Advanced Spaceborne Thermal Emission And Reflection Radiometer Images Research Articles

Integrated Approach for Lithological Classification Using ASTER Imagery in a Shallowly Covered Region—The Eastern Yanshan Mountain of China

This paper studied the applicability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data for lithological classification in the shallowly covered Eastern Yanshan Mountain of Eastern China. The interpreted objects include quartz sandstone, carbonate rock, gneiss, and andesite. An integrated approach was employed to process the remote sensing data: First, the matched filtering method, accompanied by the ASTER library and imagery spectra as reference, was used to enhance the targeted information, namely the remotely visible (typical) rock outcrops. As the andesite is frequently weathered to iron-rich minerals in the field, so the high-resolution SPOT6 3/1 image, instead of the ASTER image, was used to locate the outcrops. Second, the fractal digital number-frequency algorithm was developed to preliminarily extract the lithology anomaly patches; and the obtained geological anomalies were generalized into three types: anomalies related to outcrops, anomalies caused by different forms of the same lithology, and random noise. Third, digital elevation model derived slope masks, in combination with the spatial intersection operation, was used to eliminate the pseudo-outcrop anomalies and noise. Finally, the accuracy assessment was conducted by referencing the local rock-outcrop database, and the misclassification rates for quartz sandstone, carbonate rock, gneiss, and andesite are 8.9%, 12.5%, 23%, and 48.3%, respectively. This study has contributed a useful case study for remote-sensing lithology mapping in shallowly covered areas, and the proposed method should have a great potential to be applied to many similar cases.

Validating (MNF) transform to determine the least inherent dimensionality of ASTER image data of some uranium localities at Central Eastern Desert, Egypt

One of the main determinations of geological remote sensing is to develop and improve different image processing algorithms and methods for mineral mapping and rock type discrimination. This paper investigates one of those sophisticated algorithms; the validity of Minimum Noise Fraction (MNF) components to improve the spectral separability of The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor image data of Terra satellite, and to develop a standard method of noise removal and image enhancement. Previous studies that used in image processing to eliminate MNF eigenvalues, eliminate values less than the unit. However, removing MNF eigenvalues more than this value and its effect on the data, has not been examined. Therefore, in this paper, we demonstrate that we can eliminate more than the unit up to 2 eigenvalue without a negative inherent effect on the origin data structure. A comparison study using different Image Quality Measures (IQMs) methods, has been accomplished on data distribution before and after MNF transformation of the original and atmospherically corrected data. Matched Filter (MF) classification was performed on data before and after MNF to map a chosen known alteration mineral (Kaolinite) by matching the image endmember spectra and its spectra from USGS library. By examining the spectral trends of specific mineral alteration type across these transformed channels, areas of interest that are unique by the related previous well-known uranium mineralization may become superficial apparent. This examination also showed how the use of MNF as a pre-processing technique could improve the capability to extract information from ASTER data of El-Missikat, El-Eridya and Kab Amiri areas in the Central Eastern desert as a case study district for uranium mineralization occurrences.

Hydrothermally altered mineral mapping using synthetic application of Sentinel-2A MSI, ASTER and Hyperion data in the Duolong area, Tibetan Plateau, China

The Duolong area is in a strong potential copper mineralization zone associated with felsic intrusions, and several porphyry copper deposits (PCDs) have been identified. The PCDs are characterized by hydrothermal alteration zones. In this study, Sentinel-2A MultiSpectral Instrument (MSI), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Hyperion data are combined to map hydrothermally altered minerals. Three temporal Sentinel-2A MSI images are processed by integrating the Crosta technique and the anomaly-overlaying selection method to map iron oxides and hydroxyl-bearing minerals. These approaches are implemented to omit interference-induced false anomalies. The six shortwave infrared (SWIR) bands of ASTER are used to extract information on Al-OH and Mg-OH group minerals. The distribution of Al-OH minerals in the ASTER image map corresponds to that of hydroxyl-bearing minerals in the MSI image map. A combination of minimum noise fraction (MNF), pixel purity index (PPI), n-dimensional visualizer (n-D Visualizer) and matched filtering (MF) is adopted to process the Hyperion image to obtain accurate hydrothermal alteration mapping results. The overall accuracy for mineral mapping is 92.75% and the kappa coefficient is 0.89. The results of the Hyperion image are spatially consistent with those of the Sentinel-2A MSI and ASTER images. The image processing results were validated by field investigations and spectral reflectance measurements. Hydrothermally altered rocks correspond well with the five PCDs in the Duolong area. Three mineralization prospects associated with felsic intrusions are discovered in accordance with the results. The methodologies and data are effective in detecting porphyry copper mineralization in other arid areas.

