Advanced Spaceborne Thermal Emission And Reflection Radiometer Satellite Data 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.

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.

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.

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.

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.

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.

Detection of hydrothermal mineralized zones associated with listwaenites in Central Oman using ASTER data

Listwaenites are highly altered ultramafic rocks that are potentially associated with economic mineralization and research on these is extremely important worldwide. In the present study, the classification of mineralized listwaenites developed along the serpentinite–amphibolite interface of the Semail Ophiolite, its associated lithology and the zones of alteration and mineralization in the Fanjah Saddle of the Central Oman Mountains region of the Sultanate of Oman are carried out, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data. The developed band ratioing, Principal Component Analysis (PCA) and the Spectral Angle Mapper (SAM) supervised classification and image processing techniques applied on the ASTER data set have proved their capability for better interpretation and identification of hydrothermally altered rocks and associated mineralization. The hyperspectral tools (Minimum Noise Fraction (MNF), Pixel Purity Index (PPI) and nD-visualizer) extracted end member spectra and SAM classification clearly show the occurrence of minerals and their spatial distributions.The promising results are verified and confirmed in the field by identification of alteration and mineralization such as listwaenites, silicification, serpentinization and talc alteration and are validated further through laboratory analysis. The confirmation of the occurrence of base metal mineralization along the serpentinite–amphibolite interface in listwaenites suggests that detailed investigation in this and other arid regions which have similar geological conditions may locate mineral deposits. The hyperspectral tools applied on ASTER satellite data show that these can be used as a powerful tool to explore the listwaenites and the potential associated mineralization in other arid geographical regions worldwide.

Assessment of multispectral glacier mapping methods and derivation of glacier area changes, 1978–2002, in the central Southern Alps, New Zealand, from ASTER satellite data, field survey and existing inventory data

AbstractWe have measured the glacier area changes in the central Southern Alps, New Zealand, between 1978 and 2002 and have compiled the 2002 glacier outlines using an image scene from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Three automated classification methods were tested: (1) band ratio, (2) normalized-difference snow index and (3) supervised classification. The results were compared with the glacier outlines photo-interpreted from the ASTER data, and were further validated using GPS-aided field mapping of selected test glaciers. The ASTER 3/4 band ratio provided the best results. However, all the classification methods failed to extract extensive debris-covered parts of the glaciers. Therefore, the photo-interpreted 2002 outlines were used when comparing with the existing 1978 glacier inventory derived from aerial photographs. Our results show a ∼17% reduction of glacier area, mainly driven by the retreat of the large valley glaciers. Despite the large climatic gradient from west to east, glaciers on both sides of the Main Divide lost similar percentages of area, except Franz Josef and Fox Glaciers which advanced. Smaller glaciers were found to have changed very little in the study period.

Identification and mapping of soil erosion areas in the Blue Nile, Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

Abstract. The area of the Upper Blue Nile in Eastern Sudan is considered prone to soil erosion which is an important indicator of the land degradation process. In this study, an erosion identification and mapping approach is developed based on adaptations to the regional characteristics of the study area and the availability of data. This approach is derived from fusion between remote sensing data and geographical information systems (GIS). The developed model is used to map the spatial distribution of soil erosion caused by the rains of 2006 using automatic classification of multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Shuttle Radar Topography Mission (SRTM) digital elevation model is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gully, Flat_land, Mountain and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently, the results are up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS) products of the same dates. Because the selected study site is representative of the wider Blue Nile region, it is expected that the approach presented could be applied to larger areas.

Using ASTER satellite data to calculate riparian evapotranspiration in the Middle Rio Grande, New Mexico

Riparian evapotranspiration (ET) in the Rio Grande Basin in New Mexico, USA is a major component of the hydrological system. Over a period of several years, ET has been measured in selected locations of dense saltcedar and cottonwood vegetation. Riparian vegetation varies in density, species and soil moisture availability, and to obtain accurate measurements, multiple sampling points are needed, making the process costly and impractical. An alternative solution involves using remotely sensed data to estimate ET over large areas. In this study, daily ET values were measured using eddy covariance flux towers installed in areas of saltcedar and cottonwood vegetation. At these sites, remotely sensed satellite data from the National Aeronautics and Space Administration (NASA) Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to calculate the albedo, normalized difference vegetation index (NDVI) and surface temperature. A surface energy balance model was used to calculate ET values from the ASTER data, which were available for 7 days in the year. Comparison between the daily ET values of saltcedar and cottonwood measured from the flux towers and calculated from remote sensing resulted in a mean square error (MSE) of 0.16 and 0.37 mm day−1, respectively. The regional map of ET generated from the remote sensing data demonstrated considerable variation in ET, ranging from 0 to 9.8 mm day−1, with a mean of 5.5 mm day−1 and standard deviation of 1.85 mm day−1 (n = 427481 pixels) excluding open water. This was due to variations in plant variety and density, soil type and moisture availability, and the depth to water table.

