Advanced Spaceborne Thermal Emission And Reflection Radiometer Research Articles

Application of remote sensing data integration in detecting mineralized granitic zones: A case study of the Gabal Al-Ijlah Al-Hamra, Central Eastern Desert, Egypt

The Gabal Al-Ijlah Al-Hamra granites in the Central Eastern Desert of Egypt are rich in rare metal-bearing minerals. The enhanced Senetinal-2-Planet fused image with 3 m spatial resolution using Gram–Schmidt fused technique was successfully used in detailed discrimination of the rock units in the study area. Various enhanced remote sensing data of Sentinel-2, Landsat-9, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and fused ASTER-Sentinel-2 datasets were used in the mapping process and verified by field investigation and petrographic analysis. The hydrothermal mineralized alteration zones related to rare metal-bearing granites were identified using ASTER and Sentinel-2 fused images. According to petrographic and ASTER mineral indices, various types of alteration zones, including sericitization, chloritization, carbonatization, kaolinitization and silicification were detected. The surface structural features were well detected using Soble directional filtering of Sentinel-1 enhanced image. The major structural directions that have been detected in Al-Ijlah Al-Hamra granitic pluton are NW-SE and NE-SW. These major trends were used to detect potential pathways for migration and concentration of rare-metals. The hyperspectral TerraSpec Halo mineral identifier (ASD) as well as petrographical investigation successfully identified the rock-forming minerals (i.e. quartz, K-feldspar, plagioclase, biotites, muscovite, chlorite, kaolinite, sericite) of syenogranites and alkali feldspar granites in the Gabal Al-Ijlah Al-Hamra area. Rare metal-bearing minerals including zircon, rutile, allanite, parisite and xenotime were identified using Scanning Electron Microscopy (SEM) coupled with Energy Dispersive X-Ray Spectroscopy (EDS). The results of remote sensing data, field observations and petrographic investigation are successfully used in exploration for rare metal-bearing minerals in the Central Eastern Desert of Egypt and similar areas worldwide.

Determination of Parameters for Watershed delineation using various satellite derived Digital Elevation Models and its accuracy

<p>Digital Elevation Model (DEM) is an inevitable tool for many applications, such as natural resource management. In the present scenario, it is available with various resolutions from meter to sub-meter accuracy. These data are used extensively to explore the river basin's physical features by detecting and extracting watershed boundaries, elevation points, drainage networks, flow directions, and morphological parameters. Although many researchers have used DEMs to delineate the watershed boundaries of the river basin, accuracy makes the significant distinction and usage of various DEMs. In this study, the accuracy of watershed delineation derived from various open-source DEMs such as Shuttle Radar Topographic Mission (SRTM), Advanced Spaceborne Thermal Emission, and Reflection Radiometer (ASTER), Cartosat-1, and ALOS Palsar, in the vaigai river basin have been observed. The Arc SWAT hydrological modeling tool was used to delineate the watershed boundary using the DEMs mentioned above. Eventually, the outcome is validated with the help of base data received from TN-PWD (Tamilnadu Public Work Department). The results attained from the extraction of the watershed boundary from various DEMs reveal that the watershed boundary delineated from ALOS – Palsar is closely matching with the actual boundary of vaigai river basin. The regression analysis of the watershed on area and perimeter obtained from the ALOS Palsar DEM yielded R2 as 0.97 and 0.99. This R2 exhibits the close fitness of the predicted value with data obtained from TN-PWD data. The ALOS Palsar DEM provided low vertical errors and high vertical accuracy compared to other DEMs. Overall the ALOS Palsar DEM generated outcome exhibited comparatively better results than the rest of the DEMs.</p>