Application of remotely sensed data in detecting zinc-lead bearing mineralized zones in Westkunlun Huoshaoyun area

The combination of Landsat 8 Operational Land Imager (OLI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data is an efficient tool for mapping and interpreting lead-zinc mineralization in some area with high altitude or intensely rugged topography, where conventional geological mapping and systematic geochemical sampling become limitation and time consuming. This task is completed by using band ratios (BRs), principal component analysis (PCA), and spectral matched filtering (SMF) method. And it conclude that, (6/5, 7/6, 4/7) RGB color composite and (5/4, 6/5, 7/6) RGB color composite of Landsat 8 OLI, [(6+8)/4, 8/4, 5/3] RGB color composite and [3/2, (6+8)/4, 3/6] RGB composite of ASTER image, PC 3,4,5 of Landsat8 and ASTER images, contain useful information for lithological mapping. Lead-zinc mineralization zones could be exactly discriminated by spectral matched filtering (SMF) technique and ascertained by field work and XRD analysis. Consequently, the methodology proposed demonstrates a high potential of Landsat 8 OLI and ASTER data in lithological units discrimination and lead-zinc mineralization zones extraction in west Kunlun Mountains.

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.

Porphyry Copper Deposit Prognosis in the Middle Region of the Bangonghu–Nujiang Metallogenic Belt, Tibet, Using ASTER Remote Sensing Data

AbstractThe Bangonghu–Nujiang metallogenic belt is considered to be Tibet’s third copper belt after the Yulong and Gangdese copper belts. The Duolong gold‐rich porphyry copper deposit, located in the western part of the Bangonghu–Nujiang belt was recently recognized as a superlarge prospect. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) was used to characterize the Duolong porphyry deposit alteration area, and three methods, color enhancement, band ratio transformation, and spectral angle mapping, were utilized to extract the phyllic and argillic alteration zones, which are typically considered the most important predictors of porphyry copper. Seven prospecting areas, which match mapped alteration zones, were delineated in the Duolong deposit. In addition, an ASTER image of the eastern region of the Bangonghu–Nujiang belt in the Xiongmei area was used to extract alteration information, and an area with image characteristics similar to the Duobuza and Bolong ore deposits was identified as a prospecting area. Numerous malachite outcrops were identified in the field, and both laboratory analysis and isotopic dating confirmed that the deposit had formed concurrently with the Duobuza deposit (119 Ma). Geologic mapping at the 1:5000 scale was conducted in the area, and three types of ore‐bearing rocks were identified, indicating that this area has significant potential to host ore deposits. The discovery of the Xiongmei copper mining area is significant for the Bangonghu–Nujiang belt.

Satellite observations of fumarole activity at Aluto volcano, Ethiopia: Implications for geothermal monitoring and volcanic hazard

Fumaroles are the surface manifestation of hydrothermal circulation and can be influenced by magmatic, hydrothermal, hydrological and tectonic processes. This study investigates the temporal changes in fumarole temperatures and spatial extent on Aluto, a restless volcano in the Main Ethiopian Rift (MER), in order to better understand the controls on fluid circulation and the interaction between the magmatic and hydrothermal systems. Thermal infrared (TIR) satellite images, acquired by the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) over the period of 2004 to 2016, are used to generate time series of the fumarole temperatures and areas. The thermal anomalies identified in the ASTER images coincide with known fumaroles with temperatures >80°C and are located on or close to fault structures, which provide a pathway for the rising fluids. Most of the fumaroles, including those along the major zone of hydrothermal upwelling, the Artu Jawe Fault Zone, have pixel-integrated temperature variations of only ~2±1.5°C. The exception are the Bobesa fumaroles located on a hypothesised caldera ring fault which show pixel-integrated temperature changes of up to 9°C consistent with a delayed response of the hydrothermal system to precipitation. We conclude that fumaroles along major faults are strongly coupled to the magmatic-hydrothermal system and are relatively stable with time, whereas those along shallower structures close to the rift flank are more strongly influenced by seasonal variations in groundwater flow. The use of remote sensing data to monitor the thermal activity of Aluto provides an important contribution towards understanding the behaviour of this actively deforming volcano. This method could be used at other volcanoes around the world for monitoring and geothermal exploration.

