Geographic Information System Technology Research Articles

Eliciting expert opinion on GIS use for surveillance and disease response in the aquatic animal health domain

Since the 1980s, Geographical Information Systems (GIS) have been integrated into animal farming technologies for purposes such as enhancing production performances and veterinary epidemiology. In aquaculture, however, there seems to be limited application of GIS, and its potential is widely overlooked, especially for aquatic animal health management. This study describes the results of a world expert opinion elicitation on the current implementation of GIS for surveillance and disease response in the aquatic animal health domain. An online survey was submitted in autumn 2023, including both closed and open questions. With a response rate of 41.2% (21 out of 51), the answer analysis highlighted that, especially when knowledge and practical skills in geomatics, information technology and remote sensing are required, a group of advanced GIS technologies is underutilized (web-based solutions, SDI, citizen science). An artificial intelligence-based inductive text analysis was performed confirming a limited exploitation of GIS mainly due to management (financial support, training, collaboration) and methodology (data suitability, modelling analyses and integration) constraints. Furthermore, despite acknowledging the importance of planning in GIS project development, most experts did not follow any written or unwritten procedures that, according to their answers, should in fact encompass sustainable principles (integration of GIS solutions into other applications or processes), and reuse of resources (guidelines and best practices, data, methods, layouts). Shared guidelines for developing GIS projects, identifying available data sources, and long-term-maintenance planning of GIS and related geospatial data, should be pursued for using GIS technologies more effectively in the aquatic animal health domain.

Integration of two different road network models for emergency rescue pathfinding in indoor and outdoor environments

Abstract The environment of buildings and outdoor transportation in urban areas is becoming increasingly complex. This poses a challenge for rescue pathfinding once an emergency occurs, which relies on the generation of road network models. To better balance efficiency and accuracy in pathfinding, a three-dimensional integrated road network model (3D-IRNM) derived from grid and topological road network models was developed in this study. Firstly, a cross-platform data loading method from building information model to geographic information systems (GIS) is proposed, to serve as a data source for road network model generation, visual enhancement, and breaking the barriers between different spatial data format models. Then, the topological and grid road network models are generated in indoor spaces of different functions, with IRNM obtained by the integration strategy. The 3D-IRNM can be formed by extracting indoor vertical paths from the stairs and connecting them with the IRNM of each floor. To further combine the 3D-IRNM with outdoor environments, a CrossNode model is then proposed. Besides, an adaptive pathfinding algorithm is also proposed. Finally, the construction of an emergency pathfinding system based on GIS technology is achieved. The pathfinding algorithm and the structure of 3D-IRNM help the pathfinding both efficiency and accuracy. The practicability of the designed 3D-IRNM together with its pathfinding algorithm is well verified.

Elevating Tanzania's Tourism: Integrating GIS, AR and AI for Immersive Exploration and Promotion

This study presents a comprehensive examination of the integration of Geographic Information Systems (GIS), Augmented Reality (AR) and Artificial Intelligence (AI) in tourism promotion in Tanzania. The literature review underscores the significance of these technologies in enhancing visitor experiences, destination management, and marketing strategies. The proposed integrated system design combines GIS's spatial mapping capabilities, AI's personalised recommendations, and AR's immersive content delivery to optimise tourist satisfaction and engagement. Key components include the GIS module for spatial data management, the AI recommendation engine for personalised suggestions, and the AR interface for immersive content overlay. Discussions highlight how the proposed system, by addressing critical challenges in the tourism sector, aligns with existing research findings and reassures its effectiveness. Ultimately, the study emphasises the potential of GIS, AR and AI technologies to revolutionise tourism promotion in Tanzania, fostering sustainable growth and cultural appreciation while enhancing visitor experiences.

