Delineation of coalfield surface fires by thresholding Landsat TM-7 day-time image data

Surface fires are common in coalfields where coal is mined or exposed to sunlight for long durations of time. The heat energy emitted from these fires affects the signal recorded by sensors operating in the shortwave infrared regions of the electromagnetic spectrum. The Landsat TM/ETM+ band-7 is sensitive to solar reflected radiation as well as emitted radiation from a target. The ‘maximum solar reflection threshold’ method proposed in this study uses the highest spectral radiance that can be attributed to solar reflection as the conservative threshold to segregate the pixels with emitted component from those with reflected component of the EM energy. Investigations with Landsat TM/ETM+ data indicate a reflectance value of 0.23–0.25 as the most representative highest reflectance (threshold) in coal mining areas. The method apparently has the advantage that it is based on the reflectance characteristics of materials (sandstone-shale mixtures) typically found in coal mining areas.     

Assessing image processing techniques for geological mapping: a case study in Eljufra,Libya

Various image processing techniques were experimented with in this study to evaluate their efficiency for geological mapping in the Eljufra area of northwest Libya. Remote sensing data including multi-spectral optical Landsat Enhanced Thematic Mapper (ETM+), Synthetic Aperture Radar (ERS-2 SAR) and Digital Elevation Models (DEMs) extracted from the Shuttle Radar Topography Mission (SRTM) data were used to trace different lithological units as well as extracting geological lineaments in the study area. The study area is located in an arid environment mostly devoid of any vegetation. Most lithological and structural units are distinguishable based on their topographic form and spectral properties. Fusion of ETM+ and ERS-2 images was experimented with to further identify lithological units. Shaded relief techniques were implemented to enhance terrain perspective views and to extract geological lineaments. The results discriminated different rock units and modified formation boundaries and revealed new geological lineaments. Nine rock units were identified and plotted in the new geological map defined by the new boundaries. The dominant lineaments tend to run in the NNW-SSE and NNE-SSW directions. Analysis and interpretation of the lineaments provided information about the tectonic evolution of the study area.     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.     

Validating the use of object-based image analysis to map commonly recognized landform features in the United States

ABSTRACT

The U.S. Geological Survey (USGS) National Geospatial Program (NGP) seeks to i) create semantically accessible terrain features from the pixel-based 3D Elevation Program (3DEP) data, and ii) enhance the usability of the USGS Geographic Names Information System (GNIS) by associating boundaries with GNIS features whose spatial representation is currently limited to 2D point locations. Geographic object-based image analysis (GEOBIA) was determined to be a promising method to approach both goals. An existing GEOBIA workflow was modified and the resulting segmented objects and terrain categories tested for a strategically chosen physiographic province in the mid-western US, the Ozark Plateaus. The chi-squared test of independence confirmed that there is significant overall spatial association between terrain categories of the GEOBIA and GNIS feature classes. Contingency table analysis also suggests strong category-specific associations between select GNIS and GEOBIA classes. However, 3D visual analysis revealed that GEOBIA objects resembled segmented regions more than they did individual landform objects, with their boundaries often failing to correspond to match what people would likely perceive as landforms. Still, objects derived through GEOBIA can provide initial baseline landscape divisions that can improve the efficiency of more specialized feature extraction methods.     

Localized versus wide-ranging effects of the post-Soviet wars in the Caucasus on agricultural abandonment

Wars are frequent and can affect land use substantially, but the effects of wars can vary greatly depending on their characteristics, such as intensity or duration. Furthermore, the spatial scale of the effects can differ. The effects of wars may be localized and thus close to conflict locations if direct mechanisms matter most (e.g., abandonment because active fighting precludes farming), or wide-ranging, e.g., farther away from conflict locations, if indirect mechanisms predominate (e.g., no access to agricultural inputs). Our goal was to quantify how the very different wars in the Caucasus region during post-Soviet times most likely affected agricultural abandonment at different scales. We analyzed data on conflict locations plus Landsat-derived land-cover data from 1987 to 2015, and applied matching statistics, difference-in-differences estimators, and logistic panel regressions. We examined the localized versus wide-ranging effects of the different wars on permanent agricultural abandonment and inferred to direct and indirect mechanisms that may have resulted in agricultural abandonment. While permanent agricultural abandonment was overall surprisingly limited across the Caucasus, up to one third of abandonment was most likely related to the wars. Among the wars, the war in Chechnya was by far the most intense and longest, but its effect on abandonment was similar to the less intense and relatively short war in Abkhazia. 47 % and 45 % of agricultural abandonment was related to each war, respectively. The reason was that the effect of the war in Chechnya was more localized, and abandonment occurred near conflict locations, in contrast to Abkhazia, where the effect was wide-ranging and abandonment occurred farther away from conflict locations. In contrast, the war in South Ossetia showed no significant effect on abandonment, and the war in Nagorno-Karabakh had the surprising pattern that abandonment was higher where no war had occurred. For each of the wars, abandonment was predominately related to the nearest conflict locations, but in Abkhazia additional conflict locations within 10 km further increased the probability of abandonment. We infer that the direct mechanisms of the war such as bombing, and active fighting most likely resulted in a localized effect close to conflict locations in Chechnya and in Nagorno-Karabakh. However, in Nagorno-Karabakh subsidies for new settlers after the war, (i.e., a positive wide-ranging effect), potentially reduced the amount of abandonment there. In contrast, negative wide-ranging effects such as refugee movements and post-war restrictions on their return is related to broad-scale abandonment in Abkhazia. In summary, permanent agricultural abandonment was not necessarily higher in a war with a high overall intensity. Instead, the effect of a given war varied in scale, and was related to the relative importance of direct and localized versus indirect and wide-ranging mechanisms, including postwar events and policies, which is likely the case for other wars, too.     

