The sandstone-hosted stratiform copper mineralization at Mwitapile and its relation to the mineralization at Lufukwe, Lufilian foreland, Democratic Republic of Congo

The Lufilian foreland is a triangular-shaped area located in the SE of the Democratic Republic of Congo and to the NE of the Lufilian arc, which hosts the well-known Central African Copperbelt. The Lufilian foreland recently became an interesting area with several vein-type (e.g., Dikulushi) and stratiform (e.g., Lufukwe and Mwitapile) copper occurrences. The Lufilian foreland stratiform Cu mineralization is, to date, observed in sandstone rock units belonging to the Nguba and Kundelungu Groups (Katanga Supergroup).The Mwitapile sandstone-hosted stratiform Cu prospect is located in the north eastern part of the Lufilian foreland. The host rock for the Cu mineralization is the Sonta Sandstone of the Ngule Subgroup (Kundelungu Group). A combined remote sensing, petrographic and fluid inclusion microthermometric analysis was performed at Mwitapile and compared with similar analysis previously carried out at Lufukwe to present a metallogenic model for the Mwitapile- and Lufukwe-type stratiform copper deposits. Interpretation of ETM+ satellite images for the Mwitapile prospect and the surrounding areas indicate the absence of NE–SW or ENE–WSW faults, similar to those observed controlling the mineralization at Lufukwe. Faults with these orientations are, however, present to the NW, W, SW and E of the Mwitapile prospect. At Mwitapile, the Sonta Sandstone host rock is intensely compacted, arkosic to calcareous with high silica cementation (first generation of authigenic quartz overgrowths). In the Sonta Sandstone, feldspar and calcite are present in disseminated, banded and nodular forms. Intense dissolution of these minerals caused the presence of disseminated rectangular, pipe-like and nodular dissolution cavities. Sulfide mineralization is mainly concentrated in these cavities. The hypogene sulfide minerals consist of two generations of pyrite, chalcopyrite, bornite and chalcocite, separated by a second generation of authigenic quartz overgrowth. The hypogene sulfide minerals are replaced by supergene digenite and covellite. Fluid inclusion microthermometry on the first authigenic quartz phase indicates silica precipitation from an H₂O–NaCl–CaCl₂ fluid with a minimum temperature between 111 and 182 °C and a salinity between 22.0 and 25.5 wt.% CaCl₂ equiv. Microthermometry on the second authigenic quartz overgrowths and in secondary trails related to the mineralization indicate that the mineralizing fluid is characterized by variable temperatures (Th = 120 to 280 °C) and salinities (2.4 to 19.8 wt.% NaCl equiv.) and by a general trend of increasing temperatures with increasing salinities.Comparison between Mwitapile and Lufukwe indicates that the stratiform Cu mineralization in the two deposits is controlled by similar sedimentary, diagenetic and structural factors and likely formed from a similar mineralizing fluid. A post-orogenic timing is proposed for the mineralization in both deposits. The main mineralization controlling factors are grain size, clay and pyrobitumen content, the amount and degree of feldspar and/or calcite dissolution and the presence of NE–SW to ENE–WSW faults. The data support a post-orogenic fluid-mixing model for the Mwitapile- and Lufukwe-type sandstone-hosted stratiform Cu deposits, in which the mineralization is related to the mixing between a Cu-rich hydrothermal fluid, with a temperature up to 280 °C and a maximum salinity of 19.8 wt.% NaCl equiv., with a colder low salinity reducing fluid present in the sandstone host rock. The mineralizing fluid likely migrated upwards to the sandstone source rocks along NE–SW to ENE–WSW orientated faults. At Lufukwe, the highest copper grades at surface outcrops and boreholes were found along and near to these faults. At Mwitapile, where such faults are 2 to 3 km away, the Cu grades are much lower than at Lufukwe. Copper precipitation was possibly promoted by reduction from pre-existing hydrocarbons and non-copper sulfides and by the decrease in fluid salinity and temperature during mixing. Based on this research, new Cu prospects were proposed at Lufukwe and Mwitapile and a set of recommendations for further Cu exploration in the Lufilian foreland is presented.     

