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本文利用多时相Landsat TM/ETM+影像分析了兖州市1998年和2002年的土地利用/覆盖变化。综合考虑波段间相关系数和OIF指数,选择最佳波段组合进行图像解译,并在此基础上运用最大似然分类器(MLC)和支持向量机(SVM)的分类方法对遥感影像进行分类。进而利用SVM分类结果进行土地利用遥感动态监测,获取兖州市土地利用/覆盖变化信息,并与社会经济统计资料的统计结果进行比较。最后提取TM/ETM+影像的RDVI,基于线性混合像元分解模型分析了植被覆盖的变化。结果表明,基于多时相TM/ETM+影像分析的土地利用/覆盖变化与实际统计数据较吻合,适合动态监测土地利用变化,且精度较高。 相似文献
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针对目前遥感水系提取存在的问题,提出了一种基于数学形态学的遥感影像水系提取方法。该方法在光谱模式识别提取水体信息的基础上,利用数学形态学方法将提取的水体结果进行断线连接、去噪及细化等处理,从而得到连续的水系。以Landsat ETM+影像为例进行了实验,结果表明,该方法可以提取连续、完整的水系;且提取的水系精度与现势性均优于国家测绘局发布的1∶25万数字线划图(DLG)水系。 相似文献
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基于新型水体指数(NWI)进行水体信息提取的实验研究 总被引：6，自引：0，他引：6
基于遥感数据构建的水体指数模型可用于水体信息的提取。本文在对水体及其背景地物进行光谱特征分析的基础上,结合水体在近红外和中红外波段(相当于Landsat TM/ETM+影像的Band 4,Band 5和Band 7)同时具有强吸收这一典型特征,提出了一种新型的水体指数NW I(New W ater Index)。将该指数在含不同水体类型的遥感影像上进行实验,均获得了较好的提取效果。利用文献样本数据所作的实验表明,NW I具有很强的普适性,可用于水体信息的快速提取,且具有较高的精度。 相似文献
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赣榆县作为东部沿海城市城镇化发展尤为突出。本文选取1987年、2000年和2009年3期Landsat TM/ETM遥感影像作为主要数据源,利用ArcGIS软件数字化功能对城镇建成区进行提取,并将3期提取结果进行叠加分析,通过城镇扩展面积比重、城镇扩展指数、城镇用地扩展强度指数、城市紧凑度指数和城市用地分形维数模型对城镇扩展动态特征进行分析。 相似文献
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海岸带水体遥感信息全自动提取方法 总被引：1，自引：0，他引：1
在对经典的水体遥感信息提取方法分析的基础上,针对海岸带水体的特点了提出一种新的方法,该方法通过“像元-对象”及“全域-局部”的双重尺度转换,综合利用了海岸带水体遥感信息的光谱特征、空间特征、统计特征和不确定性,有机结合了地学知识与数据挖掘方法,实现了海岸带水体遥感信息的全自动提取。对我国四大海域不同类型海岸带的Landsat ETM+遥感影像进行试验,发现应用该方法能够兼顾宏观和微观的水体特征,提取结果具有较好的完整性和连续型,相对精度优于监督分类法和阈值分割法。 相似文献
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为研究环境一号(HJ-1)CCD影像在土地利用中的应用能力,选取HJ-1 A/B CCD和Landsat ETM+作为数据源,在遥感影像土地利用要素识别、土地利用计算机分类精度、土地利用信息提取二级分类精度和土地利用分类等方面,对HJ-1A/B CCD数据和Landsat ETM+数据在土地利用分类中的应用能力进行对比研究,结果表明土地利用分类应用中,HJ-1 A/B CCD基本可以替代Landsat ETM+,且HJ-1 A/B CCD数据光谱敏感性更强,反映地物细节的能力更强,比Landsat ETM+数据更有优势的结论。 相似文献
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提出了一种基于多点地统计学理论的遥感影像融合方法,旨在用多点地统计模拟提高融合后影像的空间分辨率。模拟从训练图像中提取包含空间相关性信息的模型,再通过基于模式的判别准则实现局部相似图案的重现。其中采用面-点协同克里格法为模拟提供制约条件,以解决不同数据支撑间的转换问题。实验用于Landsat ETM+影像的融合,结果表明,基于面-点协同克里格的多点地统计模拟方法与未考虑数据支撑差异的模拟相比较能达到更高的融合精度。该方法亦可用于其他类型空间数据的套合。 相似文献
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基于多源遥感数据的水体信息提取研究 总被引：1，自引：0，他引：1
卫星遥感技术已被广泛应用到水体信息提取中,但目前基于遥感技术的水体信息提取多采用单一的遥感数据源,而没有充分利用多源数据的信息复合优势,因此,提取结果经常受天气气候或空间分辨率限制。本文研究了不同尺度、不同平台的多种遥感数据源的水体信息提取方法。首先,基于波谱间关系决策树分类算法对Landsat ETM+图像进行水体提取,利用其分辨率优势较准确地提取出水体范围;其次,在Radarsat SAR图像上利用阈值法粗提取水体信息后,结合DEM剔除阴影得到水体信息;最后,利用灾前Landsat ETM+图像水体信息提取结果和灾中Radarsat SAR图像水体信息提取结果,进行差值处理,得到洪水淹没范围。研究结果可以为洪水灾害监测与评估提供信息依据。 相似文献
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采用遥感技术对矿区生态环境进行动态监测,对于人类健康和资源合理开发利用具有重要意义。本文以临沂苍峄矿区为研究区,采用多时相Landsat TM/ETM+/OLI遥感影像,运用单波段法、谱间关系法、水体指数法等多种方法提取水体信息。在此基础上提出一种新的水体变化信息提取流程,即运用RGB彩色合成法对不同时相影像进行合成,根据不同色调反映像元的不同变化趋势,发现并提取变化信息,实现了矿区水体信息的变化监测。 相似文献
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Cyanobacterial bloom is a growing environmental problem in inland waters. In this study, we propose a method for monitoring levels of cyanobacterial blooms from Landsat/ETM+ images. The visual cyanobacteria index (VCI) is a simple index for in-situ visual interpretation of cyanobacterial blooms levels, by classifying them into six categories based on aggregation (e.g., subsurface blooms, surface scum). The floating algae index (FAI) and remote sensing reflectance in the red wavelength domain, which can be obtained