Seguimiento de los cambios en el uso del suelo y la cobertura del suelo utilizando tecnicas de teledeteccion y SIG en la Isla de Phu Quoc, Provincia de Kien Giang, Vietnam

The changes in land use and land cover (LULC) are among the primary drivers of global environmental changes in many developing countries. In this study, LULC changes were assessed on Phu Quoc Island, located in Kien Giang province, Vietnam, from 2001 to 2022. The study utilized remote sensing and Geographic Information System (GIS) technology using Landsat images for the years 2001, 2009, and 2022. Image classification for each year was conducted through supervised classification using a maximum likelihood classifier, with the main LULC classes being forests, bare land, agricultural areas, water bodies, and built-up areas. The accuracy of the classification was evaluated using the kappa coefficient, achieving values consistently above 0.8 for all three images. Over the 20-year period (2001-2022), the area of forest, agriculture, and water bodies decreased by 14.90 km2, 30.96 km2, and 0.64 km2, respectively. Meanwhile, the areas of bare land and built-up areas increased by 22.22 km2 and 24.28 km2, respectively. Additionally, this study employed the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI) to quickly assess LULC changes, obtaining results consistent with the supervised classification. The findings underscore the importance of closely monitoring LULC changes to facilitate effective natural resource management and maintain a sustainable environment.

Application of Geographic Information System (GIS) Technology to Formulate Unused Spring Water Optimization Strategy

Background: This article presents the findings of a comprehensive community empowerment program that focused on the application of Geographic Information System (GIS) technology for the optimization strategy formulation of unused spring water. Contribution: The contribution of this program address the challenge for better utilization of unused spring water and promote sustainable water management practices. Method: The study employed GIS technology to identify and map unused springs, followed by hydrological analysis and water quality assessment to inform the development of optimization strategies. Results: This program suggested infrastructure development, water conservation measures, and distribution network design to enhance water availability. Conclusion: The findings show that GIS approach is suitable for further applications in other Indonesian mountainous villages with similarly shared community traits. However, further some locality aspects, including, but not limited to community leadership and economic power, need to be assessed further, as they play significant influences on the success of the program

Shaping school for childhood myopia: the association between floor area ratio of school environment and myopia in China

AimTo investigate the association of floor area ratio (FAR), an indicator of built environments, and myopia onset.MethodsThis prospective cohort study recruited 136 753 children aged 6–10 years from 108 schools...

Agriculture data analysis using parallel k-nearest neighbour classification algorithm

A cost-effective and effective agriculture management system is created by utilizing data analytics (DA), internet of things (IoT), and cloud computing (CC). Geographic information system (GIS) technology and remote sensing predictions give users and stakeholders access to a variety of sensory data, including rainfall patterns and weather-related information (such as pressure, humidity, and temperatures). They have unstructured format for sensory data. The current systems do a poor job of analysing such data since they cannot effectively balance speed and memory usage. An effective categorization model (ECM) on agriculture management system is proposed to address this research difficulty. First, a classification technique called priority-based k-nearest neighbour (KNN) is provided to categorize unstructured multi-dimensional data into a structured form. Additionally, the Hadoop MapReduce (HMR) framework is used to do classification utilizing a parallel approach. Data from real-time IoT sensors used in agriculture is the subject of experiments. The suggested approach significantly outperforms previous approaches that are computing time, memory efficiency, model accuracy, and speedup.

Pengembangan Aplikasi Pencarian Lokasi Pabrik Tahu di Kota Depok Berbasis Android Menggunakan Metode Location Based Service (LBS) dengan Android Studio

In this modern era, technology is advancing rapidly, allowing for the search of tofu factories using smartphones. This study aims to develop an application to locate tofu factories in Depok City utilizing GIS (Geographic Information System) technology and GPS (Global Positioning System) integrated with the Android Google Maps platform. The application is designed to facilitate the public in finding the nearest tofu factory locations. This Android-based tofu factory search application employs Location Based Service (LBS) methods to provide real-time location information. The primary objective of this research is to simplify the process for the community in Depok to find tofu factories, thereby improving efficiency and saving time. Additionally, this application is expected to assist tofu factory owners in attracting more customers by providing accurate and accessible location information. The methodology includes literature review, direct observation, and application development using Java programming language in Android Studio. The results show that the application significantly simplifies the process for the community in Depok to find tofu factories, improving efficiency and saving time. Furthermore, the application is expected to assist tofu factory owners in attracting more customers by providing accurate and accessible location information

