Visual Identification Research Articles

Visualizing biomarkers and their association with clinical outcomes: A machine learning approach

IntroductionClinical investigators often seek to identify biomarkers that are associated with clinical outcomes. The challenge is that biomarkers tend to be numerous, often inter-correlated, and with varying degrees of association with the clinical outcome of interest. We developed a straightforward, effective visualization approach that allows investigators to see the inter-correlations of biomarkers and their association with clinical outcomes rendered in a 2-dimensional (2-D) plot. MethodWe extracted pairwise differences between outcome groups. Next, a t-SNE machine learning method was applied to reduce dimensionality of the data into 2-dimensional data. This data was then rendered as 2-D plots allowing visualization of either the original biomarker values or their ranking in the sample. We apply this method to a dataset of 235 subjects with data of 114 metabolomic biomarkers and cardiovascular outcomes. ResultThe 2-D plots demonstrated that the metabolite biomarkers with high degrees of association with the outcome tend to be positioned away from non-significant markers. Markers that are correlated with each other are positioned in clusters. An online demo version application of this visualization tool is available at http://52.9.140.88:3838/MarkersVu/. ConclusionThis is an effective approach to visualize biomarkers and their correlations, allowing rapid visual identification of biomarkers and marker clusters with potentially higher degree of association with the outcome.

Water-Soluble Single-Benzene Chromophores: Excited State Dynamics and Fluorescence Detection.

Two water-soluble single-benzene-based chromophores, 2,5-di(azetidine-1-yl)-tereph- thalic acid (DAPA) and its disodium carboxylate (DAP-Na), were conveniently obtained. Both chromophores preserved moderate quantum yields in a wide range of polar and protonic solvents. Spectroscopic studies demonstrated that DAPA exhibited red luminescence as well as large Stokes shift (>200 nm) in aqueous solutions. Femtosecond transient absorption spectra illustrated quadrupolar DAPA usually involved the formation of an intramolecular charge transfer state. Its Frank–Condon state could be rapidly relaxed to a slight symmetry-breaking state upon light excitation following the solvent relaxation, then the slight charge separation may occur and the charge localization became partially asymmetrical in polar environments. Density functional theory (DFT) calculation results were supported well with the experimental measurements. Unique pH-dependent fluorescent properties endows the two chromophores with rapid, highly selective, and sensitive responses to the amino acids in aqueous media. In detail, DAPA served as a fluorescence turn-on probe with a detection limit (DL) of 0.50 μM for Arg and with that of 0.41 μM for Lys. In contrast, DAP-Na featured bright green luminescence and showed fluorescence turn-off responses to Asp and Glu with the DLs of 0.12 μM and 0.16 μM, respectively. Meanwhile, these two simple-structure probes exhibited strong anti-interference ability towards other natural amino acids and realized visual identification of specific analytes. The present work helps to understand the photophysic–structure relationship of these kinds of compounds and render their fluorescent detection applications.

Rapid and simultaneous visual typing of high-risk HPV-16/18 with use of integrated lateral flow strip platform.

A biosensor for rapid and simultaneous visual identification of high-risk human papillomavirus (HPV) genotypes 16 and 18 in clinical samples based on polymerase chain reaction (PCR) integrated lateral flow strip platform was developed. Using an one-step protocol to extract nucleic acid rapidly and the functionalized primer sets specific to HPV-16 and 18 were designed for the simultaneous amplification. In the presence of target HPV genotypes, the corresponding functionalized primer sets will participate in the PCR process and produce numerous duplex functionalized dsDNA amplicons. With the bridge effect of duplex functionalized dsDNA amplicons between gold nanoparticles-fluorescein isothiocyanate antibody conjugates (AuNP-FITC antibody conjugates) and other two antibodies on corresponding test line (T1 or T2), visualized color signals on test lines could be obtained directly visible with a naked eye. Combining the high amplification efficiency of PCR and the visualized sensing of LFS, as low as 700 copies of HPV-16 and 18 DNA were detected simultaneously within 75 min, which can promote application in the resource limited settings.Graphical abstractHigh-risk genotypes of HPV-16 and HPV-18 were easily and simultaneously screened with the amplification-assisted molecular lateral flow strip by on-site observation in the resource-limited settings. Supplementary InformationThe online version contains supplementary material available at 10.1007/s00604-022-05449-5.

