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This study aims to map minerals of hydrothermal alteration zones in the Rehamna Massif, formerly site of large exploitation of Pb-Zn, Ba-Pb and W-Sn hosted within the Paleozoic basement, using the advantages of remote sensing technique. In this regard, ASTER remote sensing data have been used as a substrate for spectral processing, namely band ratios, to identify hydrothermal alteration zones characteristic of polymetallic mineralization. Band ratio technique leads us to map the Phyllic, Argillic, Prophylitic, Oxidation and kaolinite zones. Other ratios such as Muscovite, Allunite, Calcite and Fe-oxides were also computed. The areas reported were locally compared with the geological setting. The compilations of the results facilitate the identification of eight potential sites suitable for a possible tactical research phase. These results can encourage mining exploration and guide mining companies to the most potentially ore-bearing sites and support the economic development of the Rehamna area. [ABSTRACT FROM AUTHOR]

East African lakes support the food and water security of millions of people. Yet, a lack of continuous long-term water quality data for these waterbodies impedes their sustainable management. While satellite-based water quality retrieval methods have been developed for lakes globally, African lakes are typically underrepresented in training data, limiting the applicability of existing methods to the region. Hence, this study aimed to (1) assess the accuracy of existing and newly developed water quality band algorithms for East African lakes and (2) make satellite-derived water quality information easily accessible through a Google Earth Engine application (app), named LAndsat water QUality retrieval tool for east African lakes (LAQUA). We collated a dataset of existing and newly collected in situ surface water quality samples from seven lakes to develop and test Landsat water quality retrieval models. Twenty-one published algorithms were evaluated and compared with newly developed linear and quadratic regression models, to determine the most suitable Landsat band algorithms for chlorophyll-a, total suspended solids (TSS), and Secchi disk depth (SDD) for East African lakes. The three-band algorithm, parameterised using data for East African lakes, proved the most suitable for chlorophyll-a retrieval (R2 = 0.717, p < 0.001, RMSE = 22.917 μg/L), a novel index developed in this study, the Modified Suspended Matter Index (MSMI), was the most accurate for TSS retrieval (R2 = 0.822, p < 0.001, RMSE = 9.006 mg/L), and an existing global model was the most accurate for SDD estimation (R2 = 0.933, p < 0.001, RMSE = 0.073 m). The LAQUA app we developed provides easy access to the best performing retrieval models, facilitating the use of water quality information for management and evidence-informed policy making for East African lakes. [ABSTRACT FROM AUTHOR]

The efficacy of remote sensing techniques for mineral exploration has been proven through several geological investigations. Therefore, this study used remote sensing techniques to delineate uranium prospective zones in the oriental part of Reguibat shield. This region is desert, flat and uncovered by vegetation and presents suitable characteristics for use of satellite images. Radiometric calibration, atmospheric correction, colour composite, principal component analysis (PCA), lineament extraction and band ratios were the main methods performed for the pre-processing and the processing of Landsat 8 OLI images. The findings of the current study revealed lithological units dominated by felsic rocks in association with metasediment, highlighted using band composite (bands 7, 5 and 3, then 7, 2, and 1, in RGB), PCs (PC1, PC2, and PC3) and band ratio (7/5, 5/4, and 6/7 in RGB). The lineament extraction and analysis indicated major deformation trending NNE-SSW affecting geological units of the area. The prospective uraniferous zone delineated showed a spatial distribution in relation with an identified shear zone which suggests a reasonable structural control of the mineralization. The results from this study were validated with existing data from previous map and ground truthing from fieldwork, and they showed high level of agreement. The result of this study further demonstrated the applicability of Landsat 8 OLI as suitable lithological mapping tool in the desert areas. The methodology employed in this research has wide-ranging applications in the identification and delineation of potential uranium-rich regions using remote sensing techniques. For uranium exploration purpose, this approach can be effectively utilized in various other regions to delineate new uraniferous area within the Reguibat shield, as well as in arid and semi-arid areas across the globe. [ABSTRACT FROM AUTHOR]

Chlorophyll-a concentration (Chl-a) is commonly used as a proxy for phytoplankton abundance in surface waters of large lakes. Mapping spatial and temporal Chl-a distributions derived from multispectral satellite data is therefore increasingly popular for monitoring trends in trophic state of these important ecosystems. We evaluated products of eleven atmospheric correction processors (LEDAPS, LaSRC, Sen2Cor, ACOLITE, ATCOR, C2RCC, DOS 1, FLAASH, iCOR, Polymer, and QUAC) and 27 reflectance indexes (including band-ratio, three-band, and four-band algorithms) recommended for Chl-a concentration retrieval. These were applied to the western basin of Lake Ontario by pairing 236 satellite scenes from Landsat 5, 7, 8, and Sentinel-2 acquired between 2000 and 2022 to 600 near-synchronous and co-located in situ-measured Chl-a concentrations. The in situ data were categorized based on location, seasonality, and Carlson's Trophic State Index (TSI). Linear regression Chl-a models were calibrated for each processing scheme plus data category. The models were compared using a range of performance metrics. Categorization of data based on trophic state yielded improved outcomes. Furthermore, Sentinel-2 and Landsat 8 data provided the best results, while Landsat 5 and 7 underperformed. A total of 28 Chl-a models were developed across the different data categorization schemes, with RMSEs ranging from 1.1 to 14.1 μg/L. ACOLITE-corrected images paired with the blue-to-green band ratio emerged as the generally best performing scheme. However, model performance was dependent on the data filtration practices and varied between satellites. [ABSTRACT FROM AUTHOR]

East African lakes support the food and water security of millions of people. Yet, a lack of continuous long-term water quality data for these waterbodies impedes their sustainable management. While satellite-based water quality retrieval methods have been developed for lakes globally, African lakes are typically underrepresented in training data, limiting the applicability of existing methods to the region. Hence, this study aimed to (1) assess the accuracy of existing and newly developed water quality band algorithms for East African lakes and (2) make satellite-derived water quality information easily accessible through a Google Earth Engine application (app), named LAndsat water QUality retrieval tool for east African lakes (LAQUA). We collated a dataset of existing and newly collected in situ surface water quality samples from seven lakes to develop and test Landsat water quality retrieval models. Twenty-one published algorithms were evaluated and compared with newly developed linear and quadratic regression models, to determine the most suitable Landsat band algorithms for chlorophyll-a, total suspended solids (TSS), and Secchi disk depth (SDD) for East African lakes. The three-band algorithm, parameterised using data for East African lakes, proved the most suitable for chlorophyll-a retrieval (R2 = 0.717, p < 0.001, RMSE = 22.917 μg/L), a novel index developed in this study, the Modified Suspended Matter Index (MSMI), was the most accurate for TSS retrieval (R2 = 0.822, p < 0.001, RMSE = 9.006 mg/L), and an existing global model was the most accurate for SDD estimation (R2 = 0.933, p < 0.001, RMSE = 0.073 m). The LAQUA app we developed provides easy access to the best performing retrieval models, facilitating the use of water quality information for management and evidence-informed policy making for East African lakes.