from Landsat/ETM+ images, were related to the VCI for estimating cyanobacteria bloom levels from the Landsat/ETM+ images. Nine field campaigns were carried out at Lakes Nishiura and Kitaura (Lake Kasumigaura group), Japan, from June to August 2012. We also collected reflectance spectra at 20 stations for different VCI levels on August 3, 2012. The reflectance spectra were recalculated in correspondence to each ETM+ band, and used to calculate the FAI. The FAI values were then used to determine thresholds for classifying cyanobacterial blooms into different VCI levels. These FAI thresholds were validated using three Landsat/ETM+ images. Results showed that FAI values differed significantly at the respective VCI levels except between levels 1 and 2 (subsurface blooms) and levels 5 and 6 (surface scum and hyperscum). This indicated that the FAI was able to detect the high level of cyanobacteria that forms surface scum. In contrast, the Landsat/ETM+ band 3 reflectance could be used as an alternative index for distinguishing surface scum and hyperscum. Application of the thresholds for VCI classifications to three Landsat/ETM+ images showed that the volume of cyanobacterial blooms can be effectively classified into the six VCI levels. 相似文献
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北京市农村居民点用地的遥感动态监测及驱动力分析 总被引：1，自引：0，他引：1
基于遥感与GIS技术,利用多源遥感数据(陆地卫星MSS、TM或ETM+影像,"北京一号"小卫星数据)提取北京市农村居民点用地.结合DEM数据对北京市农村居民点用地的现状及区位意义进行分析,将北京市重新分区.分3个时间段(1978年9月～1995年4月、1995年5月～2000年3月、2000年4月～2005年11月)对改革开放以来的北京农村居民点用地进行动态监测.引人多项指标对北京全市及各区、县的农村居民点用地进行时空变化特征与景观特征分析.选取14项社会、经济指标,利用主成分分析法定量分析影响北京市农村居民点用地变化的驱动力,对于农村的合理规划具有导向作用. 相似文献
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Forest cover plays a key role in climate change by influencing the carbon stocks, the hydrological cycle and the energy balance. Forest cover information can be determined from fine-resolution data, such as Landsat Enhanced Thematic Mapper Plus (ETM+). However, forest cover classification with fine-resolution data usually uses only one temporal data because successive data acquirement is difficult. It may achieve mis-classification result without involving vegetation growth information, because different vegetation types may have the similar spectral features in the fine-resolution data. To overcome these issues, a forest cover classification method using Landsat ETM+ data appending with time series Moderate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data was proposed. The objective was to investigate the potential of temporal features extracted from coarse-resolution time series vegetation index data on improving the forest cover classification accuracy using fine-resolution remote sensing data. This method firstly fused Landsat ETM+ NDVI and MODIS NDVI data to obtain time series fine-resolution NDVI data, and then the temporal features were extracted from the fused NDVI data. Finally, temporal features combined with Landsat ETM+ spectral data was used to improve forest cover classification accuracy using supervised classifier. The study in North China region confirmed that time series NDVI features had significant effects on improving forest cover classification accuracy of fine resolution remote sensing data. The NDVI features extracted from time series fused NDVI data could improve the overall classification accuracy approximately 5% from 88.99% to 93.88% compared to only using single Landsat ETM+ data. 相似文献
