Advanced Spaceborne Thermal Emission And Reflection Radiometer Satellite Research Articles

Interpretation of hydrothermal alteration and structural framework of the Huize Pb–Zn deposit, SW China, using Sentinel-2, ASTER, and Gaofen-5 satellite data: Implications for Pb–Zn exploration

The Huize Pb–Zn deposit is one of the largest and high–grade Pb–Zn deposits in the world, containing more than 7 Mt Pb and Zn reserves at an ore grade of ∼30–35 % Pb + Zn. Therefore, brownfield exploration of additional Pb and Zn orebodies at Huize Pb–Zn deposit is of high priority. Hydrothermal alteration minerals and structural features are typically associated with Pb–Zn mineralization, which can be identified quickly and economically using a multi-source remote sensing satellite dataset. In this study, Sentinel-2, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Gaofen-5 (GF-5) satellite remote sensing imagery were employed for brownfield exploration of additional Pb–Zn orebodies in the Huize Pb–Zn deposit. The Sentinel-2 satellite remote sensing imagery was used to interpret the structure and map oxides/hydroxides by implementing the band ratio (BR) and principal components analysis (PCA) method; the ASTER satellite data were applied to map argillic, quartz, and carbonate hydrothermal alteration minerals using the PCA method; the GF-5 satellite data were utilized to map hematite, kaolinite, calcite, and dolomite minerals by the mixture tuned matched filtering (MTMF) method; and the mapped hydrothermal alteration information was verified by field reconnaissance and laboratory analysis. Finally, remote sensing geological exploration characteristics of the Huize Pb–Zn deposit were summarized by comprehensively analyzing the hydrothermal alteration minerals and structural characteristics, and three new brownfield exploration target zones of Pb–Zn mineralization were delineated. The study can provide a reference for the brownfields exploration in the vicinity of an existing Pb–Zn deposit around the world.

Mapping of mafic-ultramafic rocks in SMUC-SGT, India using ASTER & Sentinel-2A satellite images

The Salem Mafic–Ultramafic Complex (SMUC) is a major complex in southern Granulite Terrane (SGT), in the northern part of the Cauvery Suture Zone (CSZ), India, also known as the Chalk Hills of Salem. The present study aims to review the efficiency of satellite image processing and related techniques to map the Mafic-Ultramafic rocks in Salem Mafic-Ultramafic Complex (SMUC). This mapping is done using atmospherically corrected Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Sentinel-2A satellite image data. The processes employed were image enhancement techniques like Band Combinations (BC), Principal Component Analysis (PCA), and Minimum Noise Fraction (MNF) to map the various rock types. Band combinations constructed from the output of PCA and MNF in RGB format showed promising results in discriminating various rock units. The Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) classifications techniques were used to classify ASTER and Sentinel-2A satellite images for the study area. The classified lithologies showed strong match with the lithology map published by the Geological Survey of India (GSI), other researches, and field investigation. Particularly, SVM classification of Sentinel-2A MNF + DEM showed 90% overall accuracy when compared with field investigation. The study proved that the processing of VNIR and SWIR bands of ASTER and Sentinel-2A Satellite images coupled with DEM and ground investigation has excellent potential in mapping Mafic-Ultramafic rocks in SMUC SGT.

ASTER and GF-5 Satellite Data for Mapping Hydrothermal Alteration Minerals in the Longtoushan Pb-Zn Deposit, SW China

