Geographic Information System Data Research Articles

Integrated approaches for road extraction and de-noising in satellite imagery using probability neural networks

Remote sensing plays a crucial role in detecting and monitoring natural resources, extending its applications to various fields, such as geography, topographical surveying, and geoscience disciplines, including land management, forest monitoring, crop identification, soil mapping, and ocean resource finding. Road extraction holds significant importance among these applications, contributing to the development of Geographic Information Systems (GIS). The automatic updating of GIS information has become essential in daily life. Road extraction stands out as a prominent application within remote sensing image systems, addressing challenges related to intensity and width. Intensity challenges involve variations in spectral or color values of roads, while width challenges pertain to the issues associated with the size and structure of roads during the extraction process. Addressing the challenges associated with road extraction from remote sensing imagery is crucial for achieving accurate and efficient results. This paper under consideration compares the conventional and contemporary methods of road extraction, emphasizing completeness and correctness metrics. Conventional methods involve techniques like CLAHistogramEqualization for enhancement and fuzzy c-mean clustering for extraction, resulting in incremental improvements. To enhance results further, images are de-noised using Gray World Optimization and iterative domain-guided image filtering. To improve efficiency in road extraction, the authors proposed a contemporary approach through probability neural networks with de-noised images. The comparison is made based on the completeness and correctness of both conventional and contemporary methods.

TELEHEALTH ENHANCES RETENTION OF PATIENTS WITH INFLAMMATORY BOWEL DISEASE WITHIN A TERTIARY CARE INFLAMMATORY BOWEL DISEASE CENTER

Abstract INTRODUCTION Telehealth care in the ambulatory setting has dramatically increased in the COVID and post-COVID period in medicine. Understanding how this may impact the care of patients (pts) with inflammatory bowel disease (IBD) is important. This study aims to evaluate the pattern of use of telehealth care in a tertiary care IBD center. METHODS Pts seen at a tertiary care IBD center from January 2018 to March 2020 and August 2020 to January 2023 were included. Pts seen between March 2020 and July 2020 were excluded as the institution had mandatory telehealth visits during this period. Data was obtained from the Electronic Medical Record after IRB approval. Office visit types were based on billing codes, and office visits were only included in the analysis if seen by an MD or Advanced practice provider (APP). Drive time in minutes (min) was established from pt addresses using Esri geographic information systems (GIS) data, services and software. All new pts seen in the IBD Center are required to be seen in-clinic. After August 2020, pts seen in follow up can be seen at an in-clinic visit or via telehealth at the patient’s preference. Statistical analysis included Pearson Chi Square analysis for categorical variables and z-tests for means comparisons for continuous variables. RESULTS A total of 7,040 pts included. 56% were female. 89% were white, 7% Black or African American, and 76% had commercial health insurance, 17% had Medicare, 4% Medicaid, and 3% had no health insurance. New pts seen in the post-Covid period had shorter drive times than those seen in the pre-Covid period. (Table 1) Pts who had at least one year of follow up were more likely to be seen as a return visit in the post-Covid period vs the pre-Covid period (84% vs 76%, p<0.05). In the post-Covid period, 62% (3,575/5,750) pts had return IBD care by their MD or APP team delivered via telehealth. Pts seen in telehealth had significantly longer drive times than in-clinic-only pts (median 56.3 min [IQR 93.3] vs median 47.9 min [IQR 89.7]), p<0.001. (Table 2) This was significant for both the telehealth pts who had been seen in-clinic in the pre-Covid period as well as pts who were seen only in the post-Covid period. Pts who continued care only with in-clinic visits in the post-Covid period had significantly shorter drive times than pts who were seen in-clinic pre-Covid (38.8 min [IQR 60] vs 54.2 min [IQR 89.9]), p<0.001. CONCLUSION Telehealth is an effective strategy for continued multidisciplinary care at a tertiary care IBD center. More than half of patients continuing to participate in telehealth for follow up care, and patients were more likely to follow up in the post-Covid period. Patients who live farther away are more likely to continue IBD care via telehealth. Table 1 Overall Drive Time for New patients in the Pre- and Post-COVID periods Table 2 Drive Times for Return patients in the Pre-Covid and Post-Covid periods