Evaporite mineral mapping and determining their source rocks using remote sensing data in Sirjan playa, Kerman, Iran

In this research, evaporite minerals of Sirjan playa, Iran were mapped using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 images. Spectral angle mapper (SAM) was applied to map evaporite minerals of the study area. Two kinds of reference spectra were used for classifying the images that consist of: (1) recorded reflectance spectra of evaporite minerals and (2) image-derived spectra which were acquired from images based on GPS coordinates of samples. Determination of evaporite minerals assessed by X-ray diffraction (XRD) on field samples which were collected in October 2015 when the lake was completely dry. After image classification, the overall accuracy of 95.27% for Landsat 8 images and 91.81% for ASTER images were achieved, respectively, using image-derived spectra. SAM classification using samples’ spectra showed lower accuracy of 85.96 and 80.31% for ASTER and Landsat images, respectively. Therefore, the image-derived spectra produced better classification accuracy. For determining the main source of inflows of the sediments into the playa, drainage system of Sirjan basin, that was derived using digital elevation model, false color composite image, mosaic of old aerial photographs and map of evaporite minerals were used. It showed that the main source of inflows of the sediments to the playa is from volcanic and sedimentary rocks of Urumieh-Dokhtar mountains located in the north-east and eastern parts of the playa.

Detecting and mapping different types of iron mineralization in Sangan mining region, NE Iran, using satellite image and airborne geophysical data

The Sangan mining region is the largest Fe skarn in western Asia has emplaced into the Khaf-Kashmar-Bardaskan volcano-plutonic belt in the NE Iran. In this region, carbonate rocks of Jurassic skarnified and hosted different epigenetic types of iron minerals, including magnetite, hematite, goethite, and limonite. The combination of remote sensing and airborne geophysical data is a powerful tool for mapping and interpreting iron mineralization in some area with intensely rugged topography or a broad expanse area, where systematic sampling and conventional geological mapping has some limitation and time consuming. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data and airborne geophysical magnetometry data were used for evaluating and mapping different types of iron mineralization in the Sangan mining region. Preprocessing of the datasets involved band ratio (BR), principal component analysis (PCA), spectral angle mapper (SAM), and constrained energy minimization (CEM) of the visible-near infrared and short wave infrared ASTER data were used to map four types of iron minerals (magnetite, hematite, goethite, and limonite). For preparing a lithological mapp of this region, an RGB image produced by combination of BR and PCA, (R:(5+7)/6, G:PC3, B:PC 5). Implementing SAM and CEM technique were useful for mapping and detecting magnetite, hematite, goethite, and limonite. The Reduce To the Pole (RTP) map of the airborne geophysical magnetometry data is a practical tool for iron ore exploration that were used in this region for enhancing high anomalous signature of magnetite after extracting granitoid rocks. The integration of the extracted information from the ASTER image processing algorithms and geophysical magnetometry, mapped iron mineralization and identified new potential of high magnetite mineralization. The results verified by geological map and comprehensive fieldwork. This integration model can generalize to other arid and semi-arid regions with iron potential for both regional and district scales.

An Alternative Approach for Registration of High-Resolution Satellite Optical Imagery and ICESat Laser Altimetry Data.