Artificial intelligence and high-resolution anoscopy: automatic identification of anal squamous cell carcinoma precursors using a convolutional neural network.

High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell cancer (ASCC) precursors. Although it is superior to other diagnostic methods, particularly cytology, the visual identification of areas suspected of having high-grade squamous intraepithelial lesions remains difficult. Convolutional neural networks (CNNs) have shown great potential for assessing endoscopic images. The aim of the present study was to develop a CNN-based system for automatic detection and differentiation of HSIL versus LSIL in HRA images. A CNN was developed based on 78 HRA exams from a total of 71 patients who underwent HRA at a single high-volume center (GH Paris Saint-Joseph, Paris, France) between January 2021 and January 2022. A total of 5026 images were included, 1517 images containing HSIL and 3509 LSIL. A training dataset comprising 90% of the total pool of images was defined for the development of the network. The performance of the CNN was evaluated using an independent testing dataset comprising the remaining 10%. The sensitivity, specificity, accuracy, positive and negative predictive values, and area under the curve (AUC) were calculated. The algorithm was optimized for the automatic detection of HSIL and its differentiation from LSIL. Our model had an overall accuracy of 90.3%. The CNN had sensitivity, specificity, positive and negative predictive values of 91.4%, 89.7%, 80.9%, and 95.6%, respectively. The area under the curve was 0.97. The CNN architecture for application to HRA accurately detected precursors of squamous anal cancer. Further development and implementation of these tools in clinical practice may significantly modify the management of these patients.

Robot Obstacle Recognition and Target Tracking Based on Binocular Vision

To further improve the perception ability of binocular vision sensor in getting rich environment information and scene depth information, a research method of a robot obstacle recognition and target tracking based on binocular vision was proposed. The method focused on target recognition and obstacle recognition of binocular stereo vision. The system based on obstacles of visual identification was set up. Through the analysis of the Bouguet mathematical model algorithm based on OpenCV, the binocular stereo correction was carried out and the obstacle recognition system was calibrated and corrected. Through the experimental data, it was found that the average error of the obstacle recognition and target tracking algorithm based on binocular vision could be controlled within 50 mm within the range of 2100 mm. The average time of obstacle recognition was 0.096 s and the average time consumption of the whole system was 0.466 s, indicating that the robot obstacle recognition and target tracking system based on binocular vision could meet the accuracy and real-timeness requirements of obstacle recognition and detection.

Oxidative-Stress Related Gene Polymorphism in Endometriosis-Associated Infertility.

Background and Objectives: Endometriosis is a benign inflammatory disease associated with infertility and chronic pelvic pain, estimated to affect 7–10% of reproductive-age women, with the possibility of malignant transformation. Recent studies focus on oxidative stress and genetic mutations as risk factors in the pathophysiology of endometriosis-associated infertility. Materials and Methods: This case-control study is the first in Eastern European women that aimed to investigate four genes’ genetic polymorphisms that encode antioxidant enzymes involved in oxidative stress (glutathione peroxidase 1, GPX1 198Pro > Leu, catalase CAT-262C > T, glutathione S-transferase M1, and T1 null genotype) and their association with endometriosis-related infertility. We compared 103 patients with endometriosis-associated infertility with 102 post-partum women as the control group. Results: The endometriosis group had a mean age of 34.5 +/− 6.12 years, while the control group’s mean age was 35.03 +/− 5.95 years. For CAT-262C > T polymorphism, the variant genotypes were significantly more frequent in the endometriosis group. Moreover, for the GPX1 198Pro > Leu, the endometriosis group had significantly more frequent CT and TT genotypes. The null genotype of GSTM1 was detected significantly higher in the endometriosis group. No significant differences were found in the frequency of GSTT1 between the two groups. This study suggests that GPX1 198Pro > Leu, CAT-262C > T, and GSTM1 polymorphisms may be risk factors and that the association between the GSTM1-GSTT1 null genotype may play a significant role in endometriosis-associated infertility. Moreover, this study suggests that the GSTT1 null genotype does not influence the disease. Visual identification of endometriotic lesions with microscopic confirmation is the accepted gold standard for diagnosing endometriosis, but general anesthesia and laparoscopy are required. Conclusions: In this regard, a panel of genetic or laboratory markers is needed for the early diagnostics of this prevalent disease, especially in the case of young patients with future pregnancy intention.

