Band Ratio Images Research Articles

Spectral Characteristics of Hydrothermal Alteration in Zuru, NW Nigeria

This study demonstrated the ability of a Landsat-8 OLI multispectral data to identify and delineate hydrothermal alteration zones around auriferous prospects within the crystalline basement, North-western Nigeria. Remote sensing techniques have been widely used in lithological, structural discrimination and alteration rock delineation, and in general geological studies. Several artisanal mining activities for gold deposit occur in the surrounding areas within the basement complex and the search for new possible mineralized zones have heightened in recent times. Systematic Landsat-8 OLI data processing methods such as colour composite, band ratio and minimum noise fraction were used in this study. Colour composite of band 4, 3 and 2 was displayed in Red-Green- Blue colour image to distinguish lithologies. Band ratio image displayed in red was used to highlight ferric-ion bearing minerals (hematite, goethite, jarosite) associated with hydrothermal alteration, band ratio image displayed in green was used to highlight ferrous-ion bearing minerals such as olivine, amphibole and pyroxenes, while ratio image displayed in blue was used to highlight clay minerals, micas, talc-carbonates, etc. Band rationing helped to reduce the topographic illumination effect within images. The result of this study showed the distribution of the lithological units and the hydrothermal alteration zone which can be further prospected for mineral reserves.

Detection of hydrocarbon microseepage-induced anomalies by spectral enhancements of Landsat 7 ETM+ images in part of Assam\u2013Arakan Fold Belt, India

Subsurface hydrocarbon traps are not correctly sealed, and hydrocarbons move vertically from the reservoir as invisible traces in the form of microseepages. Long-term hydrocarbon microseepages cause surface or near-surface alterations such as bleaching of red beds, enrichment of ferrous iron minerals and higher concentrations of clay and carbonate minerals in soils/rocks. Multi- and hyperspectral remote sensing data have successfully been used to detect such alterations in many parts of the world. In India, such studies have not been carried out till now. In this study, Landsat 7 ETM+ images have been used to find out hydrocarbon microseepage-bearing areas in part of Assam–Arakan Fold Belt in the northeastern part of India. Based on the spectral characteristics of the hydrocarbon microseepage-induced altered minerals, two spectral enhancement techniques, viz. principal component analysis (PCA) and band ratio analysis, have been carried out on the Landsat 7 ETM+ images. PCA reveals that three principal component images—1457PC3, 1345PC2 and 3457PC4—show relatively better enhancement for the hydrocarbon-bearing alteration areas. Again, band ratio analysis of the images indicates that ratio images—3/1, (2 + 5)/(3 + 4) and 7/5—show excellent spectral enhancement for the hydrocarbon-induced mineral alterations. The three PC images have been combined with the three band ratio images to find out probable hydrocarbon microseepage areas. The remote sensing-derived prospect areas have been validated with surface geochemical, seismic/geologic and gravity data available in the area.

Satellite image analysis of changes in glacier cover in Canada's northern Mackenzie Mountain Range (1987–2017)

The state of a group of glaciers in the northern Mackenzie Mountains across the Yukon‐Northwest Territories border was investigated over a period of three decades, using Landsat TM and OLI imagery from 1987, 1994, 1999, 2004, 2013, and 2017 to examine changes in glacier extents. A thresholded red/shortwave infrared band ratio image was used to delineate glacier boundaries. The total area of 74 glaciers in the study area decreased from 52.78 ± 1.32 km2 in 1987 to 24.89 ± 0.62 km2 in 2017, a loss of 27.89 ± 1.39 km2 or 52.8 ± 2.6%, with a mean rate of reduction of 1.8% · a−1. Smaller glaciers experienced larger relative changes in area. In this study, the rates of reduction are high compared to decreases reported for other glaciers in the region in the late 20th century. Based on linear extrapolation of the trend in values of total glacier area, it is predicted—subject to uncertainties in how glaciers diminish in size and eventually disappear—that the study area could be free of visible glacier cover within three decades.

