Color Composite Images Research Articles

Integration of C-band SAR and high-resolution optical images for delineating palaeo-channels in Nagaur and Barmer districts, western Rajasthan, India.

Identifying hitherto unknown palaeo-channels, especially in the arid regions of the Thar Desert, is crucial since these channels may form excellent aquifers, and are also associated with valuable ore deposits of many precious minerals. This study employed integrated C-band Synthetic Aperture Radar (SAR) of Sentinel-1A and high-resolution multispectral Sentinel-2A data of pre- and post-monsoon seasons (June and November) to delineate playas and palaeo-channels. This approach is the first of its kind for this area. The palaeo-channels were delineated through a detailed visual inspection of colour composite (CC) images of Sentinel-2A data, SAR backscatter (VH) images and fused SAR and optical images. Then, we studied the topographic profiles generated from the Shuttle Radar Topography Mission -Digital Elevation Model (SRTM-DEM) across the identified palaeo-channels, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) to further confirm the existence of a palaeo-channel's course and playas. As a result, several playas and palaeo-channels in the area were successfully identified, some of which were previously unmapped and undetected. The results indicate that the post-monsoon datasets are more useful for the precise delineation of palaeo-channels due to the presence of relatively higher moisture along the palaeo-channels' courses.

Geoecological assessment and environmental monitoring within the boundaries of the impact of the development of gold deposits using GIS technologies

An interdisciplinary approach is used in the study of this problem. Well-known methods are used in the work. The ground-based phase of the research consisted of sampling. The results indicate intense pollution. High concentrations of compounds of mercury, arsenic, copper, lead, zinc were recorded. Deciphering the Landsat 8 (GloVis) images made it possible to supplement the mining and environmental monitoring by studying the dynamics of changes in the areas of placer gold mining. Data processing was carried out on the basis of the open geoinformation system Qgis. Image processing methods: False Color Composite (FCC) images in artificial colors; Band Ratio (BR) creates complex band ratios. Digitization of the images showed increasing areas of disturbed land. For the first time, a geo-ecological assessment using GIS technologies was carried out. Over a long period of time, ground monitoring data are entered into the Qgis database. The practical significance of the work is confirmed by the Patent of the Russian Federation and substantiated by the creation of a method to ensure the environmental safety of technogenically polluted areas using bioremediation.

Crop Cultivation at Wartime – Plight and Resilience of Tigray’s Agrarian Society (North Ethiopia)

ABSTRACT During the 2021 conflict in Tigray (north Ethiopia), crop cultivation has been hampered by warfare. Oxen have been looted and killed, farm inputs and tools destroyed by Ethiopian and Eritrean soldiers. Farmers felt vulnerable out in the open with their oxen. To produce, farmers evaluated risks involved with ploughing and organised lookouts. Overall, a large part of the land had been tilled in difficult conditions, and crops sown that require minimal management, without fertiliser, what led to low yields. True Colour Composite images, produced from Sentinel satellite imagery show that smallholder irrigation schemes were operational. There was a shift from commercial crops to cereals. The situation in western Tigray was particular, as there has been ethnic cleansing of the population and often the 2020 rainfed crops had even not been harvested. Overall, our findings show that the Tigrayan smallholder farming system is resilient, thanks to community self-organisation, combining common strategies of agrarian societies in wartime: spatio-temporal shift in agricultural activities to avoid the proximity with soldiers and shifts in crop types. Rather unique is the relying on communal aid, while the blockade of the Tigray region made that outmigration and off-farm income were no options for the farmers.

Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens

AbstractConventional histological stains, such as hematoxylin plus eosin (H&E), and immunohistochemistry (IHC) are mainstays of histology that provide complementary diagnostic information. H&E and IHC currently require separate slides, because the stains would otherwise obscure one another. This consumes small specimen, limiting the total amount of testing. Additionally, performing H&E and IHC on different slides does not permit comparison of staining at the single cell level, since the same cells are not present on each slide, and alignment of tissue features can be problematic due to changes in tissue landscape with sectioning. We have solved these problems by performing conventional staining and IHC on the same slide using invisible IHC chromogens, such that the chromogens are not visible when viewing the conventional stain and the conventional stain is excluded from images of the IHC. Covalently deposited chromogens provided a convenient route to invisible chromogen design and are stable to reagents used in conventional staining. A dual-camera brightfield microscope system was developed that permits simultaneous viewing of both visible conventional stains and invisible IHC chromogens. Simultaneous staining was demonstrated on several formalin-fixed paraffin-embedded tissue specimens using single and duplex IHC, with chromogens that absorb ultraviolet and near infrared light, followed by H&E staining. The concept was extended to other conventional stains, including mucicarmine special stain and Papanicoulou stain, and further extended to cytology specimens. In addition to interactive video review, images were recorded using multispectral imaging and image processing to provide flexible production of color composite images and enable quantitative analysis.Conventional histological and cytological stains, including hematoxylin & eosin and Papanicolaou, are combined with immunohistochemistry and simultaneously evaluated on the same specimen slide by use of invisible chromogens. Visible and invisible light used to illuminate the specimen are separated and directed to color and monochrome cameras, respectively, providing conventional stain and immunohistochemistry in side-by-side videos on the computer monitor. Alternatively, multispectral imaging of single microscope fields provides archiving and further evaluation utilizing image processing.

Diffusion-weighted image analysis along the perivascular space (DWI–ALPS) for evaluating interstitial fluid status: age dependence in normal subjects

PurposeThe purpose of this study was to evaluate the interstitial fluid status in a wide range of age groups using diffusion-weighted image analysis along the perivascular space (DWI–ALPS) method, which is a simplified variation of diffusion tensor image analysis along the perivascular space (DTI–ALPS).Materials and methodsThis retrospective study included data from 128 patients who underwent clinical magnetic resonance imaging (MRI) studies, including DWI, and were found to have no abnormal findings in the brain on MRI. Three motion-probing gradients of the DWI were applied in an orthogonal direction to the imaging plane. Apparent diffusion coefficient images in the x-, y-, and z-axes were retrospectively generated, and composite color images were created to locate the projection and association fiber area on the slice including the body of the lateral ventricle. ALPS indices were calculated, and correlations with age were evaluated using linear and second-degree regression analysis. Linear regression analysis was also performed for a subgroup of patients older than 40 years. In addition, an analysis of variance (ANOVA) test among the generations was performed.ResultsThe linear regression analysis between age and the ALPS index showed a correlation coefficient of −0.20 for all age group and −0.51 for the subgroup older than 40 years. The second-degree regression analysis showed a correlation coefficient of 0.39. ANOVA showed that the 40’s generation showed a statistically significant higher value of ALPS index compared to all other generations except for the 30’s generation. While, the 70’s generation showed a statistically significant lower value of the ALPS index compared to all other generations.ConclusionsThe analysis of the DWI–APLS method showed a correlation between age and the ALPS index in second-degree distribution which peaked in the 40’s generation. This finding in normal subjects may be fundamental in the analysis of disease cases.Secondary abstractWe tried to evaluate the glymphatic system status in a wide range of age groups using diffusion-weighted image analysis along the perivascular space (DWI–ALPS) method, and the results showed a correlation between age and the ALPS index in second-degree distribution which peaked in the 40’s generation.

Natural Radioactivity and Radiological Implications of Stream Sediments at Wadi Aidib Area, South Eastern Desert, Egypt

Wadi Aidib lies at the extreme southern part of the Eastern Desert, Egypt, between 22o15'- 22o21' N and Longitudes 36o20'-36o30' E. Landsat ETM+ false color composite image (bands 3, 2, 1) was used for regional discrimination for different rock types and provide an excellent base map for the study area, morphological features of the stream deposits of the study area were known from Landsat ETM images, in addition to several field observations. The studied stream sediments accumulate in the form of alluvial fans. They are mainly composed of sands, gravels, boulders and contain some heavy valuable minerals which are derived from metavolcanics, metasediments, quartz diorite, biotite and alkali feldspar granites. Heavy liquid separation and magnetic separation techniques in addition to microscopic examination for the studied stream sediment samples were applied to identify the heavy minerals in these sediments. These minerals are represented by magnetite, ilmenite, rutile, garnet, zircon, monazite and Green silicates. The distribution of some elements in the study area is clear that they are concentrated near the outcrops of granites. The radionuclide concentrations were measured in different stations using a calibrated gamma-ray portable detector (RS 230) and the heavy minerals causing radioactivity were separated by heavy liquids and determined by binuclear and environmental scanning electron microscopes. Uranium ranges between 5.25 and 32.05 ppm with an average of 16.63 ppm, Th between 4.4 and 17 ppm with 11.34 ppm as an average and potassium fall between 1.8 and 5.15% with an average of 3.4 %. Correlation between soil radioactivity and its mineralogical content indicate that the high radionuclides contents are mainly attributed to the presence monazite which is the principal source of both uranium and thorium. Uranium high concentrations could be related to the metamict zircon. Absorbed Dose Rate (D), annual effective dose equivalent radium equivalent activity, external and internal hazard index, in addition to activity gamma index caused by gamma emitting natural radionuclide are determined from the obtained values of 238U, 232Th and 40K. Fairly, some of the studied stations do not satisfy the universal standards. 40K plays the main and most important role in dose rate contribution.