Identifying Emeishan basalt by supervised learning with Landsat-5 and ASTER data

Multispectral-sensor images are advantageous in terms of discriminating major lithologies due to their high spatial resolution and intermediate spectral resolution, in addition to their low cost and high accessibility in comparison to hyperspectral images. In this study, Landsat-5 Thematic Mapper ™ and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data—which are the most widely used multispectral data for the discrimination of the mixed rock units—are utilized to identify basalts in our study area. Further, prior knowledge regarding basalt-distribution areas in our study region is obtained from the geological-survey results conducted by the Sichuan Geological Survey at 2005, which is used as the reference of correction to assess our identified results. Small portions of this prior area of basalt distribution were verified through field checks, which were then determined as sites for use as training data for remote-sensing imagery. Three supervised-classification algorithms within ENVI 5.3—k-nearest neighbors (KNN), maximum likelihood classification (MLC), and support vertical machine (SVM)—were utilized for model identification. As a result, six models were constructed, including the KNN prediction of basalts by ASTER images, SVM prediction by ASTER, MLC prediction by ASTER, KNN prediction by Landsat-5 images, SVM prediction by Landsat-5, and MLC prediction by Landsat-5. The performances of the six models, in terms of precision and accuracy, show that the optimum model is Landsat-5 by SVM, with a precision of 70.92% and accuracy of 99.97%, followed by the ASTER by SVM model, with a precision of 67.72% and accuracy of 99.89% and the Landsat-5 by KNN model, with a precision of 57.23% and accuracy of 99.85%.

Integrating Aster Images Processing and Fieldwork for Identification of Hydrothermal Alteration Zones at the Oumjrane-Boukerzia District, Moroccan Anti-Atlas

Mapping from remote sensing has become more effective in the field of geology, mainly in lithological discrimination and identification of hydrothermal alteration zones. The use of this technique consists in obtaining information about the rock mass and the main ones existing in the inaccessible areas. Satellite data from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor represent a favorable potential for detecting the spectral signatures of mineral zones and identifying their nature. These data are more reliable in places where the climate is arid with less abundant vegetation, as at the Oumjrane-Boukerzia mining district. This region which is part of the Eastern Anti-Atlas, is composed of several mineralized veins which still require detailed studies and exploration by the technique of remote sensing. In this work we applied several processing techniques on ASTER imagery such as Colored Composition, Principal Component Analysis and Ratio Bands. The use of the reports of the specialized Bands makes it possible to identify some hydrothermal alteration minerals within the mining district of Oumjrane Boukerzia. These minerals are represented mainly by iron oxides and hydroxides (Hematite, jarosite, limonite and goethite), carbonate minerals (dolomite, calcite), clay minerals (Illite, kaolinite and chlorite) and quartz minerals. This work allows us to produce a map of hydrothermal alteration zones which can be used as a valuable reference in the strategy of mining exploration for the base metals (Cu, Pb, Zn and Ba), in the mining district of Oumjrane-Boukerzia and in the entire Eastern Anti-Atlas.

A Robust Framework for Resolution Enhancement of Land Surface Temperature by Combining Spatial Downscaling and Spatiotemporal Fusion Methods

Land surface temperature (LST) products with high spatial resolution and short revisiting cycles are crucial for environmental studies. However, due to the tradeoff between spatial and temporal resolutions of satellite observations, such data are not directly available. Spatial downscaling and spatiotemporal fusion methods are existing solutions for this problem, but their robustness is limited under different surface conditions. Here, we propose a Robust Framework for Combining Downscaling and spatiotemporal Fusion methods (RFCDF) to generate the synthesized daily high-resolution LST with high accuracy in different landscapes. RFCDF introduces a novel weighting strategy that determines pixel-level weights using an empirical function under the constraint of the image-level weights of two predictions. We implement the framework using the thermal sharpening algorithm (TsHARP) and Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) data in Beijing and Baotou, as well as Landsat 8 and simulated coarse resolution imagery in nine sub-regions with different surface landscapes in Beijing. Our results demonstrate that RFCDF can generate more accurate estimations and preserve more spatial details than either individual or combination methods, improving accuracy by 0.1–0.6 K and 0.4–1.3 K in the two study areas, respectively. Moreover, the proposed framework is robust, reducing the root mean square error of estimations by 8-24% under different surface conditions. RFCDF can also generate dense high-resolution LST time series, which is crucial for studying the surface thermal environment at a finer scale.

