Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Earth Sciences
Title: Humanitarian applications of machine learning with remote-sensing data: review and case study in refugee settlement mapping
Abstract: The coordination of humanitarian relief, e.g. in a natural disaster or a conflict situation, is often complicated by a scarcity of data to inform planning. Remote sensing imagery, from satellites or drones, can give important insights into conditions on the ground, including in areas which are difficult to access. Applications include situation awareness after natural disasters, structural damage assessment in conflict, monitoring human rights violations or population estimation in settlements. We review machine learning approaches for automating these problems, and discuss their potential and limitations. We also provide a case study of experiments using deep learning methods to count the numbers of structures in multiple refugee settlements in Africa and the Middle East. We find that while high levels of accuracy are possible, there is considerable variation in the characteristics of imagery collected from different sensors and regions. In this, as in the other applications discussed in the paper, critical inferences must be made from a relatively small amount of pixel data. We, therefore, consider that using machine learning systems as an augmentation of human analysts is a reasonable strategy to transition from current fully manual operational pipelines to ones which are both more efficient and have the necessary levels of quality control. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations’.
Extracted statement — Output/Application: Natural disasters
Research field: Earth Sciences
Title: Petrography, XRD Analysis and Identification of Talc Minerals near Chhabadiya Village of Jahajpur Region, Bhilwara, India through Hyperion Hyperspectral Remote Sensing Data
Abstract: The larger synoptic view and contiguous channels arrangement of Hyperion hyperspectral remote sensing data enhance the minor spectral identification of earth’s features such as minerals, atmospheric gasses, vegetation and so on. Hydrothermal alteration minerals mostly associated with vicinity of geological structural features such as lineaments and fractures. In this study Hyperion data is used for identification of hydrothermally altered minerals and alteration facies near Chhabadiya village of Jahajpur area, Bhilwara, Rajasthan. There are some minerals such as talc minerals identified through Hyperion imagery. The identified talc minerals correlated and evaluated through petrographic analysis, XRD analysis and spectroscopic analysis. The validation of identified minerals completed by field survey, field sample spectra and USGS spectral library talc mineral spectra. The conclusion is that Hyperion hyperspectral remote sensing data have capability to identify the minerals, mineral assemblage, alteration minerals and alteration facies.
Extracted statement — Techniques/Methods: Petrographic analysis
Research field: Earth Sciences
Title: Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data
Abstract: This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.
Extracted statement — Analysis: Pixel Purity Index
Research field: Earth Sciences
Title: A short survey of hyperspectral remote sensing applications in agriculture
Abstract: Hyperspectral sensors are devices that acquire images over hundreds of spectral bands, thereby enabling the extraction of spectral signatures for objects or materials observed. Hyperspectral remote sensing has been used over a wide range of applications, such as agriculture, forestry, geology, ecological monitoring and disaster monitoring. In this paper, the specific application of hyperspectral remote sensing to agriculture is examined. The technological development of agricultural methods is of critical importance as the world's population is anticipated to continuously rise much beyond the current number of 7 billion. One area upon which hyperspectral sensing can yield considerable impact is that of precision agriculture - the use of observations to optimize the use of resources and management of farming practices. For example, hyperspectral image processing is used in the monitoring of plant diseases, insect pests and invasive plant species; the estimation of crop yield; and the fine classification of crop distributions. This paper also presents a detailed overview of hyperspectral data processing techniques and suggestions for advancing the agricultural applications of hyperspectral technologies in Turkey.
Extracted statement — Application: Precision agriculture
Research field: Earth Sciences
Title: ASTER Data Analyses for Lithological Discrimination of Sittampundi Anorthositic Complex, Southern India
Abstract: ASTER is an advanced Thermal Emission and Reflection Radiometer, a multispectral sensor, which measures reflected and emitted electromagnetic radiation of earth surface with 14 bands. The present study aims to delineate different rock types in the Sittampundi Anorthositic Complex (SAC), Tamil Nadu using Visible (VIS), near-infrared (NIR) and short wave infrared (SWIR) reflectance data of ASTER 9 band data. We used different band ratioing, band combinations in the VNIR and SWIR region for discriminating lithological boundaries. SAC is also considered as a lunar highland analog rock. Anorthosite is a plagioclase-rich igneous rock with subordinate amounts of pyroxenes, olivine and other minerals. A methodology has been applied to correct the cross talk effect and radiance to reflectance. Principal Component Analysis (PCA) has been realized on the 9 ASTER bands in order to reduce the redundancy information in highly correlated bands. PCA derived FCC results enable the validation and support to demarcate the different lithological boundaries defined on previous geological map. The image derived spectral profiles for anorthosite are compared with the ASTER resampled laboratory spectra, JHU spectral library spectra and Apollo 14 lunar anorthosites spectra. The Spectral Angle Mapping imaging spectroscopy technique has been practiced to classify the ASTER image of the study area and found that, the processing of ASTER remote sensing data set can be used as a powerful tool for mapping the terrestrial Anorthositic regions and similar kind of process could be applied to map the planetary surfaces (E.g. Moon).