Mapping Proterozoic unconformity-related uranium deposits in the Rockhole area, Northern Territory, Australia using landsat ETM+

The Rockhole area, Northern Territory, Australia, hosts a number of Proterozoic unconformity-related uranium deposits. The geology of the area features within Paleoproterozoic rocks of the Pine Creek Orogen, near the unconformity with overlying platform cover sandstone of the Paleo- to Mesoproterozoic McArthur Basin. Landsat Enhanced Thematic Mapper plus (ETM+) data was used in the Rockhole area to assist in mapping geological structures and lithology, and to identify anomalous concentrations of ferrous minerals, the product of alteration, which can be indicators of buried uranium mineralization. Several image-processing procedures were applied to the ETM+ data to identify, isolate and enhance mineralogical information as simple and complex false color composites. ETM+ 754 shown as red green and blue respectively was the best simple image. Overall, complex images based on Principal Component Analysis proved to be the most useful products. Sandstone, shale and siltstone, the target lithologies, Koolpin Formation, the target stratigraphic unit, and bleaching pattern due to the removal of iron(II) compounds, the target alteration pattern, were confidently mapped to provide information required by the mineral emplacement model, which ultimately identified areas of likely uranium mineralization. Thus the contrasting behavior of the two principle oxidation states of uranium and iron can be utilized to map/delineate bleached alteration zones associated with economic concentrations of uranium using multispectral sensors like Landsat or better hyperspectral sensors.     

Comparative analyses of East Texas forest cover maps generated from Landsat and AVHRR data

Comparing satellite data derived map products are affected by differences in data characteristics, image acquisition dates, processing techniques, and classification schemes used for assigning pixels to a thematic class. By comparing two forest maps generated from Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Very High Resolution Radiometer (AVHRR) images acquired on the same day, and processed using identical classification scheme and methods these differences were minimized. The ETM+ derived map had higher classification accuracy values and more precise area estimates than the AVHRR derived map. In the ETM+ derived map, 87 of the 599 verification data were misclassified, whereas in the AVHRR derived map, 155 of the 469 verification data were misclassified. Detailed error analyses by land cover class revealed that a land use based definition of forest accounted for 74% (64 out of 87) and 57% (89 out of 155) of the classification errors in ETM+ and AVHRR derived maps, respectively.     

Response of the barrier island coastal region of southwestern Nigeria to climate and non-climate forcing

Despite threats emanating from the influence of climate and non-climate forcing on the barrier island coastal region of southwestern Nigeria, the extent of the coastal erosion is poorly understood. We report evidence of coastal erosion and sediment accumulation in the region over a 34-year period (1973–2017), using Landsat imagery at intervals of approximately six years. Landsat image corrections and various water-extraction algorithms were used to systematically delineate coastal erosion and accumulation in the area. The region was subdivided into western and eastern subregions separated by Lagos Harbour. In the west, erosion took place during the periods 1973–1979, 1979–1984, 1990–1999 and 2005–2011, whereas in the east, erosion occurred during 1973–1979, 1990–1999 and 1999–2005. Coastal sediment accumulation occurred in the east during 1979–1984, 1984–1990, 2005–2011 and 2011–2017, whereas gains in the west occurred during 1984–1990, 1999–2005 and 2011–2017. The study revealed substantial net erosion of 1 228.1 ha in the region as a whole, over the full period. Sediment accumulation accompanying the coastal erosion appears to be linked to longshore drift. Erosion between 1973 and 2011 was probably attributable to climate change (storms and tidal conditions), longshore drift, the inflow and outflow of water at Lagos Harbour, coastal morphology and, possibly, human impacts. However, the coastal changes between 2011 and 2017 were more obviously associated with human activities, such as development of the Eko Atlantic construction project. Coastal surveillance, together with the use of environmentally sensitive protective measures, could possibly help to reduce coastal erosion in the region. Careful coastal management practices, including artificial nourishing and the installation of resilient structures (e.g. seawalls), should be undertaken to protect human settlements that are already at risk from sea-level rise.     

