Geographic Information System Model Research Articles

Prehospital Ground and Helicopter-Based Extracorporeal Cardiopulmonary Resuscitation (ECPR) Reduce Barriers to ECPR: A GIS Model

ABSTRACT Introduction Evidence suggests that Extracorporeal Cardiopulmonary Resuscitation (ECPR) can improve survival rates for nontraumatic out-of-hospital cardiac arrest (OHCA). However, when ECPR is indicated over 50% of potential candidates are unable to qualify in the current hospital-based system due to geographic limitations. This study employs a Geographic Information System (GIS) model to estimate the number of ECPR eligible patients within the United States in the current hospital-based system, a prehospital ECPR ground-based system, and a prehospital ECPR Helicopter Emergency Medical Services (HEMS)-based system. Methods We constructed a GIS model to estimate ground and helicopter transport times. Time-dependent rates of ECPR eligibility were derived from the Resuscitation Outcome Consortium (ROC) database, while the Cardiac Arrest Registry to Enhance Survival (CARES) registry determined the number of OHCA patients meeting ECPR criteria within designated transportation times. Emergency Medical Services (EMS) response time, ECPR candidacy determination time, and on-scene time were modeled based on data from the EROCA trial. The combined model was used to estimate the total ECPR eligibility in each system. Results The CARES registry recorded 736,066 OHCA patients from 2013 to 2021. After applying clinical criteria, 24,661 (3.4%) ECPR-indicated OHCA were identified. When considering overall ECPR eligibility within 45 minutes from OHCA to initiation, only 11.76% of OHCA where ECPR was indicated were eligible in the current hospital-based system. The prehospital ECPR HEMS-based system exhibited a four-fold increase in ECPR eligibility (49.3%), while the prehospital ground-based system showed a more than two-fold increase (28.4%). Conclusions The study demonstrates a two-fold increase in ECPR eligibility for a field-deployable ground-based system and a four-fold increase for a prehospital ECPR HEMS-based system compared to the current hospital-based OHCA system. This novel GIS model can inform future ECPR implementation strategies, optimizing systems of care.

An Assessment of Accessibility from a Socially Sustainable Urban Mobility Approach in Mass Transit Projects: Contributions from the Northern Central American Triangle

This article aims to address the lack of research on the social dimension of sustainability, also known as social sustainability, in urban mobility projects, primarily in cities of the Global South. It proposes a strategy to partially assess social sustainability, focusing on accessibility, which is one of the key dimensions for conducting such an evaluation. To this end, a comparative analysis of three study cases is conducted in the capital cities of the Northern Central American Triangle (NCAT) before and after the construction of bus rapid transit (BRT) projects between 2000 and 2020. Accessibility is evaluated through equity and spatial efficiency indicators obtained through geographical information system (GIS) modeling, including layers representing transportation networks, populated areas, and locations of basic urban facilities. The result is an unprecedented assessment of accessibility in the NCAT capitals, which shows how the Guatemala City BRT project has improved the city’s social sustainability by reducing access times to basic urban facilities, mainly public health clinics and educational facilities, and narrowing the inequality gap as compared to projects in San Salvador and Tegucigalpa, the other capital cities in the NCAT. Additionally, it is emphasized that this methodology can be replicated in the Global South while considering the scarcity of information and the use of open-source software in the process.

An “Earthly” Manifestation of Power: The Architectural and Urban Contexts of Iznik Tiles Produced under the Patronage of the Ottoman Palace

ABSTRACT Çini-making, which is an Ottoman underglaze ceramics tradition included in the UNESCO Representative List of the Intangible Cultural Heritage of Humanity, was used extensively in the monumental architecture of the Ottoman Empire in the fifteenth and seventeenth centuries, including mosques built by the Ottoman sultans and their family members. Iznik tiles reveal undeciphered relationships between Ottoman patronage and monumental architecture, and unwritten architectural rules and norms concerning tile designs. To contribute to the conservation, interpretation, and presentation of the mosque spaces, it is important to understand the tangible and intangible cultural qualities of Iznik tiles. This study examines the cultural qualities of Iznik tiles by analysing the historical and architectural qualities of the five selected sultanic mosques and by integrating the literature and field surveys through Geographic Information Systems (GIS) modelling and database. We aim to analyse and develop an evaluation model to investigate the cultural qualities of Iznik tiles on regional, urban, and architectural scales using GIS.