Mineral exploration of Iwo-Apomu Southwestern Nigeria using aeromagnetic and remote sensing

The tectonic framework, lithostructural and mineralised zones of Iwo-Apomu region of Precambrian Basement Complex rocks were investigated using integrated aeromagnetic and satellite remote datasets. Fast Fourier Transforms (FFT) performed on aeromagnetic data were: Butterworth Filter (BF), Reduction to Magnetic Equator (RTE), Regional field, Residual field, Tilt-Angle Derivative (TDR), First and Second Vertical Derivative (FVD and SVD), Tilt angle and Total horizontal derivative (TDR and TDHR), and Total Gradient Amplitude (TGA); which range from −31.97 – 123.24, −27.12 – 131.75, 1.52 – 117.90, −58.55 – 50.42, −1.35 – 1.36, −0.0712 – 0.0643, 0.0004 – 0.0102, 0.005 – 0.261 respectively. Continuations and Radially Average Power Spectrum; revealed the variations of the deep-seated basement rocks, the structures and the mineralised anomalous bodies with depth. The upward continuation maps also show that the regional trends of the mapped lithologies and lineaments/faults in the area are generally in NW-SE, E-W, and NW-SE directions. These filters defined the lithostructures, lithological boundaries, geological structures, contacts, faults, folds and mineral deposit. The results of satellite data on Principal Component Analysis (PCA), False Colour Composite (FCC) images and Band Ratio (BR) discriminated the different rock types, lithostructural boundaries and alteration zones that hosted the mineralized ore bodies which trend in NE–SW and minor NW–SE and E–W directions. The combined techniques generated showing the probable positions and trend of suspected fault/fracture, mineral deposit as well as other basement structures.

Planetary Terrestrial Analogues Library Project: 3. Characterization of Samples With MicrOmega.

The Planetary Terrestrial Analogues Library (PTAL) project aims at building and exploiting a database involving several analytical techniques, to help characterize the mineralogical evolution of terrestrial bodies, starting with Mars. Around 100 natural Earth rock samples have been collected from selected locations to gather a variety of analogs for martian geology, from volcanic to sedimentary origin with different levels of alteration. All samples are to be characterized within the PTAL project with different mineralogical and elemental analysis techniques, including techniques brought on actual and future instruments at the surface of Mars (near infrared [NIR] spectroscopy, Raman spectroscopy, and laser-induced breakdown spectroscopy). This article presents the NIR measurements and interpretations acquired with the ExoMars MicrOmega spare instrument. MicrOmega is an NIR hyperspectral microscope, mounted in the analytical laboratory of the ExoMars rover Rosalind Franklin. All PTAL samples have been observed at least once with MicrOmega using a dedicated setup. For all PTAL samples, data description and interpretation are presented. For some chosen examples, color composite images and spectra are presented as well. A comparison with characterizations by NIR and Raman spectrometry is discussed for some of the samples. In particular, the spectral imaging capacity of MicrOmega allows detections of mineral components and potential organic molecules that were not possible with other one-spot techniques. In addition, it enables estimation of heterogeneities in the spatial distribution of various mineral species. The MicrOmega/PTAL data shall support the future observations and analyses performed by MicrOmega/Rosalind Franklin instrument.