Chlorophyll-a concentration (Chl-a) is commonly used as a proxy for phytoplankton abundance in surface waters of large lakes. Mapping spatial and temporal Chl-a distributions derived from multispectral satellite data is therefore increasingly popular for monitoring trends in trophic state of these important ecosystems. We evaluated products of eleven atmospheric correction processors (LEDAPS, LaSRC, Sen2Cor, ACOLITE, ATCOR, C2RCC, DOS 1, FLAASH, iCOR, Polymer, and QUAC) and 27 reflectance indexes (including band-ratio, three-band, and four-band algorithms) recommended for Chl-a concentration retrieval. These were applied to the western basin of Lake Ontario by pairing 236 satellite scenes from Landsat 5, 7, 8, and Sentinel-2 acquired between 2000 and 2022 to 600 near-synchronous and co-located in situ-measured Chl-a concentrations. The in situ data were categorized based on location, seasonality, and Carlson’s Trophic State Index (TSI). Linear regression Chl-a models were calibrated for each processing scheme plus data category. The models were compared using a range of performance metrics. Categorization of data based on trophic state yielded improved outcomes. Furthermore, Sentinel-2 and Landsat 8 data provided the best results, while Landsat 5 and 7 underperformed. A total of 28 Chl-a models were developed across the different data categorization schemes, with RMSEs ranging from 1.1 to 14.1 μg/L. ACOLITE-corrected images paired with the blue-to-green band ratio emerged as the generally best performing scheme. However, model performance was dependent on the data filtration practices and varied between satellites.

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The occurrence of spontaneous humeral fractures in primiparous dairy cows from New Zealand prompted the study of bone material from affected cows to further characterize this condition and to outline a likely pathogenesis. Previous studies indicate that these cows developed osteoporosis due to periods of suboptimal bone formation followed by increased bone resorption during the period of lactation complicated by copper deficiency. We hypothesized that there are significant differences in the chemical composition/bone quality in bones from cows with spontaneous humeral fracture compared to cows without humeral fractures. In this study, Raman and Fourier transform infrared spectroscopy band ratios were, for the first time, measured, calculated, and compared in bone samples from 67 primiparous dairy cows that suffered a spontaneous fracture of the humerus and 14 age-matched post-calving cows without humeral fractures. Affected bone showed a significantly reduced mineral/matrix ratio, increased bone remodeling, newer bone tissue with lower mineralization and, lower carbonate substitution, and reduced crystallinity. As such, is likely that these have detrimentally impacted bone quality and strength in affected cows.

As an important source of lithium and rare earth elements (REE) and other critical elements, pegmatites are of great strategic economic interest for present and future technological development. Identifying new pegmatite deposits is a strategy adopted by the European Union (EU) to decrease its import dependence on non-European countries for these raw materials. It is in this context that the GREENPEG project was established, an EU project whose main objective is to identify new deposits of pegmatites in Europe in an environmentally friendly way. Remote sensing is a non-contact exploration tool that allows for identifying areas of interest for exploration at the early stage of exploration campaigns. Several RS methods have been developed to identify Li-Cs-Ta (LCT) pegmatites, but in this study, a new methodology was developed to detect Nb-Y-F (NYF) pegmatites in the Tysfjord area in Norway. This methodology is based on spectral analysis to select bands of the Sentinel 2 satellite and adapt RS methods, such as Band Ratios and Principal Component Analysis (PCA), to be used as input in the Random Forest (RF) and other tree-based ensemble algorithms to improve the classification accuracy. The results obtained are encouraging, and the algorithm was able to successfully identify the pegmatite areas already known and new locations of interest for exploration were also defined. [ABSTRACT FROM AUTHOR]

River Ganga is one of the most significant rivers in the country. This river is the adobe for numerous aquatic species and microorganisms. The color of the river suddenly changed to green due to the rise of algal bloom in the Varanasi and nearby regions of the river Ganga during May–June 2021. These algal blooms can be detrimental to the aquatic animals of the river. This study analyzes the occurrence and the possible reasons for the algal bloom generation in the river for the considered stretch. Several factors like nutrient accumulation in the river through agricultural run-off, warm river temperature, low flow condition of the river, thermal stratification, and less turbid river water can be considered as possible reasons for algal bloom development. In this work, the optical remote sensing-based Sentinel 2 datasets have been used for the duration of mid-May 2021 to mid-June 2021. These datasets have been processed in the Google Earth Engine (GEE) platform, and chlorophyll concentration has been calculated using different satellite-based indices or band ratios. The chlorophyll concentration measurements have quantified the algal bloom growth. These indices or band ratios have been analyzed using several artificial neural network (ANN) architectures like multilayer perceptron (MLP) and radial basis function (RBF) along with the in situ values. It has been found that chlorophyll concentration has been highest for the mid-June 2021 time period in the considered river stretch. [ABSTRACT FROM AUTHOR]

The spectral signature curve behavior of basalt and its relationship with the surface reflectance (SR) values of Landsat 8 OLI data, (Operational Land Imager), is considered as the key factor for determination of the sensitive response bands for basalt interaction to be used in both Object-Oriented Principal Components (PCA) & Independent Component (ICA) analyses. Also, it is extremely beneficial in develop mathematical formulas which express the best band ratios for the precise illustration and mapping of basalts. The integration of those sensitive bands and the three mentioned methods are the main objectives of the present investigation. This should permit to create the basalt spatial distribution map for a given area. These methods were applied in west central Sinai, Egypt.The measured spectral signature reflectance curve of the basalt was resampled to meet the spectral characteristics of Landsat 8 bands, both curves were carefully examined to determine the most significant response bands for basalts; which were found to be bands 4, 5, 6 and 7. The examined spectral behavior led to three significant band ratios. Moreover, two false color composite (PC1, PC2, PC4) and (IC4, IC3, IC1) in RGB, were determined by execution and examination of the PCA and ICA images, respectively of the study area.ERDAS Imagine (2010) and ArcGIS 10.3 packages were used for digital/mathematical processing steps and to apply the resulted models on the study area.

