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Omnibus weights of evidence Method Implemented in GeoDAS GIS for Information Extraction and Integration

Journal of China University of Geosciences 2008年第4期19卷 404-409页

作者：张生元成秋明陈志军 Institute of Natural Resource and Environment Engineering Shijiazhuang University of Economics State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences Department of Earth and Space Science and Engineering York University

weights of evidence （WofE） is an artificial intelligent method for integration of information from diverse sources for predictive purpose in supporting decision making. This method has been commonly used to predict point events by integrating point training layer and binary or ternary evidential layers （multiclass evidence less commonly used）. Omnibus weights of evidence integrates fuzzy training layer and diverse evidential layers. This method provides new features in comparison with the ordinary Wore method. This new method has been implemented in a geographic information system-geophysical data analysis system and the method includes the following contents：（1） dual fuzzy weights of evidence （DFWofE）, in which training layer and evidential layers can be treated as fuzzy sets. DFWofE can be used to predict not only point events but also area or line events. In this model a fuzzy training layer can be defined based on point, line, and areas using fuzzy membership function; and （2） degree-of-exploration model for WorE is implemented through building a degree of exploration map. This method can be used to assess possible spatial correlations between the degree of exploration and potential evidential layers. Importantly, it would also make it possible to estimate undiscovered resources, if the degree of exploration map is combined with other models that predict where such resources are most likely to occur. These methods and relevant systems were vafidated using a case study of mineral potential prediction in Gejiu （个旧） mineral district, Yunnan （云南）, China.

关键词： weights of evidence fuzzy set degree of exploration GIS GeoDAS

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GIS Predictive Model for Producing Hydrothermal Gold Potential Map Using weights of evidence Approach in Gengma Region, Sanjiang District, China

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Journal of China University of Geosciences 2003年第3期14卷 283-292页

作者： Bassam F Al Bassam Faculty of Earth Resources

Gengma region, Sanjiang district is known to have some large-scale gold deposits. GIS predictive model for hydrothermal gold potential was carried out in this region using weights of evidence modeling technique. Datasets used include large-scale hydrothermal gold deposit records, geological, geophysical and remote sensing imagery. Based on the geological and mineral characteristics of areas with known gold occurrences in Sanjiang, several geological features were thought to be indicative of areas with potential for the occurrence of hydrothermal gold deposits. Indicative features were extracted from geoexploration datasets for use as input in the predictive model. The features include host rock lithology, geologic structures, wallrock alteration and associated (volcanic-plutonic) igneous rocks. To determine which of the indicative geological features are important spatial predictors of area with potential for gold deposits, spatial analysis was done through the modeling method. The input maps were buffered and the optimum distance of spatial association for each geological feature was determined by calculating the contrast and studentized contrast. Five feature maps were converted to binary predictor patterns and used as evidential layers for predictive modeling. The binary patterns were integrated in two combinations, each of which consists of four patterns in order to avoid over prediction due to the effect of duplicate features in the two structural evidences. The two produced potential maps define almost similar favorable zones. Areas of intersections between these zones in the two potential maps placed the highest predictive favorable zones in the region.

关键词： geographic information system weights of evidence mineral resource prediction Sanjiang district

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Application of weights of evidence to Mineral Potential Mapping of Yujiacun Ore Field in Northwest Yunnan Province, China

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Journal of China University of Geosciences 2003年第3期14卷 269-273页

作者： XiaQinglin ZhaoPengda ZhangShouting Institute of Mathematical Geology&RemoteSensing China University of GeosciencesWuhan430074 Institute of Land Resources&High-Technology Study China University of GeosciencesBeijing100083

The multivariate information comprehensive processing technique is especially important at present to the digital mineral prospecting. However, the GIS-based weights of evidence have provided us with a powerful tool for the quantitative assessment of mineral resource potential. In this paper, the mineralization model is established, based on the achievements made by previous researchers, to mend such deficiencies as few references on ore fields in Yujiacun, Yunnan Province and the shortage of quantitative prediction and assessment of mineral resources. In addition, the weights of evidence are used to make a systematic quantitative prediction and assessment of mineral resources there, so that 2 mineral prospecting target areas of grade Ⅰand 8 mineral prospecting target areas of grade Ⅱ are delineated, providing the further mineral resource exploration with the basis for the selection of mineral deposits.

