 674 nm and 1394 nm, were found to be highly correlated with sideroxylonal-A concentration for each of the three spectral data sets studied. Results from this study suggest that calibration equations derived from modified partial least squares regression may be used to predict sideroxylonal-A concentration, and hence leaf palatability, of Eucalyptus melliodora trees, thereby indicating that the remote estimation of habitat quality of eucalypt forests for marsupial folivores is feasible. 相似文献
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Forests play a critical role in ecological functioning, global warming and climate change through its unique potential to capture and hold carbon (C). Biomass is one of the indicator of the status of forests hence accurate assessment and biomass mapping is important for sustainable forest management. The objectives of this study is to estimate above ground biomass (AGB) from field inventory data and to map AGB combining field inventory data, remote sensing and geo-statistical model. In the present study stratified random sampling were used for estimation of biomass in which 59 plots were laid down in different homogenous strata depending on the NDVI values for the region of Maharashtra Western Ghats. The above ground biomass from field ranged from 0.05 to 271 t-dry wt ha?1 in which trees added maximum towards total biomass followed by shrubs and herbs. This paper evaluates the best vegetation indices to estimate biomass. This study was carried out by using Landsat TM satellite data and field inventory data in the Ratnagiri district of Maharashtra, India. A significant correlation was observed between biomass and vegetation indices. The best fit regression equation developed from field above ground biomass and NDVI with R2 value of 0.61 was used for spectral modeling to estimate the geospatial distribution of AGB in the entire region. The results of spatial predictions Geostatistical technique and remotely sensed data as auxiliary variables were compared using statistical error methods. This study employed Mean error, Root-Mean-Square error, Average Standard error and Root-Mean Square Standardized error. The ME, RMSE, Average Standard error and Root-Mean Square Standardized error was 0.078, 8.032, 7.982 and 0.967 respectively. The results showed that cokriging technique is one of the geostatistical method for spatial predictions of biomass in the studied region. The present study revealed that remote sensing technique combined with field sampling provides quick and reliable estimates of above ground biomass and carbon pool and can be used as baseline information for further temporal studies of biomass status of the region and in planning of forest and natural resources management. 相似文献