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Remote sensing has been widely used to map geological structure, regolith materials and hydrothermal alteration minerals in different regions of the world, based largely on the spectral characteristics of clay/carbonate and iron oxide minerals. Given that features related to minerals may form very subtle patterns in Landsat imagery, finding suitable methods for enhancing the spectral information due to alteration minerals has been the subject of much research since the satellites were launched. Although multispectral sensors such as Landsat do not have enough spectral resolution to distinguish between specific minerals, effective processing of the data does yield useful images for regional exploration and targeting when combined with a good understanding of the associated landforms. ASTER and various airborne systems can now provide useful, high-resolution mineral information. However, the cost and time taken to acquire and process good resolution spectral data should now be balanced against the enhanced spectral discrimination possible using temporal merging, or data stacking, from the existing Landsat data archive dating back to 1972. One critical characteristic of the spectra related to surface mineral composition is its persistence over time. This study proposes a further enhancement to the data using temporal merging to create images that are both easier to interpret, and more reliable indicators of lithology and alteration. The new approach is to select a large number of scenes, typically separated by two or more years, and to merge the data for each band to give a cumulative spectral signature. The technique of stacking Landsat data to create a new dataset with much greater spectral depth is termed Landsat TM3, or Landsat TM Temporal Merge for Terrain Mapping. This emphasises not only the process used to create the dataset, but also the dominant use to which these data are ideally suited, namely mapping geological and mineral-related terrains. 相似文献
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遥感大数据分析与应用正成为地球信息科学领域重要的研究内容。利用热红外遥感技术进行地热异常信息的提取可以为地热资源勘查评价提供重要的依据。Landsat系列卫星数据拥有长时间的数据积累和较高的空间分辨率,是地表热环境时空序列大数据分析的重要数据。最新一代的Landsat8 卫星热红外数据在延续了较高分辨率的同时,敏感性更强,更加适合于对地表热环境空间分布进行精确分析。本文以安徽黄山汤口-寨西工作区为研究区,分别选用2016年12月9日Landsat8 的热红外遥感数据和2009年12月6日Landsat5 TM 数据,采用大气校正方法进行地表温度的反演和对比分析,通过密度分割分析提取地热异常信息,并综合遥感地质解译信息、气象、地形等数据,对工作区地热资源有利区进行了预测。结果表明：两个时相地表温度反演结果的空间分布基本一致,利用Landsat8 热红外数据的地表温度反演结果可以有效地获取地热异常信息,所圈定的地热异常较为合理,与工作区内主要的断裂构造分布一致,且和物探勘查和钻孔实验结果相对应,可以为地热资源勘查大数据分析提供重要的数据源。 相似文献
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能源的全球性短缺以及全球环境问题的日益加剧,使得绿色新能源的研究与开发成为当今世界许多国家的一项重要任务。地热资源作为其中一员其重要性日益凸显。在地热资源的勘查中,传统的地质和地球物理勘探投入高、难度大,而遥感技术具有经济、高效、覆盖范围广等优势,已逐渐成为地热资源探测与调查的一种新技术手段。地热能开发的首选地区往往是新生代火山活动区,因其在相对较小的深度内就能获得很高的温度。本文综述了国内外利用遥感技术探测火山地热的发展历史和研究现状,介绍了这项技术在美国黄石公园、日本阿苏火山以及我国长白山火山和腾冲火山的应用。同时选取内蒙古锡林郭勒盟新生代火山活动构造区作为实例,利用美国NASA陆地卫星Landsat-7 ETM+第6波段的红外遥感数据反演了研究区的地表温度,结合ETM+7-4-1波段组合影像的地质构造解译结果以及其它相关资料对研究区地表温度分布进行了分析。结果表明,区内红外遥感地表温度异常区多位于北东东与北西向构造的交汇处或与环形构造密切相关。本文圈定了7个地表温度异常区作为这一地区下一步地热资源勘查的远景区。 相似文献
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传统的城市温度监测方法周期长、效率低,而利用热红外遥感影像进行城区温度监测的方法具有准确、简便、实用等优点。基于Landsat TM、ETM+、OLI遥感影像数据,应用辐射传输方程法对北京城区（东城区、西城区、宣武区、崇文区、朝阳区、海淀区和丰台区7个区域）2000—2014年夏季地表温度的空间分布和时间变化进行分析及温度反演,结果显示,高温区分布有一定的规律,降雨情况、植被覆盖度的变化以及城区规划都是北京城区温度变化的重要影响因素。研究结果可为减缓北京的热岛效应提供依据。 相似文献
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河川径流遥感监测研究进展 总被引：5，自引：0，他引：5
河川径流参数是用于地表水资源评估、全球变化监测和生态环境保护的基础数据.现有的河川径流监测数据基于水文监测站点获取.近年来,受经济和政治原因的影响,全球水文监测站点在逐渐减少.随着全球变化研究对区域乃至全球水文监测数据需求的增加,监测站点有限及监测数据格式多样等问题逐渐凸显.过去15年,卫星遥感技术在河川径流监测领域的研究和应用实践,使上述问题的解决成为了可能.总结了河川径流遥感监测方法和技术研究进展,包括地基高低频雷达、航空航天雷达和多光谱卫星遥感监测3个方面;介绍了全球大型河川径流与湖泊水体动态监测重大应用成果及未来研究计划.指出在未来具有全天时、全天候,高时空分辨率,以及多水文要素探测能力遥感卫星发射之前,应充分利用遥感野外观测实验,完善河川径流监测技术方法,并综合应用已有高时空分辨率的多光谱和微波遥感数据,开展径流监测应用研究. 相似文献