关键词： weights of evidence GIS Yujiacun ore field mineral prediction

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Using weights of evidence in the Spatial Relation Between Infected Snails and Geographic Factors

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Geo-Spatial Information Science 2009年第3期12卷 217-224页

作者：赵安鲍曙明宫鹏 School of Geography and Environmental Science Jiangxi Normal University Key Lab of Poyang Lake Wetland and Watershed Research Jiangxi Normal University and Ministry of Education

Schistosomiasis is a serious public health problem in the middle-lower Yangtze River Basin in China. Study of spatial variation of snail distribution that is related to microgeographic factors can help to choose pertinent measures for snail extinguishment and environment rebuilding. This paper studied the theoretical architecture of weights-of-evidence approach. The case study was made for spatial relation between the occurrence of infected snails and geographic factor combinations in Waijiazhou marshland of Poyang Lake region in China. The multievidence data came from the geographical factor combinations by crossing operation of vegetation coverage grade layer, cattle route distance grade layer, and special environment layer (181 combinations in total) in GIS. The calculation of weight contrast index shows that high vegetation coverage, cattle route distance of <45 meters, and special geographic factor "ground depression" had direct spatial relation with the occurrence of infected snails. The verification by crossing operation in GIS indicated 72.45% of the infected snails concentrated on the areas of positive weight contrast index (sequenced in an order of weight contrast index from high to low), demonstrating the high efficiency of the model established in finding infected snails according to the geographic factor combinations that can be explicitly discerned in the study area.

关键词： weights of evidence Bayesian conditional probability infected snail Poyang Lake region

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Resource prediction and assessment based on 3D/4D big data modeling and deep integration in key ore districts of North China

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Science China Earth Sciences 2021年第9期64卷 1590-1606页

作者： Gongwen WANG Zhiqiang ZHANG Ruixi LI Junjian LI Deming SHA Qingdong ZENG Zhenshan PANG Dapeng LI Leilei HUANG School of Earth Sciences and Resources China University of Geosciences(Beijing)Beijing100083China Tianjin Geological Survey Center of China Geological Survey Tianjin300170China Shenyang Geological Survey Center of China Geological Survey Shenyang110000China Key Laboratory of Mineral Resources Institute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China Institutions of Earth Science Chinese Academy of SciencesBeijing100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing100049China Development Research Center of China Geological Survey Beijing100037China Shandong Academy of Geological Sciences Jinan250013China

The North China district has been subjected to significant research with regard to the ore-forming dynamics,processes,and quantitative forecasting of gold deposits;it accounts for the highest number of gold reserves and annual products in *** on the top-level design of geoscience theory and the method adopted by the National Key R&D Project(deep process and metallogenic mechanism of North China Craton(NCC)metallogenic system),this paper systematically collects and constructs the geoscience data(district,camp,and deposit scales)in four key gold districts of North China(Jiaojia-Sanshandao,Southern Zhaoping,Wulong,and Qingchengzi).The settings associated with the geological dynamics of gold deposits were quantitatively and synthetically analyzed,namely:NCC destruction,metallogenic events,genetic models,and exploration ***-dimensional(3D)and four-dimensional(4D)geological modeling was performed using the big data on the districts,while the district-scale 3D exploration criteria were integrated to construct a quantitative exploration *** them,FLAC3D modelling and the Geo Cube software(version 3.0)were used to implement the numerical simulation of the 3D geological models and the constraints of the fluid saturation parameters of the Jiaojia fault to reconstruct the 4D fault structure models of the Jiaojia fault(with a depth of 5000 m).Using Geo Cube3.0,multiple integration modules(general weights of evidence(Wof E),Boost Wof E,Fuzzy Wof E,Logistic Regression,Information Entropy,and Random Forest)and exploration criteria were integrated,while the C-V fractal classification of A,B and C targets in four districts was carried *** research results are summarized in the following four areas:(1)Four gold districts in the study area have more than three targets(the depth is 3000 m),and the class A,B and C targets exhibit a good spatial correlation with gold bodies that are controlled by mining engineering at depths greater than 1000 m.(2)The Boost Wof

