铀矿地质遥感的创新、进步与持续发展

文章回顾了核工业北京地质研究院铀矿地质遥感发展的创新历程,论述了遥感技术的应用及发展推动了铀矿地质研究的科技进步,探讨了未来如何持续发展铀矿地质遥感,使其在铀矿地质勘查领域发挥更大作用。     

Thermal infrared remote sensing in assessing groundwater and surface-water resources related to Hannukainen mining development site,northern Finland

Mining development sites occasionally host complicated aquifer systems with notable connections to natural surface water (SW) bodies. A low-altitude thermal infrared (TIR) imaging survey was conducted to identify hydraulic connections between aquifers and rivers and to map spatial surface temperature patterns along the subarctic rivers in the proximity of the Hannukainen mining development area, northern Finland. In addition to TIR data, stable isotopic compositions (δ ¹⁸O, δD) and dissolved silica concentrations were used as tracers to verify the observed groundwater (GW) discharge into the river system. Based on the TIR survey, notable GW discharge into the main river channel and its tributaries (61 km altogether) was observed and over 500 GW discharge sites were located. On the basis of the survey, the longitudinal temperature patterns of the studied rivers were found to be highly variable. Hydrological and hydrogeological information is crucial in planning and siting essential mining operations, such as tailing areas, in order to prevent any undesirable environmental impacts. The observed notable GW discharge was taken into consideration in the planning of the Hannukainen mining development area. The results of this study support the use of TIR imagery in GW–SW interaction and environmental studies in extensive and remote areas with special concerns for water-related issues but lacking the baseline research.     

高分辨率遥感数据处理方法实验研究

近几年高分辨率遥感数据处理与应用研究越来越受到国内外学者的重视,已成为目前遥感应用研究领域的热点和难点之一。首先分析了基于像素的中分辨率卫星数据的遥感数据处理方法,包括:基于统计理论的分类方法和基于光谱信息的非参数理论方法的分类方法。在此基础上,针对高分辨率遥感图像的特点,分析了面向对象的高分辨率遥感数据处理方法。其中,图像分割是最关键的一步,即如何有效地提取出对象特征非常重要。最后,给出了高分辨率遥感数据处理方法相关算法实验,主要进行了几种图像分割算法实验,同时结合植被变化检测,进行了变化检测算法实验。     

3D ground model development for an active landslide in Lias mudrocks using geophysical,remote sensing and geotechnical methods

A ground model of an active and complex landslide system in instability prone Lias mudrocks of North Yorkshire, UK is developed through an integrated approach, utilising geophysical, geotechnical and remote sensing investigative methods. Surface geomorphology is mapped and interpreted using immersive 3D visualisation software to interpret airborne light detection and ranging data and aerial photographs. Subsurface structure is determined by core logging and 3D electrical resistivity tomography (ERT), which is deployed at two scales of resolution to provide a means of volumetrically characterising the subsurface expression of both site scale (tens of metres) geological structure, and finer (metre to sub-metre) scale earth-flow related structures. Petrophysical analysis of the borehole core samples is used to develop relationships between the electrical and physical formation properties, to aid calibration and interpretation of 3D ERT images. Results of the landslide investigation reveal that an integrated approach centred on volumetric geophysical imaging successfully achieves a detailed understanding of structure and lithology of a complex landslide system, which cannot be achieved through the use of remotely sensed data or discrete intrusive sampling alone.     

Basin hydrogeological characterization using remote sensing,hydrogeochemical and isotope methods (the case of Baro-Akobo,Eastern Nile,Ethiopia)