Detection of defect in ballastless track based on impact echo method combined with improved SAFT algorithm

Impact echo method is a superior method for structural health monitoring in concrete, but it has the disadvantages of low accuracy in detecting multi-layer structures. To overcome this limitation, an improved synthetic aperture focusing technique (SAFT) algorithm was proposed and combined with impact echo method for the detection of ballastless track. The improved SAFT algorithm makes full use of time domain echo signals containing multiple conversion elastic waves to image ballastless track defect. Simulation analysis based on finite difference time-domain (FDTD) method and a laboratory experiment were conducted to verify the effectiveness of improved SAFT algorithm combined with impact echo method for the identification of ballastless track defect. The results show that the decrease of sensor spacing and contact time in impact echo method contributes to the visual identification of defects by the improved SAFT algorithm, the visualization effect of defects can be improved by adjusting the minimum threshold level of the color scale of reconstructed image. Except for defect near the boundary, impact echo method combined with the improved SAFT algorithm has good applicability for the detection of ballastless track defects with random spatial location and number distribution.

Accuracy and Inter-observer Agreement Among Endoscopists for Visual Identification of Colorectal Polyps Using Endoscopy Images.

It is essential to accurately distinguish small benign hyperplastic colon polyps (HP) from sessile serrated lesions (SSL) or adenomatous polyps (TA) based on endoscopic appearances. Our objective was to determine the accuracy and inter-observer agreements for the endoscopic diagnosis of small polyps. High-quality endoscopic images of 30 small HPs, SSLs, and TAs were used randomly to create two-timed PowerPoint slide sets-one with and another one without information on polyp size and location. Seven endoscopists viewed the slides on two separate occasions 90days apart, identified the polyp type, and graded their confidence level. Overall and polyp-specific accuracies were assessed for the group and individual endoscopists. Chi-square tests and Kappa (κ) statistics were used to compare differences as appropriate. When polyp size and location were provided, overall accuracy was 67.1% for TAs, 50.0% for SSLs, and 41.4% for HPs; the corresponding accuracies were 60%, 44.3%, and 34.3% when polyp size and location were withheld (p < .001). Inter-observer agreement was moderate for TAs (κ = 0.50) and fair for SSLs (κ = 0.26) and HPs (κ = 0.29); the corresponding inter-observer agreements were 0.44, 0.31, and 0.17 with polyp size and location withheld. Accuracy was not affected by knowledge of polyp size, location, or confidence level. Endoscopists with ≥ 10years (vs. < 10years) of colonoscopy experience had marginally higher (56% vs. 40%, p = 0.05) accuracy for SSL diagnosis. The ability to distinguish between small TAs, SSLs, and HPs on their endoscopic appearance is poor regardless of the endoscopists' knowledge of polyp size and location.

Visual Identification of Trichosporon asahii, a Gut Yeast Associated with Obesity, Using an Enzymatic NIR Fluorescent Probe.