关键词： Geoscience big data 3D/4D modeling weights of evidence Random forest Target optimization and resources assessment Gold district in North China

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Quantifying the influence of magmatism and tectonism on ultraslow-spreading-ridge hydrothermal activity:evidence from the Southwest Indian Ridge

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Geoscience Frontiers 2023年第5期14卷 39-54页

作者： Xing Xu Shili Liao Chunhui Tao Lushi Liu School of Oceanography Shanghai Jiaotong UniversityShanghai 200030China Key Laboratory of Submarine Geosciences Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Northeast Institute of Geography and Agroecology CASChangchun 130102China

Hydrothermal activity in mid-ocean ridges(MORs)is an important intermediary for the mass and heat exchange between the ocean and *** development of hydrothermal activity on MORs is primarily controlled by coupled magmatic and tectonic *** ultraslow-spreading ridges,deepdipping low-angle normal faults with large offsets,typically detachment faults in the inside corners of ridge offsets,favor the formation of tectonic-related hydrothermal activities,whereas volcanic-related hydrothermal fields are typically developed in neovolcanic zones in this category of the ridge ***,whether tectonic or magmatic activity is dominant and to what extent they control the formation of hydrothermal activities on ultraslow-spreading ridges remain *** in the west and east of the Gallieni transform fault(TF)located in the ultraslow-spreading Southwest Indian Ridge(SWIR),namely,western area(WA)and eastern area(EA),exhibit distinct magma-supply conditions that provide favorable conditions for examining the influence of magmatic and tectonic *** generated prediction models for these areas using the spatial analysis of the water depth,minor faults,large faults,ridge axis,nontransform discontinuity(NTD)inside corners,TF inside corners,Bouguer gravity anomaly,magnetic anomalies,and seismic *** employing the weights of evidence method,we reported that the formation of seafloor hydrothermal systems in SWIR was primarily correlated to the NTD inside corner,ridge axis,and minor fault(i.e.,contrast values(C)of 4.186,3.727,and 3.482 in WA and 4.278,3.769,and 3.135 in EA).Furthermore,EA was significantly affected by the TF inside corner(C=3.501),whereas WA was influenced by large faults(C=4.062).Our results demonstrated that tectonism was the primary controlling factor in the development of hydrothermal activities in the study area,and the contribution of magmatism was secondary,even in WA,which has a relatively robust magma *** d

关键词： Southwest Indian Ridge Hydrothermal activity weights of evidence Spatial analysis Magmatism and tectonism

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Predictive GIS Model for Potential Mapping of Cu,Pb,Zn Mineralization

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Geo-Spatial Information Science 2006年第2期9卷 151-156页

作者： Tarik. B. Benomar BIAN Fuling State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University 129 Luoyu Road Wuhan 430079 China　

ABSTRACT The geologic features indicative of Cu, Pb, Zn mineral deposits in a area are fractures （structure）, and host rock sediments. Datasets used include Cu, Pb, Zn deposit points record, geological data, remote sensing imagery （Landsat TM5）. The mineral potential of the study area is assessed by means of GIS based geodata integration techniques for generating predictive maps. GIS predictive model for Cu, Pb, Zn potential was carried out in this study area （Weixi） using weight of evidence. The weights of evidence modeling techniques is the data driven method in which the spatial associations of the indicative geologic features with the known mineral occurrences in the area are quantified, and weights statistically assigned to the geologic features. The best predictive map generated by this method defines 24 % the area having potential for Cu, Pb, Zn mineralization further exploration work.