Low-Cost Data, High-Quality Models: A Semi-Automated Approach to LOD3 Creation

In the dynamic realm of digital twin modeling, where advancements are swiftly unfolding, users now possess the unprecedented ability to capture and generate geospatial data in real time. This article delves into a critical exploration of this landscape by presenting a meticulously devised workflow tailored for the creation of Level of Detail 3 (LOD3) models. Our research methodology capitalizes on the integration of Apple LiDAR technology alongside photogrammetric point clouds acquired from Unmanned Aerial Vehicles (UAVs). The proposed process unfolds with the transformation of point cloud data into Industry Foundation Classes (IFC) models, which are subsequently refined into LOD3 Geographic Information System (GIS) models leveraging the Feature Manipulation Engine (FME) workbench 2022.1.2. This orchestrated synergy among Apple LiDAR, UAV-derived photogrammetric point clouds, and the transformative capabilities of the FME culminates in the development of precise LOD3 GIS models. Our proposed workflow revolutionizes this landscape by integrating multi-source point clouds, imbuing them with accurate semantics derived from IFC models, and culminating in the creation of valid CityGML LOD3 buildings through sophisticated 3D geometric operations. The implications of this technical innovation are profound. Firstly, it elevates the capacity to produce intricate infrastructure models, unlocking new vistas for modeling digital twins. Secondly, it extends the horizons of GIS applications by seamlessly integrating enriched Building Information Modeling (BIM) components, thereby enhancing decision-making processes and facilitating more comprehensive spatial analyses.

Geoinformatics and RUSLE model-based soil erosion assessment in a tropical mountainous area of Chite watershed, Mizoram, India

Soil erosion remains a persistent menace to the sustainability of agriculture and the environment in tropical mountainous regions. Soil erosion assessment is therefore necessary to identify degraded land areas for implementing effective conservation and management strategies. Hence, this study focuses on estimating potential soil erosion and analyzing their spatial patterns in the Chite watershed, situated in the Eastern Himalayas, India, using the Revised Universal Soil Loss Equation (RUSLE) model in Geographic Information System (GIS) platform. Various datasets encompassing remote sensing, ground observations, and laboratory analysis were employed to prepare the model’s input factors. The estimated mean erosion rate of the study area is 6.10 t ha-1 year-1, which produces a total soil loss of about 357580.90 t year-1. Spatial analysis reveals that about 5.79% of the watershed is under a relatively severe erosion category, contributing 70.13% of the total soil loss. Soil erosion appraisal with respect to the land use/ land cover (LULC) indicates a considerable consequence of various anthropogenic activities in the watershed. Higher rates of soil erosion are mainly observed on the bare land, cropland, and settlement areas which are characterized by steep and continuous slopes. The present findings were also validated with previous work undertaken in some comparable regions. This research can serve as a reliable tool towards the development of successful soil conservation measures and for promoting sustainable land use planning in this ecologically sensitive tropical mountainous region.

Geoinformation model for risk management in Burundi

This paper is focused on the development of a geographic information system model for decision preparation. The application of indicator approach for visualization of risks associated with agricultural activities is presented. The paper describes not only the functioning of the geographic information model, but also the interaction between the geographic information model, database and web application in order to present in real time the geographic risks inhibiting agricultural activities.