Satellite optical images and altimetry data are two major data sources used in Antarctic research. The integration use of these two datasets is expected to provide more accurate and higher quality products, during which data registration is the first issue that needs to be solved. This paper presents an alternative approach for the registration of high-resolution satellite optical images and ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry data. Due to the sparse distribution characteristic of the ICESat laser point data, it is difficult and even impossible to find same-type conjugate features between ICESat data and satellite optical images. The method is implemented in a direct way to correct the point-to-line inconsistency in image space through 2D transformation between the projected terrain feature points and the corresponding 2D image lines, which is simpler than discrepancy correction in object space that requires stereo images for 3D model construction, and easier than the indirect way of image orientation correction via photogrammetric bundle adjustment. The correction parameters are further incorporated into imaging model through RPCs (Rational Polynomial Coefficients) generation/regeneration for the convenience of photogrammetric applications. The experimental results by using the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images and ZY-3 (Ziyuan-3 satellite) images for registration with ICESat data showed that sub-pixel level registration accuracies were achieved after registration, which have validated the feasibility and effectiveness of the presented approach.

Data Uncertainty in an Improved Bayesian Network and Evaluations of the Credibility of the Retrieved Multitemporal High-Spatial-Resolution Leaf Area Index (LAI)

Integration of multisource remote sensing data is one of the methods to invert temporal high-spatial-resolution (time-continuous and with the resolution in 10-m scale) leaf area index (LAI). However, a few studies are related to addressing the uncertainty of data sources in the inversion algorithm and investigating the relationship between the uncertainty of data sources and the credibility of inversion results. This research is designed to retrieve temporal high-resolution LAI using an improved dynamic Bayesian network approach to fuse the dynamic change information of coarse-resolution historical data with the spatial information of high-resolution remote sensing observations. In this process, the focus was on handling the uncertainty of data sources that is mainly derived from the uncertainty of high-resolution remote sensing observations. On the basis of retrieving the temporal high-resolution LAI, the credibility of the inversion results was calculated and the influence of data source uncertainty on inversion results was investigated. To implement the work framework, this study takes the Xiaoman irrigation area in the arid middle reaches of the Heihe region as the study area, the uncertainty generated during the Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) atmospheric correction process as the uncertainty in the data sources and the ASTER images as the remote sensing information, and uses the Moderate-resolution Imaging Spectroradiometer MCD15A2 historical LAI data to construct the dynamic LAI information. By constructing an improved dynamic Bayesian network, the LAI products with 15-m spatial resolution and 8-day time-series resolution were produced. The validation results revealed that the determination coefficient R 2 between LAI inversion results and actual measured values is 0.85, and the root-mean-square error (RMSE0) is 0.40 m2/m2. It was also observed that the high-resolution observation information can be severed to gradually correct the dynamic growth information during the time series inversion. This finding is manifested by the fact that with the addition of high-resolution remote sensing observation data, the reliability of the inversion results gradually increases. Meanwhile, the uncertainty of the data sources has a relatively impact on the reliability of the inversion results. When the uncertainty level of data sources is lower than 0.24, the reliability of the inversion results is high. It is concluded that the reliability of LAI will increase with the decreasing of the uncertainty level of remotely sensed data source .

Processing Methodology Based on ASTER Data for Mapping Mine Waste Dumps in a Semiarid Polysulphide Mine District

. The aim of this work is to present a simple, economic, and efficient methodology based on the use of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to map areas of mining waste composed of heterogeneous mineral mixtures. This methodology has been applied to the District of Santa María de la Paz, Mexico, to detect different mineral phases that have been previously characterized. The methodology consists of techniques such as band ratioing, Normalized Difference Tailings Index (NDTI), and Spectral Angle Mapper (SAM) classification. Experimentation with the SAM classification has established a minimum threshold of 0.08 radians for the mapping of mining waste and tailings impoundments. The results of this analysis indicate that the different techniques applied to ASTER images do not show the same level of accuracy for all waste dumps. In this study, the best technique for mapping the different mine wastes is the ferrous iron ratio, which features an overall accuracy of 93.25 % and a kappa coefficient of 0.86. The accuracy of the results suggest that the proposed methodology can be used in the detection of mine waste in mining districts that have not been fully characterized, especially in countries with a large amount of abandoned mining waste.

