Advanced Spaceborne Thermal Emission And Reflection Radiometer Datasets Research Articles

Comparison between the ASTER and ECOSTRESS global emissivity datasets

High spatial resolution global land surface emissivity datasets are valuable for various applications. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is the only accessible global emissivity data with a high spatial resolution (∼100 m). Since the launch of the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in June 2018, another high spatial resolution GED can be generated. A comprehensive comparison is needed to investigate the consistency between the ASTER and ECOSTRESS GEDs before subsequent applications and the release of the ECOSTRESS GED. We conducted a first-ever comparison between the ASTER and ECOSTRESS GEDs in two ways: 1) global spatial comparison and 2) validation using emissivity measurements at 9 sand dune and 2 vegetated sites. The results reveal that the ECOSTRESS emissivities in bands 2 and 4 are in good agreement with ASTER GED, with mean absolute biases (MAB) of ∼ 1 % averaged over the globe. The emissivity difference is the largest for snow and ice in these two bands. For band 5, the discrepancy is relatively larger with a MAB of 1.7 %. The largest emissivity difference is found over evergreen broadleaf forests in humid regions. Comparison with measurements reveals an average root-mean-square error (RMSE) of ECOSTRESS emissivity of ∼ 3 % among all the nine sand sites for all the 3 bands. At the two vegetated sites, the average RMSE is ∼ 1.5 %. The absolute biases are below 3 % in all the bands. The average RMSE between ASTER and ECOSTRESS GEDs among all sand dune sites is 1.29 %. The evaluation results demonstrate a good agreement between these two emissivity retrievals overall and high accuracy of the ECOSTRESS GED.

Orogenic Gold in Transpression and Transtension Zones: Field and Remote Sensing Studies of the Barramiya–Mueilha Sector, Egypt

Multi-sensor satellite imagery data promote fast, cost-efficient regional geological mapping that constantly forms a criterion for successful gold exploration programs in harsh and inaccessible regions. The Barramiya–Mueilha sector in the Central Eastern Desert of Egypt contains several occurrences of shear/fault-associated gold-bearing quartz veins with consistently simple mineralogy and narrow hydrothermal alteration haloes. Gold-quartz veins and zones of carbonate alteration and listvenitization are widespread along the ENE–WSW Barramiya–Um Salatit and Dungash–Mueilha shear belts. These belts are characterized by heterogeneous shear fabrics and asymmetrical or overturned folds. Sentinel-1, Phased Array type L-band Synthetic Aperture Radar (PALSAR), Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER), and Sentinel-2 are used herein to explicate the regional structural control of gold mineralization in the Barramiya–Mueilha sector. Feature-oriented Principal Components Selection (FPCS) applied to polarized backscatter ratio images of Sentinel-1 and PALSAR datasets show appreciable capability in tracing along the strike of regional structures and identification of potential dilation loci. The principal component analysis (PCA), band combination and band ratioing techniques are applied to the multispectral ASTER and Sentinel-2 datasets for lithological and hydrothermal alteration mapping. Ophiolites, island arc rocks, and Fe-oxides/hydroxides (ferrugination) and carbonate alteration zones are discriminated by using the PCA technique. Results of the band ratioing technique showed gossan, carbonate, and hydroxyl mineral assemblages in ductile shear zones, whereas irregular ferrugination zones are locally identified in the brittle shear zones. Gold occurrences are confined to major zones of fold superimposition and transpression along flexural planes in the foliated ophiolite-island arc belts. In the granitoid-gabbroid terranes, gold-quartz veins are rather controlled by fault and brittle shear zones. The uneven distribution of gold occurrences coupled with the variable recrystallization of the auriferous quartz veins suggests multistage gold mineralization in the area. Analysis of the host structures assessed by the remote sensing results denotes vein formation spanning the time–space from early transpression to late orogen collapse during the protracted tectonic evolution of the belt.

Comparison of ASTER and Sentinel-2 spaceborne datasets for geological mapping: a case study from North-East Greenland

Spaceborne remote sensing is a suitable tool for early mineral exploration and surveying large areas of high Arctic environment in a fast and cost-effective manner. While spaceborne data have been used widely to map geology in arid areas, similar approaches for remotely-sensed geological mapping of Arctic environments is yet to be developed. Freely available spaceborne optical data provides detailed information of high-quality that could potentially reduce resource exploration risk in remote regions. To this end, this study compares the use of two different multispectral spaceborne datasets (i.e. the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Sentinel-2) to map geological units in and around Wollaston Forland, North-East Greenland – an area rich in Jurassic and Cretaceous sedimentary rocks and important targets for offshore petroleum exploration. Multispectral image sensors simultaneously capture image data within multiple wavelength ranges (bands) across the electromagnetic spectrum. Each band is commonly described by the band number and the band wavelength centre position. Here, we identify the bands most suitable for geological mapping in an Arctic setting, using the Wollaston Forland area as an example. We compare the results obtained by processing spaceborne data with a published geological map for the area (Henriksen 2003).

