Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: - brady_som_output.gri, brady_som_output.grd, brady_som_output.* - desert_som_output.gri, desert_som_output.grd, desert_som_output.* The data corresponds to two sites: Brady Hot Springs and Desert Peak, both located near Fallon, NV. Input layers include: - Geothermal: Labeled data (0: Non-geothermal; 1: Geothermal) - Minerals: Hydrothermal mineral alterations, as a result of spectral analysis using Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite - Temperature: Land surface temperature (% of times a pixel was classified as "Hot" by K-Means) - Faults: Fault density with a 300mradius - Subsidence: PSInSAR results showing subsidence displacement of more than 5mm - Uplift: PSInSAR results showing subsidence displacement of more than 5mm Also, the results of the classification using Brady and Desert Peak to build 2 Convolutional Neural Networks. These were applied to the training site as well as the other site, the results are in GeoTiff format. - brady_classification: Results of classification of the Brady-trained model - desert_classification: Results of classification of the Desert Peak-trained model - b2d_classification: Results of classification of Desert Peak using the Brady-trained model - d2b_classification: Results of classification of Brady using the Desert Peak-trained model本提交材料包含标注数据集、用于机器学习模型训练的ESRI Grid文件（.gri、.grd）以及模型分类结果，具体如下： - brady_som_output.gri、brady_som_output.grd、brady_som_output.* - desert_som_output.gri、desert_som_output.grd、desert_som_output.* 本数据集对应两处研究站点：布雷迪温泉（Brady Hot Springs）与沙漠峰（Desert Peak），二者均坐落于内华达州法伦（Fallon, NV）附近。输入图层涵盖以下类别： - 地热数据：标注数据（0代表非地热区域，1代表地热区域） - 矿物数据：热液矿物蚀变信息，由针对玉髓（Chalcedony）、高岭石（Kaolinite）、石膏（Gypsum）、赤铁矿（Hematite）及七水硫酸镁（Epsomite）开展的光谱分析生成 - 温度数据：地表温度数据，统计指标为经K-Means算法分类为“高温”的像素占比 - 断层数据：半径300米范围内的断层密度 - 沉降数据：永久散射体干涉合成孔径雷达（Persistent Scatterer Interferometric Synthetic Aperture Radar, PSInSAR）结果，显示沉降位移超过5毫米 - 抬升数据：永久散射体干涉合成孔径雷达（PSInSAR）结果，显示沉降位移超过5毫米 此外，本研究使用布雷迪温泉与沙漠峰数据集构建了两个卷积神经网络（Convolutional Neural Networks, CNN），并将上述模型分别应用于训练站点与另一验证站点，分类结果均以GeoTiff格式存储，具体如下： - brady_classification：布雷迪训练模型的分类结果 - desert_classification：沙漠峰训练模型的分类结果 - b2d_classification：采用布雷迪训练模型对沙漠峰站点开展的分类结果 - d2b_classification：采用沙漠峰训练模型对布雷迪站点开展的分类结果