实测与卫星观测德基水库水质变化

德基水库集水区的气候条件适合温带水果及高冷蔬菜、茶叶的种植,德基水库集水区上游遍布果园、菜园与茶园。因此,每逢大雨来临时,大量的残留肥料常遭冲刷至水库中。这些残留的肥料中含有大量的氮、磷等营养盐,足以提供水库微生物的生长繁殖所需,也因此造成水库中二角多甲藻的大量繁殖,进而形成藻华现象。研究使用Landsat TM卫星数据,搭配传统监测模式,以监督式影像分类法分析与监测德基水库1995年的藻华现象。研究结果显示,以Landsat TM卫星数据监测德基水库的藻华现象,其准确率可达87.5%以上。由影像分类的结果可得知,德基水库二角多甲藻之藻华现象发生较严重的时期为夏天,而冬天则较为轻微。此现象发生的原因,应与集水区上游的农业经营模式息息相关。此外,德基水库藻华现象发生的区域及其程度也经由实地调查与卫星影像监测,一一获得证实。     

双桥-新路地区遥感影像的增强处理与构造解译

通过综合利用主成分分析替换法和高分辨率主成分分析融合法,对双桥-新路地区的遥感影像进行了增强处理与构造解译、甄别,突出了不同规模构造体系的特点,实现了对区内不同规模构造信息的有效补充。经后期野外验证,解译成果具有较高可信度,有助于该区热液型铀矿找矿靶区的圈定定位及后续资源潜力评价工作的开展。     

高分辨率遥感影像在新疆塔什库尔干地区沉积变质型铁矿勘查中的应用

采用Worldview-2、Quickbird高辨率分数据及Aster数据,开展了新疆塔什库尔干地区的沉积变质型铁矿遥感综合研究工作。在对研究区开展高分辨率遥感影像特征、遥感异常等成矿信息综合分析的基础上,以老并一赞坎铁矿区为例,建立了区域沉积变质型铁矿的遥感找矿模型,并利用该模型选择塔萨拉地区作为成矿有利地段进行了深入细致的研究,圈定了塔萨拉地区矿化蚀变带的分布范围。研究成果表明在布伦阔勒岩群南部的塔萨拉地区具有较好的寻找沉积变质型铁矿的前景。     

矿物微区分析中透射电镜测试技术的应用

透射电子显微镜（Transmission Electron Microscope,TEM）提供了超高的空间分辨率和多样化的微区分析方法,是纳米地质学研究的重要表征手段之一。运用TEM技术研究矿物时,由于地质样品的高度复杂性和强烈非均质性,使得实验测试过程复杂而困难。文章探索了一套适用于地质样品的TEM分析测试流程。首先根据样品特性,选择合适的样品制备方法,重点介绍了粉末制备法、离子减薄法及聚焦离子束法;然后进行目标矿物的定位,提出了一种扫描电镜（Scanning Electron Microscope, SEM）+TEM组合定位法;接着进行包括明场像、暗场像、高分辨像、电子衍射花样等不同类型图像的获取,着重说明了各种图像的成像原理、拍摄过程、注意事项和实验技巧;最后是选定关注的微区,测试元素组成及分布情况,并与常用的微区成分分析仪器进行对比,从而说明TEM成分分析的适用范围及优点。     

Evaluation of different topographic correction methods for Landsat imagery

The recent free availability of Landsat historical data provides new potentials for land-cover change studies. Multi-temporal studies require a previous radiometric and geometric homogenization of input images, to better identify true changes. Topographic normalization is one of the key steps to create consistent and radiometricly stable multi-temporal time series, since terrain shadows change throughout time. This paper aims to evaluate different methods for topographic correction of Landsat TM-ETM+ data. They were assessed for 15 ETM+ images taken under different illumination conditions, using two criteria: (a) reduction of the standard deviation (SD) for different land-covers and (b) increase in temporal stability of a time series for individual pixels. We observed that results improve when land-cover classes where processed independently when applying the more advanced correction algorithms such as the C-correction and the Minnaert correction. Best results were obtaining for the C-correction and the empiric–statistic correction. Decreases of the SD for bare soil pixels were larger than 100% for the C-correction and the empiric–statistic correction method compared to the other correction methods in the visible spectrum and larger than 50% in the IR region. In almost all tests the empiric–statistic method provided better results than the C-correction. When analyzing the multi-temporal stability, pixels under bad illumination conditions (northern orientation) improved after correction, while a deterioration was observed for pixels under good illumination conditions (southern orientation). Taken this observation into account, a simple but robust method for topographic correction of Landsat imagery is proposed.