Preliminary results for a semi-automated quantification of site effects using geomorphometry and ASTER satellite data for Mozambique, Pakistan and Turkey

Estimation of the degree of local seismic wave amplification (site effects) requires precise information about the local site conditions. In many regions of the world, local geologic information is either sparse or is not readily available. Because of this, seismic hazard maps for countries such as Mozambique, Pakistan and Turkey are developed without consideration of site factors and, therefore, do not provide a complete assessment of future hazards. Where local geologic information is available, details on the traditional maps often lack the precision (better than 1:10,000 scale) or the level of information required for modern seismic microzonation requirements. We use high-resolution (1:50,000) satellite imagery and newly developed image analysis methods to begin addressing this problem. Our imagery, consisting of optical data and digital elevation models (DEMs), is recorded from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor system. We apply a semi-automated, object-oriented, multi-resolution feature segmentation method to identify and extract local terrain features. Then we classify the terrain types into mountain, piedmont and basin units using geomorphometry (topographic slope) as our parameter. Next, on the basis of the site classification schemes from the Wills and Silva (1998) study and the Wills et al (2000) and Wills and Clahan (2006) maps of California, we assign the local terrain units with Vs30 (the average seismic shear-wave velocity through the upper 30m of the subsurface) ranges for selected regions in Mozambique, Pakistan and Turkey. We find that the applicability of our site class assignments in each region is a good first-approximation for quantifying local site conditions and that additional work, such as the verification of the terrain’s compositional rigidity, is needed.

Visual interpretation of ASTER satellite data, Part 1: Geologic mapping in the Cradle of Humankind World Heritage Site

Since the first earth observing satellite was launched in 1972, remote sensing has become a powerful tool in the arsenal of geoscientists. This satellite became known as Landsat 1 and carried the Multispectral Scanner (MSS) delivering imagery at a spatial resolution of 80, and spectral resolution from blue to near infrared. Ongoing satellite and sensor development to the end of the century produced the Landsat Thematic Mapper (TM) with improved spatial and spectral resolution, as well as the SPOT series of satellites delivering the highest spatial but limited spectral resolution. These developments culminated in the SPOT 4 (1998) and Landsat Enhanced Thematic Mapper (1999) sensors. While Landsat ETM in particular provided much improved spatial and spectral resolutions, on the basis of which a large amount of geoscientific remote sensing was conducted world wide, the data did not provide adequate spectral and spatial sensitivity to be optimally effective for geological mapping at the local scale. On 18 December 1999 the Terra platform was launched, carrying five remote sensing instruments, including ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer). ASTER consists of three separate instrument subsystems, each operating in a different spectral region, and using separate optical systems. These are the Visible and Very Near Infrared (VNIR) subsystem with a 15m-spatial resolution, the Short Wave Infrared (SWIR) subsystem with a 30m-spatial resolution and the Thermal Infrared (TIR) subsystem with a 90m-spatial resolution. ASTER effectively offers an improvement on Landsat MSS, Landsat TM, Landsat ETM+ and SPOT spectral and spatial resolutions. Given the paucity of published research on geological remote sensing at the local scale in South Africa, and particularly on the use of ASTER for geological mapping in South Africa, it is imperative that the value of ASTER be investigated. This article reports on the improved detail and scale achieved in the mapping of litho-stratigraphy, geological structures and mining-related features by the visual interpretation of processed ASTER images. ASTER imagery obtained from the EOS website was subjected to a range of image enhancement and analysis techniques including colour composites, band ratios, normalised difference indices, regression and decorrelation, in order to obtain optimal visual interpretability. Eight images thus obtained could be used for visual analysis, and it became evident that litho-stratigraphy, faults, fracture zones and elements of the regional seam system, as well as remnants of mining activities, were readily identifiable. Some of these were in accordance with the most recent and accurate geological map of the area, but many of them had apparently not been mapped. These features were annotated and were verified by field checks. In all cases the accuracy of detection and location from satellite imagery was confirmed on the ground. The improved detail and accuracy obtained by visual interpretation of processed ASTER satellite data for mapping a section of the Cradle of Humankind World Heritage Site demonstrated the potential value of this data for a variety of other geoscience applications. It appears that the improved accuracy can be ascribed jointly to the higher spatial and spectral resolution provided by ASTER data.

Estimating aboveground tree biomass and leaf area index in a mountain birch forest using ASTER satellite data

Biomass and leaf area index (LAI) are important variables in many ecological and environmental applications. In this study, the suitability of visible to shortwave infrared advanced spaceborne thermal emission and reflection radiometer (ASTER) data for estimating aboveground tree and LAI in the treeline mountain birch forests was tested in northernmost Finland. The biomass and LAI of the 128 plots were surveyed, and the empirical relationships between forest variables and ASTER data were studied using correlation analysis and linear and non‐linear regression analysis. The studied spectral features also included several spectral vegetation indices (SVI) and canonical correlation analysis (CCA) transformed reflectances. The results indicate significant relationships between the biomass, LAI and ASTER data. The variables were predicted most accurately by CCA transformed reflectances, the approach corresponding to the multiple regression analysis. The lowest RMSEs were 3.45 t ha−1 (41.0%) and 0.28 m2m−2 (37.0%) for biomass and LAI respectively. The red band was the band with the strongest correlation against the biomass and LAI. SR and NDVI were the SVIs with the strongest linear and non‐linear relationships. Although the best models explained about 85% of the variation in biomass and LAI, the undergrowth vegetation and background reflectance are likely to affect the observed relationships.