Remote sensing-based geological mapping and petrogenesis of Wadi Khuda Precambrian rocks, South Eastern Desert of Egypt with emphasis on leucogranite

The exposed Precambrian rocks along Wadi Khuda area, South Eastern Desert of Egypt, comprise gneisses, amphibolites and migmatites associations (infrastructural rocks) which are intruded by diorite, tonalite, syenogranite and leucogranite (LG). LG forms homogeneous boss like bodies, devoid to xenoliths, except along the outer margins. Chemically and mineralogically they are dissimilar to the surrounding gneisses. In the current study, band ratio and Decorrelation Stretch image processing algorithms were proposed and applied on Landsat-8, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Sentinel-2 remote sensing data to discriminate the widely exposed lithological units in the mapped area. Geochemically, I-type classification and volcanic arc environment were revealed. LG is peraluminous (ASI average of 1.09) with normative corundum up to 1.38 for LG. The LG displays limited major and trace element variations (SiO2 = 74.5–76.2%, AI203 = 13.4–14.4%), MgO = 0.03–0.19%, Na2O = 3.6–4.6%), and Rb = 55–85 ppm) probably due to textural and mineralogical homogeneity. The contents of REE in the leucogranite are low (∑REE = 21–37), but the REE patterns are [(La/Yb)n = 2.45–9.03], [(La/Sm)n = 1.09–2.6], with negative Eu anomaly, (Eu/Eu* = 0.19–0.78). The negative Eu anomaly and the low Sr content (16–92 ppm) may be attributed to the plagioclase feldspars fractionation. The leucogranites represent residual melt of syenogranite which forms Um Itly pluton at the southern flank of Wadi Khuda entrance.

A Satellite-based Remote Sensing Technique for Surface Water Quality Estimation

Remote sensing provides a synoptic view of the earth surface that can provide spatial and temporal trends necessary for comprehensive water quality (WQ) monitoring and assessment. This study explores the applicability of Landsat 8 and regression analysis in developing models for estimating WQ parameters such as pH, dissolved oxygen (DO), total dissolved solids (TDS), total suspended solids (TSS), biological oxygen demand (BOD), turbidity, and conductivity. The input image was radiometrically-calibrated using fast line-of-sight atmospheric analysis (FLAASH) and then atmospherically corrected to obtain surface reflectance (SR) bands using FLAASH and dark object subtraction (DOS) for comparison. SR bands derived using FLAASH and DOS, water indices, band ratio, and principal component analysis (PCA) images were utilized as input data. Feature vectors were then collected from the input bands and subsequently regressed together with the WQ data. Forward regression results yielded significant high R2 values for all WQ parameters except TSS and conductivity which had only 60.1% and 67.7% respectively. Results also showed that the regression models of pH, BOD, TSS, TDS, DO, and conductivity are highly significant to SR bands derived using DOS. Furthermore, the results of this study showed the promising potential of using RS-based WQ models in performing periodic WQ monitoring and assessment.

The magnetic response of hydrothermal alteration in iron-oxide basement complex, NW Nigeria

Aeromagnetic data was processed in order to delineate structural trends which may be indicative of potential gold mineral traps in the Watari hill gold prospect located between longitude 5°8''and 5°16'', and latitude 11°24'' and 11°30'' in Garin Hawal district, northwest Nigeria. Landsat-8 OLI data was processed to produce colour composite, band ratio and minimum noise fraction images that mapped the hydrothermal alteration zone in the study area. The multispectral images which were displayed in Red-Green-Blue colours were subsequently pan-sharpened to display a greater image resolution of the area. The application of enhancement algorithms such as an analytic signal to the aeromagnetic data over the alteration zone helped in mapping the mafic metavolcanics, felsic metasediments and intruding granitoid complexes. Further reductions using the second vertical derivative and tilt angle derivative filters aided in delineating fracture/faults and the contact zones of the formations, especially the metasediments-metavolcanic boundary that delineates the shear zone. This study showed that the low-angle geologic structure between the metasediments and metavolcanics where hydrothermal alteration is present is likely to accommodate veins of gold mineralization in the study area.