An integrated remote sensing, aeromagnetic and field study of the Ablah shear zone (Asir Terrane, Saudi Arabia): Structural styles and implications for the tectonic evolution

• Surface and subsurface structural mapping was carried out for the Ablah shear zone. • Northerly striking thrust faults define the positive flower structure that impacts the shallow rocks in the zone. • Shallow thrusting ends at 1.5 to 2 km depth and is converted into single thrust shear. • Contraction tectonic regime initiated the shear zone and was later superposed by dextral-transpression regime. An integration of merged remote-sensing data having different spatial/spectral resolutions with aeromagnetic data and detailed field investigation is used to identify the composite Neoproterozoic rock complexes and define the structural architecture of the Ablah Shear Zone (ASZ). The SPOT and Landsat-8 data are processed as color composite images allowed the separation of different lithologic units and associated structures. Aeromagnetic data were analyzed using the Total Magnetic Intensity (TMI) and Reduced to the Pole (RTP) methods. The resulted anomalies show seven N-S opposite-dipping thrust faults that affect the shallow crustal rocks and coalesce together at about 1.5 to 2 km depth where the rock magnetic polarities inversed. This thin-skinned thrusting was initiated by a contractional tectonic regime in the E-W direction and superposed later by a transpresssion tectonic regime in the ENE-WSW direction. This study deals with the thin-skinned thrusting deformation in the ASZ that could be occurred during the deformation of the other shear zones that affect the internal part of the Asir tectonic terrane. Two controversial tectonic meanings describe the tectonic evolution of the ASZ, the first one is the thin-skinned thrusting tectonic that indicating shallow earth s crust deformation and the second one is the occurrence of some ophiolitic slices that indicating suturing tectonic deformation. The absent of the complete ophiolitic section encourages us regarding the ASZ as a structural shearing zone rather than a suture zone.

Land cover classification of spaceborne multifrequency SAR and optical multispectral data using machine learning

This study compares the utility of multifrequency SAR and Optical multispectral data for land-cover classification of Mumbai city and its nearby regions with a special focus on water body mapping. The L-band ALOS-2 PALSAR-2, X-band TerraSAR-X, C-band RISAT-1, and Sentinel-2 datasets have been used in this work. This work is done as a retrospective study for the dual-frequency L and S-band NASA-ISRO Synthetic Aperture Radar (NISAR) mission. The ALOS-2 PALSAR-2 data has been pre-processed before the implementation of machine learning algorithms for image segmentation. Multi-looking is performed on ALOS-2 PALSAR-2 data to generate square pixels of size 5.78 m and then target decomposition is applied to generate a false-color composite RGB image. While in the case of TerraSAR-X and RISAT-1 datasets, no multi-looking was performed and direct target decomposition was applied to generate false-color composite RGB images. Similarly, for the optical dataset that has a resolution of 10 m, a true color composite, and a false color composite RGB image are generated. For the comparative study between ALOS-2 PALSAR-2 and Sentinel-2 dataset, the RGB images are divided into smaller chunks of size 500*500 pixels each to create a training and testing dataset. Ten image patches were taken from the large dataset, out of which eight patches were used to train the machine learning models Random Forest (RF), K Nearest Neighbor (KNN), and Support Vector Machine (SVM), and two patches were kept for testing and validation purpose. For training the machine learning models, feature vectors are generated using the Gabor filter, Scharr filter, Gaussian filter, and Median filter. For patch 1, the mIOU for true-color composite based Optical image varies from 0.2323 to 0.2866 with the RF classifier performing the best and the mIOU for false-color composite based Optical image varies from 0.4130 to 0.4941 with the RF classifier performing the best while for ALOS-2 PALSAR-2 data, the mIOU varies from 0.4033 to 0.4663 with the RF classifier outperforming the KNN and the SVM classifiers. For patch 2, the mIOU for true-color composite based Optical data varies from 0.3451 to 0.4517 with KNN performing the best and the mIOU for false-color composite based Optical image varies from 0.5156 to 0.5832 with the RF classifier performing the best while for ALOS-2 PALSAR-2 data, the mIOU varies from 0.4600 to 0.5178 with the RF classifier outperforming the KNN and the SVM classifiers. The gap between the performance of ALOS-2 PALSAR-2 data and Sentinel-2 optical data is observed when the IOU of water class is compared, with IOUw for the true-color composite based optical image at a maximum of 0.2525 and for false-color composite based optical image at a maximum of 0.7366 while for ALOS-2 PALSAR-2 data a maximum IOUw of 0.7948 is achieved. The better performance of SAR data as compared to true-color composite based optical image data is due to the misclassification of ground and water classes into urban and forest in the case of the true-color composite based optical dataset which can be attributed to the high similarity between water and forest classes in the case of true-color composite based optical data whereas both these classes are easily separable in case of SAR data. This issue is however resolved by using the false color composite based optical image dataset for the classification task which performs slightly better than ALOS-2 PALSAR-2 data in the overall classification task. However, the SAR data works best in water body detection as notable from the high IOU for water class in the case of SAR data. In addition to the comparative analysis between Sentinel-2 optical and ALOS-2 PALSAR-2 data, land-cover classification has been performed on X-band TerraSAR-X and C-band RISAT-1 data on a single patch and it has been found that the RF classifier performs the best, recording the mIOU 0.5815 for X-band TerraSAR-X data, mIOU of 0.4031 for the C-band RISAT-1 data, and mIOU of 0.6153 for the L-band ALOS-2 data.

