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基于神经网络的土地荒漠化信息提取方法研究 总被引：14，自引：0，他引：14
土地荒漠化是当今全球面临的重大环境问题之一,它的发生、发展及其逆转是气候、环境和人类社会经济活动综合作用的结果.区域荒漠化信息的提取技术研究是荒漠化研究进一步深入的关键,根据土地荒漠化的遥感探测机理,应用神经网络技术,利用了TM卫星遥感数据中的可见光、热红外和植被指数(NDVI)数据,建立了相应的BP神经网络的土地荒漠化信息的自动提取模型.实验应用表明,基于人工神经网络方法提取土地荒漠化发生的地点和范围等信息,其精度可达到84%.因此,应用人工神经网络方法提取土地荒漠化信息是切实可行的,并具有可推广价值. 相似文献
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为实现多光谱数据对煤矿区水体信息提取，以萍乡市芦新岭及周边煤矿为试验区，在国内外学者对水体指数法提取水体信息和应用的启发下，对试验区不同地物的波谱特征进行分析。本文首先利用数学统计方法建立一种ASTER数据综合归一化差异水体指数模型SWI ASTERxy，然后利用这一模型对试验区进行水体信息提取。试验表明，该模型能够有效地提取矿区各类水体，还可以运用在ASTER数据（或其他多光谱数据）对不同区域不同地物的提取，在遥感地物定量提取上具有很好的效果和潜力，具有一定的推广价值。 相似文献
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高光谱遥感图像光谱分辨率高、波谱连续、图谱合一,这为精细地物分类、探测和识别提供了数据基础。然而,由于高光谱遥感图像空间分辨率的局限性及地物场景的复杂分布,混合像元普遍存在于高光谱遥感图像。混合像元是高光谱遥感图像精细信息提取与分析中的难点。解决混合像元问题,实现亚像元级信息的提取与分析是近年来高光谱遥感图像解译的热点和前沿。本文系统梳理了高光谱遥感图像亚像元信息提取的主要研究内容,具体从混合像元分解、亚像元制图及亚像元目标探测3个研究方向综述了经典方法,并对国内外相关方向的研究进展、发展前沿及主要挑战进行了分析与评价,最后分析讨论了高光谱遥感图像亚像元信息提取研究在模型构建、优化求解及与应用结合等方面的研究趋势及方向。 相似文献
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金矿遥感探测之关键在于成矿构造及铁氧化物、含羟基蚀变矿物的信息提取。ＪＥＲＳ—１ＳＡＲ在构造探测方面具有很大的优势，可通过噪斑消除及边缘增强的空间滤波来提取构造信息。ＬａｎｄｓａｔＴＭ可通过主成分变换，比值分析－主成分变换来提取蚀变矿物波谱信息、抑制植被波谱干扰。这两种遥感数据的复合处理可综合蚀变与构造信息。 相似文献
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为从微观到宏观了解、掌握和运用围岩蚀变的特征与原岩特征,寻找大型矿床或大型矿集区,在总结常用遥感蚀变信息提取模型的基础上,结合主成分分析(PCA)和支持向量机(SVM)算法,建立了基于“掩模处理-主成分分析-支持向量机( MASK - PCA - SVM,MPs)”的遥感蚀变信息提取模型.在新疆哈图地区进行的基于ETM+的不同蚀变信息提取模型应用对比研究表明,使用常用模型提取出的蚀变信息和矿点吻合效果较差,而基于MPS模型提取出的蚀变信息与已知矿点的吻合率可达86.51％;结合地质专家知识、地质图和一个已知异常点的分析结果表明,基于MPS模型的蚀变信息提取精度较高,在研究区地质应用中效果较好,为今后该区的遥感蚀变信息提取工作提供了一种新思路. 相似文献
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林地信息提取与精度评价空间抽样方法研究 总被引：2，自引：0，他引：2
正林地是自然资源的重要组成部分,在减缓全球气候变化、维护生态平衡、改善生态环境等方面发挥着重要作用。遥感数据能够在不同尺度范围内开展林地资源的信息探测、目标识别和调查评估等。针对当前林地资源遥感制图的新需求,本文以北京市为例,综合利用MODIS、Landsat TM及各类遥感数据产品,开展了林地信息提取与精度评价空间抽样方法研究,采用林地遥感信息提取方法和遥感分类精度评价的采样点空间布局优化方法, 相似文献
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利用数字化的NOAA AVHRR数据进行小比例尺、准同步宏观制图是一种低成本和快速的制图方法。笔者应用本文方法制作了第一幅小比例尺的、完整的中国假彩色卫星影象地图。它包含了全部的南中国海,这是使用其他的遥感数据(如陆地卫星或SPOT卫星)难以做到的。该图采用了热红外、近红外和可见光的红波段所构成的假彩色合成方案,提供了丰富的色彩和影象信息。本图制作时实施的数据处理内容包括:地图投影变换、影象反差增强和锐化、彩色平衡调整、去云处理和海陆分离处理、利用植被指数原理的影象时相修正和数字镶嵌操作等。根据影象地图的载负量和视觉效果,图上精心选取并设计了地理要素、地图符号和注记。该图是应用遥感新技术开发的地图新产品,被十七届国际摄影测量与遥感会议选为展示成果,并被该会评为获奖成果。 相似文献
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应用NOAA/AVHRR数据测算局地水稻种植面积方法研究 总被引：29，自引：3，他引：29
本文采用在模糊监督分类中增加迭代过程的方法－－模糊监督分类一迭代法,在分解混合像元的基础上,利用ＡＶＨＲＲ数据求算水稻种植面积。根据稻田与旱地存在温度差异的特点,在分析ＡＶＨＲＲ数据统计特征的基础上,增加了第３和４两通道参加模糊监督分类,从而增加了分类橡元值矢量维数,增强了对水稻的鉴别能力。反采用的迭代法是收敛具有效的,经本方法输出的水稻种植面积百分含量图与实际水稻分布十分吻合,测算出的面积值与Ｔ 相似文献
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Jie Cheng Shunlin Liang Aixiu Nie Qiang Liu 《Journal of the Indian Society of Remote Sensing》2018,46(4):591-596
For a satellite sensor with only one or two thermal infrared channels, it is difficult to retrieve the surface emissivity from the received emissive signal. Empirical linear relationship between surface emissivity and red reflectance are already established for deriving emissivity, but the inner physical mechanism remains unclear. The optical constants of various minerals that cover the spectral range from 0.44 to 13.5 μm in conjunction with modern radiative transfer models were used to produce corresponding surface reflectance and emissivity spectra. Compared to the commonly used empirical linear relationship, a more accurate multiple linear relationship between Landsat TM5 emissivity and optical reflectances was derived using the simulated data, which indicated the necessity of replacing the empirical relationship with the new one for improving surface emissivity estimate in the single channel algorithm. The significant multiple linear relationship between broadband emissivity (BBE, 8–13.5 μm) and MODIS spectral albedos was also derived using the same data. This paper demonstrates that there is a physical linkage between surface emissive and reflective variables, and provides a theoretical perspective on estimating surface emissivity for sensors with only one or two thermal infrared channels. 相似文献
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Jeffrey M. Robel 《国际地球制图》2013,28(2):60-64
