Integration of Geological, Geochemical, Mineralogical and Remote Sensing Data for Studying Zeolite Deposits of Al-Ahyuq-Taiz, Yemen

Zeolite deposits crop out at Al-Ahyuq area, and lies at about 89 km southwest of Taiz city. It is one of the most important zeolite localities in Yemen. The study area is covered by the Yemen volcanic group. X-Ray Diffraction (XRD) analyses showed that clinoptilolite is the major type of Al-Ahyuq zeolites with high purity. Chemical analysis shows that the studied zeolitic tuff samples have silica content ranging from 63.10 wt% - 71.1wt% with an average 68.69 wt%, Fe2O3 [as total iron] with an average 2.38wt%, MgO with an average 0.44 wt% and TiO2 with an average 0.17wt%. These chemical properties of Al-Ahyuq zeolite deposits are with low impurities content such as CaO and MgO, compared to those deposits found in other countries around the world. The chemical and mineralogical studies support that the zeolite minerals of the Al-Ahyuq area formed by subaerial hydrothermal alteration of the parent volcanic glass. The ASTER bands as false colour composite (1-R, 2-G, 3-B), and band ratios 3/9 and 4/6 highlighted area of zeolite deposits dominated as bright pixels. The band ratio combination 4/6-R, 2/1-G and 3/2-B is effective in mapping of Al-Ahyuq zeolitic tuffs. Spectra after being resampled to ASTER VNIR+SWIR bands of the study area comparing with the USGS library spectra of zeolite – clinoptilolite shows almost identical and confirmed that clinoptilolite is the major of zeolite deposits in Al-Ahyuq area. Chemical and mineralogical investigation of the Al-Ahyuq zeolite (clinoptilolite) deposits recommends many important agricultural, environmental, and industrial applications. Keyword: Zeolitic tuff; clinoptilolite; XDR; XRFS; ASTER data; band ratio

How to Recognize Different Types of Trees from Quite a Long Way Away: Combining UAV and Spaceborne Imagery for Stand-Level Tree Species Identification

In order to understand how a forest may respond to environmental changes or develop over time, it is necessary to examine broad, landscape level factors. With the arrival of unmanned aerial vehicles (UAVs), the combination of both spaceborne data with high resolution UAV data can provide foresters and biologists with powerful tools to classify canopies to the species level, which we illustrate here. We combine imagery from the Operational Land Imager (OLI) of the Landsat 8 satellite with aerial imagery from a Phantom 4 UAV to map canopy composition of three tree species. We manually delineated dense stands of each tree species in the UAV imagery to extract training samples from an OLI true colour composite image to perform a fuzzy membership analysis and calculate the maximum likelihood that an individual pixel represented a particular species. We verified the accuracy of our analysis finding an overall accuracy of 0.796 and a kappa statistic of 0.728. We consider these results to be a strong demonstration of the value of using UAV and satellite imagery in tandem to investigate forest-wide effects at an individual tree level.

Color models used for the visual interpretation of satellite data

This study presents the possibilities for using different colour models for visual interpretation of satellite imagery. Using the RGB model to visualise different spectral bands as a false colour composite image make it possible for different types of objects and features on the Earth surface to be highlighted and easily discerned based on their specific colour. Examples are shown based on satellite imagery from several free sources, e.g. the USGS’s Earth Explorer, the ESA’s Copernicus Open Access Hub, etc.

The volcanic provinces of the Lennon-Picasso basin (Mercury)

<p>The volcanic provinces are embedded between the NE margin of b56 /Lennon-Picasso basin and high terrain bounding structures. Resulting plains are interested by endogenic pits associated with pyroclastic activity, in agreement with the observation that Mercury's explosive volcanic vents tend to be located along major fold and thrust belts (Byrne et al 2014) and around large impact basins. Recent large scale mapping defined them intercrater plains partly covered by smooth plains (Malliband et al 2019; Whitten et al 2020). In addition to endogenic pits, these provinces display several 10-km diameter prominent cones, sometimes aligned forming high-relief ridges, resembling  constructional edifices. In colour composite images, cone tops are peculiarly darker (blue) or, alternatively, brighter (and yellow) with respect to the surrounding material. On the surface Mercury, Wright et al. (2019) interpreted two randomly located constructional edifices of similar size, attributing their origin to a late highly viscous  stage of volcanism that followed lower-viscous stage that are thought to provide typical smooth plains. Wider et al. (2016) proposed that the encounter of highly-viscous lavas with C-rich material during the magma ascent can easily provide volatiles (Zolotov et al. 2011) that progressively accumulate and lead to explosive eruptions. The resulting high reflectance of pyroclastic deposits would arise from removal of graphite as it was consumed during oxidation. The study aims to reveal the nature of cones at the margin of the Lennon-Picasso basin and to explain the relationship between a potential long-lasting volcanic activity and the concurrent global contractional regime.</p><p>Authors received funding from the Italian Space Agency (ASI) under ASI-INAF agreement 2017-47 and from European Union’s Horizon 2020 research grant under agreement 776276- PLANMAP.</p>