Lithological mapping of ophiolitic rocks from southern part of the Sivas Basin (Turkey) using ASTER imagery

The east-west extended Sivas Basin in central-eastern Anatolia is a foreland basin that formed after the obduction of the Tethyan ophiolite during the late Cretaceous and is also a north-verging fold-and-thrust belt. The basement rocks of the basin represent mainly sedimentary (Mesozoic platform-type carbonates) and late Cretaceous Divriği ophiolitic complex. As the ophiolitic rocks are affected by intense tectonic processes, field-based mapping studies require long processes and costs. The study tests to reveal the lithological features of the ophiolitic complex outcropping around the Ulaş district of the Sivas Province using remote sensing methods and techniques. Due to arid climatic conditions and rare vegetation cover in the region, almost all outcrops of the basin rocks can be separated by spectral enhancement methods easily. Band ratio (BR), spectral indices (SI), decorrelation stretch (DS), principal component analysis (PCA), and support vector machine (SVM) on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used in this research. BR, PCA, DC, and SI techniques clearly distinguish the Divriği Ophiolitic Complex from the basement and cover sedimentary rocks. SVM distinguishes the chromite-bearing dunites from the other ophiolite-related rock units. According to image analysis performances, it has been observed that the rocks of the Divriği ophiolitic complex can be differentiated in more detail compared to a 1/100.000 scaled geological map of the region.

An integrated approach for rapid exploration of carbonatites and related mineral resources

AbstractCarbonatites are proven significant repositories of several critical and strategic elements such as rare earth elements, niobium, thorium, and uranium. Owing to their economic significance, mapping of carbonatites and associated mineral deposits has occupied prominent place in mineral resource exploration programs. In this study an integrated approach was developed to map carbonatite and related mineral deposits in the Loe‐Shilman, Northwest Himalaya of Pakistan, using remotely sensed advance space‐borne thermal emission and reflection radiometer (ASTER) multispectral data and visible near infrared and short‐wave infrared (VNIR‐SWIR) spectral characteristics of minerals in these deposits. Several image enhancement techniques, including band ratio (i.e., B4/B3), principal component and minimum noise fraction transformation (PC6 and MNF5, respectively) helped in highlighting the targeted rocks. The results demonstrate the suitability of ASTER data for discriminating carbonatite related mineral deposits from other surrounding lithologies. Results obtained from these methods were validated through field observations in the area and further confirmed through petrographic and chemical analyses of collected specimens. Field data have also served as training data to perform a supervised classification, allowing further improvement of the mapping results. Moreover, the obtained results from the techniques used for exploring carbonatites and related mineral deposits were stacked together for comparison with each other, to check their sensitivities, and assess their efficiency and accuracy. Generally, all these methods successfully highlighted carbonatites and related mineral deposits; however, when used integratively they exhibit higher degree of accuracy, and has proven to be relatively rapid and cost‐effective.

Integrated remote sensing data and field investigations for geological mapping and structural analysis. The case of SW Tichoukt ridge (Middle Atlas, Morocco)

Boulemane area is one of the important key sectors to understand the evolution of the central Middle Atlas of Morocco. It is a junction area of three Cretaceous/Paleogene unconformable sedimentary basins on the Triassic-Jurassic deposits.This work is a combination of remote sensing results (optical and radar data) supported by field observations to accurate a high-precision geological map of the study area. For this purpose, we used two types of images that are the radar image (Sentinel-1 data) and the optical multispectral images: Landsat 8 OLI (Optical Land Imager) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The two multispectral images have been spatially enhanced using the panchromatic band of the HRG-2 (High Geometric Resolution) sensor of SPOT 5, allowing the production of high spatial resolution images (5m).The colored compositions that were chosen using OIF (Optimum Index Factor), and PCA (Principal Component Analysis) allowed good discrimination of the main rock. Moreover, ASTER thermal bands have allowed the delimitation of large outcrops of yellow sandstone, conglomerate, phosphate and gypsum based on their thermal emissivity.Structural lineaments are manually extracted from Sentinel-1 radar images after applying directional filters, analyzing Landsat 8 OLI, ASTER high-resolution multispectral images, and interpreting the spatial juxtaposition of lithological features after digitizing the final lithological map.The extracted structural lineaments are grouped into major systems mainly oriented NE-SW, and NW-SE. The NE-SW system is constituted by faults inherited from the Paleozoic basement. The NW-SE transverse system is constituted by faults newly developed during the Middle Liassic.