Road networks and socio-demographic factors to explore COVID-19 infection during its different waves

The COVID-19 pandemic triggered an unprecedented level of restrictive measures globally. Most countries resorted to lockdowns at some point to buy the much-needed time for flattening the curve and scaling up vaccination and treatment capacity. Although lockdowns, social distancing and business closures generally slowed the case growth, there is a growing concern about these restrictions' social, economic and psychological impact, especially on the disadvantaged and poorer segments of society. While we are all in this together, these segments often take the heavier toll of the pandemic and face harsher restrictions or get blamed for community transmission. This study proposes a road-network-based networked approach to model mobility patterns between localities during lockdown stages. It utilises a panel regression method to analyse the effects of mobility in transmitting COVID-19 in an Australian context, together with a close look at a suburban population’s characteristics like their age, income and education. Firstly, we attempt to model how the local road networks between the neighbouring suburbs (i.e., neighbourhood measure) and current infection count affect the case growth and how they differ between delta and omicron variants. We use a geographic information system, population and infection data to measure road connections, mobility and transmission probability across the suburbs. We then looked at three socio-demographic variables: age, education and income and explored how they moderate independent and dependent variables (infection rates and neighbourhood measures). The result shows strong model performance to predict infection rate based on neighbourhood road connection. However, apart from age in the delta variant context, the other variables (income and education level) do not seem to moderate the relationship between infection rate and neighbourhood measure. The results indicate that suburbs with a more socio-economically disadvantaged population do not necessarily contribute to more community transmission. The study findings could be potentially helpful for stakeholders in tailoring any health decision for future pandemics.

The role of BIM and GIS in HS2 historic environment data management, an overview of HS2 Phase 1, UK

The HS2 historic environment programme undertaken for Phase One of HS2 between London and the West Midlands has resulted in a substantial digital archive, including Geographic Information Systems (GIS) data. According to the BIM (Building Information Modelling) approach, HS2 historic environment assets are considered as part of the construction assets, alongside the other disciplines assets such as highways, bridges, tunnels, and fencing. The GIS and spatial data play the role of a glue to demonstrate the interrelationship and hierarchy between archaeological assets, recording their location and geometry. Designating a unique asset ID (UAID) to each archaeological asset, and joining them to their attributes table and relating documents, creates a relationship between historic environment assets GIS data and their respective non-GIS data. According to HS2 digital engineering with BIM approach, HS2 historic environment core and primary assets have been identified, which the hierarchical order of them is as follows: Location Specific Written Scheme of Investigation (LS-WSI) and Project Plans (PPs) as core assets, and Written Scheme of Investigation Interventions (WSI-Interventions), Archaeological Features, and Archaeological Objects as historic environment primary assets. Such an efficient, transparent, and readable asset data structure provides a lasting and valuable legacy for the lifecycle of the project digital data. Four different systems combine to form the digital legacy of the project, which complement the physical archive. These four systems are: HS2 Asset Information Management System (AIMS) and GIS systems, as well as Online Access to the Index of Archaeological Investigations (OASIS), and supporting digital data curated with the Archaeological Data Service (ADS) systems. As significant parts of the programme legacy, HS2's historic environment physical and digital archive establish an unprecedented opportunity for knowledge creation.

Exploring the relationship between the food environment and preferences among schoolchildren in a low socioeconomic community in Sri Lanka: A GIS-based assessment.