Lipase found in the gut microbiota participates in the digestion and absorption of dietary fats. As such, the gut microbiota is involved in the regulation of the host metabolism, affecting the levels of lipids and free fatty acids, ultimately resulting in obesity. In this study, an enzymatic activatable near-infrared fluorescent probe, DDAO-C6, was developed for visually sensing endogenous lipase from gut microbes. Using DDAO-C6, a cultivated intestinal yeast strain was rapidly identified from human feces that exhibited high lipase expression and was identified as Trichosporon asahii Y2. We then determined that the colonization of the gut of mice with T. asahii Y2 increased lipase activity in the digestive tract and promoted obesity and hyperlipidemia when the mice were fed high fat diets. Above all, the present research resulted in a fluorescence visualization tool for the functional investigation of gut microbiota associated with obesity and disorders of lipid metabolism.

A Computational Tool for Detection of Soft Tissue Landmarks and Cephalometric Analysis

In facial aesthetics, soft tissue landmark recognition and linear and angular measurement play a critical role in treatment planning. Visual identification and judgment by hand are time-consuming and prone to errors. As a result, user-friendly software solutions are required to assist healthcare practitioners in improving treatment planning. Our first goal in this paper is to create a computational tool that may be used to identify and save critical landmarks from patient X-ray pictures. The second goal is to create automated software that can assess the soft tissue facial profiles of patients in both linear and angular directions using the landmarks that have been identified. To boost the contrast, we employ gamma correction and a client-server web-based model to display the input images. Furthermore, we use the client-side to record landmarks in pictures and save the annotated landmarks to the database. The linear and angular measurements from the recorded landmarks are then calculated computationally and displayed to the user. Annotation and validation of 13 soft tissue landmarks were completed. The results reveal that our software accurately locates landmarks with a maximum deviation of 1.5 mm to 5 mm for the majority of landmarks. Furthermore, the linear and angular measurement variances across users are not large, indicating that the procedure is reliable.

Simulation of Multimedia Visual Image Motion Track Marking Based on Artificial Bee Colony Algorithm

With the rapid development of electronic technology, network technology, and multimedia processing technology, people pay more and more attention to the surrounding environment. Paying attention to and handling emergencies have also become one of the main points of attention. Through the combination of multimedia and monitoring system, the collected image data are processed and integratedly controlled by the computer platform, and an intelligent monitoring system for traffic road safety can be obtained. Due to the advantages of multimedia visual image motion trajectory identification technology in road traffic safety, it can effectively prevent the chaos and influence caused by humans in chaotic situations, making it widely used. By identifying the motion trajectories of different objects, road emergencies can be effectively prevented and countermeasures can be established. Based on this, this study proposes the artificial bee colony (ABC) algorithm to identify the motion trajectory in the visual image, but the standard ABC algorithm is too slow to converge in the later stage of trajectory recognition. Therefore, this study is based on the standard ABC algorithm. The trajectory recognition simulation shows that the optimized algorithm accelerates the convergence speed and the ability of the global optimal solution in the trajectory recognition process. Then, the optimized ABC algorithm is used to identify the multimedia visual image trajectory. The experiment shows that the average correct rate of feature extraction is also about 98%. The data identification results also show that the optimized ABC algorithm fits the real trajectory better in the trajectory identification. The running time of the algorithm is shorter than the running time of other comparison algorithms, which fully shows the accuracy and superiority of the algorithm in this study.