Spatial - Temporal variability of Land Use Land Cover at Mount Merapi, Indonesia

One of the most active volcanoes in the island of Java is Merapi mount which was experienced the last major eruption peak on October 26th, 2010. This volcanic eruption was effusive eruption type where magmatic gas pressure in the crater was not too strong and magma eruption was just flown out past the slopes of the Merapi mount area. However, magmatic gas pressure and magma volume still result in deformation changes that have a direct impact on residential areas throughout the Merapi mount area. Residential areas were obtained through supervised classification process from Landsat 7 and 8-satellite imagery in the 2009, 2011 and 2019 acquisition year. The reason of observation year selection was based on pre and post eruption concept to get pattern of Merapi’s mountain body change through deformation analysis. The work focuses on spatial-temporal variability of land use land cover analysis at Mount Merapi pre and post 2010 eruption event considered here. The technique is based on NDVI (Normalized Difference Vegetation Index), Maximum Likelihood Classification (MLC) and False Colour Composite methodology. Based on change in number of pixels it was analysed. Actually, some portion of land was covered with clouds and its shadows. From the results it was observed that, water body, barren and built up features were miss classified. So finally False Colour Composite (FCC) images are used to identify the misclassified classes.

Bearing Fault Diagnosis Using Multidomain Fusion-Based Vibration Imaging and Multitask Learning.

Statistical features extraction from bearing fault signals requires a substantial level of knowledge and domain expertise. Furthermore, existing feature extraction techniques are mostly confined to selective feature extraction methods namely, time-domain, frequency-domain, or time-frequency domain statistical parameters. Vibration signals of bearing fault are highly non-linear and non-stationary making it cumbersome to extract relevant information for existing methodologies. This process even became more complicated when the bearing operates at variable speeds and load conditions. To address these challenges, this study develops an autonomous diagnostic system that combines signal-to-image transformation techniques for multi-domain information with convolutional neural network (CNN)-aided multitask learning (MTL). To address variable operating conditions, a composite color image is created by fusing information from multi-domains, such as the raw time-domain signal, the spectrum of the time-domain signal, and the envelope spectrum of the time-frequency analysis. This 2-D composite image, named multi-domain fusion-based vibration imaging (MDFVI), is highly effective in generating a unique pattern even with variable speeds and loads. Following that, these MDFVI images are fed to the proposed MTL-based CNN architecture to identify faults in variable speed and health conditions concurrently. The proposed method is tested on two benchmark datasets from the bearing experiment. The experimental results suggested that the proposed method outperformed state-of-the-arts in both datasets.

Mineral Exploration in Mawat Region, Kurdistan-Iraq, Based on Satellite Data and Terrain Prospection

The main goal of the presented exploration was to estimate potential for mineralization in the Mawat ophiolitic massif in Kurdistan, Iraq. The aim of the study was to explore existing copper mineralization and assessor elements gold, platinoids and chromium. Geological exploration detected two types of Cu occurrence a) secondary Cu carbonates (malachite) and b) Cu sulfides (chalcopyrite-pyrite). The Mawat region is mostly built of ultrabasic and basic rocks: peridotites, gabbros, serpentinites and basalts which are heavily deformed, with faults mostly oriented NNW-SSE, and NE-SW. The first phase of exploration comprised digital processing of ASTER and QuickBird satellite images, with appropriate geometrical and radiometric corrections and transformation into coordinate system. Color composite images were produced in different scales. They served to define lithological composition, tectonic settings, location of the points of interest etc. The field work was designed to check satellite data in situ, with focus on perspective rock formations, which might host copper mineralization, and other elements. The host rocks of the ore occurrences are primarily gabbros and metagabbros intersected by diabase dykes, epidote and quartz veins. Secondary mineralization is the product of surficial weathering and it is represented by malachite and limonite. The geophysical survey was very useful in the detection of area with elevated induced polarization and low resistivity. Three perspective areas have been selected for detailed explorations: Waraz, Mirava-Chenara and Konjirin-Kuradawi. The concentration of copper varies highly in very wide ranges; the maximum measured concentration of Cu was determined in Waraz area 6.7%. Some rock samples also show concentration of gold from 0.36 to 2.59 ppm Au. Keywords: Mawat ophiolitic massif, geologic-geophysical explorations, copper mineralization, Kurdistan-Iraq

