Geographic Information System Model Research Articles

GIS-Based Urban Flood Risk Assessment and Management—A Case Study of Delhi National Capital Territory (NCT), India

Urban floods are very destructive and have significant socioeconomic repercussions in regions with a common flooding prevalence. Various researchers have laid down numerous approaches for analyzing the evolution of floods and their consequences. One primary goal of such approaches is to identify the areas vulnerable to floods for risk reduction and management purposes. The present paper proposes an integrated remote sensing, geographic information system (GIS), and field survey-based approach for identifying and predicting urban flood-prone areas. The work is unique in theory since the methodology proposed finds application in urban areas wherein the cause of flooding, in addition to heavy rainfall, is also the inefficient urban drainage system. The work has been carried out in Delhi’s Yamuna River National Capital Territory (NCT) area, considered one of India’s most frequently flooded urban centers, to analyze the causes of its flooding and supplement the existing forecasting models. Research is based on an integrated strategy to evaluate and map the highest flood boundary and identify the area affected along the Yamuna River NCT of Delhi. In addition to understanding the causal factors behind frequent flooding in the area, using field-based information, we developed a GIS model to help authorities to manage the floods using catchment precipitation and gauge level relationship. The identification of areas susceptible to floods shall act as an early warning tool to safeguard life and property and help authorities plan in advance for the eventuality of such an event in the study area.

Invisible informality and the contribution of information modeling to data-based urban regulation

Recent studies have established the role of urban planning policies in feeding the growth of informal settlements in Brazilian cities, through the socio-spatial exclusion of low-income residents. The difficulties of reversing this exclusionary logic are due to several complex factors. A factor less discussed in Brazilian literature, which has began to draw the attention of scholars, is the invisibility of the informal city. This research assumes that it is necessary to regulate the urban form of precarious informal settlements, in order to prevent the deterioration of urban environmental quality. We highlight the importance of compiling data about their urban form and their built environment, in order to contribute to a reality-based regulatory policy for these settlements. After discussing the phenomenon of urban informality in Fortaleza, we applied a methodology that combines Geographic Information Systems (GIS) and City Information Modeling (CIM), to support the redefinition of urban rules for precarious settlements of informal origin. This procedure will reveal not only the extent of the inadequacies of the (past and current) land use and occupation codes, but will also present some potentialities of GIS and CIM to inform its redefinition.

PRIORITIZATION OF FOREST FIRE HAZARD RISK SIMULATION USING HYBRID GREY RELATIVITY ANALYSIS (HGRA) AND FUZZY ANALYTICAL HIERARCHY PROCESS (FAHP) COUPLED WITH MULTICRITERIA DECISION ANALYSIS (MCDA) TECHNIQUES – A COMPARATIVE STUDY ANALYSIS

Forests are important dynamic systems which are widely attracted by wild fires worldwide. Due to the complexity and non-linearity of the causative forest fire problems, employing sophisticated hybrid evolutionary algorithms is a logical task to achieve a reliable approximation of this environmental threats. This estimate will provide the outline of priority areas for preventing activities and allocation of fire fighters’ stations, seeking to minimize possible damages caused by fires. This study aims at prioritizing the forest fire risk of Wassa West district of Ghana. The study considered static causative factors such as Land use and land cover (which include forest, built-ups and settlement areas), slope, aspect, linear features (water bodies and roads) and dynamic causative factors such as wind speed, precipitation, and temperature were used. The methods employed include a Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) techniques. The fuzzy sets integrated with AHP in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. FAHP and HGRA methods were used for estimating the importance (weights) of the effective factors in forest fire modelling. Based on their modelling methods, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas were analyzed based on FAHP and HGRA. The major criteria models and fire risk model were presented based on these FAHP and HGRA weights. On the other hand, the spatial data of the sub criteria were provided and assembled in GIS environment to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risks of its classes to fire occurrence. The maps of each major criterion were obtained by weighted overlay of its sub criteria maps considering to major criterion model in GIS environment. Finally, the map of fire risk was obtained by weighted overlay of major criteria maps considering to fire risk model in GIS. The results showed that the FAHP model showed superiority than HGRA in prioritizing forest fire risk of the study area in terms of statistical analysis with a standard deviation of 0.09277 m as compared to 0.1122 m respectively. The obtained fire risk map can be used as a decision support system for predicting of the future trends in the study area. The optimized structures of the proposed models could serve as a good alternative to traditional forest predictive models, and this can be a promisingly testament used for future planning and decision making in the proposed areas.