Potential Utility of Spectral Angle Mapper and Spectral Information Divergence Methods for mapping lower Vindhyan Rocks and Their Accuracy Assessment with Respect to Conventional Lithological Map in Jharkhand, India

In this study, we have evaluated the potential use of spectral mapping algorithms in deriving spectrolithological maps of metasedimentary rocks of Vindhyan group of rocks. In this regard, we have processed visible near infrared (VNIR) and shortwave infrared (SWIR) bands of Advanced Speceborne Thermal Emission and Reflection Radiometer (ASTER) data using similarity based spectral mapping algorithms such as spectral angle mapper (SAM) and spectral information divergence (SID). Laboratory spectra were collected by Fieldspec 3© spectroradiometer for main rock types of study area and the spectra were resampled to ASTER bandwidth to compare laboratory spectra with image spectra of respective rocks. Overall matching of image spectra of rocks with their ASTER resampled laboratory counterparts justified the spectral integrity of these rocks on the image. Therefore, image spectra of rocks were used as end member for deriving spectral maps using SAM and SID method. These maps were compared with the conventional field based lithological map (consequently updated using ASTER false colour image composite and band ratio images). SAM spectral map had over all accuracy of 67.41% and the SID map had overall accuracy of 69.67%. Present study has brought out the fact that spectral mapping algorithms would be useful in deriving moderate accuracy lithological maps even if the sedimentary rocks are of close mineralogy and these rocks have very close reflectance spectra within the spectral bandwidth of ASTER sensor. Spectral maps corroborate well with the discrete geochemical data.

Lithological discrimination of accretionary complex (Sivas, northern Turkey) using novel hybrid color composites and field data

One of the most appropriate approaches to better understand and interpret geologic evolution of an accretionary complex is to make a detailed geologic map. The fact that ophiolite sequences consist of various rock types may require a unique image processing method to map each ophiolite body. The accretionary complex in the study area is composed mainly of ophiolitic and metamorphic rocks along with epi-ophiolitic sedimentary rocks. This paper attempts to map the Late Cretaceous accretionary complex in detail in northern Sivas (within İzmir-Ankara-Erzincan Suture Zone in Turkey) by the analysis of all of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands and field study. The new two hybrid color composite images yield satisfactory results in delineating peridotite, gabbro, basalt, and epi-ophiolitic sedimentary rocks of the accretionary complex in the study area. While the first hybrid color composite image consists of one principle component (PC) and two band ratios (PC1, 3/4, 4/6 in the RGB), the PC5, the original ASTER band 4 and the 3/4 band ratio images were assigned to the RGB colors to generate the second hybrid color composite image. In addition to that, the spectral indices derived from the ASTER thermal infrared (TIR) bands discriminate clearly ultramafic, siliceous, and carbonate rocks from adjacent lithologies at a regional scale. Peridotites with varying degrees of serpentinization illustrated as a single color were best identified in the spectral indices map. Furthermore, the boundaries of ophiolitic rocks based on fieldwork were outlined in detail in some parts of the study area by superimposing the resultant maps of ASTER maps on Google Earth images of finer spatial resolution. Eventually, the encouraging geologic map generated by the image analysis of ASTER data strongly correlates with lithological boundaries from a field survey.

Detection of blueberry internal bruising over time using NIR hyperspectral reflectance imaging with optimum wavelengths