Collaborative Pricing of Green Supply Chain of Prefabricated Construction

In the process of carbon peak and carbon neutrality, prefabricated buildings have developed rapidly, and the concept of green and low carbon has been introduced into the field of prefabricated buildings. This paper establishes an information sharing platform based on BIM (Building Information Modeling), RFID (Radio Frequency IDentification), and GIS (Geographic Information System) technologies from the green supply chain of prefabricated buildings. On the basis of information sharing, the Stackelberg two-stage game is used to analyze and compare the overall profit of the supply chain under the centralized pricing decision and the decentralized pricing decision. Through numerical simulation, this paper analyzes the relationship between pricing and the overall profit of the supply chain, compares the difference of the overall profit of supply chain under two different pricing strategies, centralized pricing and decentralized pricing, and analyzes the influence of information sharing degree on the overall profit of the supply chain. The results show that the overall profit of the supply chain under centralized pricing decisions is significantly higher than that under decentralized pricing decisions. The higher the degree of information sharing, the greater the overall profit of the supply chain.

Digitalization in Indonesia’s Agrifood Sector in the Wake of the COVID-19 Pandemic

COVID-19 has disrupted Indonesia’s agricultural food supply chain, leading to the massive mintage and exertion of digitalization in the food and agriculture (agrifood) sector. This study systematically mapped the landscape of agrifood digital technology studies and startups in Indonesia and its relation to the COVID-19 pandemic. A systematic evidence evaluation was harnessed for this study to obtain data, which were translated into thematic and interactive maps. The study shows that COVID-19 has hampered some agrifood activities but has positively accelerated the development of digital technologies in the sector. The Government of Indonesia has issued national initiatives and policies that support implementing digital technologies in the agrifood sector. The digital technologies studied and utilized in Indonesia’s agrifood industry are websites, the Internet of Things (IoT), global positioning system (GPS) and geographic information system (GIS) technology, artificial intelligence (AI), big data, and robotics. About 22.8 percent of the reviewed literature discusses the ripple effects of COVID-19 on the digitalized agrifood sector in the country. Most startups are in the form of farmers’ advisory, mechanization platforms, digital marketplace, e-commerce, traceability, food delivery, and peer-to-peer lending. Both the studies and applications are primarily concentrated on Java island and have benefited from digital technologies, such as IoT, blockchain, AI, smartphone or Android, mobile apps, GPS/GIS, and drones. Startup companies have applied strategic measures to cope with the implications of the pandemic, such as suspending some of their activities.

Geospatial Analysis of Soil Fertility in Muzaffarpur District, Bihar, India: Integrating GPS and GIS Technologies

The soil fertility maps generated using Global Positioning System (GPS) and Geographic Information Systems (GIS) serve as crucial tools for effective nutrient management decision-making. However, soil fertility data for the Minapur, Kanti, and Marwan blocks of Muzaffarpur district, Bihar, India was found to be insufficient. Therefore, a soil fertility inventory research was conducted in these three blocks to create thematic soil fertility maps. A total of 40 geo-referenced composite soil samples were collected from various locations within the study area using a handheld GPS device. The processed soil samples were analyzed for various soil fertility parameters using standard methods. Soil nutrient status and fertility maps were then created using ArcGIS software with Inverse Distance Weighted (IDW) interpolation techniques. The results clearly indicated that the soil reaction was alkaline, with a pH value exceeding 7.5. The content of soil organic matter, potassium, and sulphur was found to be low to medium, while available nitrogen and phosphorus levels were recorded as very low in these blocks. Finally it is concluded that the study generated thematic soil fertility maps for Minapur, Kanti, and Marwan blocks of Muzaffarpur district, Bihar, revealing alkaline soil with low to medium organic matter, potassium, and sulphur and very low nitrogen and phosphorus levels.