APPLICATION OF REMOTE SENSING IN LITHOLOGICAL DISCRIMINATION OF PRECAMBRIAN BASEMENT ROCKS OF ZUNGERU AREA, PART OF SHEET 163 (ZUNGERU NW), NORTH CENTRAL NIGERIA

Remote sensing technology has advanced significantly, making it useful for geological applications such as structural and lithological mapping, as well as mineral prospecting and mapping. This study looks at how certain enhancement techniques on Landsat 7 ETM+ data can be used to map surface geology, resulting in color composite imagery that can be interpreted and validated through field mapping exercises. Because some of these rocks are poorly exposed and some portions of the research region are inaccessible, field mapping was supplemented by remote sensing lithological mapping techniques. False Color Composite images for bands (7:4:1 and7:5:4), Principal Component analysis (PC1, 2, 3 and PC4, 5, 6) and RGB composite images of Landsat band ratios (1/3:5/7:3/5 and5/1:5/7:4) proved useful in determining the approximate boundaries of the various lithology in the research area. Gneiss and quartzites occur in the central and western quadrants of the study area, mylonites and schist in the eastern quadrant, and amphibolite in the southern and southeastern quadrants, according to GPS sample locations of the individual rock types found in the study area plotted on the processed images. The contact relationships between these rocks are mostly gradational and interlayered. As a result, a thorough examination of satellite optical imagery, such as Landsat data, can greatly aid lithological inquiry and the creation of more detailed geological maps in areas that are inadequately understood.

Interpretation of the Geological Romance of Kendari Bay Using Landsat 5 TM

Kendari Bay is part of Kendari City. Kendari Bay is a city landmark in addition to its economic and environmental functions.. The condition of Kendari Bay is experiencing a fairly high sedimentation problem, so that it begins to cause problems with land availability and space utilization patterns in the Kendari Bay area. The endogenous process of dynamic earth activities is a part that needs to be considered in managing that problems. This study aims the geological conditions of Kendari Bay by using remote sensing as a form of studying the geological conditions of Kendari Bay. Using Landsat 5 TM imagery in 1990, it was used to see the natural geological conditions of Kendari Bay, using the false color composite method and interpretation of photo images visually and validated through field observations. Landsat image processing and interpretation using Quantum GIS, resulted in Kendari bay can be divided into several physiography, namely coastal zone, estuary zone, fluvial zone, plain zone, hill zone, and mountain zone (Head land). The physiography can be seen from the geological characteristics such as the lithology which is composed of alluvial deposits to limestone. The results of interpretation of composite color images and validation of direct observation data in the field show a qualitative suitability.

MURAL LINEAR FEATURE ENHANCEMENT ALGORITHM COMBINING SEMI-SUPERVISED IMAGE SEGMENTATION AND DIMENSIONALITY REDUCTION

Abstract. Due to the influence of natural and human factors, the linear features in the murals are partially blurred, which brings great challenges to the digital preservation and virtual restoration of cultural heritage. Taking the advantages of non-invasive measurement as well as the rich image and spectral information of hyperspectral technology, we proposed a linear feature enhancement method by combining semi-supervised superpixel segmentation with block dimension reduction. The main research work includes: (1) The true color composite image was segmented to obtain the label data by using the local spatial information of the superpixel image and the global feature information extracted by fuzzy c-means (FCM) clustering.(2) According to the label data, the preprocessed hyperspectral data were divided into homogeneous regions, whose dimensionality was reduced by principal component analysis (PCA) and kernel principal component analysis (KPCA). (3) The principal component images with the largest gradient after dimensionality reduction were respectively selected and normalized. The optimal principal component images normalized by the block PCA and block KPCA dimensionality reduction algorithms are superimposed to produce the linear feature enhancement images of murals. The hyperspectral images of some murals in Qutan Temple, Qinghai Province, China were used to verify the method. The results show that the spatial information and the spectral information of different pattern areas in the hyperspectral image can be fully used by combining the superpixel FCM image segmentation algorithm with the dimensionality reduction algorithm. of. It can highlight the linear information in the hyperspectral images of fades murals.