Uncertainties in Prediction of Streamflows Using SWAT Model—Role of Remote Sensing and Precipitation Sources

Watershed modelling is crucial for understanding fluctuations in water balance and ensuring sustainable water management. The models’ strength and predictive ability are heavily reliant on inputs such as topography, land use, and climate. This study mainly focuses on quantifying the uncertainty associated with the input sources of the Digital Elevation Model (DEM), Land Use Land Cover (LULC), and precipitation using the Soil and Water Assessment Tool (SWAT) model. Basin-level modelling is being carried out to analyze the impact of source uncertainty in the prediction of streamflow. The sources for DEM used are National Elevation Dataset (NED)-United States Geological Survey (USGS), Shuttle Radar Topographic Mission (SRTM), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), whereas for LULC the sources were the National Land Cover Database (NLCD), Continuous Change Detection Classification (CCDC), and GAP/LANDFIRE National Terrestrial Ecosystems dataset. Observed monitoring stations (Gage), Climate Forecast System Reanalysis (CFSR), and Tropical Rainfall Measuring Mission (TRMM) satellites are the respective precipitation sources. The Nash-Sutcliffe Efficiency (NSE), Coefficient of Determination (R2), Percent Bias (PBIAS), and the ratio of Root Mean Square Error to the standard deviation (RSR) are used to assess the model’s predictive performance. The results indicated that TRMM yielded better performance compared to the CFSR dataset. The USGS DEM performs best in all four case studies with the NLCD and CCDC LULC for all precipitation datasets except Gage. Furthermore, the results show that using a DEM with an appropriate combination can improve the model’s prediction ability by simulating streamflows with lower uncertainties. TheVIKOR MCDM method is used to rank model combinations. It is observed from MCDM analysis that USGS DEM combinations with NLCD/CCDC LULC attained top priority with all precipitation datasets. Furthermore, the rankings obtained from VIKOR MCDM are in accordance with the validation analysis using SWAT.

Remote sensing of Listvenite rock for Kaymaz Gold Deposit, Eskişehir-TÜRKİYE

The Kaymaz Gold Deposit (KGD) is an economically important gold deposit in Eskişehir, Central Anatolia, Türkiye. The deposit occurred in very rare non carbonate-containing and highly silicified listvenite rock, an alteration product of serpentine in the Tavşanlı Zone, located south of the İzmir–Ankara–Erzincan Suture Zone. We studied the alteration in the KGD through petrographic examination and XRD analyses. We used Fourier-transform infrared (FTIR) spectroscopy to study the spectral absorption properties of field samples. The absorbance and reflectance patterns of the samples were used to derive mineral maps using the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) and Sentinel-2 images. The argillized zone was mapped using ASTER band ratio images 4/6, 4/9, 7/6, and RGB (red-green-blue) composite images. In addition, the 11/2 and 10/11 band ratios of Sentinel-2 were used to map Fe-oxyhydroxide containing listvenite and serpentinite, respectively. The images of band ratios and derived RGBs discriminated the altered rocks as well as the metamorphic and ultramafic rocks occurring around the open-pit mine and can be used to explore new deposits in similar geological settings. The results were verified and confirmed in the field, which showed that the ore zone is highly silicified with significant Fe-oxyhydroxide content.

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.