Hydrothermal alteration minerals are an effective prospecting indicator. Advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite data are some of the most commonly adopted multispectral data for the mapping of hydrothermal alteration minerals. Compared to multispectral data, hyperspectral data have stronger ground object recognition ability. Chinese Gaofen-5 (GF-5) is the first hyperspectral satellite independently developed by China that has the advantages of both wide-width and high-spectral-resolution technology. However, the mapping ability of GF5 data for hydrothermal alteration minerals requires further study. In this study, ASTER and GF-5 satellite data were implemented to map hydrothermal alteration minerals in the Longtoushan Pb-Zn deposit, SW China. Selective principal component analysis (SPCA) technology was employed to map iron oxide/hydroxides, argillic, quartz, and carbonate minerals at the pixel level using ASTER data, and the mixture tuned matched filtering (MTMF) method was implemented for the extracted hematite, kaolinite, calcite, and dolomite at the sub-pixel level using GF-5 data. When mapping the hydrothermal alteration minerals, the distribution features of the hydrothermal alteration minerals from the Longtoushan Pb-Zn deposit were systematically revealed. A comprehensive field investigation and petrographic study were conducted to verify the extraction accuracy of the hydrothermal alteration minerals. The results showed that the overall accuracies for the ASTER and GF-5 data were 82.6 and 92.9 and that the kappa coefficients were 0.78 and 0.90, respectively. This indicates that the GF-5 data are able to map hydrothermal alteration minerals well and that they can be promoted as a hyperspectral data source for mapping systematic hydrothermal alteration minerals in the future.

Identification of Phyllosilicates in the Antarctic Environment Using ASTER Satellite Data: Case Study from the Mesa Range, Campbell and Priestley Glaciers, Northern Victoria Land

In Antarctica, spectral mapping of altered minerals is very challenging due to the remoteness and inaccessibility of poorly exposed outcrops. This investigation evaluates the capability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite remote sensing imagery for mapping and discrimination of phyllosilicate mineral groups in the Antarctic environment of northern Victoria Land. The Mixture-Tuned Matched-Filtering (MTMF) and Constrained Energy Minimization (CEM) algorithms were used to detect the sub-pixel abundance of Al-rich, Fe3+-rich, Fe2+-rich and Mg-rich phyllosilicates using the visible and near-infrared (VNIR), short-wave infrared (SWIR) and thermal-infrared (TIR) bands of ASTER. Results indicate that Al-rich phyllosilicates are strongly detected in the exposed outcrops of the Granite Harbour granitoids, Wilson Metamorphic Complex and the Beacon Supergroup. The presence of the smectite mineral group derived from the Jurassic basaltic rocks (Ferrar Dolerite and Kirkpatrick Basalts) by weathering and decomposition processes implicates Fe3+-rich and Fe2+-rich phyllosilicates. Biotite (Fe2+-rich phyllosilicate) is detected associated with the Granite Harbour granitoids, Wilson Metamorphic Complex and Melbourne Volcanics. Mg-rich phyllosilicates are mostly mapped in the scree, glacial drift, moraine and crevasse fields derived from weathering and decomposition of the Kirkpatrick Basalt and Ferrar Dolerite. Chlorite (Mg-rich phyllosilicate) was generally mapped in the exposures of Granite Harbour granodiorite and granite and partially identified in the Ferrar Dolerite, the Kirkpatrick Basalt, the Priestley Formation and Priestley Schist and the scree, glacial drift and moraine. Statistical results indicate that Al-rich phyllosilicates class pixels are strongly discriminated, while the pixels attributed to Fe3+-rich class, Fe2+-rich and Mg-rich phyllosilicates classes contain some spectral mixing due to their subtle spectral differences in the VNIR+SWIR bands of ASTER. Results derived from TIR bands of ASTER show that a high level of confusion is associated with mafic phyllosilicates pixels (Fe3+-rich, Fe2+-rich and Mg-rich classes), whereas felsic phyllosilicates (Al-rich class) pixels are well mapped. Ground truth with detailed geological data, petrographic study and X-ray diffraction (XRD) analysis verified the remote sensing results. Consequently, ASTER image-map of phyllosilicate minerals is generated for the Mesa Range, Campbell and Priestley Glaciers, northern Victoria Land of Antarctica.