Morpho-structural and thermo-mechanical characterization of recycled polypropylene and polystyrene from mixed post-consumer plastic waste

In this work, a complete sorting and characterization of dirty non-recyclable mixed plastic (plasmix fraction) from municipal solid waste was performed. The procedure comprised a visual inspection and identification of the materials presented in the mixed plastic bales, and subsequent moisture and dirt content determination. Afterwards, both polypropylene and polystyrene fractions obtained from the sorting process were recycled and physico-mechanically and thermally characterized for the assessment of recycled material quality. The dirty non-recyclable mixed plastic from municipal solid waste was composed of polypropylene (28.89 %), polyethylene terephthalate (22.02 %), polystyrene (9.65 %) and rigid polyethylene (4.68 %). Regarding the moisture and dirt content of the mixed plastic fraction, the results were highly variable, mainly due to the heterogeneity of the material, its origin, atmospheric conditions, etc. The average sum of both parameters (moisture and dirt) was around 15 %. The mechanical properties were within the expected range for each type of polymer, noting that polystyrene recycled materials are more brittle than recycled polypropylene. The recycling of non-food polypropylene wastes yielded a material with higher impact resistance (70 kJ m−2) and Young´s modulus (1934 MPa) as compared to that obtained from the recycling of food packages. Concerning the polystyrene recyclates, it is worth mentioning that recycled materials obtained from foamed residues (expanded polystyrene and extruded polystyrene showed approximately twice the tensile strength with respect to the recycled materials from high impact polystyrene and general-purpose polystyrene residues. In some cases, infrared and thermal analyses revealed cross-contamination with traces of other polymers.

Sensitive and visual identification of Chlamydia trachomatis using multiple cross displacement amplification integrated with a gold nanoparticle-based lateral flow biosensor for point-of-care use.

Chlamydia trachomatis is the leading cause of bacterial sexually transmitted infection (STI) and remains a major public health challenge, especially in less-developed regions. Establishing a rapid, inexpensive, and easy-to-interpret point-of-care (POC) testing system for C. trachomatis could be critical for its treatment and limiting further transmission. Here, we devised a novel approach termed a multiple cross displacement amplification integrated with gold nanoparticle-based lateral flow biosensor (MCDA-AuNPs-LFB) for the highly specific, sensitive, user-friendly, and rapid identification of C. trachomatis in clinical samples. A suite of MCDA primers based on the C. trachomatis ompA gene from 14 serological variants (serovar A-K, L1, L2, and L3) were successfully designed and used to establish the assay. Optimal assay conditions were identified at 67°C, and the detection procedure, including nucleic acid preparation (approximately 5 min), MCDA amplification (30 min), and AuNPs-LFB visual readout (within 2 min), was completed within 40 min. The all-in cost for each test was approximately $5.5 USD. The limit of detection (LoD) was 10 copies/reaction, and no cross-reaction was observed with non-C. trachomatis microbes. A total of 135 suspected C. trachomatis-infection genital secretion samples were collected and simultaneously detected using real-time quantitative PCR (qPCR) in our assay. Compared with the qPCR technology, the MCDA-AuNPs-LFB sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 96.20%, 94.92%, and 100%, respectively. Hence, our MCDA-AuNP-LFB assay exhibited considerable potential for POC testing and could be used to identify C. trachomatis in clinical settings, particularly in low-income regions.

Examining the Visual Attention Patterns and Identification Accuracy of Adults With Aphasia for Grids and Visual Scene Displays.

We compared the degree of cognitive processing needed by people with aphasia to identify themes depicted in grids and visual scene displays (VSDs). We also compared the accuracy of theme identification for both display types. Eye-tracking technology was employed to measure the visual processing patterns of 21 adults with aphasia when interpreting themes presented through grids and VSDs. Additionally, we assessed theme identification accuracy by having participants select themes from four choices after viewing each display. Participants more rapidly identified VSDs than grid displays, and VSDs required fewer visual fixations to process than grids. No significant differences were noted between grids and VSDs for theme identification accuracy; however, results indicate a ceiling effect for the variable, as participant accuracy levels were nearly 100% for both display conditions. Results from this study add to a growing body of evidence supporting the use of VSDs for adults with aphasia. Both display types were accurately identified; however, VSDs were processed more efficiently than grids indicating that both display types may prove effective for people with aphasia; however, VSDs may require less cognitive effort to effectively use than grid displays.