Applying the Soil and Water Assessment Tool Model for Integrated Lake Basin Management in Northern Vietnam: Case Study of the Thac Ba Reservoir Basin

Recent land use changes in the form of deforestation, agricultural development, industrialization, and urbanization have caused water quality and quantity problems in many watersheds in Vietnam necessitating the development of appropriate policy interventions. This research explores the possibility of using a coupled Geographic Information System and hydrological model (Soil and Water Assessment Tool [SWAT]) to assess the impact of land use changes on stream flows in the Thac Ba reservoir basin in the Northern Vietnam in three different land use change scenarios: expansion of forest lands, return to the nature, and expansion of the urban area. The Nash-Sutcliffe Efficiencies of 0.895 and 0.869 were obtained after the calibration and validation processes, respectively. The nutrient and sediment loadings are currently being assessed pending the acquisition of observed data and model calibration. Further studies will be conducted to have a look at the likely effects of climate changes on the water quality and quantity of the Thac Ba reservoir as well as providing an insight of how the SWAT model for the Thac Ba reservoir basin can be applied to the much larger and nationally more important basin, the HoaBinh reservoir basin which provides drinking water to the capital Hanoi. According to the scenarios of land use change conditions, an increasing trend in stream flow may be expected in the next decades caused by increasing rainfall amounts. Therefore, flooding and the reduced reservoir capacity are major problems in the target area, and there must be improvement of watershed management by applying the Integrated Lake Basin Management concept.

Probabilistic Analysis of the Obstruction of Water Sources Due to the Occurrence of Rainfall-Triggered Mass Movements

This paper presents a methodology for the probabilistic estimation of the obstruction of water streams generated by shallow mass movements triggered by rainfall. The study focuses on the Ovejas River, a tributary stream of the Medellín River, in the jurisdiction of the municipality of San Vicente in the department of Antioquia (Colombia). The occurrence of a mass movements was evaluated by deterministic and probabilistic methods based on the automation of processes of Geographic Information Systems (GIS) and spatial modeling. The spatial distribution of the mass movement hazard was estimated in terms of Factor of Safety (FoS) values by the deterministic method with physical basis SLIDE (Slope - Infiltration - Distributed Equilibrium), which allows the hazard zonation by calculating a FoS for rainfall-induced mass movements with different return periods. The rainfall regimes of the study area are estimated by means of a simple scaling Log Normal Model. On the other hand, the Probability of Failure (PF) analysis was performed under Rosenblueth’s punctual estimates method (PEM), which allows incorporating the uncertainty of the soil parameters. Subsequently, the resulting zones with high hazard that could detach and reach the Ovejas River channel are identified as sources for runout modeling by means of the Flow R model, thus estimating the extent of mass movement in probabilistic terms. In all the analyzed scenarios, the sliding material from the critical stability zones has a high probability of spreading to the riverbed of the main river. This analysis makes possible to identify those areas of the riverbed that should be analyzed with more detail and require possible intervention for the protection of the riverbed.

