A Comparative Study of Landsat‐7 and Landsat‐8 Data Using Image Processing Methods for Hydrothermal Alteration Mapping

Comparing spaceborne satellite images of Landsat‐8 Operational Land Imager (OLI) and Landsat‐7 Enhanced Thematic Mapper plus (ETM+) was undertaken to investigate the relative accuracy of mapping hydrothermal alteration minerals. The study investigated the northern part of Rabor, which contains copper mineralization occurrences, and is located in the Kerman Cenozoic magmatic assemblage (KCMA), Iran. Image processing methods of band ratio, principal component analysis (PCA), and spectral angle mapper (SAM) were used to map the distribution of hydrothermally altered rocks associated with the porphyry copper mineralization. The band ratio combination of both sensors for mapping altered areas showed similar outcomes. PCA exposed variations in the spatial distribution of hydroxyl‐bearing minerals. The representation of hydrothermal areas using OLI data was more satisfactory than when using ETM+ data. SAM analysis found similar results for mapping hydroxyl‐bearing zones. Verification of the results came through ground investigation and laboratory studies. Rock samples (n = 56) were collected to validate results using thin sections, X‐ray diffraction (XRD) and spectral analyses. Field observations and laboratory analysis revealed that phyllic and propylitic alterations dominate the alteration zones in the study area. Argillic and iron oxides/hydroxides alterations were observed to a lesser degree. The results indicate that alteration maps prepared by OLI data using PCA for visual interpretation are more suitable than those of ETM+ due to a higher radiometric resolution and lower interference between vegetation and altered areas. As the spectral bandwidth of ETM+ band 7 covers absorption feature of propylitic alteration, better mapping of propylitic alterations is achieved using ETM+ data.     

Evaluating the sensitivity of wetlands to climate change with remote sensing techniques

Wetlands are valuable ecosystems that provide many valuable services, yet many of these important ecosystems are at risk because of current trends in climate change. The Prairie Pothole Region (PPR) in the upper‐midwest of the United States and south‐central Canada, characterized by glacially sculpted landscapes and abundant wetlands, is one such vulnerable region. According to regional/global climate model predictions, drought occurrence will increase in the PPR region through the 21st century and thus will probably cause the amount of water in wetlands to decline. Water surface area (WSA) of Kidder County, ND, from 1984–2011 was measured by classifying TM/ETM+(Landsat Thematic Mapper / Enhanced Thematic Mapper Plus) images through the modified normalized difference water index. We then developed a linear model based on the WSA of these wetlands and historical climate data and used this to determine the wetland sensitivity to climate change and predict future wetlands WSA in the PPR. Our model based on Palmer drought severity index (PDSI) of the current year (PDSI_{t ? 0}) and of the previous two years (PDSI_{t ? 2}) can explain 79% of the annual wetland WSA variance, suggesting a high sensitivity of wetlands to drought/climate change. We also predicted the PPR wetlands WSA in the 21st century under A1B scenario (a mid‐carbon emission scenario) using simulated PDSI based on Intergovernmental Panel on Climate Change AR4 22‐model ensemble climate. According to our prediction, the WSA of the PPR wetlands will decrease to less than half of the baseline WSA (defined as the mean wetlands WSA of the 2000s) by the mid of the 21st century, and to less than one‐third by the 2080s, and will then slightly increase in the 2090s. This considerable future wetland loss caused only by climate change provides important implication to future wetland management and climate adaptation policy. Copyright © 2012 John Wiley & Sons, Ltd.     

A 30 meter land cover mapping of China with an efficient clustering algorithm CBEST

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.     

近40 a来天山台兰河流域冰川资源变化分析

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。     

基于TM影响的不同季节北京城市热环境研究

利用2005～2006年4景北京Landsat TM影像,通过热红外波段反演地表温度,揭示不同季节城市热环境分布特征及其空间差异。分别利用遥感反演的地面温度和地面气象站观测的气温数据,计算地表热岛强度和空气热岛强度,并分析其季节变化,结果表明：城区相对近郊区,热岛效应在夏季显著;城区相对于乡村,四季都存在较强的热岛效应。     

Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining

Mining affects the environment in different ways depending on the physical context in which the mining occurs. In mining areas with an arid environment, mining affects plants’ growth by changing the amount of available water. This paper discusses the effects of mining on two important determinants of plant growth—soil moisture and groundwater table (GWT)—which were investigated using an integrated approach involving a field sampling investigation with remote sensing (RS) and ground-penetrating radar (GPR). To calculate and map the distribution of soil moisture for a target area, we initially analyzed four models for regression analysis between soil moisture and apparent thermal inertia and finally selected a linear model for modeling the soil moisture at a depth 10 cm; the relative error of the modeled soil moisture was about 6.3% and correlation coefficient 0.7794. A comparison of mined and unmined areas based on the results of limited field sampling tests or RS monitoring of Landsat 5-thermatic mapping (TM) data indicated that soil moisture did not undergo remarkable changes following mining. This result indicates that mining does not have an effect on soil moisture in the Shendong coal mining area. The coverage of vegetation in 2005 was compared with that in 1995 by means of the normalized difference vegetation index (NDVI) deduced from TM data, and the results showed that the coverage of vegetation in Shendong coal mining area has improved greatly since 1995 because of policy input RMB￥0.4 per ton coal production by Shendong Coal Mining Company. The factor most affected by coal mining was GWT, which dropped from a depth of 35.41 m before mining to a depth of 43.38 m after mining at the Bulianta Coal Mine based on water well measurements. Ground-penetrating radar at frequencies of 25 and 50 MHz revealed that the deepest GWT was at about 43.4 m. There was a weak water linkage between the unsaturated zone and groundwater, and the decline of water table primarily resulted from the well pumping for mining safety rather than the movement of cracking strata. This result is in agreement with the measurements of the water wells. The roots of nine typical plants in the study area were investigated. Populus was found to have the deepest root system with a depth of about 26 m. Based on an assessment of plant growth demands and the effect of mining on environmental factors, we concluded that mining will have less of an effect on plant growth at those sites where the primary GWT depth before mining was deep enough to be unavailable to plants. If the primary GWT was available for plant growth before mining, especially to those plants with deeper roots, mining will have a significant effect on the growth of plants and the mechanism of this effect will include the loss of water to roots and damage to the root system.     

1980-2010年西藏波密地区典型冰川变化特征及其对气候变化的响应

运用遥感(RS)与地理信息系统(GIS)技术, 结合波密县1960-2010年气象数据, 分析了西藏波密地区冰川的主要分布特征和典型大冰川1980-2010年的时空变化. 结果显示: 波密县共有冰川数量2 040条, 总面积为4 382.5 km², 其中, 分布在海拔4 000~6 000 m的高山冰川总面积达4 086 km², 占冰川总面积的93.2%; 南坡分布冰川1 504条, 面积3 180.04 km², 分别占波密冰川总量的73.73%和72.56%, 而北坡占还不到三分之一. 提取1980、 1990、 2000和2010年4期面积大于20 km²的24条大冰川面积进行对比分析, 1980-2010年间波密县大冰川面积总体呈减小趋势, 由1980年的1 592.78 km²退缩至2010年1 567.04 km², 共退缩了25.74 km²; 其中, 1980-1990年冰川变化贡献最大, 冰川面积退缩了16.62 km², 占冰川总面积退缩量的64.6%. 波密县气象站数据显示, 50 a来冰川退缩主要受温度持续上升的影响, 降水量变化对冰川变化影响不大.     

基于TM遥感数据的汶川地震极重灾区生态恢复研究

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...     

基于SEBS模型和Landsat 8数据的黑河下游蒸散发时空特性分析

对黑河下游地区蒸散发量的估算及其时空特性的研究,有助于进一步了解流域水循环,合理利用水资源,防止生态环境进一步恶化。利用SEBS模型估算了黑河下游额济纳绿洲2014年15天的日蒸散量,将SEBS估算的日蒸散与不同下垫面5个站点的EC实测值进行对比,其均方根误差和确定性系数分别为1.2 mm、0.85（5个站点）,0.5 mm、0.96（2个站点）,表明SEBS模型的结果是合理的,可以适用于黑河下游额济纳绿洲地区的地表蒸散量的估算。同时分析了黑河下游蒸散发的时空变化规律,结果表明,黑河下游额济纳绿洲地区,蒸散发在时间上存在明显的季节变化规律：夏季 > 春季 > 秋季 > 冬季;空间上呈现明显的沿河分布的趋势。不同土地覆被类型蒸散发有相似的季节变化特征,但其季节变化幅度并不相同,规律为：水体 > 耕地 > 灌丛地 > 草地 > 裸土地 > 沙地。     

遥感技术在川西甲基卡大型锂矿基地找矿填图中的应用

四川甲基卡矿田是中国乃至于世界上锂矿资源最集中的地区之一,目前运用遥感技术开展甲基卡型锂矿的研究工作尚较为薄弱,文章运用遥感技术在甲基卡特殊地貌区开展找矿填图应用研究,建立了研究区典型岩石及矿物的波谱数据库,总结了研究区黑云母片岩、十字石片岩、十字石堇青石片岩、角岩、二云母花岗岩、含锂辉石伟晶岩、无矿伟晶岩、石英脉、长石斑晶、锂辉石单晶、云母、绿柱石的波谱特征;之后分别基于中等分辨率遥感数据Landsat 8和高空间分辨率遥感数据Geoeye-1进行图像处理和信息提取,开展了地质填图应用初步研究。研究结果表明遥感技术作为一种新兴的技术手段,对甲基卡型锂矿的填图及找矿具有重要的指导意义,可以作为今后地质找矿工作的"先头兵"。