Hydrogeochemical and isotopic signatures of the waters of the Baro-Akobo River Basin show deviation from signatures in other Ethiopian river basins. In this study, hydrogeochemical and isotope methods were employed to determine regional and local hydrogeology and characteristics of the basin. Optical, thermal and radar remote sensing products were used to update geological and structural maps of the basin and determine sampling points using the judgment sampling method. A total of 363 samples from wells, springs, rivers, lakes, swamps and rain were collected for this study, and an additional 270 water quality data sets were added from previous studies. These data were analyzed for their hydrogeochemical characteristics and isotope signatures. Analysis of the oxygen, deuterium and tritium isotopes shows the groundwater of the basin is modern water. Among all basins in Ethiopia, the Baro-Akobo Basin shows the highest enrichment. This indicates the proximity of the rainfall sources, which presumably are the Sudd and other wetlands in South Sudan. The hydrochemical properties of the waters show evapotranspiration is the dominant hydrologic process in the basin and explains the large amount of water that is lost in the lowland plain. Analysis of radon-222 shows no significant groundwater flux over the wetlands, which are part of Machar Marshes. This shows evaporation to be dominant hydrologic process in this zone. Results from all analyses help explain the limited holding capacity of the aquifers in the recharge zone and their vulnerability to anthropogenic impacts and climate variability. There is a trend of decreasing surface flow and rainfall and increasing water soil erosion.     

基于遥感图像分割和形态学的黄土滑坡后壁自动提取方法

基于黄土滑坡后壁的光谱和形状特征,提出了利用区域生长合并方法分割高分辨率遥感影像,提取滑坡后壁区域,经过二值化构图处理后,获得滑坡后壁主要格架,以表征黄土滑坡的方法。首先充分考虑黄土滑坡后壁在遥感影像中所呈现出的独特光谱特征和半圆状或圈椅状的形状特征,利用区域生长合并的方法,在生长参数为47.5,合并参数49的状态下进行影像分割,获得初步的黄土滑坡后壁形状;其次,填充分割过程中产生的孔洞,对获得的滑坡后壁进行细部构图;最后,采用二值化骨骼提取算法,提取滑坡后壁的主要格架,作为黄土滑坡的标志。该方法是对黄土滑坡遥感解译工作中,滑坡表达方法的改进和提高。     

Flood monitoring, mapping and assessing capabilities using RADARSAT remote sensing, GIS and ground data for Bangladesh

Remote sensing is the most practical method available to managers of flood-prone areas for quantifying and mapping flood impacts. This study explored large inundation areas in the Maghna River Basin, around the northeastern Bangladesh, as determined from passive sensor LANDSAT data and the cloud-penetrating capabilities of the active sensors of the remote imaging microwave RADARSAT. This study also used passive sensor LANDSAT wet and dry images for the year 2000. Spatial resolution was 30 m by 30 m for comparisons of the inundation area with RADARSAT images. RADARSAT images with spatial resolution of 50 m by 50 m were used for frequency analysis of floods from 2000 to 2004. Time series images for 2004 were also used. RADARSAT remote sensing data, GIS data, and ground data were used for the purpose of flood monitoring, mapping and assessing. A supervised classification technique was used for this processing. They were processed for creating a maximum water extent map and for estimating inundation areas. The results of this study indicated that the maximum extent of the inundation area as estimated using RADARSAT satellite imaging was about 29, 900.72 km² in 2004, which corresponded well with the heavy rainfall around northeast region, as seen at the Bhairab Bazar station and with the highest water level of the Ganges–Brahmaputra–Meghna (GBM) Rivers. A composite of 5 years of RADARSAT inundation maps from 2000 to 2004, GIS data, and damage data, was used to create unique flood hazard maps. Using the damage data for 2004 and the GIS data, a set of damage maps was also created. These maps are expected to be useful for future planning and flood disaster management. Thus, it has been demonstrated that RADARSAT imaging data acquired over the Bangladesh have the ability to precisely assess and clarify inundation areas allowing for successful flood monitoring, mapping and disaster management.     

Desertification in western Rajasthan (India): an assessment using remote sensing derived rain-use efficiency and residual trend methods

Natural Hazards - Owing to its impact on global ecosystem, climate change and related effects is being perceived as a serious issue worldwide especially in the arid and semi-arid regions. Climatic...     

