A Colourimetric Approach to Ecological Remote Sensing: Case Study for the Rainforests of South-Eastern Australia

To facilitate the simplification, visualisation and communicability of satellite imagery classifications, this study applied visual analytics to validate a colourimetric approach via the direct and scalable measurement of hue angle from enhanced false colour band ratio RGB composites. A holistic visual analysis of the landscape was formalised by creating and applying an ontological image interpretation key from an ecological-colourimetric deduction for rainforests within the variegated landscapes of south-eastern Australia. A workflow based on simple one-class, one-index density slicing was developed to implement this deductive approach to mapping using freely available Sentinel-2 imagery and the super computing power from Google Earth Engine for general public use. A comprehensive accuracy assessment based on existing field observations showed that the hue from a new false colour blend combining two band ratio RGBs provided the best overall results, producing a 15 m classification with an overall average accuracy of 79%. Additionally, a new index based on a band ratio subtraction performed better than any existing vegetation index typically used for tropical evergreen forests with comparable results to the false colour blend. The results emphasise the importance of the SWIR1 band in discriminating rainforests from other vegetation types. While traditional vegetation indices focus on productivity, colourimetric measurement offers versatile multivariate indicators that can encapsulate properties such as greenness, wetness and brightness as physiognomic indicators. The results confirmed the potential for the large-scale, high-resolution mapping of broadly defined vegetation types.

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.

Utilizing landsat-8 sensor operational land image data for hydrothermal alteration mapping within Anka Schist Belt, northwestern Nigeria

Exploring for mineral deposits within the Anka Schist Belt involves the use of traditional geological techniques such as geochemical and geophysical studies that are very expensive and time consuming. There is therefore need for a better alternative that will provide accurate and reliable information with cost effective and time efficient solution. This effort seeks to explore the potential of remotely sensed digital data in highlighting mineralized zones through hydrothermal alteration studies. Landsat 8 OLI data covering the investigated area was used to detect and map locations of hydrothermal alterations. Image processing methods used were spectral enhancement, false colour composites, band rationing and Principal Component Analysis. Results of false colour composites of band 5: 7: 3 highlighted generally locations of hydrothermal alterations. Band ratios of 4/2, 6/7 and 6/5 revealed the presence of ferric iron minerals, clay rich minerals and ferrous minerals respectively. Principal Components (PCs) of two sets of images (2, 4, 5, 7 H-image and 2,5,6,7 F-image) depicting iron-oxide and hydroxyl mineral deposits as bright pixels were generated. Colour composite of H, F and H+F images enhanced the location of the mineral deposits, by showing areas of mineralization in dark blue (Fe rich), bright yellow (clay rich) and white (Fe and clay rich areas) pixels. Field coordinates of mining locations were superimposed on the remote sensing generated mineral map. The results were found to be in tune. This study recommends the use of remote sensing and geospatial technology in mineral studies through hydrothermal alteration within the basement complex rocks of Nigeria.

Is the Eye Like What It Sees? A Critique of Aristotle on Sensing by Assimilation

Aristotle held that perception consists in the reception of external sensory qualities (or sensible forms) in the sensorium. This idea is repeated in many forms in contemporary philosophy, including, with regard to vision, in the idea (still not firmly rejected) that the retinal image consists of points of colour. In fact, this is false. Colour is a quality that is constructed by the visual system, and though it is possible to be a realist about colour, it is completely misleading to think of it as received by the retina. Moreover, such supposedly “charitable” interpretations of Aristotle’s doctrines, based on misconceptions of perception-science, distort our understanding of his historical context.

Age Determination of Blood-Stained Fingerprints Using Visible Wavelength Reflectance Hyperspectral Imaging

The ability to establish the exact time a crime was committed is one of the fundamental aims of forensic science. The analysis of recovered evidence can provide information to assist in age determination, such as blood, which is one of the most commonly encountered types of biological evidence and the most common fingerprint contaminant. There are currently no accepted methods to establish the age of a blood-stained fingerprint, so progress in this area would be of considerable benefit for forensic investigations. A novel application of visible wavelength reflectance, hyperspectral imaging (HSI), is used for the detection and age determination of blood-stained fingerprints on white ceramic tiles. Both identification and age determination are based on the unique visible absorption spectrum of haemoglobin between 400 and 680 nm and the presence of the Soret peak at 415 nm. In this study, blood-stained fingerprints were aged over 30 days and analysed using HSI. False colour aging scales were produced from a 30-day scale and a 24 h scale, allowing for a clear visual method for age estimations for deposited blood-stained fingerprints. Nine blood-stained fingerprints of varying ages deposited on one white ceramic tile were easily distinguishable using the 30-day false colour scale.

Fusion of Unmanned Aerial Vehicle Panchromatic and Hyperspectral Images Combining Joint Skewness-Kurtosis Figures and a Non-Subsampled Contourlet Transform

To obtain fine and potential features, a highly informative fused image created by merging multiple images is usually required. In our study, a novel fusion algorithm called JSKF-NSCT is proposed for fusing panchromatic (PAN) and hyperspectral (HS) images by combining the joint skewness-kurtosis figure (JSKF) and the non-subsampled contourlet transform (NSCT). The JSKF model is used first to derive the three most sensitive bands from the original HS image according to the product of the skewness and the kurtosis coefficients of each band. Afterwards, an intensity-hue-saturation (IHS) transform is used to obtain the luminance component I of the produced false-colour image consisting of the above three bands. Then the NSCT method is used to decompose component I of the false-colour image and the PAN image. The weight-selection rule based on the regional energy is adopted to acquire the low-frequency coefficients and the correlation between the central pixel and its surrounding pixels is used to select the high-frequency coefficients. Finally, the fused image is obtained by applying an IHS inverse transform and an inverse NSCT transform. The unmanned aerial vehicle (UAV) HS and PAN images under low- and high-vegetation coverage of wheat at the flag leaf stage (Stage I) and the grain filling stage (Stage II) are used as the sample data sources. The fusion results are comparatively validated using spatial (entropy, standard deviation, average gradient and mean) and spectral (normalised difference vegetation, NDVI, and leaf area index, LAI) assessments. Additional comparative studies using anomaly detection and pixel clustering also demonstrate that the proposed method outperforms other methods. They show that the algorithm reported herein can better preserve the original spatial and spectral characteristics of the two types of images to be fused and is more stable than IHS, principal components analysis (PCA), non-negative matrix factorization (NMF) and Gram-Schmidt (GS).