Extracted statement — Analysis: Principal Component Analysis (PCA)
Research field: Earth Sciences
Title: Lithological mapping using Landsat 8 OLI and Terra ASTER multispectral data in the Bas Drâa inlier, Moroccan Anti Atlas
Abstract: Abstract. Lithological mapping is a fundamental step in various mineral prospecting studies because it forms the basis of the interpretation and validation of retrieved results. Therefore, this study exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units in the Bas Drâa inlier, at the Moroccan Anti Atlas. This task was completed by using principal component analysis (PCA), band ratios (BR), and support vector machine (SVM) classification. Overall accuracy and the kappa coefficient of SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological map of the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 OLI data in lithological units discrimination.
Extracted statement — Methods: Principal Component Analysis (PCA)
Research field: Earth Sciences
Title: Mapping hydrothermal alteration minerals using high-resolution AVIRIS-NG hyperspectral data in the Hutti-Maski gold deposit area, India
Abstract: ABSTRACT The present study exploits high-resolution hyperspectral imagery acquired by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor from the Hutti-Maski gold deposit area, India, to map hydrothermal alteration minerals. The study area is a volcanic-dominated late Archean greenstone belt that hosts major gold mineralization in the Eastern Dharwar Craton of southern India. The study encompasses pre-processing, spectral and spatial image reduction using Minimum Noise Fraction (MNF) and Fast Pixel Purity Index (FPPI), followed by endmember extraction using n-dimensional visualizer and the United States Geological Survey (USGS) mineral spectral library. Image derived endmembers such as goethite, chlorite, chlorite at the mine site (chlorite mixed with mined materials), kaolinite, and muscovite were subsequently used in spectral mapping methods such as Spectral Angle Mapper (SAM), Spectral Information Divergence (SID) and its hybrid, i.e. SIDSAMtan. Spectral similarity matrix of the target and non-target-based method has been proposed to find the possible optimum threshold needed to obtain mineral map using spectral mapping methods. Relative Spectral Discrimination Power (RSDPW) and Confusion Matrix (CM) have been used to evaluate the performance of SAM, SID, and SIDSAMtan. The RSDPW and CM illustrate that the SIDSAMtan benefits from the unique characteristics of SAM and SID to achieve better discrimination capability. The Overall Accuracy (OA) and kappa coefficient (ҡ) of SAM, SID, and SIDSAMtan were computed using 900 random validation points and obtained 90% (OA) and 0.88 (ҡ), 91.4% and 0.90, and 94.4% and 0.93, respectively. Obtained mineral map demonstrates that the northern portion of the area mainly consists of muscovite whereas the southern part is marked by chlorite, goethite, muscovite and kaolinite, indicating the propylitic alteration. Most of these minerals are associated with altered metavolcanic rocks and migmatite.
Extracted statement — yields: Relative Spectral Discrimination Power (RSDPW)
Research field: Earth Sciences
Title: Simple mineral mapping algorithm based on multitype spectral diagnostic absorption features: a case study at Cuprite, Nevada
Abstract: Abstract. Hyperspectral remote sensing has been widely used in mineral identification using the particularly useful short-wave infrared (SWIR) wavelengths (1.0 to 2.5 μm). Current mineral mapping methods are easily limited by the sensor’s radiometric sensitivity and atmospheric effects. Therefore, a simple mineral mapping algorithm (SMMA) based on the combined application with multitype diagnostic SWIR absorption features for hyperspectral data is proposed. A total of nine absorption features are calculated, respectively, from the airborne visible/infrared imaging spectrometer data, the Hyperion hyperspectral data, and the ground reference spectra data collected from the United States Geological Survey (USGS) spectral library. Based on spectral analysis and statistics, a mineral mapping decision-tree model for the Cuprite mining district in Nevada, USA, is constructed. Then, the SMMA algorithm is used to perform mineral mapping experiments. The mineral map from the USGS (USGS map) in the Cuprite area is selected for validation purposes. Results showed that the SMMA algorithm is able to identify most minerals with high coincidence with USGS map results. Compared with Hyperion data (overall accuracy=74.54%), AVIRIS data showed overall better mineral mapping results (overall accuracy=94.82%) due to low signal-to-noise ratio and high spatial resolution.