The food environment in school neighborhoods plays a crucial role in manipulating the food choices of schoolchildren. This study investigated the relationship between the food environment in neighborhoods and the dietary practices of government school students in a low socioeconomic setting in Sri Lanka. This cross-sectional study surveyed the neighborhood food environment of selected schools (n = 30) in the Monaragala District, Sri Lanka, using geographical information system (GIS) data and collected dietary information from a representative sample of schoolchildren (n = 603). Chi-square and Spearman correlation tests were performed using SPSS version 23.0 to estimate the associations between the food environment and BMI, while ArcGIS 10.4.1 was used to analyze the GIS data. The majority of the students (35.5%) were 15 years old, and approximately 51% were females. The mean BMI of the study participants was 18.14 (±3.28). More than 90% of outlets within proximity sold unhealthy foods. Consumption of confectionaries was 72.3% of the students, whereas healthy food choices ranged from 5% to 12%. A positive correlation between consuming unhealthy food and distance to outlets from school was observed (p<0.05). The risk of consuming low-nutrition food doubled (OR = 2.47, 95% CI: 1.52-3.89) among the students studying in schools where a larger proportion of energy-dense food was sold in closer proximity. In conclusion, the density and proximity of outlets that sell food with low nutrients in the school neighborhood environment were positively associated with students' unhealthy food item choices.

The spatiotemporal evolution of rural landscape patterns in Chinese metropolises under rapid urbanization.

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided.

Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina.

Estuarine water quality is declining worldwide due to increased tourism, coastal development, and a changing climate. Although well-established methods are in place to monitor water quality, municipalities struggle to use the data to prioritize infrastructure for monitoring and repair and to determine sources of contamination when they occur. The objective of this study was to assess water quality and prioritize sources of contamination within Town Creek Estuary (TCE), Beaufort, North Carolina, by combining culture, molecular, and geographic information systems (GIS) data into a novel contamination source ranking system. Water samples were collected from TCE at ten locations on eight sampling dates in Fall 2021 (n = 80). Microbiological water quality was assessed using US Environmental Protection Agency (U.S. EPA) approved culture-based methods for fecal indicator bacteria (FIB), including analysis of total coliforms (TC), Escherichia coli (EC), and Enterococcus spp. (ENT). The quantitative microbial source tracking (qMST) human-associated fecal marker, HF183, was quantified using droplet digital PCR (ddPCR). This information was combined with environmental data and GIS information detailing proximal sewer, septic, and stormwater infrastructure to determine potential sources of fecal contamination in the estuary. Results indicated FIB concentrations were significantly and positively correlated with precipitation and increased throughout the estuary following rainfall events (p < 0.01). Sampling sites with FIB concentrations above the U.S. EPA threshold also had the highest percentages of aged, less durable piping materials. Using a novel ranking system combining concentrations of FIB, HF183, and sewer infrastructure data at each site, we found that the two sites nearest the most aged sewage infrastructure and stormwater outflows were found to have the highest levels of measurable fecal contamination. This case study supports the inclusion of both traditional water quality measurements and local infrastructure data to support the current need for municipalities to identify, prioritize, and remediate failing infrastructure.

Structural and Stratigraphic Study of Hazara-Kashmir Syntaxis with the Aid of Geographic Information System and Field Data Approach

Abstract This research area is located along the Hazara-Kashmir Syntaxis in the sub-Himalaya. The Hazara-Kashmir Syntaxis runs through numerous areas within Mirpur district. One of the key characteristics of the Hazara-Kashmir Syntaxis is its antiformality. The project area is bounded to the east by the Riasi fault and to the west by the Jhelum fault, while to the south it is bounded by Salt Range Thrust. Research is being conducted in the areas of Narmah, Sahan, Pirgali, Kas Guma, Mohra Jangu, and Kalri. Fold-and-thrust belts are present in the sub-Himalayan region ofPakistan. Essentially, there are two major folds: the Sahan syncline and the Gaiyan anticline. The Sahan syncline is characterized by an open fold and a southwest orientation. In contrast, open-to-close folds in Gaiyan anticlines are oriented to the southwest. The area is characterized by five major faults: the Narmah fault, the Dhok Poran fault, the Dubal fault, the Pirgali fault, and the Jabi fault. Folds and faults in the project area are the product of NE-SW or NW-SE compaction of the Himalaya. In the research project area sedimentary rocks of Early Miocene- Recent age are located. The rocks which are exposed in the study area includes: the Early-Middle Miocene Kamlial Formation, Middle-Late Miocene Chinji Formation, Late-Miocene Nagri Formation, Late-Miocene Dhok Pathan Formation, Pliocene Soan Formation, and Quaternary Alluvium deposits. Sedimentary structures in the area consist primarily of crossed bedding and rip-ups. These structures define the facing of stratigraphic units.

