Illumination effects on the differenced Normalized Burn Ratio's optimality for assessing fire severity

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.     

Determination of land degradation causes in Tongyu County,Northeast China via land cover change detection

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.     

1990—2018年中巴经济走廊冰湖时空变化特征

中巴经济走廊是贯通南北丝路的关键枢纽。在全球变暖的背景下, 区域内冰川变化情况复杂, 部分冰川出现前进或跃动现象, 冰湖溃决的风险在不断上升, 进而威胁中巴经济走廊的建设与民生安全。基于1990—2018年Landsat TM/ETM+/OLI遥感影像, 利用目视解译方法提取了中巴经济走廊3期冰湖编目数据, 并分析了28年来该区域内冰湖的总体变化趋势、 空间异质性以及成因。结果表明： 中巴经济走廊目前共发育有2 380个冰湖, 总面积为（131.76±19.08） km², 集中分布于喀喇昆仑山脉和喜马拉雅山脉; 1990—2018年期间, 冰湖总体面积扩张速度为0.48%·a^-1, 但各个山脉不同规模冰湖面积变化差异较大。中巴经济走廊在气温和降水的共同作用下, 区内冰湖面积呈扩张趋势, 同时气温和降水变化率的空间差异使得冰湖面积变化存在空间差异; 冰川的快速退缩增加了区内冰湖溃决的风险。     

利用天宫一号和Landsat7对地观测数据的森林变化检测

由于自然演替和一些干扰因素的影响,森林覆盖处在不断的变化中.结合云南省西双版纳地区的天宫一号高光谱数据以及Landsat影像,研究了热带森林覆盖制图与变化检测的自动化识别方法.首先分析了每景影像中红光波段的光谱属性,依据直方图提取出纯净森林像元,然后计算影像中各像元与纯净森林像元之间的光谱相似性,从而得到森林指数并以此为依据提取出每景影像对应的森林覆盖图,将多期的森林覆盖专题图进行叠加分析即可得到森林变化专题图.结果表明:(1)使用天宫一号高光谱影像可以进行森林覆盖自动化提取,生成的森林覆盖图合理地反映了森林分布状况;(2)与多期遥感影像结合进行森林变化信息提取,提取结果很好地体现了森林减少和森林恢复情况,对新恢复的未郁闭森林也可以进行有效检测.     

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.