Early detection of internal bruising is one of the major challenges in blueberry postharvest quality sorting processes. The potential of using near infrared (NIR) hyperspectral reflectance imaging (950–1650nm) with reduced spectral features was investigated for blueberry internal bruising detection 30min to 12h after mechanical impact. A least squares support vector machine (LS-SVM) was used to develop classification models to compute the spatial distribution of bruising based on the spectra extracted from regions of interest (ROIs) at four measurement times (30min, 2h, 6h, and 12h after mechanical impact). Three feature selection methods were used to select optimum wavelengths or band ratio images for bruising detection. The classification model, developed using optimum wavelengths selected by competitive adaptive reweighted sampling (CARS) (CARS-LS-SVM model) and full spectra (full spectra-LS-SVM), had similar performance in the identification of bruised blueberries. Band ratio images (1235nm/1035nm) achieved a comparable accuracy with the CARS-LS-SVM model at 6h, and higher accuracy than CARS-LS-SVM and full spectra-LS-SVM models at 12h. The overall classification accuracies of 77.5%, 83.8%, 92.5%, and 95.0% were obtained by band ratio images for blueberries 30min, 2h, 6h, and 12h after impact, respectively. In order to evaluate the performance of the proposed methods, additional validation samples were processed by the detection algorithm. The overall discrimination accuracies for healthy and bruised blueberries in the validation set were 93.3% and 98.0%, respectively, for CARS-LS-SVM model, and 93.3% and 95.9%, respectively, for band ratio images. The overall results indicated that NIR reflectance imaging can detect blueberry internal bruising as early as 30min after mechanical impact, and band ratio images computed from two wavelengths showed great potential to detect blueberry internal bruising on the packing line.

Detecting decayed peach using a rotating hyperspectral imaging testbed

A hyperspectral imaging system with a moving testbed has been developed for detection of the disease caused by Rhizopus stolonifera in peaches. The all-around hyperspectral imaging of the whole peach was obtained, which can identify the decayed area fully and is suitable for online monitoring. Three single-band images (709, 807, and 874 nm) which were selected by statistical methods and an image segmentation algorithm were applied to locate the decayed area of peaches was developed based on band ratio image coupled with a simple thresholding method. The performance of image segmentation algorithm of the single-band images was evaluated. The detection accuracy of peaches classified as ‘sound’, ‘slight-decayed’, ‘moderate-decayed’ and ‘severe-decayed’ were 95%, 66.29%, 100% and 100%, respectively. The spectral information was extracted from the decayed area to improve the detection accuracy. The six optical wavelengths were selected by SPA (successive projections algorithm) from the full spectral range. The classification accuracy of sound and rotten peaches was 100% if only these two categories were applied. Our results demonstrated that the hyperspectral imaging method offers the potential to be used to automatically detect fungal infection in peaches.

Using hyperspectral imaging to discriminate yellow leaf curl disease in tomato leaves

This paper investigated the possibility of discriminating tomato yellow leaf curl disease by a hyperspectral imaging technique. A hyperspecral imaging system collected hyperspectral images of both healthy and infected tomato leaves. The reflectance spectra, first derivative reflectance spectra and absolute reflectance difference spectra in the wavelength range of 500–1000 nm of both background and the leaf area were analyzed to select sensitive wavelengths and band ratios. 853 nm was selected to create a mask image for background segmentation, while 720 nm from the reflectance spectra, four peaks (560, 575, 712, and 729 nm) from the first derivative spectra and, four wavelengths with higher values (586, 720 nm) and lower values (690, 840 nm) in the absolute difference spectra were selected as a set of sensitive wavelengths. Four band ratio images (560/575, 712/729, 586/690, and 720/840 nm) were compared with four widely used vegetation indices (VIs). 24 texture features were extracted using grey level co-occurrence matrix (GLCM), respectively. The performance of each feature was evaluated by receiver operator characteristic (ROC) curve analysis. The best threshold values of each feature were calculated by Yonden’s index. Mean value of correlation (COR_MEAN) extracted from the band ratio image (720/840 nm) had the best performance, whose AUC value was 1.0. The discrimination result for a validation set based on its best threshold value was 100%. This research also demonstrated that multispectral images at 560, 575 and 720 nm have a potential for detecting tomato yellow leaf curl virus infection in field applications.