Spatial Analysis to Determine Black Spot Area in Kulon Progo Regency, Yogyakarta, Indonesia

Nowadays the number of traffic accidents increase due to the surging volume of road traffic. The efforts to reduce number of accidents is important, especially to identify the location and causes the accidents. Therefore, this study aims to identify black spot areas, which are areas with a high concentration of traffic accidents, in Kulon Progo Regency in Yogyakarta, Indonesia. The method used is spatial analysis by combining analysis of traffic accident data and geographic information system (GIS) data using ArcGIS software. The study focused on provincial road consist of primary collector 2 and 3, as well as national road segments. The analysis of accident data allowed the identification of hotspots where accidents occur most frequently. Hotspot analysis methods such as Local Statistic Analysis and Kernel Density Estimation were used to assess the spatial patterns and clustering of accidents. The study found that the black spot area in Kulon Progo Regency was mainly concentrated on the National Road Segment, with fewer occurrences on the Provincial Road with function of Primary Collector 2 and minimal presence on the Primary Collector 3 Road Segment. This result can be used to develop strategies to mitigate accidents and improve road safety in the area.

Automated Correction of GIS Data for Loads and Distributed Energy Resources in Secondary Distribution Networks

Currently, utilities are making significant efforts to correct their secondary models in geographic information systems (GISs) to capture the distribution system performance due to the increased penetration of distributed energy resources (DERs) such as renewable energy resources, distributed energy storage, and electric vehicles (EVs). However, their databases are often not reliable in terms of GIS coordinates of elements such as loads and DERs resulting in an approximate representation of the secondary distribution network. This paper presents an automated tool for accurate secondary network topology GIS coordinates correction. The proposed automated tool provides a more accurate feeder topology for utilities to estimate and operate distribution systems by assigning the load and DER nodes to their corresponding customer location. To simplify the complexity of the proposed new tool, only two commonly available inputs are being used as input data: municipal parcel GIS delimitation data, and utility secondary feeder topology database. A three-stage framework is proposed to develop the automated tool: the first stage reads and processes the raw input data; the second stage works automatically with no human intervention to assign the load and DER nodes to their associated location; the third stage provides the load and DER coordinates and physical address. The proposed procedure is implemented on an actual feeder from an electrical utility with high penetration of DERs.The results show that the proposed method provides a more accurate estimation of the topology of the feeder in terms of coordinates.

Landslide Susceptibility Mapping using Geographic Information System (GIS) and Remote Sensing Data in North Luwu, South Sulawesi Province, Indonesia

Climate, topography, and rock conditions in Indonesia are relatively diverse, both physical and chemical, these conditions can cause adverse consequences such as floods, landslides, forest fires, and droughts. The Information from Volcanology and Geological Disaster Mitigation on Monday, July 13, 2020, flash floods and flow of debris due to landslides have occurred in Masamba and Baebunta, North Luwu, South Sulawesi Province. The purpose of this paper is to map the distribution of landslide susceptibility area using remote sensing and GIS data. The Method used to analyze the landslide susceptibility estimation model refers to the Indonesian Center for Agricultural Land Resources Research and Development (ICALRD). The parameters used in this model are rainfall, soil type, rock type, slope, land use, and land movement. The ICALRD Landslide Susceptibility Estimation Model in study area shows that there are three classes of landslide susceptibility, such as low, medium, and high susceptibilities. There are six subdistricts which are in medium to high landslide susceptibility, and the others are low to medium landslide susceptibility. The locations of landslides and flash floods that occurred in Masamba and Baebunta indicate areas with medium to high landslide susceptibility.

