Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis

Crósta, Álvaro Penteado; Filho, Carlos Roberto de Souza; Azevedo, Francisco Fransualdo de; Brodie, Colin G.

doi:10.1080/0143116031000152291

Cited by 356 publications

(174 citation statements)

References 8 publications

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“…Applying principle component analysis (PCA; for a full mathematical description, see Richards and Jia (2006;chapter 6.1)), or empirical orthogonal functions (EOFs; e.g., Denbo and Allen, 1984;Hamlington et al, 2011;Lorenz, 1956) allows the assessment of independent structures within complex data sets. Because both approaches share a similar methodology, here, PCA is used to determine which spatial factors are controlling patterns of LST within the time series.…”

Section: Principle Component Analysismentioning

confidence: 99%

Identification of catchment functional units by time series of thermal remote sensing images

Müller

Bernhardt

Schulz

2014

Hydrol. Earth Syst. Sci.

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Abstract. The identification of catchment functional behavior with regards to water and energy balance is an important step during the parameterization of land surface models.An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST).For the mesoscale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) was extracted and analyzed, applying a novel process chain.First, the application of mathematical-statistical pattern analysis techniques demonstrated a strong degree of pattern persistency in the data. Dominant LST patterns over a period of 12 years were then extracted by a principal component analysis. Component values of the two most dominant components could be related for each land surface pixel to land use data and geology, respectively. The application of a data condensation technique ("binary words") extracting distinct differences in the LST dynamics allowed the separation into landscape units that show similar behavior under radiationdriven conditions.It is further outlined that both information component values from principal component analysis (PCA), as well as the functional units from the binary words classification, will highly improve the conceptualization and parameterization of land surface models and the planning of observational networks within a catchment.

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Section: Principle Component Analysismentioning

confidence: 99%

Identification of catchment functional units by time series of thermal remote sensing images

Müller

Bernhardt

Schulz

2014

Hydrol. Earth Syst. Sci.

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“…Developed Selective Principal Component Analysis (DSPCA) has been successfully proposed and applied on previous Landsat data by (Crósta & Moore 1990), thus a DSPCA was carried out in order to map Al-OH bearing altered rocks in this study. The input data of this technique is a subset of spectral bands containing specific spectral characteristics of the target material (Crósta et al 2003). …”

Section: Resultsmentioning

confidence: 99%

Targeting Hydrothermal Alterations Utilizing Landsat-8 Andaster Data in Shahr-E-Babak, Iran

Safari

Pour

Maghsoudi

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Shahr-e-Babak tract of the Kerman metalogenic belt is one of the most potential segments of Urumieh-Dokhtar (Sahand-Bazman) magmatic arc. This area encompasses several porphyry copper deposits in exploration, development and exploitation hierarchy. The aim of this study is to map hydrothermal alterations caused by early Cenozoic magmatic intrusions in Shahr-e-Babak area. To this purpose, mineral mapping methods including band combinations, ratios and multiplications as well as PCA and MNF data space transforms in SWIR and VNIR for both ASTER and OLI sensors. Alteration zones according to spectral signatures of each type of alteration mineral assemblages such as argillic, phyllic and propylitic are successfully mapped. For enhancing the target areas false color composites and HSI-RGB color space transform are performed on developed band combinations. Previous studies have proven the robust application of ASTER in geology and mineral exploration; nonetheless, the results of this investigation prove applicability of OLI sensor from landsat-8 for alteration mapping. According to the results, evidently OLI sensor data can accurately map alteration zones. Additionally, the 12-bit quantization of OLI data is its privilege over 8-bit data of ASTER in VNIR and SWIR, thus OLI high quality results, which makes it easy to distinguish targets with enhanced color contrast between the altered and unaltered rocks.

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“…Para cada periodo se estimó el Índice de Vegetación de Diferencia Normalizada (NDVI) (14 y 15, datos para invierno y verano, respectivamente) (Townshend et al, 1985). También se han aplicado una serie de algoritmos sobre las imágenes seleccionadas para obtener indicadores mineralógicos (Sabins, 1981;Crosta et al, 2003), mediante combinación de las siguientes funciones estandarizadas "Clay Minerals" (minerales de arcilla, CMI) (16 y 19), "Ferrous Minerals" (minerales ferrosos, FMI) (17 y 20) y "Iron Oxide" (óxidos de hierro, IOI) (18 y 21). Para cada una de las funciones se han realizado los cálculos correspondientes a la estación de verano (Julio) e invierno (Febrero).…”

Section: Iii2 Variables Ambientales Modelizadasunclassified

Efectos de las variables ambientales en la estimación de materia orgánica del suelo a escala regional en un ambiente semiarido (Región de Murcia, España)

Pérez‐Cutillas¹,

Barberá²,

García³

2017

BAGE

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RESUMENLa estimación de valores edáficos mediante el empleo de técnicas de modelización espacial, basada en procesos y variables ambientales, es utilizada en este trabajo para analizar el efecto que tienen estas variables sobre la materia orgánica del suelo (MOS). La discusión es enormemente interesante por las conclusiones que se pueden extraer de las distintas implicaciones que ejercen los patrones ecológicos en su distribución y variabilidad espacial. En este estudio se ha utilizado una base de datos de 1126 muestras de materia orgánica en capa arable del suelo en la Región de Murcia (SE de España), con el fin de estimar el contenido de la MOS a escala regional (más de 10000 km 2 ) mediante el uso de 21 variables ambientales como predictores. Entre las variables más influyentes destacan las asociadas al relieve (i.e. la pendiente, las curvaturas del terreno), la acumulación de flujo vinculada a las redes de drenaje, la precipitación, la radicación solar y ciertos índices específicos obtenidos mediante técnicas de teledetección, como el NDVI o el Índice Mineralógico de Arcillas CMI.Palabras clave: Propiedades del suelo, materia orgánica del suelo, modelización, SIG, variables ambientales, teledetección.Boletín de la Asociación de Geógrafos Españoles N.º 75 -2017, págs. 175-191 I.S.S.N.: 0212-9426

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Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis

Cited by 356 publications

References 8 publications

Identification of catchment functional units by time series of thermal remote sensing images

Identification of catchment functional units by time series of thermal remote sensing images

Targeting Hydrothermal Alterations Utilizing Landsat-8 Andaster Data in Shahr-E-Babak, Iran

Efectos de las variables ambientales en la estimación de materia orgánica del suelo a escala regional en un ambiente semiarido (Región de Murcia, España)

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