Species distribution modelling of Calamus floribundus Griff. (Arecaceae) using Maxent in Assam

The present work examines the potential habitat distribution of Calamus floribundus using the Maxent model in Geographic Information System(GIS) in Assam. For the prediction, 19 bioclimatic variables downloaded from the worldclim website are used. Landuse (MODIS MCD12Q1 Version 6), aspect and slope data are also used for a better prediction. The model used a Jackknife test to identify the significant environmental variables for the prediction. The predictive model shows a highly significant AUC validation statistics of 0.96. Such predictions could be used to conserve the species in present and future climatic scenarios. The present communication also deals with ecology, local uses and the current distribution of the species. A taxonomic description is also added along with photographs for easy identification.

A combined approach for flood hazard assessment using hydrological, hydraulic and GIS modeling case study of El Hamiz Wadi, Algeria

Flood hazard is one of the most destructive natural phenomena causing a significant material damage and human losses in Algeria during the past decade. The aim of this study is to assess and characterize the flood hazard in El Hamiz watershed (Algeria). In addition, this study identifies areas and elements prone to this hazard to minimize the damages and losses. The methodology used in the present study is based on a combination of hydrological and hydraulic modeling using the Hec-Ras software and mapping techniques using a Geographic Information System (GIS). The flood hazard assessment model of El Hamiz wadi using different hydrological (rainfall / runoff transfer and return period), hydraulic (water level and flow velocity) and exposure (land use data and socio-economic data) parameters revealed that the downstream part of the studied area is the most susceptible to flood events. The mapping of flood-prone areas indicated the extent of this phenomena on the El Hamiz wadi banks, especially through heavy submersion of residential areas characterized by a high urban concentration including inhabitants, activities and infrastructures.

RootTarget: A dynamic model enabling the targeted application of plant growth regulators for rice

Societal Impact StatementThe rising global population and the increasingly conspicuous effects of climate change are putting growing pressure on the agricultural industry. Food production must increase significantly with little or no access to extra land; therefore, new approaches are urgently required to increase crop productivity. The strategic application of plant growth regulators is one method of achieving this, made possible by RootTarget. RootTarget maps regional land use and resource availability, identifying locations where crops could benefit from the application of plant growth regulators. Such targeted application can contribute to creating a more resilient and sustainable farming system.Summary Developing novel strategies for optimising crop productivity is essential to meet the requirement of doubling food production by 2050. Geographic information system (GIS) software provides the opportunity to develop models for targeted application of plant growth regulators in rice‐growing regions based on water availability and agricultural practices, in order to optimise yields. GIS was used to identify rice‐growing areas with adequate irrigation, a high evapotranspiration index or suitable sowing technique for site‐specific application of plant growth regulators. Rule‐based decisions were incorporated into a GIS model in order to identify key areas where plant growth regulators should be applied. This approach allows information sharing between multiple stakeholders including researchers, companies and farmers with the aim of maximising crop productivity. A root growth promoter (RGP) was identified that promotes root growth under optimum conditions but not when applied concurrently with a drought stress. The effect of the RGP diminishes as the severity of the stress increases. These data were used to execute queries to identify regions with a suitable drought index, growing practice and adequate irrigation. Two hundred and twenty‐nine million hectares of land, spanning four continents, were identified as having the potential to benefit from application of the RGP. Significant areas of land used for rice production were identified that could benefit from application of the RGP. This study highlights the potential to incorporate academic research into models for research dissemination to the agricultural industry and increase crop productivity.

Modeling electricity consumption patterns during the COVID-19 pandemic across six socioeconomic sectors in the State of Qatar