Spatial Data Handling System in The Nasai Village Area, South Papua

Merauke Regency is one of the districts in the South Papua Province, geographically located between 1370 - 1410 East Longitude and 50 - 90 South Latitude. With an area of ​​up to 45,013.35 km2 or 38.2 percent of the total area of ​​South Papua Province, making Merauke Regency the largest district not only in South Papua Province but also among other districts in Indonesia. Administratively, Merauke Regency has 22 districts. With the expansion of new provincial territories, Merauke Regency became part of South Papua Province along with Boven Digoel, Asmat and Mappi Regencies. This expansion is based on Law No. 14 of 2022. Merauke has 22 districts/sub-districts and 190 villages. The existence of 190 villages means that spatial data collection is still considered a normal thing, even though spatial data collection in an area is very important, especially with current technological advances. Accurate and integrated management of spatial data is important in planning and decision making in a region, especially in the Nasai Village area, South Papua. This research aims to examine a comprehensive spatial data handling system in this area, using Geographic Information System (GIS) technology as a tool. The methods used in this research include identifying needs and problems related to spatial data, collecting spatial and non-spatial data, as well as designing an integrated geographic information system. It is hoped that the results of this research will provide an overview of the current condition of spatial data management in Nasai Village and provide system recommendations that can increase the efficiency and effectiveness of geographic information management in the area.

Ideologies in Geospatial Futurism: A Computational and Critical Discourse Inquiry Into the ArcGIS and ESRI-Blogs

Geographic information systems (GIS) are ubiquitous building blocks of geosurveillance environments embedded in everyday social practices. This article builds on the literature on geomedia, the criticisms of GIS, and communicative spaces, to delve into the realm of GIS software and spatial analytics. The data corpus consists of ArcGIS and ESRI blogs on the Environmental Systems Research Institute (ESRI) site, which defines itself as the global market leader in GIS software, location intelligence, and mapping. This project assesses the impact of their discursive representations of the future and the societal implications of these views through an iterative process of computational and critical interpretive analyses—extending from LDA topic modelling to critical discourse analysis—to unveil the ideological underpinnings of a corporate-prescribed understanding of (GIS) future. The analysis reveals that representations of the future in the main blogs of the geospatial industry are deeply embedded in ideological principles that emphasise perceived indispensability and technosolutionism as the inherent belief that complex social, political, and economic issues can be solved primarily or exclusively through technological means. The article identifies the rhetorical and structural operations in a discourse that ultimately kidnaps any alternative futures. The geospatial industry’s representations of the future serve as ideological tools that shape perceptions about societal development and democratic conditions. The critical engagement with these representations contributes to understanding the role of GIS technology in the shaping of fair futures built on democratic public spheres in the digital age.

SIGFIS: a Geographic Information System for Monitoring the Use of Water Resources in the State of Pernambuco

Objective: The objective is to develop a Geographic Information System for Monitoring (SIGFIS) for the oversight of water resource use in the State of Pernambuco, aiming to improve the efficiency of monitoring operations and water sustainability. Literature Review: The study is based on theories and applications of Geographic Information Systems (GIS) in water resource management. Method: The methodology includes an applied and descriptive study, with data collection from sources such as APAC, IBGE, and CPRM. Documental research methods and field surveys were used, along with geoprocessing. The data were standardized and integrated into a geographic database, with the creation of thematic maps and spatial analyses. Results and Discussion: The results include an improvement in the real-time monitoring capacity of water resources, allowing for a faster response to irregularities and optimization of monitoring resources. Research Implications: Practical implications include improving the efficiency of monitoring operations and APAC's response capacity, while theoretical implications reinforce the importance of GIS in water resource management. It is expected that SIGFIS will contribute to the formulation of more robust and scientifically-based public policies. Originality/Value: This study contributes to the literature by developing a specific GIS for the monitoring of water resources in Pernambuco, demonstrating the relevance of GIS technology in promoting water sustainability and improving environmental governance.

Mapping EU Member States’ Quality of Life during COVID-19 Pandemic Crisis

This study proposes an integrated methodology for the assessment and mapping of quality of life (QoL) among European Union member states in the period before and after the pandemic crisis of COVID-19. The assessment of quality of life was based on the development of composite criteria and Geographical Information Systems or GIS technology, using variables that assess quality of life. The composite criteria relate to the socioeconomic environment, employment conditions, economic conditions and health services. Each criterion was evaluated by a set of variables, and each variable was weighted based on relevant research by Greek experts. Criteria were also weighted and combined to assess overall quality of life. The methodology was applied in 27 EU member countries, and mapping led to the identification of countries with low and high quality of life. The results showed a change in the level of overall quality of life in the EU countries before and after the pandemic period, although on a limited scale, since there is a slight reclassification of the countries’ positions. The analysis also revealed the highest level of quality of life in four EU countries [Sweden, Denmark, the Netherlands and Luxembourg] that show an increased GDP per capita, combining a low level of arrears and a low level of inability to make ends meet, whereas four countries showed the lowest level of quality of life [Greece, Bulgaria, Romania and Croatia] in both periods.