A simple approach for monitoring vegetation change using time series remote sensing analysis: A case study from the Thathe Vondo Area in Limpopo Province, South Africa

This study presents a simple approach of spatiotemporal change detection of vegetation cover based on analysis of time series remotely sensed images. The study was carried out at Thathe Vondo Area, which is characterised by episodic variation of vegetation gain and loss. This variation is attributable to timber and tea plantations and their production cycles, which periodically result in either vegetation gain or loss. The approach presented here was implemented on two ASTER images acquired in 2007 and 2017. It involved the combined use of band combination, unsupervised image classification and Normalised Difference Vegetation Index (NDVI) techniques. True colour composite (TCC) images for 2007 and 2017 were created from combination of bands 1, 2 and 3 in red, blue and green, respectively. The difference image of the TCC images was then generated to show the inconsistencies of vegetation cover between 2007 and 2017. For analytical simplicity and interpretability, the difference image was subjected to ISODATA unsupervised classification, which clustered pixels in the difference image into eight classes. Two ISODATA derived classes were interpreted as vegetation gain and one as vegetation loss. These classes were confirmed as regions of vegetation gain and loss by NDVI values of 2007 and 2017. In addition, the polygons of vegetation gain and loss regions were created and superimposed over the TCC images to further demonstrate the spatiotemporal vegetation change in the area. The vegetation change statistics show vegetation gain and loss of 10.62% and 2.03%, respectively, implying a vegetation gain of 8.59% over the selected decade.Significance:
 
 Vegetation change detection is essential in environmental monitoring and management of an area. This study presents a simple approach for assessing vegetation change over time. The approach involveschange detection through the difference of spectral values of vegetation pixels of time series remotelysensed images.

A Preliminary Study on Heavy Oil Location in Central Sumatra using Remote Sensing and Geographic Information Sytem

Heavy oil which is classifi ed as non conventional oil is the target of exploration in the world. In Indonesia, the potential for heavy oil exploration is quite large, especially in the Central Sumatra basin. This study aims to map the location of potential heavy oil based on remote sensing data and regional gravity data supported by a geographic information system. Landsat 8 OLI satellite data is processed to produce 567 (RGB) color composite images, then further processing is carried out with DEM data to produce fusion images; mapping the vegetation index, clay mineral index, iron oxide index, surface temperature. The gravity data is used for mapping subsurface geological structures. Overlay analysis is carried out on the results of remote sensing data processing and interpretation of surface and subsurface geology. Based on the analysis, it shows that heavy oil fi elds are generally found on the surface and subsurface structures which are relatively identical and located on the edge of the basement high. Based on this analysis, the locations that have the potential for heavy oil and gas traps are on the northeast edge, Dalu-dalu High, the edge of Kampar High, the west edge of Kuantan High, the southwest edge of the Beruk High, the southwest edge of the Sembilan High.

How to recognize different types of trees from quite a long way away: combining UAV and spaceborne imagery for stand-level tree species identification

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.

A Metaheuristics Framework for Weighted Multi-band Image Fusion

The main objective of hyper/multispectral image fusion is producing a composite color image that allows for an appropriate visualization of the relevant spatial and spectral information. In this paper, we propose a general framework for spectral weighting-based image fusion. The proposed methodology relies on weight updates conducted using nature-inspired algorithms and a goodness-of-fit criterion defined as the average root mean square error. Simulations on four public data sets and a recent Landsat 8 image of Brullus Lake, Egypt, as an area of study prove the efficiency of the proposed framework. The purpose of the study is to present a framework of multi-band image fusion that produces a fused image of high quality to be further used in computer processing and the results show that the image produced by the presented framework has the highest quality compared with some of the state-of-the art algorithms. To prove the increase in the image quality, we used general quality metrics such as Universal Image Quality Index, Mutual Information, the Variance and Information Measure.