关键词： geographic information system weights of evidence mineral resource prediction

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Quantitative prediction and evaluation of geothermal resource areas in the southwest section of the Mid-Spine Belt of Beautiful China

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International Journal of Digital Earth 2022年第1期15卷 748-769页

作者： Zhe Chen Ruichun Chang Wenbo Zhao Sijia Li Huadong Guo Keyan Xiao Lin Wu Dong Hou Lu Zou College of Mathematics and Physics Chengdu University of TechnologyChengduPeople’s Republic of China Digital Hu Line Research Institute Chengdu University of TechnologyChengduPeople’s Republic of China Geomathematics Key Laboratory of Sichuan Province ChengduPeople’s Republic of China Key Laboratory of Digital Earth Science Chinese Academy of SciencesAerospace Information Research InstituteBeijingPeople’s Republic of China University of Chinese Academy of Sciences BeijingPeople’s Republic of China International Research Centre of Big Data for Sustainable Development Goals (CBAS) BeijingPeople’s Republic of China MNR Key Laboratory of Metallogeny and Mineral Assessment Institute of Mineral ResourcesChinese Academy of Geological SciencesBeijingPeople’s Republic of China

The geothermal resources in the southwest section of the Mid-Spine Belt of Beautiful China are abundant,but the quantitative prediction and evaluation of geothermal resources are very difficult. Based on geographic information system (GIS) and remote sensing (RS) platforms,six impact factors,namely land surface temperature,fault density,Gutenberg–Liszt B value,formation combination entropy,distance to river and aeromagnetic anomaly were selected. Through the establishment of the certainty factor model (CF),weights of the information entropy certainty factor model (ICF) and weights of the evidence certainty factor model (ECF),the geothermal potential in the study area were predicted quantitatively. Based on the ECF results,the six main geothermal resource areas were delineated. The results show that (1) ECF had high prediction accuracy (success index is 0.00405%,area ratio is 0.867);(2) The geothermal resource areas obtained were Ganzi–Ya’an–Liangshan,Panzhihua–Liangshan,Dali–Chuxiong,Nujiang–Baoshan,Diqing–Dali,and Lijiang–Diqing. The results provide a basis for the effective development and utilization of geothermal resources in the southwest section of the mid-ridge belt.

关键词： Mid-Spine Belt of Beautiful China certainty factor geothermal resource area weights of evidence

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A Predictive GIS Model for Potential Mapping of Copper, Lead, and Zinc in Langping Area, China

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Geo-Spatial Information Science 2009年第4期12卷 243-250页

作者： Tarik. B. Benomar HU Guangdao BIAN Fuling Research Center of Spatial Information & Digital Engineering Wuhan University 129 Luoyu RoadWuhan 430079 China Faculty of Earth Resources China University of Geosciences 388 Lumo Road Wuhan 430074 China

Mineral resource potential mapping is a complex analytical process,which requires the consideration and the inte-gration of a number of spatial evidences like geological,geomorphological,and wall rock *** aim of this paper is to establish mineral exploration model for copper,lead,and zinc in Lanping basin area using the capability of analytical tools of Geographic Information System(GIS) and remote sensing data to generate maps showing favorable mineralized *** geo-exploration dataset used for the research includes copper,lead,and zinc deposits,geological maps,topographic maps,structural maps,and ETM+ *** features indicative of potential copper,lead,and zinc were extracted from the datasets input in the predictive *** method of weights of evidence modeling is a probability-based technique for generating mineral potential maps using the spatial distribution of indicative features with respect to the known mineral *** method of weights of evidence probabilistic modeling provides a quantitative method for delineating areas with potential of copper,lead,and zinc mineral deposits in the Lanping Basin ***(W+,W-) and contrast(C=(W+) -(W-) ) calculations guide the data-driven *** four most important spatial features for exploration guide for copper,lead,and zinc mineralization hosted in the Lanping Basin area are alteration zones,faults,host rocks,and *** host rocks and deep faults have the strongest spatial association with the known copper,lead,and zinc *** hydrothermal alteration zones have the moderate spatial association with the copper,lead,and zinc *** predicted high-favorability zones do not show the strong affinity with *** distribution of 22(copper,lead,and zinc) occur-rences in the Lanping Basin was examined in terms of spatial association with various geological *** analysis of these relationships using GIS and weights of evidence modeling has pr

关键词： remote sensing geographic information system weights of evidence Lanping Basin(China)

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