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基于长时间序列遥感数据的鄱阳湖水面面积监测分析 总被引：1，自引：0，他引：1
国产高分辨率卫星的快速发展可有效弥补遥感湖泊监测中影像分辨率不足的问题,更加及时、准确地实现湖泊动态监测。利用1996～2012年155景Landsat影像和2013～2016年34景GF影像为数据源,结合湖口站水位监测数据,分别选用改进的归一化差异水体指数MNDWI和归一化差异水体指数NDWI方法提取卫星遥感影像的水体信息,同时采用统计分析的方法建立了4个时间段的鄱阳湖水体面积-水位关系模型。结果表明:在空间上,鄱阳湖水体面积整体呈现缓慢缩小的趋势;在时间上,除秋季鄱阳湖面积有明显下降趋势外,其他季节整体趋势变化不大;经验证,鄱阳湖四季水体面积-水位呈现二次函数关系。 相似文献
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遥感变化检测技术发展综述 总被引：32，自引：2，他引：32
卫星遥感的复轨能力，稳定一致的传感器参数和系列运行计划，连续记录了地表的显著变化信息。对遥感观测到的变化信息，还需要区分是地表物理生物要素变化引起的变化，还是辐射传输路径上其它干扰因素造成的变化信息，需要从各种变化信息组分中区分目标变化信息。因此，遥感变化检测是遥感信息科学、地球系统科学、统计学和计算机技术等学科技术交叉后新的增长点，代表了当前遥感数据处理技术发展方向。为了促进遥感变化检测技术在我国的发展，收集阅读了近几年国外主要遥感刊物发表的论文、专著，综合了我国遥感变化检测技术发展现状以及大量的网络资料。 相似文献
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ZHAO Yingjun LIU Dechang Beijing Research Institute of Uranium Geology Beijing 《《地质学报》英文版》2000,74(2):381-383
This paper introduces how to use remote sensing images including Landsat (MSS and TM) andairborne radioactivity images to identify the type of rocks in the areas covered by vegetation. The relationship between light spectrum (Landsat MSS and TM) and energy spectrum (U, Th and K) is discussed on the basis of correlation analysis, and it is proven that there are correlations between the Landsat MSS or TM data and the U, Th and K. data. By using the fusion technique, new images were generated, which contain both the light spectrum and the energy spectrum information.Taking the Lucong basin as the study area, the present paper demonstrates the successful identification of various types of rocks using the fusion technique. Different types of rocks are represented by different colours on the new light-energy spectrum images, so that volcanic rocks of the Jurassic and Cretaceous periods can be discriminated. Another example, in the Lingquan basin in Northeast China, not only the different types of rocks are su 相似文献
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Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island,Malaysia 总被引：3，自引：1，他引：2
Kok Chooi Tan Hwee San Lim Mohd Zubir MatJafri Khiruddin Abdullah 《Environmental Earth Sciences》2010,60(7):1509-1521
Land surface temperature (LST) plays an important role in local, regional and global climate studies. LST controls the distribution
of the budget for radiation heat between the atmosphere and the earth’s surface. Therefore, it is important to evaluate abrupt
changes in land use/land cover (LULC). Penang Island, Malaysia has been experiencing a rapid and drastic change in urban expansion
over the past two decades due to growth in industrial and residential areas. The aim of this study was to investigate and
evaluate the impact of LST with respect to land use changes in Penang Island, Malaysia. Three supervised classification techniques
known as maximum likelihood, minimum distance-to-mean and parallelepiped were applied to the images to extract thematic information
from the acquired scene by using PCI Geomatica 10.1 image processing software. These remote sensing classification techniques
help to examine land-use changes in Penang Island using multi-temporal Landsat data for the period of 1999–2007. Training
sites were selected within each scene and seven land cover classes were assigned to each classifier. The relative performance
of each technique was evaluated. The accuracy of each classification map was assessed using a reference data set consisting
of a large number of samples collected per category. Two Landsat satellite images captured in 1999 and 2007 were chosen to
classify the LULC types using the maximum likelihood classification method, determined from visible and near-infrared bands.