Bathymetric mapping is integral to maintaining marine ecosystems, managing coastal zones, and safeguarding the environment. However, achieving accurate large-scale bathymetric maps remains a challenge in China, particularly in nearshore turbid waters. To address this gap, we leveraged seasonal Gaofen-6 (GF-6) data to conduct bathymetry mapping in the Yellow River Delta-Laizhou Bay area. In our study, we found that longer wavelengths, such as those in the red-edge2 and near-infrared (NIR) bands, exhibited superior performance in determining bathymetry. Moreover, specific band ratios derived from GF-6 data—such as Blue/NIR (BN), Violet/NIR (VN), Blue/Red-edge2 (BE), Violet/Red-edge2 (VE), Green/NIR (GN), and Green/Red-edge2 (GE)—showed promising outcomes, particularly in turbid nearshore waters. When comparing models, the random forest regression (RFR) model outperformed the classification and regression trees (CART) model in turbid nearshore areas, showing higher R2 values and lower RMSE. Notably, both models demonstrated higher accuracy in March compared to May and October. Incorporating the Normalized Difference Turbidity Index (NDTI) notably improved bathymetric results, especially in turbid sea regions. Furthermore, nearshore bathymetry proved highly susceptible to natural processes, seasonal variations, and human activities. The significant discrepancies in bathymetry among coastal areas emphasize the need for tailored management strategies to enhance coastal management and foster sustainable marine economic development. • The GF-6 data with different seasons were used to map nearshore bathymetry. • Longer wavelengths had better bathymetric performance in nearshore turbid waters. • The band ratios of BN, VN, BE, VE, GN and GE had good bathymetry performances. • Better bathymetry results were modelled with NDTI, especially in the turbid sea. • Adaptive strategies were proposed according to water depth and human activities. [ABSTRACT FROM AUTHOR]

As an important source of lithium and rare earth elements (REE) and other critical elements, pegmatites are of great strategic economic interest for present and future technological development. Identifying new pegmatite deposits is a strategy adopted by the European Union (EU) to decrease its import dependence on non-European countries for these raw materials. It is in this context that the GREENPEG project was established, an EU project whose main objective is to identify new deposits of pegmatites in Europe in an environmentally friendly way. Remote sensing is a non-contact exploration tool that allows for identifying areas of interest for exploration at the early stage of exploration campaigns. Several RS methods have been developed to identify Li-Cs-Ta (LCT) pegmatites, but in this study, a new methodology was developed to detect Nb-Y-F (NYF) pegmatites in the Tysfjord area in Norway. This methodology is based on spectral analysis to select bands of the Sentinel 2 satellite and adapt RS methods, such as Band Ratios and Principal Component Analysis (PCA), to be used as input in the Random Forest (RF) and other tree-based ensemble algorithms to improve the classification accuracy. The results obtained are encouraging, and the algorithm was able to successfully identify the pegmatite areas already known and new locations of interest for exploration were also defined.

Background: The organic matter (OM) in soils interacts with polyvalent cations such as Ca2+ through hydroxyl (OH), carboxylic acid, ester, keto, aldehyde (summarized as C=O), and carboxylate (COO−) functional groups. Such interactions affect the bonding strength of the double bond between the C and the O atom in the functional groups, which is assumed to shift the wavenumber (WN) region of O–H (hydroxyl), C=O, COO−, and OMcat (i.e., C=O interacting with cations plus O–H groups) absorption band maxima in the Fourier transform infrared (FTIR) spectra. Such band shifts limit the evaluation of spectral information on OM in soil samples. Aims: The objective of this study was to analyze the extent of band shifts and the changes in absorption band intensities for relations with cation concentrations, and to estimate effects of band shifts on OM properties such as potential wettability of OM evaluated from FTIR absorption band ratios. Methods: Polygalacturonic acid (PGA) solutions were mixed with a CaCl2 solution at different relations. The freeze‐dried mixtures were analyzed with FTIR spectroscopy in the mid‐infrared spectral range by using KBr‐technique. The FTIR spectra were interpreted with respect to O–H, C=O, COO−, and OMcat bands, the latter reflecting the formation of PGA‐Ca2+ complexes. Results: The FTIR spectra of the PGA–Ca mixtures compared to that of pure PGA indicate band shift effects by CaCl2 addition on both, intensity and WN value of the OMcat, C=O and COO− absorption band maxima. The COO−/C–O–C ratio increased with Ca2+ concentration while the C–H/C–O–C ratio decreased. Furthermore, the C=O and COO− absorption band maxima were shifted towards lower WN values, while the OMcat absorption band was shifted towards higher WN values. The shift of OMcat band maxima was two times higher than that of the C=O band maximum and increased with Ca2+ concentration. Conclusion: Spectral band shifts depend on polyvalent cation concentration and limit automated interpretations of FTIR spectra without prior soil‐specific spectral corrections. [ABSTRACT FROM AUTHOR]

The spectral signature curve behavior of basalt and its relationship with the surface reflectance (SR) values of Landsat 8 OLI data, (Operational Land Imager), is considered as the key factor for determination of the sensitive response bands for basalt interaction to be used in both Object-Oriented Principal Components (PCA) & Independent Component (ICA) analyses. Also, it is extremely beneficial in develop mathematical formulas which express the best band ratios for the precise illustration and mapping of basalts. The integration of those sensitive bands and the three mentioned methods are the main objectives of the present investigation. This should permit to create the basalt spatial distribution map for a given area. These methods were applied in west central Sinai, Egypt. The measured spectral signature reflectance curve of the basalt was resampled to meet the spectral characteristics of Landsat 8 bands, both curves were carefully examined to determine the most significant response bands for basalts; which were found to be bands 4, 5, 6 and 7. The examined spectral behavior led to three significant band ratios. Moreover, two false color composite (PC1, PC2, PC4) and (IC4, IC3, IC1) in RGB, were determined by execution and examination of the PCA and ICA images, respectively of the study area. ERDAS Imagine (2010) and ArcGIS 10.3 packages were used for digital/mathematical processing steps and to apply the resulted models on the study area. [ABSTRACT FROM AUTHOR]