Extracted statement — Analysis: Simple mineral mapping algorithm (SMMA)
Research field: Earth Sciences
Title: Application of remote sensing methods to hydrology and water resources
Abstract: Abstract A brief review of research in remote sensing of water resources indicates that there are many positive results, and some techniques have been applied operationally. Currently, remote sensing data are being used operationally in precipitation estimates, soil moisture measurements for irrigation scheduling, snow water equivalent and snow cover extent assessments, seasonal and short term snowmelt runoff forecasts, and surface water inventories. In the next decade other operational applications are likely using remote measurements of land cover, sediment loads, erosion, groundwater, and areal inputs to hydrological models. Many research challenges remain, and significant progress is expected in areas like albedo measurements, energy budgets, and evapotranspiration estimation. The research in remote sensing and water resources also has much relevance for related studies of climate change and global habitability.
Extracted statement — Application: Soil moisture
Research field: Earth Sciences
Title: Spatial distribution of altered minerals in the Gadag Schist Belt (GSB) of Karnataka, Southern India using hyperspectral remote sensing data
Abstract: Abstract Spatial distribution of altered minerals in rocks and soils in the Gadag Schist Belt (GSB) is carried out using Hyperion data of March 2013. The entire spectral range is processed with emphasis on VNIR (0.4–1.0 μm) and SWIR regions (2.0–2.4 μm). Processing methodology includes Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes correction, minimum noise fraction transformation, spectral feature fitting (SFF) and spectral angle mapper (SAM) in conjunction with spectra collected, using an analytical spectral device spectroradiometer. A total of 155 bands were analysed to identify and map the major altered minerals by studying the absorption bands between the 0.4–1.0-μm and 2.0–2.3-μm wavelength regions. The most important and diagnostic spectral absorption features occur at 0.6–0.7 μm, 0.86 and at 0.9 μm in the VNIR region due to charge transfer of crystal field effect in the transition elements, whereas absorption near 2.1, 2.2, 2.25 and 2.33 μm in the SWIR region is related to the bending and stretching of the bonds in hydrous minerals (Al-OH, Fe-OH and Mg-OH), particularly in clay minerals. SAM and SFF techniques are implemented to identify the minerals present. A score of 0.33–1 was assigned for both SAM and SFF, where a value of 1 indicates the exact mineral type. However, endmember spectra were compared with United States Geological Survey and John Hopkins University spectral libraries for minerals and soils. Five minerals, i.e. kaolinite-5, kaolinite-2, muscovite, haematite, kaosmec and one soil, i.e. greyish brown loam have been identified. Greyish brown loam and kaosmec have been mapped as the major weathering/altered products present in soils and rocks of the GSB. This was followed by haematite and kaolinite. The SAM classifier was then applied on a Hyperion image to produce a mineral map. The dominant lithology of the area included greywacke, argillite and granite gneiss.
Extracted statement — Analysis: Spectral Angle Mapper (SAM)
Research field: Earth Sciences
Title: Utilization of Hyperion data over Dongargarh, India, for mapping altered/weathered and clay minerals along with field spectral measurements
Abstract: Hyperion data acquired over Dongargarh area, Chattisgarh (India), in December 2006 have been analysed to identify dominant mineral types present in the area, with special emphasis on mapping the altered/weathered and clay minerals present in the rocks and soils. Various advanced spectral processes such as reflectance calibration of the Hyperion data, minimum noise fraction transformation, spectral feature fitting (SFF) and spectral angle mapper (SAM) have been used for comparison/mapping in conjunction with spectra of rocks and soils that have been collected in the field using Analytical Spectral Devices's FieldSpec instrument. In this study, 40 shortwave infrared channels ranging from 2.0 to 2.4 μm were analysed mainly to identify and map the major altered/weathered and clay minerals by studying the absorption bands around the 2.2 and 2.3 μm wavelength regions. The absorption characteristics were the results of O–H stretching in the lattices of various hydrous minerals, in particular, clay minerals, constituting altered/weathered rocks and soils. SAM and SFF techniques implemented in Spectral Analyst were applied to identify the minerals present in the scene. A score of 0–1 was generated for both SAM and SFF, where a value of 1 indicated a perfect match showing the exact mineral type. Endmember spectra were matched with those of the minerals as available in the United States Geological Survey Spectral Library. Four minerals, oligoclase, rectorite, kaolinite and desert varnish, have been identified in the studied area. The SAM classifier was then applied to produce a mineral map over a subset of the Hyperion scene. The dominant lithology of the area included Dongargarh granite, Bijli rhyolite and Pitepani volcanics of Palaeo-Proterozoic age. Feldspar is one of the most dominant mineral constituents of all the above-mentioned rocks, which is highly susceptible to chemical weathering and produces various types of clay minerals. Oligoclase (a feldspar) was found in these areas where mostly rock outcrops were encountered. Kaolinite was also found mainly near exposed rocks, as it was formed due to the weathering of feldspar. Rectorite is the other clay mineral type that is observed mostly in the southern part of the studied area, where Bijli rhyolite dominates the lithology. However, the most predominant mineral type coating observed in this study is desert varnish, which is nothing but an assemblage of very fine clay minerals and forms a thin veneer on rock/soil surfaces, rendering a dark appearance to the latter. Thus, from this study, it could be inferred that Hyperion data can be well utilized to identify and map altered/weathered and clay minerals based on the study of the shape, size and position of spectral absorption features, which were otherwise absent in the signatures of the broadband sensors.