Investigating and Predicting the Extension of Dunes Using Land Change Modeler (LCM) in the North West of Yazd, Iran

In the present study, in order to calculate the movement of sand dunes in the period between 2001 and 2010, the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) images were used. The training samples were obtained from the field, and the images of the years 2001 and 2010 were classified using maximum likelihood algorithm and decision making tree. The study area was classified into four classes, including vegetated areas, urban areas, sand dunes, and bare lands. Accuracy of the created land cover maps was assessed using five hundred ground control points, Google Earth, and Landsat 7 satellite images. Based on the results, the overall accuracy and kappa coefficient for the maps of 2001 and 2010 were estimated 96%, 0.94 and 98%, 0.98, respectively. In the next step, the resulted land cover maps were used as input for Land Change Modeler (LCM) and Markov calculation. Statistical outputs and change map of this model show the extensive changes in the dunes during the study period. In addition, the area of sand dunes increased from 12,103 to 14,355 hectares. However, 6 hectares of vegetated areas around the Ashkezar and Zarch cities in the North West of Yazd changed to sand dunes. The highest probability of change in the dunes is the change of dunes to bare lands and the lowest probability is the change of dunes to vegetation lands. These results show the movement and change of the dunes in this arid zone.

Application of Airborne Geophysical and ASTER Data for Hydrothermal Alteration Mapping in the Sar-Kuh Porphyry Copper Area, Kerman Province, Iran

Known deposits are appropriate sites for investigating significant exploratory keys that could be helpful in mineral exploration in corresponding regions or similar areas. This study was performed to delineate hydrothermal alteration model and some geophysical characteristics of the SarKuh porphyry copper deposit located within the southern part of the central Iranian Cenozoic magmatic belt (CICMB). Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images have been used to produce hydrothermal alteration map using a fractal-aided spectral angle mapper (SAM) method. Airborne data were used to study magnetic-radiometric properties of the deposit. Image processing of ASTER images and laboratory studies proved the presence of two types of phyllic ale ration called intense and weak phyllic based on abundance of sericite mineral. It realized that radiometric anomalies of 40K, eTh and eU are limited to boundary of phyllic zone. Radiometric ratios e.g. eTh/40K were good enough to enhance phyllic zone.

ASTER spectral analysis for alteration minerals associated with gold mineralization

This study presents classifications of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery based on spectral analysis of alteration minerals associated with gold mineralization in Abo Marawat area which is located in the Central Eastern Desert of Egypt. Spectral analysis of continuum removed reference spectra of alteration minerals alunite, kaolinite, sericite, and calcite from USGS and JPL spectral libraries show shifts in position, shape, and strength most probably related to changes in sample purity and particle size of analyzed samples. Spectral Information Divergence (SID) classification method proved successful for mapping sericite, calcite, and clay minerals. Spectral Angle Mapper (SAM) classification identified only sericite and calcite alteration minerals. The identified alteration zones are coincidence with the field sampling and geological map of the study area. The microscopic examination of samples collected from the quartz veins and hydrothermally altered wall-rocks from near surface and subsurface at Abu Marawat gold mine shows sericitization, argillaceous, and carbonatization alteration zones. Gold occurs as very fine inclusions in pyrite, chalcopyrite, and sphalerite and also found filling the fractures between chalcopyrite grains. This study concludes that ASTER image classifications using reference spectra are a stable and reproducible technique for mapping gold related hydrothermal alteration zones in areas with no dominant vegetation cover.

Observation of submarine sand waves using ASTER stereo sun glitter imagery

Signatures of sun glitter images strongly depend on the viewing angle. Stereo observation can provide more valuable information than observation from one angle. In this work, the sun glitter patterns caused by submarine sand waves were studied using stereo images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which operates a high spatial resolution (15 m) optical and near-infrared sensor on board the Terra satellite. The previous imaging geometrical model has been improved, and the difference in the viewing angle among pixels is considered. We found that brightness reversal occurs in some stereo imagery of submarine sand waves. Based on the imaging geometry model, an interaction model of current topography, and a sun glitter radiance transfer model, a simulation model was developed for sun glitter from submarine sand waves at multiple viewing angles. The cases of nadir-looking and backward-looking were simulated with the model. The results show the following differences between the two viewing angles, which have also been observed in the ASTER images. Both tendency and extent of the simulated radiance are in good agreement with those in actual images. In the nadir-looking view, obvious differences have been observed between the normalized significant radiance from smooth and rough facets. This difference increases with increasing viewing angle, to a peak, and then decreases. However, in most cases, the difference in the back view is smaller and shows an opposite tendency regarding the viewing angle from the nadir-looking view. Thus, the sand-wave characteristics in the nadir-looking images seem to be more enhanced than that in the backward-looking images.