北京城市地表温度的遥感时空分析

运用Landsat TM/ETM+和Terra ASTER数据,对北京市1990~2007年夏季的地表温度进行了反演,并对地表温度的空间分布、时间变化作出了分析。对Landsat TM/ETM+数据的温度反演采用了普适性单波段算法,ASTER数据的温度反演采用了劈窗算法。通过对地表温度数据的直方图均衡处理以及综合对比分析,总结出北京地区历年来夏季地表温度的空间分布格局及该格局随北京城市发展的变化规律,分析了研究成果的不足,提出了下一步要努力的方向。     

青海省柴达木盆地西北缘盐类矿产遥感预测研究

利用ETM多光谱遥感图像,在对盐湖区的遥感影像特征和主要地物光谱特征分析的基础上,通过波段组合变换,压抑粘土及砂砾层等地物的影响,将盐类矿产信息增强提取出来。对比前人的钾盐矿田勘查成果,所提取的盐类信息异常与现代新盐带、湿盐滩和现正在开采的钾盐矿区十分吻合。结合区域地质背景与成矿条件的分析研究,圈定了4个预测区、9处有利地段,为进一步盐类矿产勘查提供了科学依据和目标地。     

Predicting grain protein content of winter wheat using remote sensing data based on nitrogen status and water stress

Advanced site-specific knowledge of grain protein content of winter wheat from remote sensing data would provide opportunities to manage grain harvest differently, and to maximize output by adjusting input in fields. In this study, remote sensing data were utilized to predict grain protein content. Firstly, the leaf nitrogen content at winter wheat anthesis stage was proved to be significantly correlated with grain protein content (R² = 0.36), and spectral indices significantly correlated to leaf nitrogen content at anthesis stage were potential indicators for grain protein content. The vegetation index, VI_green, derived from the canopy spectral reflectance at green and red bands, was significantly correlated to the leaf nitrogen content at anthesis stage, and also highly significantly correlated to the final grain protein content (R² = 0.46). Secondly, the external conditions, such as irrigation, fertilization and temperature, had important influence on grain quality. Water stress at grain filling stage can increase grain protein content, and leaf water content is closely related to irrigation levels, therefore, the spectral indices correlated to leaf water content can be potential indicators for grain protein content. The spectral reflectance of TM channel 5 derived from canopy spectra or image data at grain filling stage was all significantly correlated to grain protein content (R² = 0.31 and 0.37, respectively). Finally, not only this study proved the feasibility of using remote sensing data to predict grain protein content, but it also provided a tentative prediction of the grain protein content in Beijing area using the reflectance image of TM channel 5.     

Wetland vegetation biomass estimation and mapping from Landsat ETM data:a case study of Poyang Lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18-28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.     

A New Model for Quantifying Anisotropic Scale Invariance and for Decomposition of Mixing Patterns

A new power–law function has been derived to represent the relationship between area of the set consisting of wave numbers with spectral energy density above S (A(>S)) on the two-dimensional frequency plane and S. The power–law relation holds if the field concerned possessing isotropic scale invariance or generalized scaling invariance involves rotational and ratio-scale changing transforms. The equation is valid for dealing with common exploration geophysical and geochemical fields encountered in mineral exploration and environmental assessment. This power–law function not only provides a new model for characterizing anisotropic scaling invariance for generalized scaling field, for example, estimating the power exponent of power spectrum of generalized scale invariance measure in frequency domain, but also forms a theoretical base for the S–A filtering technique developed for decomposing a mixing field into components on the basis of distinct scaling properties in the frequency domain. It is demonstrated that the method has potential to become a general technique for image processing and pattern recognition.     

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of Tm3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.