The propagation of the COVID-19 pandemic, and the associated measures taken by many countries to slow down the spread of the disease, has significantly affected all aspects of people's lives, including the global energy sector. This study aims to investigate the impact of the pandemic on the spatial patterns of electricity consumption in six socioeconomic sectors (residential (villa and flat), industrial, commercial, government, and productive farms) in the State of Qatar. The spatiotemporal patterns of electricity consumption have been assessed using various Geographic Information Systems (GIS) and spatial statistical modeling prior and during the pandemic. The results demonstrate variations in electricity consumption within and between the six sectors. The main changes in the electricity consumption within sectors during the pandemic year is during the lockdown phase. Spatially, some sectors are affected by the pandemic, and hence the pattern and the spatial and temporal distribution of electricity consumption has changed during the pandemic year compared to pre-pandemic years. The results also show that there were variations of spatial clustering of electricity consumption among these sectors. Most of the high-high clustering patterns are located in the mid-eastern and northeastern parts of Qatar. The highest variation in electricity consumption between sectors occurred in the productive farms due to its massive development during the pre-pandemic period and were not affected by the pandemic. There is a sharp decline in electricity consumption in both the industrial and commercial sectors during the pandemic year. Other sectors witnessed an increase in electricity consumption during the summer months, which was mainly due to travel restrictions imposed by many countries around the world. This analysis is vital for policymakers to detect the changes in electricity consumption patterns in the context of emergencies such as the pandemic.

GIS-based approach for morphometric characteristics and development of hydrographs for the upper watershed of Jebba Reservoir, Nigeria

Nigeria's Jebba sub-basins are synonymous to frequent flooding, high rate of erosion, depletion of soil nutrients and unsustainable water use. The uncontrolled flooding may be a result of numerous factors related to topography, geology, climate and human activity. The present work was an attempt to describe the application of Geographical Information System (GIS) and Digital Elevation Model (DEM) for the estimation of morphometric characteristics of eight sub-basins in the upstream watershed of Jebba reservoir, Nigeria. Morphometric characteristics such as topographic, areal, relief and network were determined. Soil Conservation Service (SCS) technique was applied to estimate hydrographs. The study revealed that sub-basin number 3 had the lowest time of concentration and maximum depth of runoff while sub-basin number 2 had maximum ratio of circulation of 1.8 and it is tagged as the area that is highly prone to flood. The peak runoff in the sub-basins ranged between 330.10 and 924.86 m3/s (25-year return period) and for 100-year intervals ranged between 502.69 to 1408.40 m3/s. The estimated peak runoffs can be adopted for designing and constructing erosion control structures in the catchment area.

An Approach toward Integrated Management for Wadi Haseeb Watershed using Remote Sensing GIS and Hydrological modeling System, East Khartoum, Sudan

This study has been conducted in Wadi Haseeb Watershed, which originates from the upland in South East of Khartoum State. It descends in the North West direction to the confluence with the Blue Nile. The objective of this study was to specify an integrated management strategy to harness the potentiality of the watershed for sustainable agricultural purposes. An integrated approach of remote sensing (RS), geographic information system (GIS), hydrologic engineering center geospatial hydrologic modeling extension (HEC-GeoHMS) and hydrologic modeling system (HMS4.0) was performed to develop a daily rainfall-runoff model. The watershed was delineated and divided into four basins yielding an average water volume of 23 million cubic meters month-1. The results indicated that the first scenario needed 48 MCM month-1 whereas watershed discharge was 23 MCM month-1 with a deficit of 25 MCM month-1. The second scenario needed 32 MCM month-1, leading to a deficit of 9 MCM month-1. The third scenario needed 4 MCM month-1 with a water surplus of 19 MCM month-1. However, it was not economically and technically feasible to construct a canalization system for this small area. The questionnaire analysis indicated that high flood levels increased the cultivated area of some farms from 0.8 to 22 ha and the yield of sorghum from 400 to 2500 kg ha-1. The effect of the flood on the cultivated area and crop yield was highly significant (P ≤ 0.01) during high flood periods and significant (P ≤ 0.05) during the low floods.