北京市门头沟区洪水地质灾害遥感调查评价

文章叙述了北京市门头沟地区洪水、泥石流等灾害遥感技术调查的概况。对该区主要灾害的类型及其危害程度作了评价，同时按受害程度，将村镇分为4类，并对每类村镇应采取的措施，提出了具体意见。对日后可能发生严重灾害的潜在因素进行了分析，并对灾害的防治提出建议。     

Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico

Hydrographic data, including particulate organic carbon (POC) from the Northeastern Gulf of Mexico (NEGOM) study, were combined with remotely-sensed SeaWiFS data to estimate POC concentration using principal component analysis (PCA). The spectral radiance was extracted at each NEGOM station, digitized, and averaged. The mean value and spurious trends were removed from each spectrum. De-trended data included six wavelengths at 58 stations. The correlation between the weighting factors of the first six eigenvectors and POC concentration were applied using multiple linear regression. PCA algorithms based on the first three, four, and five modes accounted for 90, 95, and 98% of total variance and yielded significant correlations with POC with R ² = 0.89, 0.92, and 0.93. These full waveband approaches provided robust estimates of POC in various water types. Three different analyses (root mean square error, mean ratio and standard deviation) showed similar error estimates, and suggest that spectral variations in the modes defined by just the first four characteristic vectors are closely correlated with POC concentration, resulting in only negligible loss of spectral information from additional modes. The use of POC algorithms greatly increases the spatial and temporal resolution for interpreting POC cycling and can be extrapolated throughout and perhaps beyond the area of shipboard sampling.     

航天遥感信息提取技术方法与地质遥感技术在植被覆盖地区的找矿应用

简述宽波段或高光谱遥感技术方法及亚象元、低概率目标探测技术的研究及应用现状。结合大兴安岭地区矿产资源勘查的背景条件，系统阐述该技术在植被覆盖地区地质找矿的应用流程。这一研究方案的实施及可能获得的成果，将改善在植被覆盖地区的地质找矿工作。     

长时间序列北极海冰密集度遥感数据的比较评估

基于空间分辨率和精度更高的BLM海冰密集度数据集, 评估了两种时间跨度较长、 应用广泛的25 km分辨率海冰密集度遥感数据集——NSIDC数据集和SICCI数据集。两种数据集与BLM数据集的海冰面积变化趋势相同, 但均低于基于BLM数据集得到的海冰面积, 其中基于SICCI数据集得到的海冰面积更接近BLM数据集。相比于NSIDC数据集, SICCI数据集的年、 月平均和日海冰面积偏差分别低81.88%、 80.90%、 81.44%, 且其海冰密集度平均偏差为-3.28%, 低于NSIDC数据的4.36%, 因此在进行北极地区整体海冰面积及海冰密集度分析时应选用SICCI数据集。按纬度、 海冰密集度值分情况对两种数据进行比较, 发现NSIDC数据集对开阔水域和浮冰区的区分效果较差, 其在低纬度和低密集度区域的平均偏差分别为10.11%和13.13%, 而SICCI数据集的平均偏差达到0.05%和0.44%, 是研究低纬度和中低海冰密集度区域的首选数据。与之相对, NSIDC数据集对中高纬度高海冰密集区域, 特别是近北极点区域的反映能力优于SICCI数据集, 平均偏差为1.08%, 均方根偏差为7.76%, 因此进行中高纬度高海冰密集度区域分析时首选NSIDC数据集。对两类数据集在北极东北航道上的分段评估结果发现, 低纬度海冰边缘地带或中低海冰密集度区域占比较高的航段区, SICCI数据集更接近BLM数据集, 这些航段应使用SICCI数据集进行分析; 而在中高纬度高海冰密集度区域占比较高的航段区, NSIDC数据集更加贴合, 应为首选数据集。     

