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61.
Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.  相似文献   
62.
The volume of properties affected by foreclosure over the past decade suggests the potential for dramatic change in vegetation cover due to changes in management. Yet, the specific pathology of each foreclosure, the temporal asynchrony among foreclosures, and differences in the area available for vegetation growth across properties presents challenges to observing and measuring change. This paper develops and tests a difference in deviations approach that compares the parcel NDVI to a neighborhood norm before and after foreclosure. The difference in deviations approach addresses the challenges of separating parcel-level change corresponding to foreclosure and identifies changes on both small and large parcels. The method relies on a time series of Landsat Normalized Difference Vegetation Index (NDVI) data, individual home foreclosure records and property tax assessment data for Maricopa County, Arizona from 2002 to 2012. To establish the level of difference associated with observable landscape change, we use a probit regression model, coding Google Earth images for properties across the range of observed deviations of difference. The basic assumption underlying the approach is that if foreclosure coincides with a change in management, it will lead to changes in vegetation structure and thus, NDVI values. We estimate that 13% of home foreclosures in Maricopa County over the period from 2002 to 2012 resulted in declines in vegetation whereas 6.5% resulted in vegetation increases. Future uses of this method for understanding landscape management in residential landscapes are discussed.  相似文献   
63.
李瑶  潘竟虎 《干旱区地理》2015,38(1):111-119
在ENVI和GIS支持下,提出了基于Landsat 8遥感影像的地温反演劈窗算法,提取兰州市中心城区地表温度。利用FNEA和混合光谱分解法确定了兰州市中心城区的城市热岛中心、不透水面和植被盖度,分析了城市热岛空间分布格局以及地表温度与下垫面之间的关系。结果显示:基于Landsat 8数据地温反演的劈窗算法是可行的。兰州中心城区的高温区分布较集中,地表温度与植被呈较强的负相关,与不透水面呈不显著的正相关,与其他非光合物质呈正相关。  相似文献   
64.
Mohsin Jamil Butt 《水文研究》2012,26(24):3689-3698
Estimation of snow cover characteristics (snow grain size, snow contamination, snow depth and liquid water content) from satellite data are important components for many hydrological models used for the water resource management. This research aimed to use Landsat ETM+ (Enhanced Thematic Mapper Plus) data to estimate the snow pack characteristics in northern Pakistan. The Normalized Difference Snow Index (NDSI), Snow Contamination Index (SCI) and Snow Grain Size Index (SGI) are applied to estimate the snow cover characteristics in northern Pakistan for the first time. Qualitative maps are generated to show the snow cover distribution, snow contamination concentration and snow grain size distribution over snow cover area. Our results show that NDSI, SCI and SGI can be effectively used to identify snow area, contaminated snow and ageing snow. Furthermore, the results of the current study indicate that in the HKH region 99.8% of the snow is least contaminated whereas 94.50% of the area has fine snow grain size. As no such attempt in the past has been made in northern Pakistan, it is envisaged that the results of this study will be helpful in planning remote sensing data for the water resource management and in characterizing the snow cover for the climate change applications in the region. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
65.
Tongyu County in Northeast China is highly prone to land degradation due to its fragile physical settings characterized by a flat topography, a semi-arid climate, and a shallow groundwater table. This study aims to determine the causes of land degradation through detecting the long-term trend of land cover changes. Degraded lands were mapped from satellite images recorded in 1992 and 2002. These land cover maps revealed that the area subject to land degradation in the form of soil salinization, waterlogging and desertification increased from 2400 to 4214 km2, in sharp contrast to most severely degraded land that decreased by 122.5 km2. Newly degraded land stems from productive farmland (263 km2), harvested farmland (551 km2), and grassland (468 km2). Therefore, the worsened degradation situation is attributed to excessive reclamation of grassland for farming, over cultivation, overgrazing, and deforestation. Mechanical, biological, ecological and engineering means should be adopted to rehabilitate the degraded land.  相似文献   
66.