Insight into land cover dynamics and water challenges under anthropogenic and climatic changes in the eastern Nile Delta: Inference from remote sensing and GIS data

The destabilization of delta's worldwide due to climate change and human activities presents challenges in meeting the growing demands for freshwater and food. The Nile Delta in Egypt is a prime example of a vulnerable region facing various stressors. In order to preserve land and water resources, it is crucial to monitor the spatial and temporal changes in Land Use/Land Cover (LULC), shoreline, and Terrestrial Water Storage (TWS) in these vulnerable regions This study comprehensively investigates the dynamic changes in LULC and their associated water and soil responses in the Eastern Nile Delta under these combined impacts. To achieve this goal, a combination of remote sensing techniques utilizing Landsat (5, 8, and 9), and GRACE datasets, along with field observations and Geographic Information System (GIS) tools, was employed. Accordingly, shoreline changes show coastal erosion rates ranging from 5.28 to 34.92 m/year due to climate change-induced SLR, with continued inland movement predicted for the next 20 years. Moreover, the dynamic changes in urbanization and alterations in agricultural cover have considerable penalties for water demand. Analysis of GRACE data indicates a notable reduction in average TWS by 77.89 mm between 2002 and 2017, with an annual rate, estimated at −5.821 mm/year. Soil sampling in highly vulnerable areas confirms agricultural degradation attributed to elevated salinity levels, with EC values ranging from 3.60 to 190 ds/m. These finds provide valuable insights for stakeholders and policymakers, to make reliable strategies regarding water allocation, land use regulations, and climate change adaptation in the worldwide vulnerable deltas.

Управление устойчивостью аграрного землепользования на локальном уровне с использованием ГИС-технологий и специального картографического материала

The purpose of the study: analysis of geoecological factors and conditions affecting the sustainability of agricultural land use in the forest-steppe zone of the Altai Krai and its assessment. Research methods: The main scientific method of this study was system analysis, which was used to study the agricultural landscape management system. Methods of analysis and synthesis were used to identify structural units of land management, structuring the land information system (LIS) and special cartographic material, as well as studying the structure of agricultural landscapes. We also used the cartographic method in the design of unique map diagrams and information analysis in modeling agricultural land use. Research results. Based on the results of a long-term assessment of the sustainability of three agricultural land uses located in different natural and climatic zones, the conditions and factors that form the basis of the agricultural land use management system using GIS technologies were established. We found out that in order to manage the sustainability of agricultural landscapes, the mandatory information layers included in the data bank of a geographic information system (land information system) must include the following special cartographic materials: maps (scale 1:10000 or 1:25000) – landscape, soil, slope steepness, erosion, types of areas, tracts, lands, as well as the geomorphological profile of the surface. By processing materials with an information system, it is possible to implement at least 10 models for managing the sustainability of agricultural land use, which involve varying the structure of lands, lands, crop rotations, a set of crops, farming systems, a list of agro-, phyto-, reclamation techniques and measures aimed at achieving ecological and economic balance and, as a consequence, the efficiency of use of land resources. Conclusions. 1. Based on long-term spatio-temporal studies of agricultural landscapes of agricultural enterprises, a mandatory set of special cartographic materials of the geographic information system data bank has been determined, aimed at managing the sustainability of agricultural land use. 2. Using unique cartographic materials as an example, the possibility of modeling management scenarios in different natural conditions, characterized by different stability and efficiency, is shown. Modeling of agricultural land use makes it possible to determine capital investments and economic costs (economic and agronomic sustainability) when implementing the selected model, created on the basis of an analysis of the limiting factors of the territory. 3. The results of scientific research can be used in managing the sustainability of agricultural land use at the level of a municipal district and agricultural organization.