A COMPARATIVE ANALYSIS OF SPECTRAL INFORMATION EXTRACTION ALGORITHMS FOR TARGET DETECTION OF HYDROTHERMAL ALTERATION ZONES USING ASTER SATELLITE IMAGE DATA

Abstract. The focus of this paper is to evaluate the performance of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data for target detection of hydrothermal alteration zones associated with geothermal (GT) springs as proxy for narrowing areas of interest. The study employed the Per-pixel Spectral Angle Mapper (SAM) and the Sub-pixel Linear Spectral Unmixing (LSU) algorithms for spectral information extraction by using the ASTER satellite image data. In both cases, image endmember spectra specifically for kaolinite, alunite, and illite and calcite zones were selected and extracted by using the Analytical Imaging and Geophysics (AIG)-developed processing methods. The results of the analysis show that both SAM and LSU discriminated targets of interest better when employing image spectra and poorly when using library spectra. However, the Per-pixel SAM is unsuitable for target detection and more suited where the objective of the investigation is to classify whole scene and not particular targets as in this case. The LSU was found to be effective for discriminating alterations associated with the thermal springs especially where image endmember spectra are employed for analysis, thus recommended for prefeasibility mapping of GT related resources.

ASTER and WorldView-3 satellite data for mapping lithology and alteration minerals associated with Pb-Zn mineralization

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and WorldView-3 (WV-3) satellite remote sensing data were used for mapping lithological units and hydrothermal alteration zones associated with Pb-Zn mineralization in the Kerman–Kashmar Tectonic Zone (KKTZ), Iran. The visible near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) bands of ASTER were used to map iron oxide/hydroxides, Al-OH minerals, Fe,Mg-OH minerals, quartz and carbonate minerals. The VNIR bands of WV-3 were used to discriminate Fe3+ and Fe2+ absorption intensities. Selective Principal Component analysis (SPCA), Spectral Angle Mapper (SAM), Linear Spectral Unmixing (LSU) and Automatic Lineament Extraction techniques were implemented. Lithological units were discriminated based on Al/Fe-OH, Fe2+/Fe3+ and Mg-Fe-OH/CO3 absorption properties. The spatial distribution of hematite, goethite, jarosite, gypsum, calcite, dolomite, kaolinite and muscovite were comprehensively detected. Some prospective zones were identified in the intersection of N-S, NW-SE and NE-SW trending fault systems, gossan, argillic/phyllic and dolomitic units.

Prospecting Fe-Skarn mineralization using ASTER satellite data: case study from Ravanj village, Markazi Province, Iran

The study area is located in Iran central zone and Urumieh-Dokhtar volcanoplutonic belt. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data was used to identify alteration zones associated with Fe-Skarn mineralization in the Ravanj village, Markazi Province, Iran. Argillic, phyllic and propylitic alteration zones are typically associated with Fe-Skarn mineralization in the study area. In this research, the Selective Principal Component Analysis (SPCA) method was applied to VNIR + SWIR bands of ASTER remote sensing data. Bands 1, 4, 6 and 8 were designated for identification clay minerals. Bands 4, 5, and 6 were selected for argillic alteration mapping. Bands 1, 2, and 4 were used to identification iron oxides/hydroxide minerals. Bands 5, 6, and 7 were chosen to map phyllic alteration zones. Bands 7, 8, and 9 were nominated to specify propylitic alteration mapping. According to the eigenvector statistics calculated using SPCA for ASTER, inverse SPC4 image identified clay minerals and SPC2 images detected argillic alteration, oxides/hydroxide minerals, phyllic alteration and propylitic alteration. In this paper, SPCA technique is an appropriate method because of the distinction between alteartion minerals, vegetation for Fe-Skarn mineralization exploration.

Mapping Listvenite Occurrences in the Damage Zones of Northern Victoria Land, Antarctica Using ASTER Satellite Remote Sensing Data

Listvenites normally form during hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represent a key indicator for the occurrence of ore mineralizations in orogenic systems. Hydrothermal/metasomatic alteration mineral assemblages are one of the significant indicators for ore mineralizations in the damage zones of major tectonic boundaries, which can be detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data were used to detect listvenite occurrences and alteration mineral assemblages in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL), Antarctica. Spectral information for detecting alteration mineral assemblages and listvenites were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineralogical assemblages containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were detected in the damage zones of the study area by implementing PCA/ICA fusion to visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate lithological groups were mapped and discriminated using PCA/ICA fusion to thermal infrared (TIR) bands of ASTER. Fraction images of prospective alteration minerals, including goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and possible zones encompassing listvenite occurrences were produced using LSU and CEM algorithms to ASTER VNIR+SWIR spectral bands. Several potential zones for listvenite occurrences were identified, typically in association with mafic metavolcanic rocks (Glasgow Volcanics) in the Bowers Mountains. Comparison of the remote sensing results with geological investigations in the study area demonstrate invaluable implications of the remote sensing approach for mapping poorly exposed lithological units, detecting possible zones of listvenite occurrences and discriminating subpixel abundance of alteration mineral assemblages in the damage zones of the Wilson-Bowers and Bowers-Robertson Bay terrane boundaries and in intra-Bowers and Wilson terranes fault zones with high fluid flow. The satellite remote sensing approach developed in this research is explicitly pertinent to detecting key alteration mineral indicators for prospecting hydrothermal/metasomatic ore minerals in remote and inaccessible zones situated in other orogenic systems around the world.