Investigation of geochemical characteristics and hydrothermal alteration zone mapping supported by remote sensing of a porphyry copper prospect, southeastern Iran: integrated applications to exploration

The area discussed in this exploration methodology case study is situated along the Sistan Suture Zone where the granitoid suite is a mantle-derived multiphase intrusive complex. One of the characteristics of this region is the presence of large areas of sulfide-bearing, quartz-rich stockwork and pyritic veins. Geochemical findings show that it is limited to the calc-alkaline to shoshonitic series intrusions and is associated with a volcanic arc (I-type) formed within an active continental margin subduction setting. The associated intrusive complex has characteristics consistent with Cu productive porphyries, supported by high K-adakitic Sr/Y, La/Yb, Y and Al 2 O 3 /TiO 2 geochemical signatures. The stockwork mineralization includes the hypogene (chalcopyrite and bornite), with locally superimposed supergene (covellite, malachite, goethite and hematite) zones. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images (visible-near infrared (VNIR), and shortwave infrared (SWIR) bands) and mixture tuned matched filtering (MTMF) algorithm enable identification of each hydrothermal alteration type, especially where pictures were innovatively classified using a concentration–number (C–N) fractal method. Four alteration types are evident (i.e. phyllic, argillic and propylitic), as well as secondary (supergene) jarosite, that are associated with gossans, which are an indicator of the hypogene pyritic shell. The propylitic alteration envelopes the phyllic and argillic varieties, forming a belt around the pyritic shell; alteration assemblages were confirmed by X-ray powder diffraction (XRD) analysis. Finally, all results show a mineralization alteration pattern within the case study region that is similar to those of known porphyry copper and associated molybdenum- and gold-bearing systems in this region of Iran and worldwide.

Processing of Multispectral ASTER Data to Delineate Bauxite Abundant Zones and its Geochemical Characterisation Deposited over Deccan Traps of Central India in Mainpat Plateau, Surguja District, Chhattisgarh

Abstract The current study deals with the application of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral data to delineate bauxite deposits over Mainpat plateau, Surguja district, Chhattisgarh, India. Application of specific band combinations help to delineate bauxite in the (SWIR) region (2.16-2.33 μm) and visible near infrared (VNIR) band (0.4–1.0 μm) of multispectral ASTER data. Various image processing techniques like atmospheric correction, minimum noise fraction, pixel purity index, n-dimensional visualiser, and spectral angle mapper were applied to ASTER image to delineate bauxite rich zones. The pure pixels were differentiated from the mixed pixels using pixel purity index which were further subjected to n-dimensional visualiser to identify the target end-members. The presence of bauxite was confirmed by comparing the spectral signatures of end-members with in-built spectral plots of United States Geological Survey spectral libraries and categorized as bauxite and ferruginous bauxite. Finally, the end-members were categorised as bauxite and ferruginous bauxite and mapped using spectral angle mapper. The result obtained was further compared with the lithological map provided by Geological Survey of India for accuracy. Then XRF analysis was carried out for the collected samples to confirm the presence of bauxite and ferruginous bauxite. Geochemical analysis also categorized the samples as bauxite and ferruginous bauxite that added accuracy to the results obtained from remote sensing technique. This study might be considered as a time saving eco-friendly exploitation of natural resources and finally the potential of multispectral ASTER data for mapping mineral resources.

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

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

Multispectral discrimination of spectrally similar hydrothermal minerals in mafic crust: A 5000 km2 ASTER alteration map of the Oman–UAE ophiolite