This study presents an automated methodology to generate training data for surface water mapping from a single Sentinel-2 granule at 10 m (4 band, VIS/NIR) or 20 m (9 band, VIS/NIR/SWIR) resolution without the need for ancillary training data layers. The 20 m method incorporates an ensemble of three spectral indexes with optimal band thresholds, whereas the 10 m method achieves similar results using fewer bands and a single spectral index. A spectrally balanced and randomly generated set of training data based on the index values and optimal thresholds is used to fit machine learning classifiers. Statistical validation compares the 20 m ensemble-only method to the 20 m ensemble method with a random forest classifier. Results show the 20 m ensemble-only method had an overall accuracy of 89.5% (±1.7%), whereas the ensemble method combined with the random forest classifier performed better, with a ~4.8% higher overall accuracy: 20 m method (94.3% (±1.3%)) with optimal spectral index and SWIR thresholds of −0.03 and 800, respectively, and 10 m method (93.4% (±1.5%)) with optimal spectral index and NIR thresholds of −0.01 and 800, respectively. Comparison of other supervised classifiers trained automatically with the framework typically resulted in less than 1% accuracy improvement compared with the random forest, suggesting that training data quality is more important than classifier type. This straightforward framework enables accurate surface water classification across diverse geographies, making it ideal for development into a decision support tool for water resource managers.

Surface glacier facies are superficial expressions of a glacier that are distinguishable based on differing spectral and structural characteristics according to their age and intermixed impurities. Increasing bodies of literature suggest that the varying properties of surface glacier facies differentially influence the melt of the glacier, thus affecting the mass balance. Incorporating these variations into distributed mass balance modelling can improve the perceived accuracy of these models. However, detecting and subsequently mapping these facies with a high degree of accuracy is a necessary precursor to such complex modelling. The variations in the reflectance spectra of various glacier facies permit multiband imagery to exploit band ratios for their effective extraction. However, coarse and medium spatial resolution multispectral imagery can delimit the efficacy of band ratioing by muddling the minor spatial and spectral variations of a glacier. Very high-resolution imagery, on the other hand, creates distortions in the conventionally obtained information extracted through pixel-based classification. Therefore, robust and adaptable methods coupled with higher resolution data products are necessary to effectively map glacier facies. This study endeavours to identify and isolate glacier facies on two unnamed glaciers in the Chandra-Bhaga basin, Himalayas, using an established object-based multi-index protocol. Exploiting the very high resolution offered by WorldView-2 and its eight spectral bands, this study implements customized spectral index ratios via an object-based environment. Pixel-based supervised classification is also performed using three popular classifiers to comparatively gauge the classification accuracies. The object-based multi-index protocol delivered the highest overall accuracy of 86.67%. The Minimum Distance classifier yielded the lowest overall accuracy of 62.50%, whereas, the Mahalanobis Distance and Maximum Likelihood classifiers yielded overall accuracies of 77.50% and 70.84% respectively. The results outline the superiority of the object-based method for extraction of glacier facies. Forthcoming studies must refine the indices and test their applicability in wide ranging scenarios. [ABSTRACT FROM AUTHOR]

The exploration of carbonate-hosted Pb-Zn mineralization is challenging due to the complex structural-geological settings and costly using geophysical and geochemical techniques. Hydrothermal alteration minerals and structural features are typically associated with this type of mineralization. Application of multi-sensor remote sensing satellite imagery as a fast and inexpensive tool for mapping alteration zones and lithological units associated with carbonate-hosted Pb-Zn deposits is worthwhile. Multiple sources of spectral data derived from different remote sensing sensors can be utilized for detailed mapping a variety of hydrothermal alteration minerals in the visible near infrared (VNIR) and the shortwave infrared (SWIR) regions. In this research, Landsat-8, Sentinel-2, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and WorldView-3 (WV-3) satellite remote sensing sensors were used for prospecting Zn-Pb mineralization in the central part of the Kashmar–Kerman Tectonic Zone (KKTZ), the Central Iranian Terrane (CIT). The KKTZ has high potential for hosting Pb-Zn mineralization due to its specific geodynamic conditions (folded and thrust belt) and the occurrence of large carbonate platforms. For the processing of the satellite remote sensing datasets, band ratios and principal component analysis (PCA) techniques were adopted and implemented. Fuzzy logic modeling was applied to integrate the thematic layers produced by image processing techniques for generating mineral prospectivity maps of the study area. The spatial distribution of iron oxide/hydroxides, hydroxyl-bearing and carbonate minerals and dolomite were mapped using specialized band ratios and analyzing eigenvector loadings of the PC images. Subsequently, mineral prospectivity maps of the study area were generated by fusing the selected PC thematic layers using fuzzy logic modeling. The most favorable/prospective zones for hydrothermal ore mineralizations and carbonate-hosted Pb-Zn mineralization in the study region were particularly mapped and indicated. Confusion matrix, field reconnaissance and laboratory analysis were carried out to verify the occurrence of alteration zones and highly prospective locations of carbonate-hosted Pb-Zn mineralization in the study area. Results indicate that the spectral data derived from multi-sensor remote sensing satellite datasets can be broadly used for generating remote sensing-based prospectivity maps for exploration of carbonate-hosted Pb-Zn mineralization in many metallogenic provinces around the world.