LITHOLOGICAL MAPPING USING LANDSAT 8 OLI AND ASTER MULTISPECTRAL DATA IN IMINI-OUNILLA DISTRICT SOUTH HIGH ATLAS OF MARRAKECH

Abstract. 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 and structural map in the south High Atlas of Marrakech. The method of analysis was used by principal component analysis (PCA), band ratios (BR), Minimum noise fraction (MNF) transformation. We performed a Support Vector Machine (SVM) classification method to allow the joint use of geomorphic features, textures and multispectral data of the Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite. 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. The application of the SVM methods on ASTER and Landsat satellite data show that these can be used as a powerful tool to explore and improve lithological mapping in mountainous semi-arid, the overall classification accuracy of Landsat8 OLI data is 97.28% and the Kappa Coefficient is 0.97. The overall classification accuracy of ASTER using nine bands (VNIR-SWIR) is 74.88% and the Kappa Coefficient is 0.71.

Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods

ABSTRACTLithological mapping using satellite images, particularly the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data help in effectively defining the best initial targets for regional exploration. ASTER data allow for the discrimination of rock units in the broader region. This research work is focused on the use of remote sensing techniques for geological mapping using ASTER satellite image and generating a geological map of Sangan region. The study area is located in southeast of Khorasan-e-Razavi province and at the eastern edge of the Khaf-Kashmar-Bardskan Volcano-Plutonic Metallogenic Belt in northeast Iran. Band ratio (BR), spectral angle mapper (SAM) and support vector machines (SVMs) methods were used for classifying the main lithologic units in Sangan region. The results of BR, SAM and SVM techniques were quantitatively compared with geological boundaries mapped in the field showing an accuracy of nearly 79 %. SVMs method, in comparison to conventional methods of classification, was known to provide superior results. As the final result of this research, integration of remote sensing and field investigations led to generating high accuracy geological map in the Sangan region. Application of the methods has invaluable implications for geological mapping and mineral exploration in inaccessible regions.

Integration of SPOT-5 and ASTER satellite data for structural tracing and hydrothermal alteration mineral mapping: implications for Cu–Au prospecting

ABSTRACTThe integration of information extracted from the Syste`m Pour l’Observation de la Terre (SPOT) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, comprehensive field and mineralogy studies demonstrates that phyllic alteration zone associated with northwestern (NW)–southeastern (SE) structural fractures is a high potential zone for Cu–Fe–Au vein-type mineralisation in the Bajestan region, the Lut block, east Iran. The fractal pattern was calculated for fractures map using the Box-Counting algorithm to the SPOT-5 data. Statistical parameters of fractures, such as density, intensity and fractures’ intersection were also determined. Band composition, specialised band ratio and Spectral Angle Mapper (SAM) classification methods were implemented to the ASTER dataset for detecting hydrothermal alteration zones, such as propylitic, phyllic, argillic and gossan. Results indicate that the maximum value of the fractal dimension, intensity, density and the intersection of the fractures are concentrated in the NW and SE parts of SPOT image maps. In the other hand, phyllic alteration zone containing sericite, alunite, kaolinite and jarosite mineral assemblages was also identified in several zones of the NW and SE parts of the ASTER image maps. Integration of the results indicates the high potential zones for the occurrence of Cu–Fe–Au mineralisation in the Bajestan region.