Alteration Mapping for Lead-Zinc-Barium Mineralization in Parts of the Southern Benue Trough, Nigeria, Using ASTER Multispectral Data

The lead-zinc-barium deposits of the southern Benue Trough, Nigeria belong to a suite of clastic dominated fracture filling hydrothermal vein deposits. The alteration types and spread are poorly known yet required to aid exploration. Band ratio composites (BRC), Principal Component Analysis (PCA), and Minimum Noise Fraction (MNF) were applied to a full scene Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery covering the study area. Spectral analysis of sulphide minerals known in the area led to the development of the (B1+B3)/2 ratio, which provided a highly effective sulphide discriminant. PCA and MNF bands with high eigenvectors in the absorption features of target minerals qualified as colour composite candidates for alteration mapping. This study demonstrated the effectiveness of combining the BRC, PCA and MNF techniques in the discrimination of ferric-ferrous/sulphide and silica alteration zones in the Southern Benue Trough.

TEXTURE ANALYSIS FOR LAND USE LAND COVER (LULC) CLASSIFICATION IN PARTS OF AHMEDABAD, GUJARAT

The present study addresses the potential of RADARSAT-2 data for Land Use Land Cover (LULC) Classification in parts of Ahmedabad, Gujarat, India. Texture measures of the original SAR data were obtained by the Gray Level Co-occurrence Matrix (GLCM). Results suggested False Colour Composite (FCC) of Mean, Homogeneity and Entropy showed a good discrimination of different land cover classes. Further, Principal Component Analysis (PCA) was also applied to the eight texture measures and FCC of Principal components is generated. Unsupervised classification is carried out for the above generated FCCs and accuracy assessment is carried out. The result of classification shows that the PCA generated from GLCM texture measures could obtain higher accuracy than using only the classification carried out by texture measures. Overall results of the study suggested possible use of single polarization and single date Radarsat-2 data for LULC classification with better accuracy using PCA generated image.

Ultracompact H ii regions with extended emission: the complete view

ABSTRACT In this paper, we present the results of a morphological study performed on a sample of 28 ultracompact H ii (UC H ii) regions located near extended free–free emission, using radio continuum (RC) observations at 3.6 cm with the C and D Very Large Array (VLA) configurations, with the aim of determining a direct connection between them. By using previously published observations in B and D VLA configurations, we compiled a final catalogue of 21 UC H ii regions directly connected with the surrounding extended emission (EE). The observed morphology of most of the UC H ii regions in RC emission is irregular (single- or multipeaked sources) and resembles a classical bubble structure in the Galactic plane with well-defined cometary arcs. RC images superimposed on colour composite Spitzer images reinforce the assignations of direct connection by the spatial coincidence between the UC components and regions of saturated 24 μm emission. We also find that the presence of EE may be crucial to understand the observed infrared excess because an underestimation of ionizing Lyman photons was considered in previous works (e.g. Wood & Churchwell; Kurtz, Churchwell & Wood).

An analysis of flooding coverage using remote sensing within the context of risk assessment

Results of research of the identification of flooding as a result of groundwater table fluctuations on the example of the valley of the River Vistula, with the use of multi-spectral Sentinel-2 images from the years 2017–2018 are presented. An analysis of indexes of water use, calculated on the basis of green, red and shortwave infrared (SWIR) bands, for extraction of water objects and flooded areas was carried out. Based on the analyses conducted, a mapping method was developed, using three water indexes (MNDWI Modified Normalised Difference Water Index, NDTI Normalised Difference Index and NDPI Normalised Difference Pond Index). Results show that the 10 metre false colour composite RNDTIGNDPIBMNDWI obtained significantly improved submerged extractions more than did individual water indexes. Moreover, the 10-m-images of MNDWI and NDPI, obtained by the sharpening High Pass Filter (HPF), may represent more detailed spatial information on floods than the 20-m-MNDWI and NDPI, obtained from original images.

SPATIAL PREDICTION MODELS FOR LANDSLIDE ACTIVITY MAPPING USING VEGETATION ANOMALIES

An area that located in Kundasang which in Ranau district in Sabah, Malaysia that lies along the bank of Kundasang valley was chosen for comparing the reliability of frequency ratio (FR) and weight of evidence (WoE) methods for landslide activity probability mapping by using related vegetation anomalies indicator. The locations of 47 and 189 of active and dormant landslides respectively were identified using 4 raster layers (topographic openness, hillshade, colour composite and high resolution orthophoto). Each landslide activites were randomly divided into two groups as training (70%) and testing (30%) datasets. Tree height irregularities, DVI, NDVI, SAVI, and OSAVI were considered as landslide bio-indicator. The landslide activity probability maps were prepared using the FR and WoE method. The generated maps were validated by calculating the success and prediction rates from area under receiver operating characteristics (ROC) curve. The results of WoE method were relatively reliable (AUC > 0.8) for dormant landslide while only about 40% of active landslide have been predicted accurately. Similar trend yielded for FR method where least accuracy for active landslide prediction.