Extracted statement — Techniques/Methods: Spectral Angle Mapper (SAM)
Research field: Earth Sciences
Title: The spectral analysis and information extraction for small geological target detection using hyperion image
Abstract: Imaging spectroscopic technique has been used for the mineral and rock geological mapping and alteration information extraction successfully with many reasonable results, but it is mainly used in arid and semi-arid land with low vegetation covering. In the case of the high vegetation covering, the outcrop of the altered rocks is small and distributes sparsely, the altered rocks is difficult to be identified directly. The target detection technique using imaging spectroscopic data should be introduced to the extraction of small geological targets under high vegetation covering area. In the paper, we take Ding-Ma gold deposit as the study area which located in Zhenan country, Shanxi province, the spectral features of the targets and the backgrounds are studied and analyzed using the field reflectance spectra, in addition to the study of the principle of the algorithms, some target detection algorithms which is appropriate to the small geological target detection are introduced. At last, the small altered rock targets under the covering of vegetation in forest are detected and discriminated in imaging spectroscopy data with the methods of spectral angle mapper (SAM), Constrained Energy Minimization (CEM) and Adaptive Cosine Estimator (ACE). The detection results are reasonable and indicate the ability of target detection algorithms in geological target detection in the forest area.
Extracted statement — Techniques/Methods: Spectral Angle Mapper (SAM)
Research field: Earth Sciences
Title: The Performance of Maximum Likelihood, Spectral Angle Mapper, Neural Network and Decision Tree Classifiers in Hyperspectral Image Analysis
Abstract: Several classification algorithms for pattern recognition had been tested in the mapping of tropical forest cover using airborne hyperspectral data. Results from the use of Maximum Likelihood (ML), Spectral Angle Mapper (SAM), Artificial Neural Network (ANN) and Decision Tree (DT) classifiers were compared and evaluated. It was found that ML performed the best followed by ANN, DT and SAM with accuracies of 86%, 84%, 51% and 49% respectively.
Extracted statement — Techniques/Methods: Spectral Angle Mapper (SAM)
Research field: Earth Sciences
Title: Mapping hydrothermal alteration minerals using high-resolution AVIRIS-NG hyperspectral data in the Hutti-Maski gold deposit area, India
Abstract: ABSTRACT The present study exploits high-resolution hyperspectral imagery acquired by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor from the Hutti-Maski gold deposit area, India, to map hydrothermal alteration minerals. The study area is a volcanic-dominated late Archean greenstone belt that hosts major gold mineralization in the Eastern Dharwar Craton of southern India. The study encompasses pre-processing, spectral and spatial image reduction using Minimum Noise Fraction (MNF) and Fast Pixel Purity Index (FPPI), followed by endmember extraction using n-dimensional visualizer and the United States Geological Survey (USGS) mineral spectral library. Image derived endmembers such as goethite, chlorite, chlorite at the mine site (chlorite mixed with mined materials), kaolinite, and muscovite were subsequently used in spectral mapping methods such as Spectral Angle Mapper (SAM), Spectral Information Divergence (SID) and its hybrid, i.e. SIDSAMtan. Spectral similarity matrix of the target and non-target-based method has been proposed to find the possible optimum threshold needed to obtain mineral map using spectral mapping methods. Relative Spectral Discrimination Power (RSDPW) and Confusion Matrix (CM) have been used to evaluate the performance of SAM, SID, and SIDSAMtan. The RSDPW and CM illustrate that the SIDSAMtan benefits from the unique characteristics of SAM and SID to achieve better discrimination capability. The Overall Accuracy (OA) and kappa coefficient (ҡ) of SAM, SID, and SIDSAMtan were computed using 900 random validation points and obtained 90% (OA) and 0.88 (ҡ), 91.4% and 0.90, and 94.4% and 0.93, respectively. Obtained mineral map demonstrates that the northern portion of the area mainly consists of muscovite whereas the southern part is marked by chlorite, goethite, muscovite and kaolinite, indicating the propylitic alteration. Most of these minerals are associated with altered metavolcanic rocks and migmatite.
Extracted statement — yields: Spectral Angle Mapper (SAM)