How Reliable Is Endoscopic Stone Recognition? A Comparison Between Visual Stone Identification and Formal Stone Analysis.

Objective: To assess the diagnostic accuracy and intra-observer agreement of endoscopic stone recognition (ESR) compared with formal stone analysis. Introduction: Stone analysis is a corner stone in the prevention of stone recurrence. Although X-ray diffraction (XRD) and infrared spectroscopy are the recommended techniques for reliable formal stone analysis, this is not always possible, and the process takes time and is costly. ESR could be an alternative, as it would give immediate information on stone composition. Materials and Methods: Fifteen endourologists predicted stone composition based on 100 videos from ureterorenoscopy. Diagnostic accuracy was evaluated by comparing the prediction from visual assessment with stone analysis by XRD. After 30 days, the videos were reviewed again in a random order to assess intra-observer agreement. Results: The median diagnostic accuracy for calcium oxalate monohydrate was 54% in questionnaire 1 (Q1) and 59% in questionnaire 2 (Q2), whereas calcium oxalate dihydrate had a median diagnostic accuracy of 75% in Q1 and 50% in Q2. The diagnostic accuracy for calcium hydroxyphosphate was 10% in Q1 and 13% in Q2. The median diagnostic accuracy for calcium hydrogen phosphate dihydrate and calcium magnesium phosphate was 0% in both questionnaires. The median diagnostic accuracy for magnesium ammonium phosphate was 20% in Q1 and 40% in Q2. The median diagnostic accuracy for uric acid was 22% in both questionnaires. Finally, there was a diagnostic accuracy of 60% in Q1 and 80% in Q2 for cystine. The intra-observer agreement ranged between 45% and 72%. Conclusion: Diagnostic accuracy of ESR is limited and intra-observer agreement is below the threshold of acceptable agreement.

Individual Differences in Categorical Judgment of L2 Stops: A Link to Proficiency and Acoustic Cue-Weighting.

This study investigated individual differences in Korean adult learners' categorical perception of L2 English stops with an aim to explore the relationship of gradient categorizations to perceptual sensitivity to acoustic cues and L2 proficiency. Korean young adult L2 learners of English (N = 49) participated in two speech perception tasks (visual analog scaling and forced-choice identification) in which they listened to English voiced and voiceless stops and Korean lax and aspirated stops with Voice Onset Time (VOT) and F0 manipulated to form a continuum. It was found that in both L1 and L2 stop perception, listeners' gradient category judgment was associated with greater reliance on language-specific redundant cues (i.e., F0 in L2 English and VOT in L1 Korean) and that in the perception of L2 stops, categorical listeners who tended to be less sensitive to F0 were the ones with a higher level of L2 English proficiency. The results suggest that the categorical manner of judging L2 stops reflects learners' better knowledge of L2-specific acoustic cue-weightings, based on which less relevant acoustic information is effectively suppressed.

Nanoparticle-Based Lateral Flow Biosensor Integrated With Loop-Mediated Isothermal Amplification for Rapid and Visual Identification of Chlamydia trachomatis for Point-of-Care Use.

Chlamydial infection, caused by Chlamydia trachomatis, is the most common bacterial sexually transmitted infection and remains a major public health problem worldwide, particularly in underdeveloped regions. Developing a rapid and sensitive point-of-care (POC) testing for accurate screening of C. trachomatis infection is critical for earlier treatment to prevent transmission. In this study, a novel diagnostic assay, loop-mediated isothermal amplification integrated with gold nanoparticle-based lateral flow biosensor (LAMP-LFB), was devised and applied for diagnosis of C. trachomatis in clinical samples. A set of LAMP primers based on the ompA gene from 14 C. trachomatis serological variants (serovar A-K, L1, L2, L3) was successfully designed and used for the development of C. trachomatis-LAMP-LFB assay. The optimal reaction system can be performed at a constant temperature of 67°C for 35 min. The total assay process, including genomic DNA extraction (~15 min), LAMP reaction (35 min), and LFB readout (~2 min), could be finished within 60 min. The C. trachomatis-LAMP-LFB could detect down to 50 copies/ml, and the specificity was 100%, no cross-reactions with other pathogens were observed. Hence, our C. trachomatis-LAMP-LFB was a rapid, reliable, sensitive, cost-effective, and easy-to-operate assay, which could offer an attractive POC testing tool for chlamydial infection screening, especially in resource starvation settings.