Thermal sharpening of land surface temperature maps based on the impervious surface index with the TsHARP method to ASTER satellite data: A case study from the metropolitan Kuala Lumpur, Malaysia

Measuring high spatial/temporal land surface temperature (LST) is a significant key in urban climate studies. Current satellite thermal sensors have a trade-off in their spatial and temporal resolution. The objective of this study is to develop an adaptive thermal sharpening (TsHARP) algorithm to downscale LST by utilizing impervious surface (IS) index in urban areas. The study utilizes the aggregated sharpened LST retrieved from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) L1B image derived over Kuala Lumpur, Malaysia on the 14th Feb 2003. Kuala Lumpur is among the fastest growing metropolitan regions in terms of population and economy in South-East Asia. With the application of the proposed downscaling procedure on ASTER data covering Kuala Lumpur, it was found that all the evaluated resolutions attained superior results compared to the traditional methods of over urban imagery particularly for environments with heterogeneous land covers. Furthermore, the proposed adaptive TsHARP method showed optimal performance at the 240 m resolution with a correlation coefficient of R2 = 0.85 and RMSE 1.83 °C. The model enhances the capability of the adapted TsHARP in unmixing temperature with decreasing resolution. It concluded that applying such improved technique to ASTER satellite data is an urgent and cost-effective application, which is indeed very timely to input for urban/cities landscape planning for metropolitan regions around the world.

Identification of hydrothermal alteration minerals associated with geothermal system using ASTER and Hyperion satellite data: a case study from Yankari Park, NE Nigeria

Concealed and fossilized geothermal systems are not characterized by obvious surface manifestations like hotsprings and fumaroles, therefore, could not be easily identifiable using conventional techniques. In this investigation, the applicability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion data-sets were evaluated in discriminating hydrothermal alteration minerals associated with geothermal systems as a proxy in identifying subtle Geothermal systems at Yankari Park, Nigeria. Feature-oriented principal component selection, spectral angle mapper, linear spectral unmixing were applied to ASTER data based on spectral characteristics of hydrothermal alteration key minerals for a systematic selective extraction of the information of interest. Analytical imaging and geophysics-developed processing methods were applied to Hyperion data for mapping iron oxide/hydroxide minerals and clay mineral assemblages in hydrothermal alteration zones. The results indicate that ASTER and Hyperion could be complemented for reconnaissance stage of targeting subtle alteration mineral assemblages associated with geothermal systems.

Lithological and alteration mineral mapping in poorly exposed lithologies using Landsat-8 and ASTER satellite data: North-eastern Graham Land, Antarctic Peninsula

Antarctica remains a remote and logistically difficult region to conduct geological field mapping and mineral exploration. Remote sensing satellite imagery has high potential to provide a solution to overcome the difficulties and limitations associated with geological field mapping and mineral exploration in inaccessible regions. In this study, the applications of Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were investigated to extract geological information for lithological and alteration mineral mapping in poorly exposed lithologies located in inaccessible regions. The north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping approach. A two-stage methodology was adopted to distinguish pixel and sub-pixel targets in the satellite images. In the first stage, Continuum Removal (CR) spectral mapping tool and Independent Components Analysis (ICA) technique were applied to Landsat-8 and ASTER spectral bands to map the pixels related to poorly exposed lithological units. The second step was established based on the application of target detection algorithms to shortwave infrared bands of ASTER for detecting spectral features attributed to alteration mineral assemblages at the sub-pixel level. Pixels composed of distinctive absorption features of alteration mineral assemblages and Si-O bond emission minima features were detected by applying CR mapping tool to reflective and thermal bands of Landsat-8 and ASTER. Anomaly pixels related to spectral features of Al-O–H, Fe, Mg-O–H and CO3 groups as well as lithological attributions from felsic to mafic rocks were detected by the implementation of ICA technique to reflective and thermal bands of Landsat-8 and ASTER. ICA method provided image maps of alteration mineral assemblages and lithological units (mafic to felsic trend) for poorly mapped and/or unmapped regions. Fractional abundance of alteration minerals such as muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite were detected in poorly exposed lithologies using target detection algorithms. Several prospecting areas for Cu, Mo, Au and Ag mineralization related to propyllitically and argillically altered units of Andean Intrusive Suite (AIS) were identified in the southern sector of the study region. The results of this investigation demonstrated the applicability of Landsat-8 and ASTER spectral data for lithological and alteration mineral mapping in poorly exposed lithologies located in inaccessible regions, particularly using the image processing algorithms that are capable of detecting anomaly pixels and sub-pixel targets in the remotely sensed images, where no prior information is available. In conclusion, a simple and robust satellite-based remote sensing approach for mapping poorly exposed lithologies in inaccessible regions was established, which is comprehensively applicable for lithological and alteration mineral mapping in the Antarctic environments and hydrothermal ore minerals prospecting in other inaccessible regions around the world.