Cultural context index: A geospatial measure of social determinants of health in the United States

Minority populations will continue to grow in the United States. Such pluralism necessitates iterative, geospatial measurements of cultural contexts. Our objective in this study was to create a measure of social determinants of health in geographic areas with varying ethnic, linguistic, and religious diversity in the United States. We extracted geographic information systems data based on community characteristics that have known associations with population health disparities from 2015 to 2019. We used principal component analysis to construct a Cultural Context Index (CCI). We created the CCI for 73,682 census tracts across 50 states and five inhabited territories. We identified hot and cold spots that are the highest and lowest CCI quintile, respectively. Hot spots census tracts were mostly located in metropolitan areas (84.8%), in the Southern census region (41.5%), and also had larger Black and Hispanic populations. The census tracts with the greatest need for culturally competent health care also had the sickest populations. Census tracts with a CCI rank of 5 (‘greatest need’) had higher prevalences of self-reported poor physical health (17.2%) and poor mental health (17.4%), compared to either the general population (13.9% and 14.5%) or to CCI rank of 1 (‘lowest need’) (11.9% and 10.8%). The CCI can pinpoint census tracts with a need for culturally competent health care and inform supply-side policy planning as healthcare and social service providers will inevitably come in contact with consumers from different backgrounds.

Geographical information system-based prevalence analysis of children’s leukemia in southwest Iran

Background. Climatic and geomorphological characteristics of a region are vital factors in the regional spread of diseases. Geographic Information System (GIS) is a useful tool for studying cancer epidemiology. This study was conducted with the aim of investigating the prevalence of childhood leukemia in Khuzestan based on 10-year GIS data of temperature, wind speed and dust level. Methods. The medical characteristics of all cases of leukemia in children admitted to Bagai 2 Ahvaz Hospital, which were diagnosed with leukemia for the first time. We collected what was diagnosed. Results. Five hundred and twelve children had acute lymphoblastic leukemia (ALL) and 100 children had acute myeloblastic leukemia (AML). The year 2015 had the highest and the year 2018 the lowest ALL rate. The peak of AML was in 2013 and the lowest was in 2018. Central cities had the highest mean particulate matter, temperature, wind speed, and the highest rate of leukemia. Conclusion. The results show that dust, temperature and wind speed are related to the prevalence of childhood leukemia in Khuzestan, Iran. Practical Implications. A wide range of environmental and genetic factors can play a role in the occurrence of cancer, so additional studies are needed to confirm the effect of particles and environmental factors such as temperature and dust on the occurrence of cancer.

ANALISIS ZONASI KAWASAN RESAPAN AIR DI KECAMATAN KWANDANG KABUPATEN GORONTALO UTARA

The research aims to determine the zoning of water catchment areas in Kwandang District and find out how appropriate the use of regional spatial planning is in water catchment areas in Kwandang District. This research emphasizes a spatial approach. Analyze the variables to be studied using the overlay method with Geographic Information System (GIS) software and data scoring to identify water catchment areas. The zoning of water catchment areas in Kwandang District can be divided based on the classification of natural infiltration potential, namely large, medium and small natural infiltration potential. Medium natural infiltration potential has the largest area of around 17375.17 Ha or 88.61% of the total water catchment area, large natural infiltration potential has an area of 2201.21 Ha or around 11.23%, while small infiltration potential has the smallest area, namely 31.64 Ha or around 0.16% of the water catchment area in Kwandang District. Water catchment areas that have small and moderate natural infiltration in terms of space use can be used for the construction and development of cultivation areas, while water catchment areas that have large natural infiltration are recommended for use of space as protected areas.&#x0D; Keyword: Zoning; Water infiltration; Kwandang district.

Evaluation of spatial patterns accuracy in identifying built-up areas within risk zones using deep learning, RGB aerial imagery, and multi-source GIS data

In the presence of natural disasters that increasingly affect urban centers, innovative methodologies that can support all the subjects and bodies involved in the disaster management system are increasingly important. This task can be enhanced in urban settings by automatically assessing at-risk buildings through satellite and aerial imagery. However, creating and implementing models with robust generalization capabilities is crucial to achieving this goal. Based on these premises, the authors proposed a deep learning approach utilizing the U-Net model to map buildings within known landslide-prone areas. They trained and validated the U-Net model using the Dubai Satellite Imagery Dataset. The model's prediction accuracy in adapting its results to urban environments in Italy, different from those involved in the training and validation stages, was tested using natural color orthoimages and diverse geographic information system (GIS) data sources. The outcomes indicate that the model's predictions are better in contexts with denser urban fabric. The level of accuracy in dispersed urban shapes worsens as building footprints cover a small portion of the total image area. Overall, the results demonstrate that the suggested methodology can effectively identify buildings in landslide risk zones, demonstrating noteworthy adaptability, making the proposed platform a tool that can be instrumental for decision-makers and urban planners in pre-disaster and post-disaster stages.