Exploiting geothermal (GT) resources requires first and foremost locating suitable areas for its development. The focus of this paper is to explore the applicability of mapping GT related anomalies by identifying mineralogy and lithological features at regional scale using image enhancement techniques on Landsat 8 satellite data. A combination of established Band ratios from literature were implemented on Landsat 8 optical bands using innovative digital image processing and knowledge-based spectral information extraction techniques which enhanced surface mineralogy and possible alteration areas of interest. The results indicate that ratios using bands; 7/4, 6/3, 5/7 and 6/7, 4/3, 5/6 and 7/5, 5/4, 6/7 respectively as RGB, were unique but corroborative in enhancing and identifying; clay rich rocks, iron oxides, micas, carbonates and possible hydrothermal alteration zones related to GT anomaly. The results could have implication for GT exploration in especially unexplored regions where expensive airborne surveys are unaffordable. Keywords: Band ratios, Landsat 8 (OLI), Geothermal, Minerals

Landsat-8 was used for the Operational Land Imager (OLI) for the southwestern part of Najaf province to detect and distinguish the most important mineral compounds of the region using several techniques for processing space images. The image processing methods used in this study includes, color composite band ratio in addition to Principal Component Analysis (PCA). Visible, near and short infrared bands have been used to detect iron oxides, iron minerals, and clay minerals, while thermal bands have been used to distinguish silicate minerals. The color composite (RGB) of the bands (B2B5B7), (B5B7B3) and (B10, B11, B7) have been used to determine region of iron oxide, clay and iron minerals as well as silicate minerals , respectively. The band ratio of 4/2, 6/5 and 6/7 have been used to detect the presence of iron oxides and iron and clay minerals, respectively. The color composition has been applied on the band ratios (6/7,6/5,4/2) to obtain a better distinction for mineral deposits in the region. From results of (PCA) and based on signal and values of eigenvectors for PCS bands, PC3 has been selected to represent clay minerals, PC4 for iron minerals and PC5 for iron oxides. The color composite application on (PC3, PC4, PC5) shows more details about the mineral deposits of the region

Abstract The basement of the Central Andes located in central-western Argentina (31º20′S - 69º22′W) is composed by the Cuyania and Chilenia terranes which were amalgamated to Gondwana in the Early-Mid Paleozoic. Between the Precordillera (Cuyania) and Frontal Cordillera (Chilenia) there are exposures of marine metasedimentary rocks associated with mafic rocks with an E-MORB chemical signature that represent the remnants of an extensional basin developed between both terranes. The stratigraphic features and the distribution of the Early-Mid Paleozoic units along the Western Precordillera were constrained by remote sensing techniques. This allowed us to identify two stages in the evolution of the sedimentary in-fill of the marine basin: an initial stage (Mid-Late Ordovician) marked by widespread extensional tectonics and a finning-upwards sequence interbedded with volcanic-plutonic mafic rocks; and a Late Ordovician?-Devonian where the sedimentation was characterized by the development of coarsening-upwards sequences with low participation of mafic rocks. Flattened parallel folds associated with pre-Andean thrusts have locally a top-to-the SW vergence. These pre-Andean (Late Devonian) structures are the relics of the Chanic orogen whose double vergence is the result of the control exerted by previous structures related to the ordovician rifting. This is constrained by the residual and regional magnetic anomalies which reflect an important correlation between deep and surface structures. We propose the inception of a subduction zone with an eastward polarity on the proto-Pacific margin of Gondwana as the responsible for the compressive geotectonic framework that led to the closure of the Western Precordillera basin during the Late Devonian and the development of the Chanic thick-skinned-dominated orogen. Graphical abstract Image 1 Highlights • An asymmetric marine basin was developed between the Chilenia and Cuyania terranes. • The Chanic orogen was a thick-skinned-dominated orogen on the proto-pacific margin of Gondwana. • Geophysical data evidence the structural features of the Western Precordillera basement. • Andean structures are strongly controlled by inherited pre-Andean anisotropies. [ABSTRACT FROM AUTHOR]

Exploiting geothermal (GT) resources requires first and foremost locating suitable areas for its development. The focus of this paper is to explore the applicability of mapping GT related anomalies by identifying mineralogy and lithological features at regional scale using image enhancement techniques on Landsat 8 satellite data. A combination of established Band ratios from literature were implemented on Landsat 8 optical bands using innovative digital image processing and knowledge-based spectral information extraction techniques which enhanced surface mineralogy and possible alteration areas of interest. The results indicate that ratios using bands; 7/4, 6/3, 5/7 and 6/7, 4/3, 5/6 and 7/5, 5/4, 6/7 respectively as RGB, were unique but corroborative in enhancing and identifying; clay rich rocks, iron oxides, micas, carbonates and possible hydrothermal alteration zones related to GT anomaly. The results could have implication for GT exploration in especially unexplored regions where expensive airborne surveys are unaffordable. [ABSTRACT FROM AUTHOR]

This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally (i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ∼18–36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18–36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three "fully"-simulated image cubes of thirty unique locations on Mars (i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (∼ 9.4 × 50 km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS. [ABSTRACT FROM AUTHOR]

In this work, radon concentrations in the polluted environment were measured within the Baghdad sample surface soil conservation, and this was done using a RAD-7 mobile detector. The work consists of four parts: The first part includes calculating the latitude and longitude of each point of the study area using the Global Positioning System (GPS). The second part of which includes Determination of 222Rn gas concentrations in surface soil samples. In the northeast part of Baghdad, the highest concentration of radon was found in Al- Shaab area (3.11 ±175.33 Bq / m3), while the lowest gas concentration in AL Gzeera area (6.67±73.00 Bq/ m3), In the northwest part of Baghdad, the highest concentration of radon was found in the al-Taji area (4.22 ± 179.33Bq / m3) and the lowest concentration of Radon gas in Al Ghazaliya area (3.11 ± 68.33 Bq/ m3). In the southeast part of Baghdad, the highest concentration of radon was found in ALWahda area (1.78 ±175. 33Bq / m3) while the lowest rate of radon gas is located in the Karada area (1.78 ± 41.67Bq / m3). The highest concentration of radon gas can be observed in the southwest part of Baghdad in Mahmudiya area (4.22 ± 185.67Bq/m3), while the lowest concentration of radon in Aamiriya (2.22 ± 78.67Bq/m3). The third part includes the applied the techniques of interpolation using the radon data available in the known sites to estimate the radon data for the non-measured area, which will help to develop an effective plan to reduce the concentration of radon in the study area. The fourth part includes the preparation of a soil surface classification map in all selected areas where the soil was classified into five species using the Erdas2014. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Kufa - Physics is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Coral reefs are complex, heterogeneous environments where it is common for the features of interest to be smaller than the spatial dimensions of imaging sensors. While the coverage of live coral at any point in time is a critical environmental management issue, image pixels may represent mixed proportions of coverage. In order to address this, we describe the development, application, and testing of a spectral index for mapping live coral cover using CASI-2 airborne hyperspectral high spatial resolution imagery of Heron Reef, Australia. Field surveys were conducted in areas of varying depth to quantify live coral cover. Image statistics were extracted from co-registered imagery in the form of reflectance, derivatives, and band ratios. Each of the spectral transforms was assessed for their correlation with live coral cover, determining that the second derivative around 564 nm was the most sensitive to live coral cover variations(r2 = 0.63). Extensive field survey was used to transform relative to absolute coral cover, which was then applied to produce a live coral cover map of Heron Reef. We present the live coral cover index as a simple and viable means to estimate the amount of live coral over potentially thousands of km2 and in clear-water reefs.

