西藏冈底斯成矿带矿化蚀变提取与成矿分析——以尼玛县帮勒地区为例

冈底斯成矿带是我国极具找矿潜力的地带,但受自然条件限制,该地带矿产资源开发程度普遍偏低。选取冈底斯成矿带北部尼玛县帮勒地区为研究区,以Landsat-8OLI数据为主要信息源,采用主成分分析法提取研究区铁染和羟基矿化蚀变信息。在GIS平台上,将提取的蚀变信息结合研究区现有地质、化探、矿产等资料进行综合分析,依据成矿理论,圈定2个成矿远景区。经野外验证,文中获取的矿化蚀变信息分布状况与已知矿点和已探明蚀变带的空间一致性高。矿化蚀变带的探明能够为区域矿产资源开发与勘查提供帮助。     

高精度遥感影像的空间投影几何精校正

几何校正为影像预处理工作做了技术准备。其精度直接影响着后续工作的质量。目前,高精度遥感影像因其空间分辨率较高、数据产品格式复杂,在实际应用中对其进行几何精校正(包括正射校正)还存在许多问题。在地面控制点(Ground Control Point,GCP)分布不均或数量不足的情况下,运用空间投影加密控制点的方法,能有效解决此类问题。本文以Quick Bird遥感卫星影像为例,阐述了该方法的可行性。     

一种结合四元数与直方图的多光谱图像自适应边缘检测方法

针对图像自适应边缘检测的难点和传统多光谱遥感图像边缘检测方法的局限性,提出了一种结合四元数与直方图的自适应边缘检测方法。该方法在四元数空间,利用矢量旋转完成了多光谱图像的边缘检测,并通过直方图统计的方法获取自适应阈值,实现了边缘图像的检测。利用陆地多光谱遥感图像和水域多光谱遥感图像分别进行实验,验证了方法的有效性。     

一种基于输入向量机的高光谱影像分类算法

支持向量机分类方法存在惩罚系数需要交叉验证获取、训练时间较长、支持向量个数随着训练样本数量的变化而变化,以及稳定性和稀疏性较差等问题。针对这些问题,提出了一种基于输入向量机的高光谱影像分类算法。该算法在核逻辑回归模型的基础上,采用前向贪心算法选择训练样本中的输入向量来进行模型的训练,达到稀疏的目的,提高影像的分类精度和分类效率。通过PHI和OMIS两组高光谱影像分类实验,结果表明基于输入向量机分类算法具有稳定性好、稀疏性强的优点。     

Demographic and Economic Changes in Remote Australia

Varied distribution of resources, populations and Indigenous people result in significant socio-economic differences among statistical local areas (SLAs) in remote Australia. These differences indicate that the experience of change at the height of the resources boom will differ among SLAs in the region. Using hierarchical cluster analysis with Ward's minimum variance method, four socio-economic clusters were identified among the 197 SLAs in the region. The first was the most disadvantaged, with limited resources and human capital and the highest percentage of Indigenous people. The other three clusters improved in sequence, with the fourth having the most resources with the highest employment rate and income but least number of Indigenous people. Multivariate analysis of variance with main and interaction effects showed changes in demographics, industry structure, human capital and income over the period of investigation for the region as a whole and differences in the extent of these changes among the clusters. Policy interventions in the region are suggested for each group to match its specific needs.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

Crossing-over between land cover and land use: Exploring spatially varying relationships in two large US metropolitan areas

Difficulties in identifying actual uses of land space from remote sensing-based land cover products often result in lost opportunities to enhance the capacity of applied research on human settlements. In an attempt to address these difficulties, this study investigates how land cover and land use are interrelated with each other and what determines the relationship patterns by analyzing detailed land use and land cover data for two large US metropolitan areas – the five-county Los Angeles and six-county Chicago regions – where a broad spectrum of human settlements, ranging from urban cores to less-urbanized edges, coexist. The analysis shows that the land cover-land use relationship substantially varies not only across regions but across neighborhoods within each region. Through multivariate regression, it is also found that the intraregional variation is highly associated with the neighborhood's stage of urbanization, median housing age, and other development characteristics, suggesting that the relationship pattern can largely be shaped by the history and evolution of urban design/development.     

Spatiotemporal patterns of tropical deforestation and forest degradation in response to the operation of the Tucuruí hydroelectric dam in the Amazon basin

The planned construction of hundreds of hydroelectric dams in the Amazon basin has the potential to provide invaluable ‘clean’ energy resources for aiding in securing future regional energy needs and continued economic growth. These mega-structures, however, directly and indirectly interfere with natural ecosystem dynamics, and can cause noticeable tree loss. To improve our understanding of how hydroelectric dams affect the surrounding spatiotemporal patterns of forest disturbances, this case study integrated remote sensing spectral mixture analysis, GIS proximity analysis and statistical hypothesis testing to extract and evaluate spatially-explicit patterns of deforestation (clearing of entire forest patch) and forest degradation (reduced tree density) in the 80,000 km² neighborhoods of the Brazil's Tucuruí Dam, the first large-scale hydroelectric project in the Amazon region, over a period of 25 years from 1988 to 2013. Results show that the average rates of deforestation were consistent during the first three time periods 1988–1995 (620 km² per year), 1995–2001 (591 km² per year), and 2001–2008 (660 km² per year). However, such rate dramatically fell to half of historical levels after 2008, possibly reflecting the 2008 global economic crisis and enforcement of the Brazilian Law of Environmental Crimes. The rate of forest degradation was relatively stable from 1988 to 2013 and, on average, was 17.8% of the rate of deforestation. Deforestation and forest degradation were found to follow similar spatial patterns across the dam neighborhoods, upstream reaches or downstream reaches at the distances of 5 km–80 km, suggesting that small and large-scale forest disturbances may have been influencing each other in the vicinity of the dam. We further found that the neighborhoods of the Tucuruí Dam and the upstream region experienced similar degrees of canopy loss. Such loss was mainly attributed to the fast expansion of the Tucuruí town, and the intensive logging activities alongside major roads in the upstream reservoir region. In contrast, a significantly lower level of forest disturbance was discovered in the downstream region.     

渭北台塬县级城市空间扩张的分形研究

基于RS与GIS技术,采用分形理论对渭北台塬县级城市空间扩张特征进行分析。结果表明:1990—2010年台塬区县级城市加速扩张,总面积扩大了2.86倍,年均增长率达8.7%。1990,2000,2010年县级城市空间形态分维值均值分别为1.08,1.09,1.21,变异系数分别为3.06,3.09,3.93,城市空间形态总体简单但渐趋复杂且不断分化。异速生长模型标度因子b值均小于1,人均城市空间较为合理但远未达到最优状态。1990—2000年城市以填充型扩张为主,2000—2010年以外延型扩张为主,用地集约性呈下降趋势。空间上,铜川塬、宝鸡塬扩张较快,人地关系较差;咸阳塬扩张最快,人地关系一般;渭南塬扩张相对较慢,人地关系较优。总体上,亟待加强城市规划以构建节约型城市空间增长模式。     

Evaluating the relationship between biomass,percent groundcover and remote sensing indices across six winter cover crop fields in Maryland,United States

Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r² = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r² = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.