Multispectral remote sensing of hydrothermal alteration in volcanogenic massive sulfide (VMS) ore systems in mafic crust is relatively uncommon, in part due to the short-wave infrared spectral similarity of several key alteration minerals: epidote, chlorite, actinolite, and serpentine. In this study, we developed regional mosaic generation and classification workflows for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery to discriminate these minerals over the entire crust of the Semail ophiolite (Oman–UAE). Spectral discrimination was achieved through adaptation of the ASTER (pre-)processing workflow to the specific mapping targets, available datasets, and location of this study. Necessary steps included the pre-selection of ASTER scenes without residual atmospheric water features, mosaic normalization based solely on overlapping target outcrops, correcting cross-mosaic ramp errors, and alteration map classification based on image-derived reference data. The resulting alteration map, validated through comparison with field mapping and sampling, is the most areally extensive continuous survey of hydrothermal alteration yet presented for oceanic crust, providing a renewed framework for research and mineral exploration of Earth's largest ophiolite. Our map confirms that the vast majority of the upper oceanic crust is regionally altered to a spilite type secondary mineral assemblage. Localized areas of epidosite alteration, marking focused hydrothermal flow paths, are confined to the upper oceanic crust, whereas areas of previously unrecognized but intense actinolite alteration are common in both the lower and upper oceanic crust. Our methodological developments expand the standard considerations necessary for regional geological mapping using infrared image mosaics. They further demonstrate the underappreciated capability of multispectral data for mapping spectrally similar rock types. Although the specifics of the method are necessarily optimized for the Oman–UAE ophiolite, re-optimization based on local reference data should allow similar results to be achieved in other well-exposed mafic-hosted VMS districts.

The ATL08 as a height reference for the global digital elevation models

ABSTRACT High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to <20 m. The evaluations of ASTER, SRTM, and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams. These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.

Orographic Construction of a Numerical Weather Prediction Spectral Model Based on ASTER Data and Its Application to Simulation of the Henan 20·7 Extreme Rainfall Event

Numerical weather prediction (NWP) has become an important method of predicting extreme weather events, but orography is one of the key factors affecting the performance of NWPs. In this paper, based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) elevation data, a method for constructing a global orographic dataset suitable for NWP spectral models is investigated. The Yin-He global spectrum model (YHGSM) is used to simulate the early and peak periods of the extreme rainfall event on 20 July 2021 in Henan Province, China, and the heavy rain in Beijing in order to verify the effectiveness and superiority of the proposed orographic construction method. It is demonstrated that in a few cases the direct two-dimensional filter can sometimes simulate more intense rainfall, but in general, the bidirectional one-dimensional filter is better than the direct two-dimensional filter in orographic processing, and the bidirectional one-dimensional filter can filter out more of the small-scale orographic information. The effect of the higher orographic resolution before conversion to spectral space is not very obvious, but it is demonstrated that the simulation results are better for the heavy-rainfall level. In conclusion, in most cases, the simulations conducted using the new global orographic dataset based on ASTER data are better than those obtained using the model’s original orography, especially for torrential and extreme rainfall. These conclusions provide a reference for future predictions of and research on extreme rainfall events.

Detection of geothermal anomalies in the Northern Lake Abaya geothermal field, Main Ethiopian Rift

The detection of geothermal anomalies using Thermal Infrared (TIR) remote sensing data is challenging because of how sensor specifications (such as the infrared wavelength used for the measurement, spectral dependence of the emissivity, angle at which the measurement is made, state of the surface and height of the sensor above the surface) and physical parameters (such as solar radiation, topography, albedo, soil compaction and coherence of rocks) affect Land Surface Temperature (LST) retrieval and analysis. This work tests whether TIR remote sensing measurements with thorough spatial and temporal sampling can improve LST retrievals. Multi-temporal TIR data from 2000 through 2019 from Landsat 7 and 8 TIR instruments and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to detect geothermal areas in the geologically active region of the southern Main Ethiopian Rift. In addition, field-based temperature data from 19 sites were evaluated for comparison to the remotely detected geothermal anomaly areas. We have used the single-channel algorithm and Normalized Difference Vegetation Index (NDVI) method of emissivity retrieval to derive LST for each year. The result shows that the mean LST is highest in 2003 (320.1 K) and lowest in 2019 (303.1 K). The change in mean LST was between −9 K to 13 K. These LST results from ASTER images were validated with MODIS LST products and showed a correlation coefficient >0.6. LST of the year 2003 has been much closer to the actual temperature value from field data. Fifteen sites (79%) fit with the identified geothermal anomaly areas. LST values in known geothermal activity sites show no correlation (< 0.5) with time attesting. That is, even though LST varies with time (e.g., day and night and seasonal changes), the LST of areas with geothermal potential remain more or less constant on yearly basis.