Modification of the original bands and integration of ancillary data in digital image classification has been shown to improve land use land cover classification accuracy. There are not many studies demonstrating such techniques in the context of the mountains of Nepal. The objective of this study was to explore and evaluate the use of modified band and ancillary data in Landsat and IRS image classification, and to produce a land use land cover map of the Galaudu watershed of Nepal. Classification of land uses were explored using supervised and unsupervised classification for 12 feature sets containing the LandsatMSS, TM and IRS original bands, ratios, normalized difference vegetation index, principal components and a digital elevation model. Overall, the supervised classification method produced higher accuracy than the unsupervised approach. The result from the combination of bands ration 4/3, 5/4 and 5/7 ranked the highest in terms of accuracy (82.86%), while the combination of bands 2, 3 and 4 ranked the lowest (45.29%). Inclusion of DEM as a component band shows promising results.

Sentinel-2A MSI is the Landsat-like spatial resolution (10-60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l'Observation de la Terre (SPOT) missions. Several simulation studies have been conducted in the last several years to show the potential of Sentinel-2A MSI (MultiSpectral Instrument). Now that real data are available, the first confirmations of this potential and comparisons with other operational systems are being made. This paper aims at evaluating Sentinel-2A MSI band ratio products that are relevant for geological remote sensing. A Sentinel-2A MSI and a Landsat 8 OLI (Operational Land Imager) scene were processed from their respective levels L1C and L1T to level L2A (bottom of atmosphere reflectance). Then, three band ratios originally defined for Landsat TM (Thematic Mapper) were used to map mineralogy associated with a hydrothermal alteration system in southeast Spain. The results obtained with Sentinel-2A MSI were compared with those obtained with Landsat 8 OLI and a simulated Sentinel-2A MSI dataset that was used before actual data were released. Results show that the images appear similar to the human eye having a correlation of approximately 0.8 and higher, but that the associated data ranges differ significantly. The resulting products are also compared to a published geologic map of the study area, and it is shown that the resulting maps correspond with the conceptual geologic model of the epithermal deposit. [ABSTRACT FROM AUTHOR]

The occurrence of spontaneous humeral fractures in primiparous dairy cows from New Zealand prompted the study of bone material from affected cows to further characterize this condition and to outline a likely pathogenesis. Previous studies indicate that these cows developed osteoporosis due to periods of suboptimal bone formation followed by increased bone resorption during the period of lactation complicated by copper deficiency. We hypothesized that there are significant differences in the chemical composition/bone quality in bones from cows with spontaneous humeral fracture compared to cows without humeral fractures. In this study, Raman and Fourier transform infrared spectroscopy band ratios were, for the first time, measured, calculated, and compared in bone samples from 67 primiparous dairy cows that suffered a spontaneous fracture of the humerus and 14 age-matched post-calving cows without humeral fractures. Affected bone showed a significantly reduced mineral/matrix ratio, increased bone remodeling, newer bone tissue with lower mineralization and, lower carbonate substitution, and reduced crystallinity. As such, is likely that these have detrimentally impacted bone quality and strength in affected cows., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wehrle-Martinez, Waterland, Naffa, Lawrence, Back, Rogers and Dittmer.)

This paper presents the methodology of an applied geophysical and remote sensing research at river deltas for their subsurface and surface structure and its application in the deltaic plain of Pineios River (Thessaly, Greece). The scope is to primarily calculate the thickness of deltaic post alpine deposits, with the contribution of Transient Electromagnetic Method (TEM), but also identify the surficial characteristics (biotic/ abiotic) of the area with the appropriate combination of spectral bands and spectral indices. Regarding the remote sensing approach, some geomorphological features were outlined. This was managed from six false color composites of the area, produced by combining spectral bands and additional five false color composites by combining several spectral indices. •The results of the TEM method along with their statistical analysis provided important information regarding the spatial distribution and thickness of the lithological units along the deltaic plain.•The combination of spectral bands 8, 7, 6 seems to adumbrate the hydrographic network of the area and even detects possible changes in the inflow.•The combination of spectral indices MSAVI2, WV-BI, WV-WI was helpful enough to geomorphological mapping of the deltaic plain., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Shoreline change dynamics along the coastal districts of South Gujarat is studied by the application of multi-temporal remote sensing datasets. The coastal zone along the three districts of Surat, Navsari and Valsad in South Gujarat, India are reported to be facing serious environmental challenges, especially due to anthropogenic impacts. This study evaluates the decadal changes in historical shoreline changes, using satellite images of Landsat TM, ETM and OLI. The analysis of shoreline changes in these districts revealed significant variations in the form of shoreline erosion. Further, the Land-use/ land–cover(LULC) maps for each district for the year 2014 is prepared using band ratios as a pre-classification step, followed by implementation of a combination of supervised and unsupervised classification called hybrid classification. An accuracy assessment is carried out for each of the datasets and the overall accuracy ranges between 90 - 95%. The LULC study is carried out in order to identify the various classes in this region which are vulnerable to the environmental degradation. The maps prepared in this research will contribute to both the development of sustainable land use planning as well as shoreline protection measures. [ABSTRACT FROM AUTHOR]