The Satellite Data Services Division (SDSD) maintains a digital browse file of Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR instrument is aboard the TIROS‐N series of spacecraft. The instrument has five channels for viewing the earth, two channels are in the visible part of the spectrum and three are in the infrared portion of the spectrum. Selected data from this instrument are converted to digital browse files and loaded on the Image Library and Browse System (1LABS). The ILABS allows SDSD personnel to review data before the digital tapes are sent to satisfy the user's order. It also allows hardcopy images be sent to users. Working in conjunction with the ILABS is the Electronic Catalog System (ECS). The ECS is able to be directly accessed by the user community and it allows the users to find data in their areas of interest. Once the data are found, then that data can be ordered from the SDSD. 相似文献
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用NOAA-AVHRR热通道数据演算地表温度的劈窗算法 总被引：50，自引：9，他引：50
气象卫星NOAA-AVHRR有两个热通道用来监测地球表面温度。劈窗算法是用这两个热通道数据演算地表温度的最常用方法。近10年来,国际遥感界已经提出了10多种劈窗算法。本文主要介绍这些劈窗算法,并比较它们的演算精度,重点放在这些算法的具体计算方面,以便有关同行在需要计算地表温度时有选择地应用. 相似文献
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《International Journal of Digital Earth》2013,6(10):784-804
Sea surface temperature (SST) retrieved from Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) polar orbiting environmental satellites were validated in the East/Japan Sea (EJS) using surface drifter measurements as ground truths from 2005 to 2010. Overall, the root-mean-square (rms) errors of multichannel SSTs (MCSSTs) and non-linear SSTs (NLSSTs) using global SST coefficients were approximately 0.85°C and 0.80°C, respectively. An analysis of the SST errors (satellite – drifter) revealed a dependence on the amount of atmospheric moisture. In addition, satellite-derived SSTs tended to be related to wind speeds, particularly during the night. The SST errors also demonstrated diurnal variations with relatively higher rms from 0.80°C to 1.00°C during the night than the day, with a small rms of about 0.50°C. Bias also exhibited reasonable diurnal differences, showing small biases during the daytime. Although a satellite zenith angle has been considered in the global SST coefficients, its effect on the SST errors still remained in case of the EJS. Given the diverse use of SST data, the continuous validation and understanding of the characteristic errors of satellite SSTs should be conducted based on extensive in-situ temperature measurements in the global ocean as well as local seas. 相似文献
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The most important advantage of the low resolution National Oceanic and Atmospheric Administration’s Advanced Very High Resolution
Radiometer (NOAA AVHRR) data is its high temporal frequency and high radiometric sensitivity which helps in vegetation detection
in the visible and near-infrared spectral regions. In areas where most of the crop cultivation is in large contiguous areas,
and if the AVHRR data are selected for time period such that the crop of interest is well discriminated from other crops,
these data can be used for monitoring vegetative growth and condition very effectively. The present study deals with the application
of AVHRR data for the monitoring of the wheat crop in its seventeen main growing districts of the Rajasthan state. The fourteen
date AVHRR data covering the entire growth period have been used to generate the normalized difference vegetation index (NDV1)
growth profile for the crop by masking the non-crop pixels following the two-date NDVI change method. The growth profile parameters
and other derived parameters, such as post-anthesis senescence rate and areas under the entire growth profile or under selected
growth periods have been related to the district average wheat yield through statistical regression models. Various methods
adopted for wheat pixels masking have been critically evaluated. It is found that the wheat yield can be predicted well by
the area under the profile in different growth periods. 相似文献
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The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which results in low calculation precision of parameters related with land surface temperature. A new fusion method is put forward where the characteristics of the high spatial resolution of VNIR (visible and near infrared) data and the high temporal resolution of thermal infrared data are fully explored in this paper. Non-linear fusion is implemented to obtain the land surface temperature in high spatial resolution and the high temporal resolution between the land surface parameters estimated from VNIR data and the thermal infrared data by means of GA-SOFM (genetic algorithms & self-organizing feature maps)-ANN (artificial neural network). Finally, the method is verified by ASTER satellite data. The result shows that the method is simple and convenient and can rapidly capture land surface temperature distribution of higher resolution with high precision. 相似文献