The West Kunlun Glacier Anomaly and Its Response to Climate Forcing during 2002–2020

Research into glacial mass change in West Kunlun (WK) has been sufficient, but most of the existing studies were based on geodetic methods, which are not suitable for specific health state analyses of each glacier. In this paper, we utilize Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery, applying the continuity equation to obtain altitudinal specific mass balance (SMB) for 615 glaciers (&gt;2 km2) during 2002–2011, 2011–2020, and 2002–2020 to research glacial health and its response to climatic forcing. The results show dissimilar glacier SMB patterns between 2002–2011 (0.10 ± 0.14 m w.e. a−1), 2011–2020 (–0.12 ± 0.14 m w.e. a−1) and 2002–2020 (−0.01 ± 0.07 m w.e. a−1). Additionally, the glacier equilibrium line altitude (ELA) in WK was 5788 m, 5744 m, and 5786 m, respectively, and the corresponding accumulation area ratios (AARs) were 0.59, 0.62, and 0.58, during 2002–2011, 2011–2020, and 2002–2020, respectively. Regarding glacier response, compared with the ordinary-least-square (OLS) model, the artificial neural network (ANN) model revealed a respectively less and more sensitive glacier SMB response to extreme negative and positive summer skin temperatures. In addition, the ANN model indicated that the glacier ELA was less sensitive when the integrated water vapor transport (IVT) change exceeded 0.7 kg m−1s−1. Moreover, compared with IVT (−121.57 m/kg m−1s−1), glacier ELA shifts were chiefly dominated by summer skin temperature (+154.66 m/℃) in the last two decades. From 2002–2011 and 2011–2020, glacier SMB was more susceptible to summer skin temperature (−0.38 m w.e./℃ and −0.16 m w.e./℃, respectively), while during 2002–2020, it was more influenced by IVT (0.45 m w.e./kg m−1s−1). In contrast with eastern WK, glaciers in western WK were healthier, although mitigation measures are still needed to safeguard glacier health and prevent possible natural hazards in this region. Finally, we believe that the inconsistent change between glacier SMB and ELAs from 2002–2020 was connected with ice rheology and that the combined effects of skin temperature and IVT can explain the WK glacier anomaly.

Detection of thermal features from space at Indonesian volcanoes from 2000 to 2020 using ASTER

Routine analysis and detection of volcanic thermal features (VTFs) are available globally for low spatial resolution (>1 km/pixel) thermal infrared (TIR) sensors. However, medium resolution (90 m/pixel) ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) TIR data, which is sensitive to smaller and cooler VTFs, have yet to be systematically examined at all active Indonesian volcanoes. We manually examined cloud-free nighttime images at 136 potentially active volcanoes from 2000 to 2020 CE and found at least 71 volcanoes with VTFs, despite the low proportion (26.5%) of cloud-free images. Of these, 34 volcanoes have VTF detections from space published for the first time (to our knowledge) and at least 44 volcanoes have non-eruptive VTFs (fumaroles, heated volcanic lakes and open vent systems). The inclusion of hotspots detected by ASTER in this study increases the percentage of Indonesian volcanoes with recorded satellite-detectable thermal features from 27% to 52%, larger than in Latin America (27%) and the US (33%) which were surveyed in the same way and is possibly due to a higher frequency of eruptions in Indonesia. The distribution of VTFs across sub-regions in Indonesia is not uniform but may be correlated with the number of volcanoes with eruptions. This multi-decadal country-wide survey highlights the potential of TIR monitoring and detection of low-temperature volcanic features that may be eruption precursors, but also the limits of the available datasets since many volcanoes only have a few cloud-free nighttime images per year.