산사태 취약성 분석: ASTER 위성영상을 이용한 점토광물인자 추출 및 공간데이터베이스의 SVM 통계기법 적용

ASTER 위성영상을 이용하여 팽창성 점토광물인 일라이트 인자 추출 및 SVM 통계분석을 통해 산사태 취약성을 평가하였다. 연구지역의 산사태 발생지역은 항공사진 판독 및 현장 조사를 통해 분석하였다. GIS 기반 공간데이터베이스로는 지형도, 토양도, 임상도, ASTER 위성사진을 이용하였다. 수치지형도에서는 경사 및 경사방향, 곡률도, 계곡과의 거리, 도로와의 거리, 토양도에서는 유효토심, 토질, 토양지형, 토양 배수정도 및 토양 모재, 임상도에서는 경급, 영급 및 밀도를 위성사진에서는 일라이트 인자를 추출하였다. 산사태 발생요인 데이터베이스와 SVM 통계분석 및 가중치 계산을 통해 각 요소간의 상관관계 취약성도를 구하였다. AUC 검증 결과 일라이트 인자 적용결과는 76.46%의 예측 정확도를 보였으며 일라이트 인자 미적용 모델은 74.09%의 예측 정확도를 나타내었다. 이는 일라이트 인자가 산사태 취약성도 작성에 있어 중요한 자료로 사용될 수 있음을 나타낸다. This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

CHROMITITE PROSPECTING USING LANDSAT TM AND ASTER REMOTE SENSING DATA

Abstract. Studying the ophiolite complexes using multispectral remote sensing satellite data are interesting because of high diversity of minerals and the source of podiform chromitites. This research developed an approach to discriminate lithological units and detecting host rock of chromitite bodies within ophiolitic complexes using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat Thematic Mapper (TM) satellite data. Three main ophiolite complexes located in south of Iran have been selected for the study. Spectral transform techniques, including minimum noise fraction (MNF) and specialized band ratio were employed to detect different rock units and the identification of high-potential areas of chromite ore deposits within ophiolitic complexes. A specialized band ratio (4/1, 4/5, 4/7) of ASTER, MNF components and Spectral Angle Mapper (SAM) on ASTER and Landsat TM data were used to distinguish ophiolitic rock units. Results show that the specialized band ratio was able to identify different rock units and serpentinized dunite as host rock of chromitites within ophiolitic complexes, appropriately. MNF components of ASTER and Landsat TM data were suitable to distinguish ophiolitic rock complexes at a regional scale. The integration of SAM and Feature Level Fusion (FLF) used in this investigation discriminated the ophiolitic rock units and prepared detailed geological map for the study area. Accordingly, high potential areas (serpentinite dunite) were identified in the study area for chromite exploration targets.The approach used in this research offers the image processing techniques as a robust, reliable, fast and cost-effective method for detecting serpentinized dunite as host rock of chromitite bodies within vast ophiolite complexes using ASTER and Landsat TM satellite data.