The influence of illumination effects on the optimality of the dNBR (differenced Normalized Burn Ratio) was evaluated for the case of the 2007 Peloponnese (Greece) wildfires using a pre/post-fire Landsat TM (Thematic Mapper) image couple. Well-illuminated pixels (south and south-east facing slopes) exhibited more optimal displacements in the bi-spectral feature space than more shaded pixels (north and north-west exposed slopes). Moreover, pixels experiencing a small image-to-image difference in illumination obtained a higher optimality than pixels with a relatively large difference in illumination. To correct for illumination effects, the c-correction method and a modified c-correction technique were applied. The resulting median dNBR optimality of uncorrected, c-corrected and modified c-correction data was respectively 0.58, 0.60 and 0.71 (differences significant for p < 0.001). The original c-correction method improved the optimality of badly illuminated pixels while deteriorating the optimality of well-illuminated pixels. In contrast, the modified c-correction technique improved the optimality of all the pixels while retaining the prime characteristic of topographic correction techniques, i.e. detrending the illumination–reflectance relationship. For a minority of the data, for shaded pixels and/or pixels with a high image-to-image difference in illumination, the original c-correction outperformed the modified c-correction technique. In this study conducted in rugged terrain and with a bi-temporal image acquisition scheme that deviated up to two months from the ideal anniversary date scheme the modified c-correction technique resulted in a more reliable change detection.  相似文献   
67.
68.
Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised classification approaches. This article used a fast clustering method—Clustering by Eigen Space Transformation(CBEST) to produce a land cover map for China. Firstly, 508 Landsat TM scenes were collected and processed. Then, TM images were clustered by combining CBEST and K-means in each pre-defined ecological zone(50 in total for China). Finally, the obtained clusters were visually interpreted as land cover types to complete a land cover map. Accuracy evaluation using 2159 test samples indicates an overall accuracy of 71.7% and a Kappa coefficient of 0.64. Comparisons with two global land cover products(i.e., Finer Resolution Observation and Monitoring of Global Land Cover(FROM-GLC) and GlobCover 2009) also indicate that our land cover result using CBEST is superior in both land cover area estimation and visual effect for different land cover types.  相似文献   
69.
近40 a来天山台兰河流域冰川资源变化分析   总被引:1,自引:1,他引:0  
台兰河流域作为阿克苏河的支流,是以冰川融水补给为主的河流,流域面积为1 324 km2。结合1:5万地形图、Landsat ETM+遥感影像及数字高程模型数据,通过综合计算机自动解译及目视解译的方法,将面向对象图像特征提取方法应用到该流域冰川信息提取中,并以影像叠加数字高程模型来提取表碛覆盖区的冰川末端边界,最后参照专家指导意见进行边界的再次修订,得到1972~2011年该流域的冰川变化数据,并分析了过去近40 a来冰川变化特征及其对气候变化的响应过程。结果表明:1972~2011年,台兰河流域冰川退缩明显,冰川总面积从435.44 km2退缩到385.38 km2,减少了50.06 km2,退缩率为11.50%,年均减少约1.25 km2,平均单条冰川面积减小0.31 km2;冰川总条数从113条减少到109条,消失冰川10条,有3条冰川分离成了9条,其余100条冰川都呈减小趋势。结合阿克苏和拜城气象站气象资料分析认为,台兰河流域冰川萎缩与该地区气温快速上升关系密切,气温上升导致的冰川消融在一定程度上抵消了降水增加对冰川的补给。  相似文献   
70.
基于TM遥感数据的汶川地震极重灾区生态恢复研究   总被引:1,自引:0,他引:1  
本文以地震极重灾区2006、2008和2011年3期Landsat TM遥感影像为数据源,利用GIS提取灾区土地利用信息,结合坡度和高程等地形因子对灾区主要生态系统面积的变化进行综合分析.结果表明:2008年地震对灾区生态环境造成严重破坏,使研究区农田、森林和草地生态系统分别减少了124.6km2、461.6km2和9...  相似文献   
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