The study revealed that the maximum likelihood classifier produced superior results and achieved a high degree of accuracy.
The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC. The results showed that
the urban (highly built-up) area increased dramatically, and grassland area increased moderately. Inversely, barren land decreased
obviously, and forest area decreased moderately. While urban (minimally built-up) area decreased slightly. These changes in
LULC caused at significant difference in LST between urban and rural areas. Strong correlation values were observed between
LST and NDVI for all LULC classes. The remote sensing technique used in this study was found to be efficient; it reduced the
time for the analysis of the urban expansion, and it was found to be a useful tool to evaluate the impact of urbanisation
with LST. 相似文献
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The continuous improvement of the launched satellites’ spatial and spectral resolutions has brought new challenges for remote sensing image segmentation technology. The traditional supervised methods greatly depend on artificial interpretation and reduce the degree of automation and robustness of image segmentation. Therefore, the article proposes a novel unsupervised multi-scale segmentation method for high-resolution remote sensing images based on automated parameterization and it mainly includes three steps, adaptive selection of scale parameter (SP) based on local area homogeneity index J-value, multi-scale segmentation based on the inter-scales boundaries constraint strategy, and region merging based on multi-features. The article makes experiments by multi-group high-resolution remote sensing images of different launched satellites and compares the proposed method with the well-known commercial software eCognition and a traditional supervised method. The results show that the proposed method can locate the object edges more accurately and extract the object outlines more completely, and needs no human intervention in segmentation process, so it can provide a generic and effective unsupervised solution for high-resolution remote sensing image segmentation. 相似文献
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The Cabo de Gata Níjar Natural Park in Spain presents certain unique characteristics which make it of great geological, ecological
and environmental interest. As a prior step to the environmental study of the park and the impact produced by the mining activities
carried out up until ten years ago, the mining and waste-tip areas were defined and a lithological discrimination carried
out. For this purpose, various remote-sensing techniques were employed to create high-resolution image documents on which
the geological and environmental mapping of the area would be based, with special attention being paid to the areas of former
mining activity because of its implications for the local environment. The merging of remote-sensing images with different
spatial/spectral resolutions has become a highly useful tool, due to their increasing availability. Such is the case of the
SPOT panchromatic and Landsat Thematic Mapper multispectral images, which are two of the most commonly used images in geological
and environmental studies based on remote sensing. Of the numerous techniques described for merging remote sensing image data,
this paper analyses those based on Intensity-Hue-Saturation, Principal Component Analysis, Spherical Coordinates, High-Pass
Filters and Colour Normalized transform, using SPOT panchromatic and Landsat TM data. The research goals were (1) to analyse
and compare some of the most commonly used methods; (2) to select the most appropriate method for a detailed geological-environmental
study, and (3) to apply the methodology to the Cabo de Gata-Níjar area, the site of one of the most distinctive natural parks
in the country.
Received: 29 November 1996 · Accepted: 29 July 1997 相似文献
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经过近50年的发展,海洋卫星遥感日益成熟,各种反演算法和数据集应运而生,大大推动了海洋水文过程的研究。围绕与海洋水文相关的重要物理参数,简要回顾了海面高度、海水深度、海表洋流及海水质量变化的卫星遥感反演基本原理、主要算法以及存在的难点和前沿性研究问题,介绍了应用遥感反演算法制成的全球海洋水文参数主要数据集,并结合目前存在的问题探讨了卫星遥感反演海洋水文参数的发展趋势及所面临的挑战。研究发现,运用多卫星、多通道、多模式的联合反演方法可以显著地提升人们监测海洋水文参数时空动态变化的能力,必将成为未来全球海洋水文遥感的主要研究方向之一。 相似文献
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Lineament extraction has long been performed through extensive field mapping. Recent advances in the field of remote sensing have made possible the availability of imageries from earth observation satellites with different Spatio-temporal resolutions, paving way for new automatic, semi-automatic, and manual techniques for the extraction of natural lineaments. The study focuses on the extraction of lineaments representing tectonic fault zones; the lineaments are extracted automatically and semi-automatically/manually. Results show that indirect information about the tectonic lineaments can be derived through automatic techniques whereas, the semi-automatic techniques are more effective to directly identify them. Detailed analyses of lineaments and landslides revealed that areas near lineaments, in general, experienced higher frequency of landslides. Moreover, it is also observed that lineaments are not the only factor that affects landslide density; other parameters like slope and lithology were also found to be the controlling factors in determining the spatial landslide distribution. Lastly, some recommendations have been made based on observations.
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