Efficiency Evaluation of Surface Water Collection Infrastructure during Floods: Information Analysis and Zoning Management

Objective: Flood events, occurring as natural and unexpected phenomena, have become increasingly prevalent in recent decades. Assessing the probability of flood risk and creating flood zoning maps in vulnerable areas, particularly urban regions, are crucial for mitigating flood damages and managing such events. This research aims to determine the flood-prone zones along the Darakeh River, located in Tehran, the capital city of Iran, by integrating the hydraulic model HEC-RAS with Geographic Information System (GIS). Methods: After establishing the physiographic characteristics of the watershed, including area, perimeter, elevation, slope, and time of concentration, influential factors on flood occurrences such as permeability, hydrological soil groups, runoff potential, curve number, land use, and vegetation cover were identified. This information, along with other hydraulic data and flow specifications such as boundary conditions, roughness coefficients, and design discharge, was incorporated into the HEC-RAS model. The model was executed for different return periods of 2, 5, 10, 25, 50, and 100 years. Subsequently, the hydraulic model outputs were transferred to the GIS model to obtain the flood-prone zones along the Darakeh River for the aforementioned return periods. Results: As observed, in the middle section of the Khoshke Channel, which has a lower gradient, the floodplain exhibits a wider extent. Furthermore, along the course of the river and after passing through a stretch of the Khoshke Channel with a reduced gradient, the floodplain's area increases up to the location of the western flood channel. Conclusion: It is concluded that areas with lower river slopes exhibited larger flood-prone zones, highlighting the necessity of increased attention to prevent significant damages in urban areas during flood events.

Adaptive cloudiness index for enhanced photovoltaic energy prediction and management in low-income smart homes using geographic information system

Solar-powered homes can be an optimal solution for the lack of continuous power sources problem in initial low-income communities. However, the challenge of Photovoltaic (PV) uncertainty can make it difficult to coordinate this vital solar energy in real-time. This paper proposes a new, low-cost solution for assessing the uncertainty of photovoltaic power generation in smart home energy management systems. The proposed index, inspired by the well-known clearness index, is an adaptive deterministic indicator that only requires free Geographic Information System (GIS) models and PV power measurement, without the need for expensive high-tech controllers or expert engineers/programmers. The proposed index successfully predicts the daily PV energy with errors of less than 3% for more than 93% of studied days, according to the 2020 measured solar radiation of the studied case in an African developing location, i.e. Cairo. Egypt.

Locustamigratoria (L.) (Orthoptera) in a warming world: unravelling the ecological consequences of climate change using GIS.

The migratory locust, Locustamigratoria (L.), a significant grasshopper species known for its ability to form large swarms and cause extensive damage to crops and vegetation, is subject to the influence of climate change. This research paper employs geographic information system (GIS) and MaxEnt ecological modelling techniques to assess the impact of climate change on the distribution patterns of L.migratoria. Occurrence data and environmental variables are collected and analysed to create predictive models for the current and future distribution of the species. The study highlights the crucial role of climate factors, particularly temperature and precipitation, in determining the locust's distribution. The MaxEnt models exhibit high-performance indicators, accurately predicting the potential habitat suitability of L.migratoria. Additionally, specific bioclimatic variables, such as mean temperature and annual precipitation, are identified as significant factors influencing the species' presence. The generated future maps indicate how this species will invade new regions especially in Europe. Such results predict the risk of this destructive species for many agriculture communities as a direct result of a warming world. The research provides valuable insights into the complex relationship between locust distribution and environmental factors, enabling the development of effective strategies for locust management and early warning systems to mitigate the impact on agriculture and ecosystems.

Sustainable solar energy development in Zakho, Iraq: a techno-economic and environmental assessment

This study presents a solar energy roadmap aimed at attracting investors to capitalize on the abundant solar resources in Zakho, Iraq, for clean energy technology. The objective is to mitigate global warming effects caused by fossil fuel combustion and promote sustainable technological development. To end this, the study employs RETScreen Expert software to validate the techno-economic and environmental viability of a grid-connected solar photovoltaic system utilizing climatic data from the Astronaut Office Information System (NASA) Database. Additionally, the Photovoltaic Geographical Information System (PVGIS) modeling method determines optimal angles for installing residential rooftop Photovoltaic (PV) systems across selected locations. Results indicate that all selected locations are suitable for solar photovoltaic projects, with Rezgari identified as the optimal district due to its highest annual solar radiation of 1863.117 kWh/m2 and the highest annual electricity production at 7905.38 kWh. The capacity factor (CF) values fall within the range of 17.395-17.574%. The study reveals an annual greenhouse gas (GHG) emissions reduction ranging from 6.9876 to 7.1123 (tCO2) across four districts. Considering the financial and environmental indicators, Rooftop Photovoltaic Systems emerge as a sustainable and efficient solution to enhance the environment and prove economically viable in Zakho City.