This paper aims at revealing the spectral characteristics of the olivine basalts exposed at Wadi Natash area, Egypt, using FieldSpec spectroradiometer. It also evaluates band ratios and fusion techniques for mapping purposes using ASTER data. Several volcanic episodes occurred during Early- to Late-Cretaceous are recorded in the study area. Early-Cretaceous olivine basalts are highly carbonated. Late-Cretaceous eruptions took place throughout several volcanic cones aligned in NW direction. Based on FieldSpec measurements and petrographic data, two groups of olivine basalt namely 'A' and 'B' are recognized. Fresh olivine basalt (group A) is characterized by low flat spectral profile with overall low reflectance values (∼20%). Spectral profile of altered olivine basalt (group B) shows moderate reflectance values (∼37%) with four little absorption features around the 1.10, 1.40, 2.00 and 2.35 μm wavelength regions. These absorption features are attributed mainly to the presence of chlorite and carbonate alteration products as indicated by petrographic examination. ASTER false colour composite band ratio image (3/2:R, 8/1:G and 8/5:B) discriminates easily the fresh and altered basalts by deep blue and reddish blue colours respectively. Image fusion between previously mentioned FCC ratios image and high spatial resolution ASTER panchromatic image are carried out using brovey and HSV transformation methods. Visual and statistical assessment methods proved that HSV fusion image yields better image interpretability results compared to brovey image. It improves the spatial resolution of original FCC ratios image with acceptable spectral preservation. The present study proved the usefulness of FieldSpec spectral profiles and the processed ASTER data for discriminating different olivine basalt groups exposed at the study area. [ABSTRACT FROM AUTHOR]

Copyright of Misr Journal of Agricultural Engineering is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sentinel-2A MSI is the Landsat-like spatial resolution (10–60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l’Observation de la Terre (SPOT) missions. Several simulation studies have been conducted in the last several years to show the potential of Sentinel-2A MSI (MultiSpectral Instrument). Now that real data are available, the first confirmations of this potential and comparisons with other operational systems are being made. This paper aims at evaluating Sentinel-2A MSI band ratio products that are relevant for geological remote sensing. A Sentinel-2A MSI and a Landsat 8 OLI (Operational Land Imager) scene were processed from their respective levels L1C and L1T to level L2A (bottom of atmosphere reflectance). Then, three band ratios originally defined for Landsat TM (Thematic Mapper) were used to map mineralogy associated with a hydrothermal alteration system in southeast Spain. The results obtained with Sentinel-2A MSI were compared with those obtained with Landsat 8 OLI and a simulated Sentinel-2A MSI dataset that was used before actual data were released. Results show that the images appear similar to the human eye having a correlation of approximately 0.8 and higher, but that the associated data ranges differ significantly. The resulting products are also compared to a published geologic map of the study area, and it is shown that the resulting maps correspond with the conceptual geologic model of the epithermal deposit.

Suspended sediment yield is a very important environmental indicator within Amazonian fluvial systems, especially for rivers dominated by inorganic particles, referred to as white water rivers. For vast portions of Amazonian rivers, suspended sediment concentration (SSC) is measured infrequently or not at all. However, remote sensing techniques have been used to estimate water quality parameters worldwide, from which data for suspended matter is the most successfully retrieved. This paper presents empirical models for SSC retrieval in Amazonian white water rivers using reflectance data derived from Landsat 5/TM. The models use multiple regression for both the entire dataset (global model, N = 504) and for five segmented datasets (regional models) defined by general geological features of drainage basins. The models use VNIR bands, band ratios, and the SWIR band 5 as input. For the global model, the adjusted R 2 is 0.76, while the adjusted R 2 values for regional models vary from 0.77 to 0.89, all significant ( p -value < 0.0001). The regional models are subject to the leave-one-out cross validation technique, which presents robust results. The findings show that both the average error of estimation and the standard deviation increase as the SSC range increases. Regional models were more accurate when compared with the global model, suggesting changes in optical proprieties of water sampled at different sampling stations. Results confirm the potential for the estimation of SSC from Landsat/TM historical series data for the 1980s and 1990s, for which the in situ database is scarce. Such estimates supplement the SSC temporal series, providing a more comprehensive SSC temporal series which may show environmental dynamics yet unknown. [ABSTRACT FROM AUTHOR]

Abstract: Sentinel-2 is ESA's medium spatial resolution (10–60m) super-spectral instrument aimed at ensuring data continuity for global land surface monitoring of Landsat and SPOT. Several simulation studies have been conducted that show the potential of Sentinel-2 for estimating biophysical and biochemical parameters such as leaf area index, chlorophyll and nitrogen, and spectral products such as the red edge position and NDVI time series, providing data continuity for a number of other operational sensors. This paper aims at simulating Sentinel-2 products that are relevant to the geology and soil science community and we compare these to well established band ratio products from ASTER. As the basis for the simulation we use airborne hyperspectral imagery from the HyMAP sensor which were spectrally and spatially resampled to the resolutions of ASTER and Sentinel-2 using actual spectral response functions and pixel aggregate, respectively. The simulated image products demonstrate a good correspondence between ASTER and Sentinel-2 VNIR and SWIR bands. A number of band ratios are proposed for Sentinel-2 to derive the following products: ferric iron, ferrous iron, laterite, gossan, ferrous silicate and ferric oxides. These are compared to established band ratios of real ASTER data as well as simulated (from HyMAP) ASTER data and they correlate favourably. Investigating the spatial patterns reveals that there is a good match between the proposed Sentinel-2 band ratio products and those of ASTER. The resulting band ratio products are compared to the local geologic map of the imaged hydrothermal area (the Rodalquilar mining area, Cabo de Gata volcanic field, SE Spain). It is shown that they support the existing conceptual geologic model of the epithermal deposit. [Copyright &y& Elsevier]

Lake Erie is biologically the most active lake among the Great Lakes of North America, experiencing seasonal harmful algal blooms (HABs). The early detection of HABs in the Western Basin of Lake Erie (WBLE) requires a more efficient and accurate monitoring tool. Remote sensing is an efficient tool with high spatial and temporal coverage that can allow accurate and timely detection of the HABs. The WBLE is heavily influenced by the surrounding terrestrial ecosystem via rivers such as the Sandusky River and the Maumee River. As a result, the optical properties of the WBLE are influenced by multiple color producing agents (CPAs) such as phytoplankton, colored dissolved organic matter (CDOM), organic detritus, and terrigenous inorganic particles. The diversity of the CPAs and their non-linear interactions makes these waters optically complex, and the task of optical remote sensing for retrieving estimates of CPAs more challenging. Chlorophyll a, which is the primary light harvesting pigment in all phytoplankton, is used as a proxy for algal biomass. In this study, several published remote sensing algorithms and band ratio models were applied to the reflectance data from the full resolution MERIS sensor to remotely estimate chlorophyll a concentrations in the WBLE. Efficiency of the sensor and the algorithms performance were tested through a least squares regression and residual analysis. The results indicate that, among the suite of existing bio-optical models, the Simis semi-analytical algorithm provided the best model results for measures of algal biomass in the optically complex WBLE with R of 0.65, RMSE 0.85 μg/l, ( n = 71, P < 0.05). The superior results of this model in detecting chlorophyll a are attributed to several factors including optimizing spectral regions that are less sensitive to CDOM and the incorporation of correction factors such as absorption effects due to pure water ( a), backscatter ( b) from suspended matter and interference due to phycocyanin ( δ), a major accessory pigment in the WBLE. [ABSTRACT FROM AUTHOR]