Self-Adaptive Gradient-Based Thresholding Method for Coal Fire Detection Based on ASTER Data—Part 2, Validation and Sensitivity Analysis

The self-adaptive gradient-based thresholding (SAGBT) method is a simple non-interactive coal fire detection approach involving segmentation and a threshold identification algorithm that adapts to the spatial distribution of thermal features over a landscape. SAGBT detects coal fire using multispectral thermal images acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. The method was detailed by our previous work “Self-Adaptive Gradient-Based Thresholding Method for Coal Fire Detection Based on ASTER Data—Part 1, Methodology”. The current study evaluates the performance of SAGBT and validates its results by using ASTER thermal infrared (TIR) images and ground temperature data collected at the Wuda coalfield (China) during satellite overpass. We further analyzed algorithm performance by using nighttime TIR images and images from different seasons. SAGBT-derived fires matched fire spots measured in the field with an average offset of 32.44 m and a matching rate of 70%–85%. Coal fire areas from TIR images generally agreed with coal-related anomalies from visible-near infrared (VNIR) images. Further, high-temperature pixels in the ASTER image matched observed coal fire areas, including the major extreme high-temperature regions derived from field samples. Finally, coal fires detected by daytime and by nighttime images were found to have similar spatial distributions, although fires differ in shape and size. Results included the stratification of our study site into two temperature groups (high and low temperature), using a fire boundary. We conclude that SAGBT can be successfully used for coal fire detection and analysis at our study site.

Mass loss from glaciers in the Chinese Altai Mountains between 1959 and 2008 revealed based on historical maps, SRTM, and ASTER images

Mass loss of glaciers in the Chinese Altai was detected using geodetic methods based on topographical maps (1959), the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) (2000), and the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) stereo images (2008). The results indicate that a continued and accelerating shrinkage has occurred in the Chinese Altai Mountains during the last 50 years, with mass deficits of 0.43 ± 0.02 and 0.54 ± 0.13 m a−1 water equivalent (w.e.) during the periods 1959–1999 and 1999–2008, respectively. Overall, the Chinese Altai Mountains have lost 7.06 ± 0.44 km3 in ice volume (equivalent to −0.43 ± 0.03 m a−1 w.e.) from 1959–2008. The spatial heterogeneity in mass loss was potentially affected by comprehensive changes in temperature and precipitation, and had a substantial correlation with glacier size and topographic settings. Comparison shows that in the Chinese Altai Mountains glaciers have experienced a more rapid mass loss than those in the Tianshan and northwestern Tibetan Plateau (TP), and the mass balance of glaciers was slightly less negative relative to those in the Russian Altai, Himalaya, and southern TP.

Comparison of multi-temporal ASTER images for hydrothermal alteration mapping using a fractal-aided SAM method

The shortwave infrared (SWIR) spectral bands of four multi-temporal images acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA’s Terra platform were analysed for evaluating the effects of acquisition properties and atmospheric pre-processing levels on the resulting hydrothermal alteration maps a using the fractal-aided Spectral Angle Mapper (SAM) method. Three ASTER level-1B products covering the Sar Cheshmeh area in Iran were used for hydrothermal alteration mapping. These images were converted to surface reflectance using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method. The low reflectance of band 5 of the level-1B products was compensated for by using the spectra of collected rock samples. Level-2 (AST2B05S) SWIR ASTER images that had already been processed were also used. Reference spectra of the main hydrothermal alteration types were extracted for each product. The threshold angles were determined using the real value–area (RV–A) fractal technique. Then, SAM classification was carried out to map hydrothermal alteration for every product. It is concluded that the level-1B products that had been converted to reflectances have a better spectral contrast than the AST2B05S product. Summer images with lower tilt angle and higher solar elevation should be used to increase the accuracy of the image classification and minimize the effect of vegetation on the spectra of index minerals. By comparing the resulting hydrothermal alteration maps with known alteration types using a confusion matrix, it was shown that the application of the RV–A fractal technique to produce less biased threshold angles increases the accuracy of SAM classification.

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.