INVESTIGATION OF THE PROCESSES OF ECOLOGICAL AND ECOSYSTEM CHANGES IN WATER BODIES USING UAV DATA

In recent years, the water landscapes of inland rivers have been subjected to significant an- thropogenic impacts exceeding the limits of their self-healing ability. Traditional methods of monitoring ge- oecological parameters - sampling of water in the field with subsequent laboratory analysis - require signif- icant financial and time costs. Traditional methods allow assessing the ecological state of the entire water- course not spatially, but pointwise. In this research, sensors on board the UAV measured solar radiation reflected from the surface of the water and used image data from different camera ranges. The combina- tion of images used was based on a common methodology for identifying key features, and a geographic information system (GIS) modelling approach was used for spatially analyze the distribution and interaction of environmental features. In addition, research the ecological condition of the Yertis River and the quality of water discharged after the municipal wastewater treatment facilities of Ust-Kamenogorsk city into the Yertis River, the data from the DJI Phantom 4 RTK/multispectral drone was processed and the normalized vegetation index NDVI, normalised water level difference index NDWI, water chromaticness index CI, tur- bidity index NDTI and chlorophyll concentration index "a" were calculated. The results obtained can serve as a basis for scientific analysis of the environmental conditions of the researching area, including for learning the processes of eutrophication and other changes in the environment.

Landslide Susceptibility Mapping Using GIS and Bivariate Statistical Models in Chemoga Watershed, Ethiopia

This study aimed to map the landslide susceptibility in the Chemoga watershed, Ethiopia, using Geographic Information System (GIS) and bivariate statistical models. Based on Google earth imagery and field survey, about 169 landslide locations were identified and classified randomly into training datasets (70%) and test datasets (30%). Eleven landslides conditioning factors, including slope, elevation, aspect, curvature, topographic wetness index, normalized difference vegetation index, road, river, land use, rainfall, and lithology were integrated with training landslides to determine the weights of each factor and factor classes using both frequency ratio (FR) and information value (IV) models. The final landslide susceptibility map was classified into five classes: very low, low, moderate, high, and very high. The results of area under the curve (AUC) accuracy models showed that the success rates of the FR and IV models were 87.00% and 90.10%, while the prediction rates were 88.00% and 92.30%, respectively. This type of study will be very useful to the local government for future planning and decision on landslide mitigation plans.

A novel socio-techno-environmental GIS approach to assess the contribution of ground-mounted photovoltaics to achieve climate neutrality in Germany

The German government’s goal of achieving climate neutrality by 2045 and increasing the use of renewable energy, particularly wind and solar power, has public support. However, the local siting of wind and solar farms is highly controversial due to land-use conflicts. We have developed a comprehensive Geographic Information System (GIS) model that integrates criteria from the literature to identify optimal locations for ground-mounted photovoltaic (GM-PV). The model is based on a holistic approach considering energy-related factors and broader environmental and climate considerations. It ensures that the shift in land use from food to energy production is consistent with the economic realities of both the agricultural and energy sectors. The unique feature of the model is its integration of socio-technical and environmental criteria, including a novel approach to achieving a dual land-use climate benefit by protecting erosion-prone soils and conserving soil carbon in areas prone to organic matter decomposition and associated CO2 release. Our multi-criteria GM-PV model includes 12 restrictions and five suitability criteria representing key socio-technical and environmental aspects. Scenario analysis highlights the sensitivity of Germany’s GM-PV potential to defined criteria. In Scenario 1, with minimal constraint, 14.2 % of Germany’s land is available for GM-PV, decreasing to 1.9 % in the highly constrained Scenario 12. Suitable areas (>10 ha) account for 0.4 % of Germany’s land area, which could cover 8.1 % of Germany’s electricity consumption in 2045 in the highly restricted scenario. The spatial distribution results show that the innovative approach of the model changes the preference of GM-PV locations based on factors such as solar radiation in the south and soil carbon storage in the north of Germany. Assuming that plant size will become more critical to realise economies of scale in the future, and significantly influences land potential and visual impact on the landscape. The application of restriction and suitability criteria significantly reduces the potential for GM-PV in Germany but also potential pitfalls for decision-makers. The GIS model can be applied in regional and local contexts to integrate local stakeholder values and generate region-specific scenarios, as criteria and thresholds can be easily adapted to local characteristics, preferences, and concerns, including those related to agriculture, biodiversity, and societal acceptance.