Integrating geologic and Landsat-8 and ASTER remote sensing data for gold exploration: a case study from Zarshuran Carlin-type gold deposit, NW Iran

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Landsat-8 data were integrated with geological data to map lithologic units, lineament features, hydrothermal alteration zones, and distribution of Fe3+-bearing minerals in the Zarshuran Carlin-type gold deposit. The dominant hydrothermal alterations related to the gold mineralization in the study area, consist of argillic, alunite, silicified, and decalcified alterations of carbonate host rocks. The alteration assemblages are accompanied by ferric iron minerals such as jarosite and hematite. The red-green-blue (RGB) combination of bands 5, 2, and 1 of the ASTER sensor provides excellent criteria for the separation of the host rock lithologic boundaries, particularly for the Oligo-Miocene andesitic volcanic rocks covering the vast parts of the study area. The ASTER lithologic map derived from RGB combination of bands 5, 2, and 1 is represented by a set of lineaments in which both the thrust and normal faults were enhanced. The band ratios obtained by the Landsat-8 and the ASTER datasets have been effectively used to delineate the alteration halos characterized by kaolinite, alunite, quartz, and ferric iron minerals both in regional and local (the Zarshuran gold mine) scales. In addition, methods such as the principal component analysis (PCA) and the selective principal component analysis (Crosta) were exerted on the ASTER data to identify the hydrothermal alteration zones. The spectral angle mapper (SAM) algorithm using the ASTER data could better differentiate the various alteration (e.g., argillic, alunite, and silicified) zones existing in the study area. The matched filtering (MF) technique processed on the Landsat-8 data was applied to characterize the ferric iron minerals (jarosite and hematite) and separate the hydrothermal alteration zones as well. The integration and combination of various image processing techniques indicated that the alteration zones at Zarshuran are affiliated with normal faults within the carbonate host rocks and can be used for prospection mapping purposes in regional scale.

DEM-based morphometry of large-scale sand dune patterns in the Grand Erg Oriental (Northern Sahara Desert, Africa)

Formerly, sand dune patterns were investigated mostly by aerial and satellite images, but more recently, geomorphometric analysis based on digital elevation models (DEMs) has become an important approach. In this paper, sand dune patterns of the Grand Erg Oriental (Sahara) are studied using the De Ferranti (2014) DEM, which is a blending of SRTM (Shuttle Radar Topography Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and other elevation datasets. In the Grand Erg Oriental, there are four large-scale dune pattern types with gradual transitions between them and with several subtypes, namely P1, consisting of large, branching linear dunes; P2, a complex pattern including small-size and widely spaced star and dome dunes; P3, a network type created mostly from crescentic dunes; and finally, P4, consisting of large and closely spaced star dunes. The largest dunes with 90–100-m mean height can be found in the southern parts of the Grand Erg Oriental, where P1 and P4 patterns dominate, and these areas are also characterised by the most intensive sand accumulation with 25–30-m equivalent sand thickness. In the present study, we use regression analysis to investigate the functional relationships between sand dune characteristics. Further on, we have elaborated a DEM-based method to delineate dunes and calculate sand volumes and dune orientations. Comparing wind rose data and sand dune axis rose diagrams, it is concluded that in some parts of the Grand Erg Oriental, the present dune types and patterns are in agreement with the actual wind regime, but in other cases, the present dune patterns are at least partially the results of former wind regimes.

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.

Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

Evapotranspiration (ET) estimates are particularly needed for monitoring the available water of arid lands. Remote sensing data offer the ideal spatial and temporal coverage needed by irrigation water management institutions to deal with increasing pressure on available water. Low spatial resolution (LR) products present strong advantages. They cover larger zones and are acquired more frequently than high spatial resolution (HR) products. Current sensors such as Moderate-Resolution Imaging Spectroradiometer (MODIS) offer a long record history. However, validation of ET products at LR remains a difficult task. In this context, the objective of this study is to evaluate scaling properties of ET fluxes obtained at high and low resolution by two commonly used Energy Balance models, the Surface Energy Balance System (SEBS) and the Two-Source Energy Balance model (TSEB). Both are forced by local meteorological observations and remote sensing data in Visible, Near Infra-Red and Thermal Infra-Red spectral domains. Remotely sensed data stem from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and MODIS sensors, respectively, resampled at 100 m and 1000 m resolutions. The study zone is a square area of 4 by 4 km2 located in a semi-arid irrigated agricultural zone in the northwest of Mexico. Wheat is the dominant crop, followed by maize and vegetables. The HR ASTER dataset includes seven dates between the 30 December 2007 and 13 May 2008 and the LR MODIS products were retrieved for the same overpasses. ET retrievals from HR ASTER products provided reference ET maps at LR once linearly aggregated at the km scale. The quality of this retrieval was assessed using eddy covariance data at seven locations within the 4 by 4 km2 square. To investigate the impact of input aggregation, we first compared to the reference dataset all fluxes obtained by running TSEB and SEBS models using ASTER reflectances and radiances previously aggregated at the km scale. Second, we compared to the same reference dataset all fluxes obtained with SEBS and TSEB models using MODIS data. LR fluxes obtained by both models driven by aggregated ASTER input data compared well with the reference simulations and illustrated the relatively good accuracy achieved using aggregated inputs (relative bias of about 3.5% for SEBS and decreased to less than 1% for TSEB). Results also showed that MODIS ET estimates compared well with the reference simulation (relative bias was down to about 2% for SEBS and 3% for TSEB). Discrepancies were mainly related to fraction cover mapping for TSEB and to surface roughness length mapping for SEBS. This was consistent with the sensitivity analysis of those parameters previously published. To improve accuracy from LR estimates obtained using the 1 km surface temperature product provided by MODIS, we tested three statistical and one deterministic aggregation rules for the most sensible input parameter, the surface roughness length. The harmonic and geometric averages appeared to be the most accurate.

HYDROTHEMAL ALTERATION MAPPING USING FEATURE-ORIENTED PRINCIPAL COMPONENT SELECTION (FPCS) METHOD TO ASTER DATA:WIKKI AND MAWULGO THERMAL SPRINGS, YANKARI PARK, NIGERIA

Abstract. Geothermal systems are essentially associated with hydrothermal alteration mineral assemblages such as iron oxide/hydroxide, clay, sulfate, carbonate and silicate groups. Blind and fossilized geothermal systems are not characterized by obvious surface manifestations like hot springs, geysers and fumaroles, therefore, they could not be easily identifiable using conventional techniques. In this investigation, the applicability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were evaluated in discriminating hydrothermal alteration minerals associated with geothermal systems as a proxy in identifying subtle Geothermal systems at Yankari Park in northeastern Nigeria. The area is characterized by a number of thermal springs such as Wikki and Mawulgo. Feature-oriented Principal Component selection (FPCS) was applied to ASTER data based on spectral characteristics of hydrothermal alteration minerals for a systematic and selective extraction of the information of interest. Application of FPCS analysis to bands 5, 6 and 8 and bands 1, 2, 3 and 4 datasets of ASTER was used for mapping clay and iron oxide/hydroxide minerals in the zones of Wikki and Mawulgo thermal springs in Yankari Park area. Field survey using GPS and laboratory analysis, including X-ray Diffractometer (XRD) and Analytical Spectral Devices (ASD) were carried out to verify the image processing results. The results indicate that ASTER dataset reliably and complementarily be used for reconnaissance stage of targeting subtle alteration mineral assemblages associated with geothermal systems.

Integration of spectral, thermal, and textural features of ASTER data using Random Forests classification for lithological mapping

The ensemble classifier, Random Forests (RF), is assessed for mapping lithology using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery over an area in southern Iran. The study area in the northern part of Rabor in the Kerman's Cenozoic magmatic arc (KCMA) is well exposed and contains some copper mineralization occurrences. In this research, the following six groups of ASTER datasets were used for RF classification: nine spectral bands in the VNIR and SWIR, five thermal bands in TIR, all 14 bands (including VNIR, SWIR, and TIR), band ratios, texture features, and principal components (PCs). The results showed that band ratios and all ASTER bands were able to more efficiently discriminate rock units than PC and texture images. The overall classification accuracies achieved were 62.58%, 55.40%, 65.04%, 67.12%, 54.54%, and 53.99% for the nine VNIR/SWIR bands, five TIR bands, all ASTER bands, band ratios, textural, and PCs datasets, respectively. Four datasets including all ASTER bands, band ratios, textural, and PCs datasets (37 bands) were combined as one group and applied in second RF classification which led to increase overall accuracy (up to 81.52%). Based on the four classified maps, an uncertainty map was produced to identify areas of variable (uncertain) classification results, which revealed that approximately 21.43% of all pixels on the classified map were highly uncertain. The RF algorithm found that 12 of the predictors were more important in the classification process. These predictors were used in a third RF classification, which resulted in an overall classification accuracy of 77.21%. Thus, the third RF classification decreases the accuracy. Field observations were used to validate our classification results.