Evaluating adaptation options to sea level rise and benefits to agriculture: The Ebro Delta showcase

Sea level rise (SLR) is threatening low-lying coastal areas such as river deltas. The Ebro river Delta (Spain) is representative of coastal systems particularly vulnerable to SLR due to significant sediment retention behind upstream dams (up to 99%), thereby dramatically reducing the capacity for deltaic sediment accretion. Rice production is the main economic activity, covering 66% of the delta area, and is negatively affected by SLR because of flooding and soil salinization. Therefore, appropriate adaptation measures are needed to preserve rice production. We combined Geographic Information Systems and Generalized Linear Models to identify zones prone to flooding and increasing soil salinity, and to calculate the so-called sediment deficit, that is the amount of sediment needed to raise the land to compensate flooding and soil salinization. We modelled SLR scenarios predicted by the IPCC Fifth Assessment Report, and analysed the economic feasibility (not the technical feasibility) of reintroducing fluvial sediments retained in the upstream river dam reservoirs into the delta plain, which can contribute to maintaining land elevation and rice production with SLR. To do this, the costs of the sediment reintroduction measures and their benefits in terms of avoided loss of rice production income were evaluated with an approximate economic cost-benefit analysis. Results predicted that between 35 and 90% of the rice field area will be flooded in the best and worst SLR scenarios considered (SLR = 0.5 m and 1.8 m by 2100, respectively), with a sediment deficit of 130 and 442 million tonnes, with an associated cost of sediment reintroduction of 13 and 226 million €. The net benefit of rice production maintenance was 24.6 and 328 €/ha. The proposed adaptation measure has a positive effect on rice production and can be considered as an innovative management option for maintaining deltaic areas under SLR.

Integrating road information modeling (RIM) and geographic information system (GIS) for effective utility relocations in infrastructure projects

PurposeTransportation infrastructure projects are inevitably delayed due to delays in the completion of underground utility relocation. Unfamiliar location, difficulty in utility identification and use of ineffective coordination practices hamper timely completion of utility relocation works. This paper aims to develop integrated road information modeling (RIM) and geographic information system (GIS) models to assist early identification of utilities and effective coordination during utility relocation in infrastructure projects.Design/methodology/approachAn ethnographic action-based case study research methodology was adopted in this paper. Two ongoing infrastructure projects with significant utility relocation delays are chosen as case studies and integrated RIM-GIS models are developed to assist utility relocation. To verify the applications of developed RIM-GIS models, a focus group discussion was conducted with 10 field experts from the considered case studies.FindingsThe application of the developed RIM-GIS models enabled 3D visualization of existing underground utilities and enabled identification of utility conflicts before the start of the construction. They also enabled facilitating coordination and reduce utility relocation delays. The evaluation of the developed models shows that the RIM-GIS model approach enabled early planning and coordination and facilitates effective management of utility relocations.Practical implicationsThe current practices of using CAD and GIS for utility relocations are inadequate due to the difficulties in characterizing utilities and ineffective coordination practices. The proposed RIM-GIS approach can be adopted as a suitable alternative for effective management of utility relocations.Originality/valueSeveral studies have contributed toward integrating BIM and GIS for the analysis of highway and utility infrastructure projects. Efforts on integrating RIM and GIS for the support and management of utility relocations in highway and utility infrastructure projects remain unexplored.

GIS Models for Vulnerability of Coastal Erosion Assessment in a Tropical Protected Area

Coastal erosion is considered a major worldwide challenge. The vulnerability assessment of coastal areas, in relation to climate change, is a key topic of worldwide increasing interest. The integration of methodologies supported by Remote Sensing, Geographical Information Systems (GIS) and in situ monitoring has allowed a viable identification of vulnerable areas to erosion. In the present study, a model was proposed to the assessment of the estuarine system of Cananéia-Iguape (Brazil), by applying the evaluation and prediction of vulnerability models for the conservation and preservation of mangroves. Approximately 1221 Km2 were classified, with 16% of the total presenting high and very high vulnerability to erosion. Other relevant aspects, were the identification and georeferencing sites that showed strong evidence of erosion and, thus, having a huge influence on the final vulnerability scores. The obtained results led to the development of a multidisciplinary approach through the application of a prediction and description model that resulted from the adaptation of the study system from a set of implemented models for coastal regions, in order to contribute to the erosion vulnerability assessment in the mangroves ecosystems (and associated localities, municipalities and communities).

