Mapping Phyllic and Argillic-Altered Rocks in Southeastern Afghanistan using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data

2007 ◽  
Author(s):  
John L. Mars ◽  
Lawrence C. Rowan
Keyword(s):  
Thermal Emission ◽  
Aster Data

scholarly journals GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 489-494 ◽  
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Volume Change ◽  
Thermal Emission ◽  
Aster Data ◽  
Rational Polynomial ◽  
The Cross ◽  
Cross Track ◽  
Along Track

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

scholarly journals A Remote-Sensing-Based Alteration Zonation Model of the Duolong Porphyry Copper Ore District, Tibet

2021 ◽  
Vol 13 (24) ◽  
pp. 5073
Author(s):  
Fojun Yao ◽  
Xingwang Xu ◽  
Jianmin Yang ◽  
Xinxia Geng
Keyword(s):  
Remote Sensing ◽  
Thermal Emission ◽  
Mineral Exploration ◽  
Porphyry Copper ◽  
Principal Component ◽  
Thermal Infrared ◽  
Copper Ore ◽  
Aster Data ◽  
Alteration Zoning ◽  
Ore District

Remote sensing (RS) of alteration zones and anomalies can provide information that is useful for geological prospecting and exploration. RS is an effective method for porphyry copper mineral exploration and prospecting prediction. More specifically, the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) data, which include 14 spectral channels from visible light to thermal infrared, are useful in such cases. This study uses visible-shortwave infrared and thermal infrared ASTER data together with surface material spectra from the Duolong porphyry copper ore district to construct an RS-based alteration zonation model of the deposit. In this study, an RS alteration zoning model is established based on ground-spectral alteration zoning results. The methods include PCA (Principal Component Analysis), Ratio, and Slope methods. The information obtained by each method is different. RS-based alteration zonation is developed based on the intersection of maps, resultant from the different methods for extracting information related to different minerals. The alteration zonation information extracted from ASTER RS data is consistent with geological observations. Using information from the RS-based model, we mapped the alteration minerals and zones of the Duolong ore district, thereby identifying prospecting target areas of the deposit.

scholarly journals GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 489-494
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Volume Change ◽  
Thermal Emission ◽  
Aster Data ◽  
Rational Polynomial ◽  
The Cross ◽  
Cross Track ◽  
Along Track

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

Evaluation of Surface Temperature and Emissivity Derived from ASTER Data: A Case Study Using Ground-Based Measurements at a Volcanic Site

2010 ◽  
Vol 27 (10) ◽  
pp. 1677-1688 ◽  
Author(s):  
África Barreto ◽  
Manuel Arbelo ◽  
Pedro A. Hernández-Leal ◽  
Laia Núñez-Casillas ◽  
María Mira ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Thermal Emission ◽  
Surface Composition ◽  
Atmospheric Correction ◽  
Naval Research ◽  
Measurement Scales ◽  
Aster Data ◽  
Spectral Contrast

Abstract The land surface temperature (LST) and emissivity (LSE) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were evaluated in a low spectral contrast volcanic site at an altitude of 2000 m on the island of Tenerife, Spain. The test site is almost flat, thermally homogeneous, and without vegetation cover or variation in its surface composition. ASTER data correspond to six scenes, under both day- and nighttime conditions during 2008. This case study analyzes the impacts of the sources of inaccuracies using the temperature–emissivity separation (TES) algorithm. Uncertainties associated with inaccurate atmospheric correction were minimized by means of local soundings and the climate advantages of the area. Concurrent ground-based radiometric measurements were performed for LST, and laboratory and field measurements for LSE, to obtain reference values. The TES evaluation showed a good level of agreement in the emissivity derived for ASTER bands 13 and 14 [root-mean-square difference (RMSD) lower than 0.002] and discrepancies in ASTER bands 10 and 11 that were within the expected performance of the algorithm (±0.015). However, out-of-threshold errors were retrieved in band 12, producing an artificial increase in spectral contrast. The underestimated TES LSE spectra point to the presence of a roughness effect at measurement scales that may increase the laboratory band emissivity values. TES LST comparison with ground data showed an RMSD value of 0.5 K. ASTER standard products AST08 (LST) and AST05 (LSE) atmospherically corrected by means of Naval Research Laboratory (NRL) data were also tested, showing a similar level of performance for the TES implemented with local soundings, but failed in high-humidity atmospheric conditions.

scholarly journals Recognition of a porphyry system using ASTER data in Bideghan – Qom province (central of Iran)

2014 ◽  
Vol 6 (2) ◽  
pp. 1765-1798 ◽  
Author(s):  
F. Feizi ◽  
E. Mansouri
Keyword(s):  
Thermal Emission ◽  
Volcanic Rocks ◽  
Principal Component ◽  
Field Investigation ◽  
Least Square ◽  
Band Ratio ◽  
Aster Data ◽  
False Color ◽  
False Color Composite ◽  
Color Composite

Abstract. The Bideghan area is located south of the Qom province (central of Iran). The most impressive geological features in the studied area are the Eocene sequences which are intruded by volcanic rocks with basic compositions. Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) image processing have been used for hydrothermal alteration mapping and lineaments identification in the investigated area. In this research false color composite, band ratio, Principal Component Analysis (PCA), Least Square Fit (LS-Fit) and Spectral Angel Mapping (SAM) techniques were applied on ASTER data and argillic, phyllic, Iron oxide and propylitic alteration zones were separated. Lineaments were identified by aid of false color composite, high pass filters and hill-shade DEM techniques. The results of this study demonstrate the usefulness of remote sensing method and ASTER multi-spectral data for alteration and lineament mapping. Finally, the results were confirmed by field investigation.

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