Study on Identification of Immature Corn Seed Using Hyperspectral Imaging

The seed maturity, which is one of the important factors that affect seed vigor, is an important quality index. During seed sorting, separating mature seeds from immature seeds can improve the vigor of seed lot and keep vigor consistency. Hyperspectral imaging that covered the range of 400~1 000 nm was used to find out the sensitive bands reflecting corn seed maturity, and corresponding images were employed to classify the immature corn seeds. Principal component analysis (PCA) algorithm was adopted to analyze the hyperspectral image. PC2 of PCA had the greatest difference between immature and mature areas on the seeds, therefore, the weighted coefficients of PC2 was selected to extract sensitive wavebands (501 nm). Regions of interest (ROI) from mature and immature area of 70 immature kernels was selected for mean spectra calculation. Partial least square regression (PLSR) algorithm was employed to analyze the spectra of ROI and extract wavelength related to maturity (518 nm). Band ratio algorithm and Kruskal-Wallis test were used to select the best band ratio that had the biggest difference between mature and immature areas (640 nm/525 nm). 864 kernels of corn seed were analyzed by gray images of the selected wavelengths as well as band ratio images. Results showed that the light color regions of the seed crown were misidentified as immature region when the images of selected single band wavelengths were used, while the band ratio image of 640 nm/525 nm could be identified correctly. The immature seeds can be separated from the mature seeds according to the area ratio of segmented immature region to the whole kernel. The correct recognition rate was 93.9%. Using the grey images of selected band ratio can differentiate immature corn seeds from mature seeds effectively, which provide a theoretical reference for the development of seed sorting device in further work.

Regional Glacier Mapping Using Optical Satellite Data Time Series

The first of two Sentinel-2 satellites, launched mid-2015, has similar characteristics as the Landsat ${\rm TM}/{\rm ETM} + /{\rm OLI}$ satellites. Together, these satellites will produce a tremendous quantity of optical images worldwide for glacier mapping, with increasing temporal coverage toward the more glacierized higher latitudes due to convergence of near-polar orbits. To exploit the potential of such near-future dense time series, methods for mapping glaciers from space should be revisited. Currently, snow and ice are typically classified from an optical satellite image using a multispectral band ratio. For each scene, mapping conditions will vary (e.g., snow, ice, and clouds) and not be equally optimal over the entire scene. The increasing amount of images makes it difficult to manually select the best glacier mapping scene as is the current practice. This work is based on the above robust image ratio method for exploiting the dense temporal image coverage. Four application scenarios using time series of Landsat type data for glacier mapping are presented. First, we synthesize an optimal band ratio image from a stack of images within one season to compensate for regional differences. The second application scenario introduces robust methods to improve automatic glacier mapping by exploiting the seasonal variation in spectral properties of snow. Third, we explore the spatio-temporal variation of glacier surface types. Finally, we show how the synthesized band ratio images from the first application scenario can be used for automatic glacier change detection. In summary, we explore automatic algorithms for glacier mapping applications that exploit the temporal signatures in the satellite data time series.

Quantitative analysis of melamine in milk powders using near-infrared hyperspectral imaging and band ratio

Since 2008, the detection of the adulterant melamine (2,4,6-triamino-1,3,5-triazine) in food products has become the subject of research due to several food safety scares. Near-infrared (NIR) hyperspectral imaging offers great potential for food safety and quality research because it combines the features of vibrational spectroscopy and digital imaging. In this study, NIR hyperspectral imaging was investigated for quantitative evaluation of melamine particles in nonfat and whole milk powders. Melamine was mixed into milk powders in a concentration range of 0.02–1.00% (w/w). A NIR hyperspectral imaging system was used to acquire images (938–1654 nm) of melamine powder, whole milk powder, nonfat milk powder, and mixtures of melamine and each of the milk powders. Two optimal bands (1447 nm and 1466 nm) were selected by a linear correlation algorithm with pure milk and pure melamine. Band ratio (B1447/1466) images coupled with a single threshold were used to create resultant images to visualize identification and distribution of the melamine adulterant particles in milk powders. The identification results were verified by spectral feature comparison between separated mean spectra of melamine pixels and milk pixels. Linear correlations (r) were found between the number of pixels identified as containing melamine and melamine concentration in nonfat milk and whole milk powders, which were 0.980 and 0.970 or higher, respectively. The study demonstrated that the combination of NIR hyperspectral imaging and simple band ratioing was promising for rapid quantitative analysis of melamine in milk powders.