Reference database of teeth images from the Family Bovidae

Researchers typically rely on fossils from the Family Bovidae to generate African paleoenvironmental reconstructions due to their strict ecological tendencies. Bovids have dominated the southern African fauna for the past four million years and, therefore, dominate the fossil faunal assemblages, especially isolated teeth. Traditionally, researchers reference modern and fossil comparative collections to identify teeth. However, researchers are limited by the specific type and number of bovids at each institution. B.O.V.I.D. (Bovidae Occlusal Visual IDentification) is a repository of images of the occlusal surface of bovid teeth. The dataset currently includes extant bovids from 7 tribes and 20 species (~3900). B.O.V.I.D. contains two scaled images per specimen: a color and a black and white (binarized) image. The database is a useful reference for identifying bovid teeth. The large sample size also allows one to observe the natural variation that exists in each taxa. The binarized images can be used in statistical shape analyses, such as taxonomic classification. B.O.V.I.D. is a valuable supplement to other methods for taxonomically identifying bovid teeth.

Traditional Chinese Medicine Recognition Based on Target Detection.

Traditional Chinese medicine (TCM) is widely used in China, but the large variety can easily lead to difficulties in visual identification. This study aims to evaluate the availability of target detection models to identify TCMs. We have collected images of 100 common TCMs in pharmacies, and use three current mainstream target detection models: Faster RCNN, SSD, and YOLO v5 to train the TCM dataset. By comparing the metrics of the three models, the results show that the YOLO v5 model has obvious advantages in the recognition of a variety of TCM, the mean average accuracy of the YOLO v5 is 94.33% and the FPS has reached 75, this model has a smaller number of parameters and solves the problem of detection and occlusion for small targets. Our experiments prove that the target detection technology has broad application prospects in the detection of TCM.

Identification of Embodied Environmental Attributes of Construction in Metropolitan and Growth Region of Melbourne, Australia to Support Urban Planning

As growth regions evolve to accommodate the increasing population, they need to develop a wider variety of residential properties to accommodate the varying needs of the residents. As a result, the new accommodation is denser which involves higher embodied water carbon and energy. This research compares the construction differences in metropolitan and growth regions of Melbourne to identify embodied carbon, water, and energy. Representative areas of 25 km2 are selected from both regions. The growth region has 80% of the built area comprised of 2nd generation low-rise residential buildings whereas the prolific construction type in the Metropolitan region is mixed purpose industrial with 30% of the built area comprising of this type. The methodology implies open-source satellite imagery to build a spatial dataset in QGIS. The visual identification of the constructions in the study areas enables to identity the materials used in their construction. The total embodied carbon, water, and energy for the Metropolitan region are 32,895 tonnes, 4192 mL, and 3,694,412 GJ, respectively, whereas in the growth region, the totals are 179,376 tonnes carbon, 2533 mL water, and 2,243,571 GJ. Whilst Metropolitan has a significantly higher overall footprint when this is compared to the population of each region, it is shown that the growth region with its current construction type has a higher embodied carbon, water, and energy per head. The total per head for Metropolitan is 226.7 GJ energy, 257 kL water, and 20 tonnes carbon, whereas in the growth region, the embodied energy, water, and carbon, respectively, per head is 287.4 GJ, 324.6 kL, and 22 tonnes. The current performance per head of the growth region is considerably lower than that of Metropolitan. Using diverse residential construction types and efficient materials can serve the demanding needs of denser populated areas.