Unsupervised Global Urban Area Mapping via Automatic Labeling from ASTER and PALSAR Satellite Images

In this study, a novel unsupervised method for global urban area mapping is proposed. Different from traditional clustering-based unsupervised methods, in our approach a labeler is designed, which is able to automatically select training samples from satellite images by propagating common urban/non-urban knowledge through the unlabeled data. Two kinds of satellite images, captured by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Phased Array L-band Synthetic Aperture Radar (PALSAR), are exploited here. In this method, spectral features are first extracted from the original dataset, followed by coarse prediction of urban/non-urban areas via weak classifiers. By developing an improved belief-propagation based clustering algorithm, a confidence map is obtained and training data are selected via weighted sampling. Finally, the urban area map is obtained by employing the Support Vector Machine (SVM) classifier. The proposed method can generate urban areamaps at a resolution of 15 m, while the same settings are used for all test cases. Experimental results involving 75 scenes from different climate zones show that our proposed method achieves an overall accuracy of 84.4% and a kappa coefficient of 0.628, which is competitive relative to the supervised SVM method.

Separation of Different Vegetation Types in ASTER and Landsat Satellite Images Using Satellite‐derived Vegetation Indices

Separation of different vegetation types in satellite images is a critical issue in remote sensing. This is because of the close reflectance between different vegetation types that it makes difficult segregation of them in satellite images. In this study, to facilitate this problem, different satellite derived vegetation indices including: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Enhanced Vegetation Index 2 (EVI2) were derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat-5 TM data. The obtained NDVI, EVI, and EVI2 images were then analyzed and interpreted in order to evaluate their effectiveness to discriminate rice and citrus fields from ASTER and Landsat data. In doing so, the Density Slicing (DS) classification technique followed by the trial and error method was implemented. The results indicated that the accuracies of ASTER NDVI and ASTER EVI2 for citrus mapping are about 75% and 65%, while the accuracies of Landsat NDVI and Landsat EVI for rice mapping are about 60% and 65%, respectively. The achieved results demonstrated higher performance of ASTER NDVI for citrus mapping and Landsat EVI for rice mapping. The study concluded that it is difficult to detect and map rice fields from satellite images using satellite-derived indices with high accuracy. However, the citrus fields can be mapped with the higher accuracy using satellite-derived indices.

점토광물의 분광반사율 및 ASTER 위성영상을 이용한 산사태 발생지역 분석

The purpose of this study is to analyze the key factors that contribute to landslide causes through swelling clay minerals and terrain analysis in landslide sites taken place of in Yongin city, Gyeonggi-do, 2011. The study was conducted based on field survey by XRD (X-ray Diffraction), XRF (X-ray fluorescence), spectroscopic analysis on soil samples obtained from landslide sites and ASTER satellite image. Illite shows absorption features; and at 0.9 and , broad water absorption features near 1.4 and , and additional Al-hydroxyl features at 2.2, 2.3 and , respectively. These absorption features are consistent with the bands 5, 6, and 7 of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite image. Illite image was extracted using band math of . From these results, we confirmed the applicability of ASTER satellite image using identification of swelling clay minerals to landslide study.

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

The mineral ore potential of many mountainous regions of the world, like the Kurdistan region of Iraq, remains unexplored. For logistical and sometimes political reasons, these areas are difficult to map using traditional methods. We highlight the improvement in remote sensing geological mapping that arises from the integration of geomorphic features in classifications. The Mawat Ophiolite Complex (MOC) is located in the NE of Iraq and is known for its mineral deposits. The aims of this study are: (I) to refine the existing lithological map of the MOC; (II) to identify the best discriminatory datasets for lithological classification, including geomorphic features and textures; and (III) to identify potential locations with high concentrations of chromite. We performed a Support Vector Machine (SVM) classification method to allow the joint use of geomorphic features, textures and multispectral data of the Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite. The updated map allowed the identification of a new mafic body and a substantial improvement of the geometry of the known lithological units. The use of geomorphic features allowed for the increase of the overall accuracy from 73% to 79.3%. In addition, we detected chromite occurrences within the ophiolite by applying Spectral Angle Mapping (SAM) technique. We identified two new locations having high concentrations of chromite and verified one of these promising areas in the field. This new body covers ~0.3 km2 and has coarsely crystalline chromite within dunite host rock. The chromium (Cr2O3) concentration is ~8.46%. The SAM and SVM methods applied on ASTER satellite data show that these can be used as a powerful tool to explore ore deposits and to further improve lithological mapping in mountainous semi-arid regions.