Delineation of Debris-Covered Glaciers Based on a Combination of Geomorphometric Parameters and a TIR/NIR/SWIR Band Ratio

Accurate mapping of glaciers is important for the management of water resources, studying glacier mass-balance, and monitoring glacier health. However, many glaciers are partially covered by debris of varying thicknesses, and these debris-covered glacier areas are difficult to distinguish clearly from the adjacent valley rock using optical remote sensing data due to their similar reflectance in the visible-to-near-infrared (VNIR) wavelength region. For better detection of the debris-covered glacier margin, a new method was proposed here which considers glacier terrain features (concave and convex landscapes) as well as VNIR reflectance, shortwave-infrared reflectance (SWIR), and thermal infrared (TIR) information. The proposed method uses several geomorphometric parameters (slope, plan, and profile curvature) and a Landsat Thematic Mapper (TM) band ratio image TM TIR/(TM NIR/TM SWIR) for mapping the Yengisogat glacier in the Shaksgam valley of China. The final debris-covered glacier boundary is generated by thresholding the band ratio image and overlaying it onto the result derived from cluster analysis performed using plan, profile curvature, and combined with mean of slope information. Evaluation of the final debris-covered glacier outline was carried out through comparison with GIS data from several reference data sets, and the final Yengisogat glacier outline had a difference of less than 1% in area compared to the reference data sets.

Spectroscopy of olivine basalts using FieldSpec and ASTER data: A case study from Wadi Natash volcanic field, south Eastern Desert, Egypt

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.

Integrated Remote Sensing and Structural Analysis Studies of Tayyib Al-Ism Area, Northwestern Arabian Shield, Saudi Arabia

Geological and structural mappings of Tayyib Al-Ism area were carried out using the rocks finite strain data, the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data and the field based observations. To analyze the finite strain in the studied rocks, the Rf /ϕ and Fry methods are applied to feldspar porphyroclasts and mafic grains from nine metavolcano-sedimentary samples (Hegaf Formation), four diorite-gabbros suite samples (Sawawin Complex), two meta-granite samples (Ifal suite) and five Zuhd alkali granite samples. The obtained data indicate traces of high to moderate level of deformation in the meta-granite and metavolcano-sedimentary rocks. The axial ratios along the XZ section range from 1.70 to 4.80 for the Rf/ϕ method and from 1.50 to 4.50 for the Fry method. A sub-vertical trend of short axes in association with sub-horizontal foliation is also observed. These informations allow us to conclude that a finite strain in the deformed granitic rocks is of the same order of magnitude as in the metavolcano-sedimentary rocks. The contacts between the metavolcano-sedimentary and granitic rocks in Tayyib al Ism area were formed during the granitic intrusions along some of the faults under brittle to semi-ductile deformation conditions. These faults have significantly influenced the geometry and style of rifting in the Red Sea during the Neogene. The finite strain was accumulated in the area during the process of deformation, which superimpose the already existed nappe structure. It indicates that the nappe contacts formed during the accumulation of finite strain. In addition to finite strain analysis, band ratio images (3/1, 5/3, 7/5) and Principal Component Analysis (PCA) technique have been used, which proved effective in mapping geological and structural features of various rock bodies exposed in the study area.

Reconstructions of local resource procurement networks at Cerro Baúl, Peru using multispectral ASTER satellite imagery and geospatial modeling

Multispectral remote sensing is increasingly common in archaeology, but is largely oriented towards site-detection applications. A high-resolution approach using ASTER data to map environmental and geological resources in the vicinity of Cerro Baúl is outlined here. Spectral mapping evaluates several band ratio and relative band depth image transforms that target diagnostic reflectance/absorption features of earth materials. Available geological resources had a high degree of spatial heterogeneity, which conditioned household strategies for obtaining raw materials. However, some variability cannot be explained by the geological environment alone. Using Minimum Convex Polygons and Kernel Density home-territory estimates, I outline the spatial organization of resource networks that differed from household to household. Differences in household resource networks suggest that socio-economic factors conditioned the use of materials, including locally-available ones. These results demonstrate the utility of multispectral remote sensing to construct palaeoecological models on a scale congruent with archaeological questions.