Agroforestry suitability evaluation using remote sensing in Jatiyoso Sub-district, Karanganyar District, Central Java, Indonesia

Abstract. Negari SIT, Ningtyas SRA, Hanun Z, Sulton MN, Kusumaningrum L, Indrawan M, Sugiyarto, Sutomo, Setyawan AD. 2023. Agroforestry suitability evaluation using remote sensing in Jatiyoso Sub-district, Karanganyar District, Central Java, Indonesia. Biodiversitas 24: 6761-6769. Agroforestry systems are critical for biodiversity conservation, land degradation mitigation, and climate change mitigation. This agroforestry approach reduces forest degradation, boosts food security, and gradually raises farmers' income. This study uses remote sensing and Geographic Information System (GIS) modeling tools to analyze land potential and agroforestry status in Jatiyoso Sub-district, Karanganyar District, Central Java, Indonesia. The data used in the analysis support data for soil fertility index, rainfall, Shuttle Radar Topography Mission (SRTM) satellite image data, and Normalized Difference Vegetation Index (NDVI). Modeling was done by integrating various thematic layers in the GIS domain. Weighting was also carried out in the analysis of land suitability. The mapping results in Jatiyoso Sub-district, Karanganyar District, showed that 18.1% (13.49 km2) had high potential as agroforestry areas, 54.9% (40.95 km2) had medium potential, and 27% (20.18 km2) had low potential. As a result, using remote sensing and GIS to determine suitable land for agroforestry could significantly impact the community, particularly farmers, landowners, and foresters, in the decision-making process for developing agroforestry systems and practices and estimating important productivity indicators. The most promising and appropriate agroforestry plants developed in Jatiyoso Sub-district are medicinal plants, but agricultural commodities like cloves, bananas, and vegetables are also present.

Spatial diffusion of public-private partnership (PPP) in China: A county-level analysis

This paper explores the spatial diffusion of Public-Private Partnership (PPP) in China, assessing the effects of regional boundaries, including political and functional boundaries, and transaction costs on this process. We conduct an empirical analysis using county-level panel data from 2014 to 2020 and employ a combination of geographic information system (GIS) and spatial autoregressive models to analyze the spatial factors influencing PPP diffusion in China. Our findings reveal three key points: First, local governments' PPP investment positively correlates with neighboring regions, indicating a contagious effect. Second, the contagious effect is more significant within the same urban agglomeration, demonstrating a boundary effect and illustrating the impact of spatial rescaling on spatial diffusion. Third, the contagious effect is more pronounced for PPP sectors with lower output measurement difficulty, suggesting transaction costs influence spatial diffusion. These findings offer valuable insights into barriers to spatial diffusion and strategies to promote the spatial diffusion of innovation.

Assessing Hydropower Potential in Nepal's Sunkoshi River Basin: An Integrated GIS and SWAT Hydrological Modeling Approach.