Coral reefs are complex, heterogeneous environments where it is common for the features of interest to be smaller than the spatial dimensions of imaging sensors. While the coverage of live coral at any point in time is a critical environmental management issue, image pixels may represent mixed proportions of coverage. In order to address this, we describe the development, application, and testing of a spectral index for mapping live coral cover using CASI-2 airborne hyperspectral high spatial resolution imagery of Heron Reef, Australia. Field surveys were conducted in areas of varying depth to quantify live coral cover. Image statistics were extracted from co-registered imagery in the form of reflectance, derivatives, and band ratios. Each of the spectral transforms was assessed for their correlation with live coral cover, determining that the second derivative around 564 nm was the most sensitive to live coral cover variations(r2 = 0.63). Extensive field survey was used to transform relative to absolute coral cover, which was then applied to produce a live coral cover map of Heron Reef. We present the live coral cover index as a simple and viable means to estimate the amount of live coral over potentially thousands of km2 and in clear-water reefs. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to reveal the spectral characteristics of the mineralized tonalite–diorite intrusions exposed at Bulghah gold mine area, Saudi Arabia, using FieldSpec spectroradiometer and Landsat ETM+ data. Gold mineralization at Bulghah gold mine is hosted mainly by Syn- to Late-orogenic tonalite–diorite intrusions aligned in N–S direction and is associated mainly with cataclastic zones and quartz veins. Based on field, petrography and FieldSpec data two main tonalite–diorite groups namely A and B are recognized. Group “A”, recorded at the mine area, is characterized by low flat spectral profiles with overall low reflectance values (~10%). These low values are attributed to the presence of high content of trans-opaque phases (hematite and goethite) as indicated by petrographic study. Spectral profiles of group “B”, recorded at Bulghah North area, show high reflectance values (~40%) with three main absorption features around the 1.45μm, 2.20μm and 2.35μm wavelength regions. These absorption features are attributed mainly to the presence of clay minerals, sericite, chlorite and carbonate alteration products. To discriminate the above mentioned tonalite–diorite groups, band ratios and Minimum Noise Fraction (MNF) techniques are conducted. Landsat false color composite band ratio image (7/4:R, 4/1:G and 4/5:B) discriminates easily the bluish brick red tonalite–diorite intrusions from the surrounding rock units but failed to distinguish the above mentioned two tonalite–diorite groups. On MNF3 image, the two tonalite–diorite groups can be distinguished easily in which group “A” has white color whereas group “B” has gray color. The present study proved the usefulness of FieldSpec spectral profiles and the processed Landsat ETM+ data for discriminating and delineating the mineralized tonalite–diorite intrusions exposed at the study area. [Copyright &y& Elsevier]

This study develops a novel support vector regression (SVR) model for retrieving the specific cyanobacterial pigment C-phycocyanin (C-PC) concentrations in cyanobacteria-dominated large turbid lakes of China. Lake Taihu, Lake Chaohu, and Lake Dianchi in China were our study areas. Five field cruises were carried out to collect data sets of optical and water quality parameters. To retrieve the C-PC, three types of reflectance forms, including single band, band ratio, and three-band-combination, were compared. The band ratio was the best candidate to serve for algorithm development. On this basis, two types of models, including linear models and a SVR model, were originally established. The previous typical algorithms were also examined. The obtained results showed that the best-performing model was the SVR model. By our validation data set, the proposed SVR model also presented accurate prediction results, with the lowest errors among all methods. The novelty of the SVR model compared to the previous ones lies in the inclusion of band ratios that are located outside of the main pigment absorption peaks but hold information on inflection points, curvature, etc., into empirical optimization. The implications of these findings indicates the potential applicability of the SVR models in lakes of the similar type. [ABSTRACT FROM AUTHOR]

Modification of the original bands and integration of ancillary data in digital image classification has been shown to improve land use land cover classification accuracy. There are not many studies demonstrating such techniques in the context of the mountains of Nepal. The objective of this study was to explore and evaluate the use of modified band and ancillary data in Landsat and IRS image classification, and to produce a land use land cover map of the Galaudu watershed of Nepal. Classification of land uses were explored using supervised and unsupervised classification for 12 feature sets containing the Landsat MSS, TM and IRS original bands, ratios, normalized difference vegetation index, principal components and a digital elevation model. Overall, the supervised classification method produced higher accuracy than the unsupervised approach. The result from the combination of bands ration 4/3, 5/4 and 5/7 ranked the highest in terms of accuracy (82.86%), while the combination of bands 2, 3 and 4 ranked the lowest (45.29%). Inclusion of DEM as a component band shows promising results. [ABSTRACT FROM AUTHOR]

Abstract: Measuring the wavelength position of the absorption feature of white micas in the 2200nm region is a useful tool in mapping the affects of hydrothermal alteration. However, this subtle wavelength shift is difficult to measure accurately using unmixing and matching algorithms that rely on spectral end members, because the wavelength position is uncorrelated to the general shape of the reflectance spectra of white micas. An alternative method is presented that uses pixel-dependent information only and that is based on extracting diagnostic spectral information of the mineral of interest through band ratios. Multiple regression analysis is then used to determine the relation between band ratios calculated from airborne imaging spectroscopy and the absorption wavelength of white micas measured in rock samples on the ground. The complicating effects of vegetation mixing with mineral signatures at the pixel level are addressed through a combination of band ratios that target the respective diagnostic absorptions. With this method the presence of white micas at the earth surface is estimated from two band ratios, and , where band ratio is proportional to the abundance of cellulose in spinifex vegetation. The absorption wavelength of white micas is then estimated from the two band ratios and . The results of both band-ratio regression analyses can then be combined to show predicted wavelengths of white mica in the areas of highest probability of containing white mica. [Copyright &y& Elsevier]