APPLICATION OF MULTISPECTRAL SATELLITE DATA FOR GEOLOGICAL MAPPING IN ANTARCTIC ENVIRONMENTS

Abstract. Remote sensing imagery is capable to provide a solution to overcome the difficulties associated with geological field mapping in the Antarctic. Advanced optical and radar satellite imagery is the most applicable tool for mapping and identification of inaccessible regions in Antarctic. Consequently, an improved scientific research using remote sensing technology would be essential to provide new and more complete lithological and structural data to fill the numerous knowledge gaps on Antarctica’s geology. In this investigation, Oscar coast area in Graham Land, Antarctic Peninsula (AP) was selected to conduct a remote sensing study using Landsat-7 Thematic Mapper (TM), Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Contrast-enhanced Red-Green-Blue (RGB) composites, band ratios and Relative Band Depth (RBD) image processing techniques were applied to Landsat-8 and ASTER dataset for establishing the spectral separation of the main lithologic groups exposed in the study area. The outcomes of this investigation demonstrated the applications of SWIR and TIR bands of the multispectral remote sensing datasets to identify lithological units and producing geological maps with suitable accuracy of ice-free rock regions in the Antarctic Peninsula. The results could be extended to map coverage of non-investigated regions further east and validated previously inferred geological observations concerning other rocks and mineral deposits throughout the Antarctica.

Integration of ASTER and landsat TM remote sensing data for chromite prospecting and lithological mapping in Neyriz ophiolite zone, south Iran

AbstractChromite deposits in Iran are located in the ophiolite complexes, which have mostly podiform types and irregular in their settings. Exploration for podiform chromite deposits associated with ophiolite complexes has been a challenge for the prospectors due to tectonic disturbance and their distribution patterns. Most of Iranian ophiolitic zones are located in mountainous and inaccessible regions. Remote sensing approach could be applicable tool for choromite prospecting in Iranian ophiolitic zones with intensely rugged topography, where systematic sampling and conventional geological mapping are limited. In this study, Landsat Thematic Mapper (TM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data were used for chromite prospecting and lithological mapping in the Neyriz ophiolitic zone in the south of Iran. Image transformation techniques, namely decorrelation stretch, band ratio and principal component analysis (PCA) were applied to Landsat TM and ASTER data sets for lithological mapping at regional scale. The RGB decorrelated image of Landsat TM spectral bands 7, 5, and 4, and the principal components PC1, PC2 and PC3 image of ASTER SWIR spectral bands efficiently showed the occurrence of major lithological units in the study area at regional scale. The band ratios of 5/3, 5/1, 7/5 applied on ASTER VNIR‐SWIR bands were very useful for discriminating most of rock units in the study area and delineation of the transition zone and mantle harzburgite in the Neyriz ophiolitic complex. Spectral Angle Mapper (SAM) technique was implemented to ASTER VNIR‐SWIR spectral bands for detecting minerals of rock units and especially delineation of the transition zone and mantle harzburgite as potential zones with high chromite mineralization in the Neyriz ophiolitic complex. The integration of information extracted from the image processing algorithms used in this study mapped most of lithological units of the Neyriz ophiolitic complex and identified potential areas of high chromite mineralization (transition zone and mantle harzburgite) for chromite prospecting targets in the future. Furthermore, image processing results were verified by comprehensive fieldwork and laboratory analysis in the study area. Accordingly, result of this investigation indicate that the integration of information extracted from the image processing algorithms using Landsat TM and ASTER data sets could be broadly applicable tool for chromite prospecting and lithological mapping in mountainous and inaccessible regions such Iranian ophiolitic zones.

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.

Satellite-based analysis of the role of land use/land cover and vegetation density on surface temperature regime of Delhi, India

The knowledge of the surface temperature is important to a range of issues and themes in earth sciences central to urban climatology, global environmental change and human-environment interactions. The study analyses land surface temperature (LST) estimation using temporal ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) datasets (day time and night time) over National Capital Territory Delhi using the surface emissivity information at pixel level. The spatial variations of LST over different land use/land cover (LU/LC) at day time and night time were analysed and relationship between the spatial distribution of LU/LC and vegetation density with LST was developed. Minimum noise fraction (MNF) was used for LU/LC classification which gave better accuracy than classification with original bands. The satellite derived emissivity values were found to be in good agreement with literature and field measured values. It was observed that fallow land, waste land/bare soil, commercial/industrial and high dense built-up area have high surface temperature values during day time, compared to those over water bodies, agricultural cropland, and dense vegetation. During night time high surface temperature values are found over high dense built-up, water bodies, commercial/industrial and low dense built-up than over fallow land, dense vegetation and agricultural cropland. It was found that there is a strong negative correlation between surface temperature and NDVI over dense vegetation, sparse vegetation and low dense built-up area while with fraction vegetation cover, it indicates a moderate negative correlation. The results suggest that the methodology is feasible to estimate NDVI, surface emissivity and surface temperature with reasonable accuracy over heterogeneous urban area. The analysis also indicates that the relationship between the spatial distribution of LU/LC and vegetation density is closely related to the development of urban heat islands (UHI).