This study assessed the hydropower potential of a mountain watershed within the Sunkoshi River basin in Sindhupalchok, Nepal, utilizing geographic information systems (GIS) and the soil and water assessment tool (SWAT) hydrological model. Topographical, soil, land use, meteorological, and discharge data were employed to assess the study area for the appropriateness of hydropower generation. SWAT was utilized to delineate the Sunkoshi basin into 23 distinct subbasins and involved the creation of a detailed river network, incorporating various hydrological attributes including stream links, stream order, stream length, and slope gradient. After that, it was employed to simulate river discharges within these subbasins. The Sequential Uncertainty Fitting Version 2 (SUFI-2) algorithm, integrated within the SWAT Calibration and Uncertainty Program (SWAT-CUP), was employed to calibrate and validate the model. This step involved the adjustment of 25 selected parameters to enhance the model's accuracy and reliability in representing the hydrological processes of the Sunkoshi basin. Model performance was assessed utilizing three well-established efficiency criteria: coefficient of determination (R2 = 0.79), Nash-Sutcliffe efficiency (NSE = 0.73), and percent bias (PBIAS = 17.59). The study identified 36 sites across streams of order 3, 4, and 5 as having potential for hydropower generation. The hydropower potential at each identified site was evaluated using estimated stream flow and topographical head at various probability of exceedance (PoE) levels (40%, 45%, 50%, and 60%). The aggregate hydropower potential of the basin was quantified, yielding a potential of 371.30 MW at a 40% PoE. The findings suggest that an integrated approach combining SWAT-based hydrological modeling within a GIS can accurately assess a river basin's hydropower potential and provide insights into further evaluation of the comprehensive environmental assessment of the fragile Himalayan watersheds.

Geographical Information System Modeling for Planning Internal Transportation in a Manufacturing Plant’s Outdoor Area

A geographical information system (GIS) is an advanced tool for collecting, managing, and analyzing spatially-referenced data. The contribution of GIS use to process performance indicators can be improved by combining it with multi-criteria decision analysis (MCDA). Combining a GIS and MCDA is, in the scientific literature, rarely discussed for planning an internal transportation system in a manufacturing plant’s outdoor area. The purpose of this article is to clarify what mangers can expect from using a combined approach when deciding on a transport fleet and the operational routing of vehicles. Beside the simulation of MCDA, the computer software ArcGIS Pro 3.0.2 with the Network Analyst extension was used for modelling the transportation system in the form of a case study. The article demonstrates the feasibility and effectiveness of GIS and MCDA use and reveals the extent of the challenge of how decision makers could make the most of ArcGIS functionality. The final solution for an internal transportation system in a manufacturing plant’s outdoor area includes such a vehicle fleet and the set time windows of orders for transport services, so that there are no violations of time windows and the work is completed within the work shift while minimizing costs, time, and distance. Decision makers can use the program without advanced knowledge of optimization approaches, following a procedure that does not differ much from that of learning to use other business software tools. On the contrary, the listed disadvantages can be summarized as the rigidity of setting detailed boundary conditions for a specific simulation scenario.

Integrated Use of GIS and USLE Models for LULC Change Analysis and Soil Erosion Risk Assessment in the Hulan River Basin, Northeastern China