基于GeoEye-1的矿山开发遥感调查与监测应用研究

以马鞍山矿区为研究区域,采用高分辨率Geoeye-1卫星遥感数据,通过影像的几何纠正、正射校正、融合等预处理,以Mapgis为数据平台,利用采矿权与遥感影像进行叠加,对开采面、矿山占地、尾矿库、矿山建筑、废弃采坑、矿山道路等信息进行解译,结合实地调查,实现矿产资源开发利用状况、矿山环境调查与监测工作。结果表明,Geoeye-1数据能够满足1：1万矿山开发遥感调查与监测,能够准确、客观、实时的监测矿山的越界开采、无证开采、擅自改变开采方式等多种违规类型及矿山开发引发的环境问题,为政府整顿矿山开发秩序、矿山地质环境恢复治理提供重要的技术支撑和决策依据。     

The development of forest damage — control and prognosis on the basis of remote sensing data

Forest damage can be caused by three types of stress which exercise their influence by predisposing, causative and contributory factors. Predisposing factors, above all permanent immision stress, cause the general diminishing of the trees' vitality. Causative fators such as long and extreme periods of dryness cause a fast and evident deterioration of the forest stand, contributory factors as eg pest attacks cause their mortification. When using remote sensing data to monitor the development of forest damage it is necessary therefore not only to pay attention to spectral signatures characterizing the degree of green space and thus the information of the canopy but also to spectral signs showing the water supply of the stands. This has not been done so far though nowadays the necessary multispectral satellite data are on regular offer. For this reason it may be suggested that the existing possibilities to predict the development of forest damage on the basis of remote sensing data have not yet been fully used.In order to examine these possibilities, in the environs of Berlin, ie in the east and south of the Land of Brandenburg both the vegetation index which has been known from literature for a long time and an index for the difference in remission identifying the water bands in the short-wave infrared have been calculated on the basis of Landsat-TM data. A multi-temporal comparison shows that despite the bad conditions of the forest in 1991 on the test site located north-east of Berlin due to a relatively good water supply in that year the pine forest damage had not progressed in 1992. This allows to draw the conclusion that at least in the pine forests of the East German interior lowland the development of forest damage is essentially determined by dryness stress. In this way on the basis of 1992 Landsat-TM data there was not only an inventory made of the actual condition of the forest on the east and south-east of the Land of Brandenburg but also trends of damage progress shown. The damage classification of pine stands be completed by a prognosis as to the development of damage.     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.An erratum to this article can be found at     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.The online version of the original article can be found at     

基于RS、GIS集成技术的黄河三角洲海岸线变迁研究

海岸线变迁是黄河三角洲地区重大环境地质问题之一。本文应用RS、GIS集成技术,通过对黄河三角洲海岸线钓口段、黄河港段和河口段3个区段28年(1976—2004年)MSS和TM系列影像数据的分析研究,发现了1976年黄河人工改道后三角洲海岸线变迁的总体规律与趋势,即北部钓口地区不断侵蚀、后退,东北部黄河港地区基本稳定,南部河口地区不断淤积、前进。这一发现对该区域的资源开发、环境保护等具有重要的指导意义。     

Image based remote sensing method for modeling black-eyed beans (Vigna unguiculata) Leaf Area Index (LAI) and Crop Height (CH) over Cyprus

In this paper, Leaf Area Index (LAI) and Crop Height (CH) are modeled to the most known spectral vegetation index — NDVI — using remotely sensed data. This approach has advantages compared to the classic approaches based on a theoretical background. A GER-1500 field spectro-radiometer was used in this study in order to retrieve the necessary spectrum data for estimating a spectral vegetation index (NDVI), for establishing a semiempirical relationship between black-eyed beans’ canopy factors and remotely sensed data. Such semi-empirical models can be used then for agricultural and environmental studies. A field campaign was undertaken with measurements of LAI and CH using the Sun-Scan canopy analyzer, acquired simultaneously with the spectroradiometric (GER1500) measurements between May and June of 2010. Field spectroscopy and remotely sensed imagery have been combined and used in order to retrieve and validate the results of this study. The results showed that there are strong statistical relationships between LAI or CH and NDVI which can be used for modeling crop canopy factors (LAI, CH) to remotely sensed data. The model for each case was verified by the factor of determination. Specifically, these models assist to avoid direct measurements of the LAI and CH for all the dates for which satellite images are available and support future users or future studies regarding crop canopy parameters.