A new band ratio technique for mapping debris-covered glaciers using Landsat imagery and a digital elevation model

Mapping of debris-covered glaciers using optical remote-sensing data is a difficult task due to the fact that the debris cover on the glacier surface has a similar reflectance to surrounding rocky or sandy areas in the visible to near-infrared wavelength region. Therefore, a new method was developed for mapping debris-covered glaciers that considers thermal and slope information in addition to visible and near-infrared information. The method was tested for delineating the Koxkar glacier and Yengisogat glacier using Landsat Enhanced Thematic Mapper Plus and Landsat Thematic Mapper imagery and Shuttle Radar Topography Mapping Mission (SRTM) data. Specifically, the method combines a new band ratio image with slope information derived from the SRTM digital elevation model to better distinguish periglacial debris and supraglacial debris. The new band ratio image considers the near infrared (NIR), shortwave infrared (SWIR), and thermal infrared (TIR) bands, and is given by TIR/(NIR/SWIR). The debris-covered glacier boundaries are generated by thresholding the new band ratio image and overlaying it onto a binary slope map. Accuracy assessment was carried out through comparisons of the classified maps with reference maps from the Randolph Glacier Inventory, Glacier Inventory GIS data of China, and a manual delineation done using Google Earth™ images. The accuracy assessment shows that the result from the proposed method has a good agreement with the different reference data sets.

Mapping of the late Neoproterozoic Basement rocks and detection of the gold-bearing alteration zones at Abu Marawat-Semna area, Eastern Desert, Egypt using remote sensing data

Intensive investigation of the basement rock units of Abu Marawat-Semna area in the northern part of Central Eastern Desert of Egypt and their gold-bearing alteration zones using remote sensing techniques is accomplished. The study area consists of a Pan-African tectono-stratigraphic sequence, where allochthonous sheets and slices of ophiolitic serpentinite-talc-carbonate components were thrusted onto an island-arc metavolcanics. These rocks were later intruded by gabbro-diorite and biotite granite and invaded by a network of quartz veins, which are locally charged with gold. The visible near-infrared (VNIR) and short-wave infrared (SWIR) reflectance data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery and Landsat 8 data were employed in the detailed geological mapping and detection of mineralized alteration zones. The results show that Landsat 8 band ratio image (b6/b2, b6/b7, and b6/b5 × b4/b5) distinguishes the lithological units. Two different types of alteration zones (1 and 2) have been recognized in the study area using ASTER spectral characteristic analysis (SCA), band ratios, principle component analysis (PCA), Minimum Noise Fraction (MNF) techniques and ascertained by field verification, XRD, and XRF investigations. Type 1 (carbonate are the main phases) is mainly confined to the ophiolitic serpentinite-talc-carbonate rocks, whereas type 2 (quartz, sericite, and kaolinite-rich alteration zone are the main phases) is located within island-arc metavolcanics. The geochemical studies recorded anomalous contents of Cr and Ni in the alteration zone type 1 while Cr reaches 1,549 ppm and Ni abundance attains about 1,052 ppm. The investigated alteration zone type 2 in the metavolcanics recorded the presence of high anomalous contents of gold (up to 36 ppm), silver (up to 200 ppm), zinc (up to 3,992 ppm), and copper (up to 83,720 ppm). The geochemical study indicates that the detected alteration zones in the metavolcanics and the ophiolitic ultramafic rocks are promising and need more detailed exploration for Au and Ag mineralization. The study proves the potentiality of the alteration zones in and around the ophiolitic serpentinite-talc-carbonate rocks and their intimately associated island-arc metavolcanics. The image processing of the remote sensing data as proposed in the present study proves its high capability in detecting the mineralized alteration zones in other tectonically and geologically similar arid regions in the Arabian-Nubian Shield (ANS) and worldwide.