Application of remote sensing and geographic information systems in irrigation water management under water scarcity conditions in Fayoum, Egypt

Egypt suffers from severe water scarcity, which affects the sustainability of agricultural production. Therefore, the sustainable use of available water resources under water scarcity requires the adoption of water allocation policies favoring conservative and efficient use. Water management with free satellite data and geographical information system modeling capabilities can be a valuable approach for optimizing the benefits from the available water resources to meet the requirements for agricultural lands. This study aims to (i) detect and evaluate changes in agricultural areas because of urbanization and reclamation activities using Landsat data in 1999, 2009, and 2019 and (ii) update the irrigation water demand by monitoring the seasonal changes of agricultural area based on normalized difference vegetation index. Water management of Fayoum Governorate in Egypt is characterized by a non-uniform distribution flow over its canals; thus, two pilot areas are selected. The first site is the Sinnuris canal, the served areas of which represents the urbanization problem. The other site is the Gharaq canal, the served areas of which represents the urbanization and agricultural expansion situations. The results reveal that changes in agricultural areas considerably affect the uniformity of water management. Urbanization activities reduce the agricultural area by ∼5.0% and 5.7% in Sinnuris and Gharaq served areas, respectively. However, the newly cultivated lands in Gharaq preserve an increase of 5.8% in the total agricultural area. The considerably changed water allocation strategies in these districts since Sinnuris has an excess of 1.5 m3/s of water supply, while the Gharaq area faced an irrigation shortage of 0.26 m3/s in 2019. As per the proposed approach, the decision-makers can readjust the water allocation plan to satisfy the water requirements for other demand areas.

Geographic information system-based approach and statistical modeling for assessing nitrate distribution in the Mitidja aquifer, Northern Algeria.

The Mitidja alluvial aquifer in northern Algeria is an important drinking, industrial, and agricultural water source. Unfortunately, nitrate contamination has led to a decrease in water quality in several areas that benefit from this source. This study employed geographic information system and statistical modeling methods to evaluate the origin, evolution, and spatiotemporal distribution of groundwater nitrate in the aquifer and investigate the influence of different hydrogeological parameters on its extent. Control points were established across various regions of the Mitidja groundwater aquifer. A total of 1185 nitrate concentrations were measured at 316 sampling points between June 1985 and May 2015. The results showed variable rates, with the 50mg/L nitrate consumption limit exceeded in 423 samples at 84 observation points. Statistical modeling showed that nitrate concentration was related to groundwater characteristics (aquifer nature, water table depth, and thickness of saturated zone) and human activities (land use, agricultural practices, and population density). Analysis of the nitrate distribution showed that the eastern and western watersheds experienced the greatest contamination. The significant nitrate concentrations in the eastern area were correlated with urban contamination, including uncontrolled urbanization, high population density, and industrial activity, while the primary origin of nitrate in the western area was correlated with agricultural activity, particularly fertilizers. The findings of this study can aid local government and water agencies in the development and implementation of regulations to help mitigate increases in nitrate concentrations.

Mapping the Spatial Distribution of the Rumen Fluke Calicophoron daubneyi in a Mediterranean Area.

Rumen flukes (Calicophoron daubneyi) represent a growing threat to the animal health, productivity and welfare of ruminants. The present study aimed to assess the spatial distribution of C. daubneyi infections in ruminants and to develop a predictive model of the environmental suitability for rumen flukes in a Mediterranean area. A cross-sectional coprological survey was conducted in 682 sheep, 73 goat and 307 cattle farms located in the Basilicata region (southern Italy). Faecal samples collected were analysed using the FLOTAC technique. Geographical Information Systems (GIS) and statistical models were developed to determine environmental risk factors and to delimitate the areas at highest risk of infections in small ruminants. The results showed 7.9% (95% CI 6.05–10.27) of sheep farms, 2.7% (95% CI 0.48–10.44) of goat farms and 55.0% (95% CI 49.62–60.99) of cattle farms were infected by C. daubneyi. The areas with high predicted risk were situated in the western part of the region. The soil texture, land use and the presence of streams and brooks were the variables statistically significant (p < 0.05) in explaining the C. daubneyi distribution in the study area. The study confirms the importance of geospatial technology in supporting parasite control strategies in livestock and demonstrates that a combined use of different geostatistical techniques can improve the prediction of the C. daubneyi infection risk in ruminants.