Scale effect on statistics of the macrophysical properties of trade wind cumuli over the tropical western Atlantic during RICO

This study investigates the effect of observational domain size and pixel resolution on the statistics of macrophysical properties of trade wind cumulus clouds over the tropical western Atlantic. In order to better facilitate comparison with model simulations, the results are presented as an extension of earlier work by Zhao and Di Girolamo (2007), who have analyzed 152 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes collected between September and December 2004 to generate comprehensive statistics of cumulus clouds at the original 60 km × 60 km domain and 15 m pixel resolution of the data. The statistics change with domain size because as the domain size becomes smaller, (1) the probability of chopping clouds by the domain boundaries into smaller clouds increases, and (2) the probability of having cloudier and clearer domains increases. In addition, degrading pixel resolution results in (1) an amalgamation of smaller clouds into larger clouds, and (2) an increase in the frequency of partially filled cloudy pixels. The mean cloud fraction in our ASTER data set increases more than fourfold, with the total number of clouds reducing 26‐fold, when pixel resolution degrades from 15 m to ∼1 km. The cloud fraction frequency distribution becomes wider with a shift of the peak toward higher values at coarser resolution. However, at smaller domain sizes, the shift of the peak toward larger values due to pixel effects is overcompensated by the increase in frequency of smaller cloud fractions. The change in cloud size distribution is significant at domains smaller than 10 km × 10 km. An increase in the cloud size at coarser resolution shifts the peak of the size distribution toward larger values. At 15 m resolution, 98% of clouds are distributed at distances less than 300 m, with a peak in the nearest‐neighbor distance at less than 50 m at all domain sizes. The peak of the nearest‐neighbor distribution becomes wider and shifts to larger distances at coarser resolution. These results clearly indicate the importance of considering scale effect when comparing cloud resolving model simulations of trade wind cumuli with observations.

Mineral mapping on the Chilean–Bolivian Altiplano using co-orbital ALI, ASTER and Hyperion imagery: Data dimensionality issues and solutions

Hyperspectral data coverage from the EO-1 Hyperion sensor was useful for calibrating Advanced Land Imager (ALI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images of a volcanic terrane area of the Chilean–Bolivian Altiplano. Following calibration, the ALI and ASTER datasets were co-registered and joined to produce a 13-channel reflectance cube spanning the Visible to Short Wave Infrared (0.4–2.4 μm). Eigen analysis and comparison of the Hyperion data with the ALI + ASTER reflectance data, as well as mapping results using various ALI+ASTER data subsets, provided insights into the information dimensionality of all the data. In particular, high spectral resolution, low signal-to-noise Hyperion data were only marginally better for mineral mapping than the merged 13-channel, low spectral resolution, high signal-to-noise ALI + ASTER dataset. Neither the Hyperion nor the combined ALI + ASTER datasets had sufficient information dimensionality for mapping the diverse range of surface materials exposed on the Altiplano. However, it is possible to optimize the use of the multispectral data for mineral-mapping purposes by careful data subsetting, and by employing other appropriate image-processing strategies.

Spectral indices for lithologic discrimination and mapping by using the ASTER SWIR bands

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a research facility instrument launched on NASA's Terra spacecraft in December 1999. Spectral indices, a kind of orthogonal transformation in the five-dimensional space formed by the five ASTER short-wave-infrared (SWIR) bands, were proposed for discrimination and mapping of surface rock types. These include Alunite Index, Kaolinite Index, Calcite Index, and Montmorillonite Index, and can be calculated by linear combination of reflectance values of the five SWIR bands. The transform coefficients were determined so as to direct transform axes to the average spectral pattern of the typical minerals. The spectral indices were applied to the simulated ASTER dataset of Cuprite, Nevada, USA after converting its digital numbers to surface reflectance. The resultant spectral index images were useful for lithologic mapping and were easy to interpret geologically. An advantage of this method is that we can use the pre-determined transform coefficients, as long as image data are converted to surface reflectance.