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城市扩展强度及其地表热特性遥感定量分析 总被引：1，自引：0，他引：1
提出定量确定城市扩展范围及其发展强度的方法——地图密度指数。以中部城市长沙为例,利用Landsat TM/ETM+数据定量评价城市扩张及其热环境特征的变化。首先,集成遥感光谱指数提取地表非渗透表面,然后利用移动窗口算法获得地图密度指数,再根据设定的阈值获得密度指数等级图,依此密度指数等级图识别城市扩展范围及其发展强度。再结合地表温度反演的数据,分析城市格局及其变化与地表热特性变化的定量关系。结果表明,自20世纪90年代以来,长沙市城市区域及其发展密度显著增加,城市发展的密度差异与地表温度相一致。地图密度指数能较好刻画城市扩展范围及其发展强度,并与地表温度空间分布存在较好的对应关系。 相似文献
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J. Norton N. Glenn M. Germino K. Weber S. Seefeldt 《International Journal of Applied Earth Observation and Geoinformation》2009,11(5):360-367
Remote sensing indices of burn area and fire severity have been developed and tested for forest ecosystems, but not sparsely vegetated, desert shrub-steppe in which large wildfires are a common occurrence and a major issue for land management. We compared the performance of remote sensing indices for detecting burn area and fire severity with extensive ground-based cover assessments made before and after the prescribed burning of a 3 km2 shrub-steppe area. The remote sensing indices were based on either Landsat 7 ETM+ or SPOT 5 data, using either single or multiple dates of imagery. The indices delineating burned versus unburned areas had better overall, User, and Producer's accuracies than indices delineating levels of fire severity. The Soil Adjusted Vegetation Index (SAVI) calculated from SPOT had the greatest overall accuracy (100%) in delineating burned versus unburned areas. The relative differenced Normalized Burn Ratio (RdNBR) using Landsat ETM+ provided the highest accuracies (73% overall accuracy) for delineating fire severity. Though SPOT's spatial resolution likely conferred advantages for determining burn boundaries, the higher spectral resolution (particularly band 7, 2.21 μm) of Landsat ETM+ may be necessary for detecting differences in fire severity in sparsely vegetated shrub-steppe. 相似文献
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遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文) 总被引：2，自引：0，他引：2
In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global
environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map,
and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250
000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery
into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised
classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy
assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify
and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area
had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km2 in 1990 to 3 794.9 km2 in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover
changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the
countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military
camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used
to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time.
Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China). 相似文献
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通过对研究区2001年10月和2007年1月Lnadsat TM/ETM+的遥感影像进行光谱特征分析,利用归一化差异水体指数(NDWI)、阈值法和谱间关系法提取研究区面状水体形态信息,在此基础上,利用分形几何理论计算不同时相巢湖流域研究区影像的各小流域面状水体的分形维数.结果表明,巢湖流域研究区各小流域面状水体明显具有分形特征,2007年各小流域面状水体的分维值相应都比2001年各小流域面状水体分维值有所降低.说明整个流域的面状水体的稳定性增大.反映了研究区人类工农业生产活动开始注重与周围地理环境的和谐发展. 相似文献