Biophysical permafrost map indicates ecosystem processes dominate permafrost stability in the Northern Hemisphere

The stability of permafrost is of fundamental importance to socio-economic well-being and ecological services, involving broad impacts to hydrological cycling, global budgets of greenhouse gases and infrastructure safety. This study presents a biophysical permafrost zonation map that uses a rule-based geographic information system (GIS) model integrating global climate and ecological datasets to classify and map permafrost regions (totaling 19.76 × 106 km2, excluding glaciers and lakes) in the Northern Hemisphere into five types: climate-driven (CD) (19% of area), CD/ecosystem-modified (41%), CD/ecosystem protected (3%), ecosystem-driven (29%), and ecosystem-protected (8%). Overall, 81% of the permafrost regions in the Northern Hemisphere are modified, driven, or protected by ecosystems, indicating the dominant role of ecosystems in permafrost stability in the Northern Hemisphere. Permafrost driven solely by climate occupies 19% of permafrost regions, mainly in High Arctic and high mountains areas, such as the Qinghai–Tibet Plateau. This highlights the importance of reducing ecosystem disturbances (natural and human activity) to help slow permafrost degradation and lower the related risks from a warming climate.

Evaluation of PM2.5 Particulate Matter and Noise Pollution in Tikrit University Based on GIS and Statistical Modeling

In this paper, we assess the extent of environmental pollution in terms of PM2.5 particulate matter and noise in Tikrit University, located in Tikrit City of Iraq. The geographic information systems (GIS) technology was used for data analysis. Moreover, we built two multiple linear regression models (based on two different data inputs) for the prediction of PM2.5 particulate matter, which were based on the explanatory variables of maximum and minimum noise, temperature, and humidity. Furthermore, the maximum prediction coefficient R2 of the best models was 0.82, with a validated (via testing data) coefficient R2 of 0.94. From the actual total distribution of PM2.5 particulate values ranging from 35–58 μg/m3, our best model managed to predict values between 34.9–60.6 μg/m3. At the end of the study, the overall air quality was determined between moderate and harmful. In addition, the overall detected noise ranged from 49.30–85.79 dB, which inevitably designated the study area to be categorized as a noisy zone, despite being an educational institution.

Construction of 3D Scene of Transmission Line Corridor Based on GIM and 3D GIS

Transmission lines have the characteristics of strip distribution, wide coverage, and close connection with the actual geographical environment. The traditional transmission line modeling method has the defects of insufficient spatial positioning ability and weak information expression ability. Therefore, in this paper, three-dimensional geographic information system (3D GIS) and grid information model (GIM) are coordinated to make the two complementary advantages and construct the three-dimensional scene of transmission line corridor. First, The visible light images and high-precision laser point cloud data of transmission line corridor are collected by helicopter, and extract power lines and towers from the laser point cloud data. Then, the oblique photogrammetric model of large-scale scene is made from visible light images and modified. Finally, according to the point cloud of power line and tower, the improved template matching method is used to realize the rapid modeling of transmission line GIM model, and the transmission line model is obtained. A complete 3D digital twin scene model of transmission line corridor is formed by fusing scene model and transmission line model. The research results show that the 3D scene construction method of transmission line corridor based on 3D GIS and GIM not only improves the efficiency of transmission line modeling, but also has a good visual effect. The abundant line information is helpful for the visual operation and maintenance management of existing transmission lines from macro to micro, which provides data support for the construction of digital power grid.