Assessment of Typical Meteorological Year Data in Photovoltaic Geographical Information System 5.2, Based on Reanalysis and Ground Station Data from 147 European Weather Stations

The Photovoltaic Geographical Information System (PVGIS) is a web application that provides free access to solar radiation and temperature data, typical meteorological year (TMY) data, and to photovoltaic performance assessment tools for any place in most parts of the world. The PVGIS was originally developed over 20 years ago, and since then, it has been under continuous development. At present, there are two versions of the PVGIS online—the older version 5.1 and the newest version 5.2. PVGIS 5.2 includes substantial improvements compared to the previous version, e.g., the update of the underlying data sets both in terms of quality, resolution, and geographical coverage and the extension of the time period used. This paper focuses on comparing the TMYs (and more specifically the TMY time series of air temperature), coming from both PVGIS 5.1 and 5.2, with the TMY produced on the basis of ground station meteorological data and with the ground station data itself. The results show that whereas overall the errors and biases for most locations are within the expected range (mean stationRMSE 4.27), these differences increase in places with complicated topography, e.g., in the Alps (maximum stationRMSE 9.50).

Evaluating urban land-use demarcation and implementation for various urban functions using GIS and survey-based data: The case of Abuja City, Nigeria

Urban planning implementation is a crucial process of urban planning to improve, attain, and maintain urban sustainability globally. However, the implementation process for land use demarcated for various urban functions is being confronted by various challenges in the Global South. This study aims to integrate questionnaire surveys of urban and regional planning experts and Geographic Information Systems (GIS), in order to investigate the level of urban planning implementation of land use demarcated for various urban functions to support strategic actions for urban sustainability. Using Abuja, Nigeria, as a case study, an urban plan, urban impervious surface map, and questionnaire data were collected, and an integrated method analysis, including qualitative and quantitative (descriptive, Euclidean Distance Modelling, and Linear Regression Modelling) was deployed. Key findings show that the vast majority of experts in urban and regional planning perceive the implementation of all land use for various urban functions to be between moderate and very high levels, except that of industrial land use perceived to be between moderate and low levels. GIS findings show that, while land uses demarcated for transportation, commercial, educational, and institutional functions are positively and significantly associated with the urban impervious surface, industrial land use and urban green spaces are negatively associated. Findings show that abuse of official privileges by distorting master plans, political interference, compromise by public servants, and inadequate funding are key challenges for urban planning implementation on land use demarcated for various urban functions. The findings in this study are crucial for strategic decision makers in urban planning to improve the implementation process for various urban land-use functions and urban sustainability in the Global South, in general, and in sub-Saharan Africa, in particular.

Geographies of landscape aesthetics: mapping landscape terminology in digitised historical travel accounts of Loch Lomond and the Trossachs

ABSTRACT This study spatially analyses aesthetic terms in historical travel accounts of the landscapes of Loch Lomond and the Trossachs from the eighteenth to the twentieth century. We applied a hybrid approach, combining qualitative methods of textual analysis with quantitative techniques of a Geographical Information System (GIS), to a corpus of 38 digitised works featuring a range of historic guidebooks and travelogues. To identify relationships between place names, landscape features and the aesthetic terms beautiful, magnificent, picturesque, romantic and sublime, we first analysed how these terms occurred together in the text. We also used digital terrain model data in GIS to explore relationships between the aesthetic terms and the elevation of place names and landscape features. The results provide evidence that the aesthetic terms magnificent and sublime were applied to describe places and landforms at higher elevations, whilst beautiful, picturesque and romantic were applied to lower-lying regions of the Loch Lomond and the Trossachs landscapes. Our findings illustrate how the cartographic capabilities of GIS, combined with text analysis, can shed light on how landscapes were historically represented in travel literature.