The Hulan River Basin is located in the black soil region of northeast China. This region is an important food-producing area and the susceptibility of black soil to erosion increases the risk of soil erosion, which is a serious environmental problem that affects agricultural productivity, water supply, and other important aspects of the region. In this paper, the changes in LULC (land use and land cover) in the basin between 2001 and 2020 were thoroughly analysed using GIS (geographic information system) and USLE (universal soil loss equation) models. The soil erosion risk in the Hulan River Basin between 2001 and 2020 was also studied and soil erosion hot spots were identified to target those that remained significant even under the implementation of soil conservation measures. Precipitation data were used to obtain the R factor distribution, LULC classification was adopted to assess the C factor distribution, soil data were employed to estimate the K factor distribution, DEM (Digital Elevation Model) data were used to generate an LS factor map, and slope and LULC data were considered to produce a P factor distribution map. These factors were based on the model parameters of the USLE. The findings of LULC change analysis over the last 20 years indicated that, while there have been nonobvious changes, agricultural land has continued to occupy the bulk of the area in the Hulan River Basin. The increase in areas used for human activities was the most notable trend. In 2001, the model-predicted soil erosion rate varied between 0 and 120 t/ha/yr, with an average of 4.63 t/ha/yr. By 2020, the estimated soil erosion rate varied between 0 and 193 t/ha/yr, with an average of 7.34 t/ha/yr. The Hulan River Basin was classified into five soil erosion risk categories. Most categories encompassed extremely low-risk levels and, over the past 20 years, the northeastern hilly regions of the basin have experienced the highest concentration of risk change areas. The northeastern hilly and mountainous regions comprised the risk change area and the regions that are most susceptible to erosion exhibited a high concentration of human production activities. In fact, the combined use of GIS and USLE modelling yielded erosion risk areas for mapping risk classes; these results could further assist local governments in improving soil conservation efforts.

Web-based platform to collect, share and manage technical data of historical systemic architectures: the Telegraphic Towers along the Madrid-Valencia path

Considering the variety of architectural Cultural Heritage typologies, systemic architectures require specific attention in the recovery process. The dimensions of "extension" and "recurrence" at geographic and technological levels affect the complexity of their knowledge process; they require systematic ways for their categorisation and comprehension to guarantee correct diagnosis and suitable rehabilitation. Recent applications involving Internet of Things (IoT) for the built Cultural Heritage have demonstrated the potentialities of three-dimensional (3D) geographic information system (GIS) models and structured databases in supporting complex degrees of knowledge for technicians, as well as management for administrators. Starting from such experiences, the work presents the setting up of a web-based platform to support the knowledge and management of systemic architectures, considering the geographical distribution of fabrics, natural and anthropic boundary conditions, and technical and administrative details. The platform takes advantage of digital models, machine and deep learning procedures and relational databases, in a GIS-based environment, for the recognition and categorisation of prevalent physical and qualitative features of systemic architectures, the recognition and qualification of dominant and recurrent decays and the management of recovery activities in a semi-automatic way. Specifically, the main digital objects used for testing the applied techniques and setting up the platform are based on Red-Green-Blue (RGB) and mapped point clouds of the historical Telegraphic Towers located along the Madrid-Valencia path, resulting from the on-site investigations. Their choice is motivated by the high level of knowledge about the cases reached in the last years by the authors, allowing them to test rules within the decision support systems and innovative techniques for their decay mapping. As the experience has demonstrated, the systematisation of technical details and operative pipeline of methods and tools allow the normalisation and standardisation of the intervention selection process; this offers policymakers an innovative tool based on traditional procedures for conservation plans, coherent with a priority-based practice.

The impact of climate and land use changes on nitrogen and phosphorus pollution in the Luhun Lake Basin, China

Introduction: Water is an important ecological factor, and non-point source pollution (NPSP) seriously affects water security. In recent years, NPSP has affected water security and human survival in China.Methods: The Luhun Lake Basin has been selected as an example region of Yellow River Basin (YRB) in China, and the trends and impacts of nitrogen (N) and phosphorus (P) has been quantitatively evaluated by using geographic information system (GIS), remote sensing (RS) and InVEST model.Results: The results show that (1) the arable land and water bodies decreased, while forest land, grass land, construction land and unutilized land increased in the 20 years. The average annual precipitation increased from the northeast to the southwest in the 20 years; (2) the N and P exports first increased in 2000–2010 and then decreased in 2010–2020, and finally increased in 2000–2020; (3) with the increase of precipitation, the N and P exports decreased in 2000–2010, 2010–2020 and 2000–2020; (4) the amount of N and P exports on arable land and construction land were more than that on the other land use types. The N and P exports on each land use type all first increased and then decreased, and the overall change trend all increased in 2000–2020.Discussion: This study demonstrates how geographic information system (GIS), remote sensing (RS) and InVEST model can be used to assess nitrogen and phosphorus pollution in data scarce regions.