Spatial modeling of the occurrences of geogenic fluoride in groundwater systems in Tanzania: Implications for the provision of safe drinking water

Inadequate data and spatial dependence in the observations during geochemical studies are among the disturbing conditions when estimating environmental factors contributing to the local variability in the pollutants of interest. Usually, spatial dependence occurs due to the researcher's imperfection on the natural scale of occurrence which affects the sampling strategy. As a consequence, observations on the study variable are significantly correlated in space. In this study, the machine learning approach was developed and used to study the environmental factors controlling the local variability in fluoride concentrations in drinking water sources of northern Tanzania within the East African Rift Valley. The approach constituted the use of geographical information systems (GIS) technology, exploratory spatial data analysis (ESDA) methods, and spatial regression modeling at a local level. The environmental variables used to study the local variation in fluoride concentration include topography, tectonic processes, water exchanges between hydrogeological layers during lateral movement, mineralization processes (EC), and water pH. The study was based on 20 local spatial regimes determined using GIS based on water sources density in the four hydrogeological environments. Specifically, the non-parametric (one-way Kruskal-Wallis sum ranks test and Multiple Comparisons Dunn Test), spatial statistics (Global Moran's I statistic), ordinary least squares (OLS) regression, and spatial lag models were used to quantify the effects of topography, tectonic processes, water exchange between hydrogeological environments and water physiochemical parameters (pH and EC) on the spatial variability of fluoride concentrations in drinking water sources at a local scale. In order of significance, the local spatial variation in fluoride concentration is influenced by the EC, topography, tectonic processes, pH, and water exchange between hydrogeological layers during water movement. The results presented in this paper are crucial for safe water access planning in naturally contaminated aquifer systems.

Establishing a Geo-Database for Drinking Water and Its Delivery and Storage Components with an Object-Based Approach

Infrastructure facilities that serve the city as a whole and should be considered as a whole should be built in an orderly and planned manner, just as cities are. Infrastructure facilities become obsolete over time. Aging infrastructure facilities may become unserviceable over time. When the need for maintenance and repair arises, it is mandatory to renew or replace infrastructure facilities. In this case, necessary maintenance/repair and renovation works should be completed as soon as possible. These infrastructure facilities may not be transferred to maps in the digital environment and may often be managed with person-oriented information, not institutional. There is a problem for decision makers, namely, that the construction, maintenance, repair and governance of infrastructure facilities cannot be carried out systematically, on time and effectively. The only way to provide such a service is through the combined use of today’s informatics, Geographical Information System (GIS) and Global Navigation Satellite System (GNSS) technologies, unlike the classical methods of the past. The aim of the study is to effectively manage the scarce resource of drinking water and its facilities, which are an important component of infrastructure facilities, with a method that uses current mapping technologies and informatics facilities. Especially after Infrastructure for Spatial Information (INSPIRE) and the transformation of Land Administration Domain Model (LADM) to the International Organization for Standardization (ISO) standard, Turkish National Geographic Information System (TNGIS) studies and many academic studies carried out in Türkiye have been modelled with Unified Modelling Language (UML) diagrams in accordance with LADM. Similarly, within the scope of this study, UML diagrams were prepared, and then a GIS database was established. Thanks to field workers, chiefs, engineers and others working on water pipelines, all necessary data, classic, as-built and digital, were gathered. These were collected in different ways in order to conduct spatial and non-spatial analysis in the study area of Trabzon. The most important result from the study is that the entire drinking water infrastructure of Trabzon has been transferred to the system in a structure that allows spatial queries, ensuring that damage detection on water components, maintenance and repair processes are carried out in the shortest time and at the lowest cost. The investigation and application of a sensor-integrated GIS-aided system, making it possible to control and monitor the use of lost and illegal water to be controlled as well as inform consumers who will be affected by possible maintenance and repair, is recommended.

Spatio-temporal variations and influencing factors analysis of coastal wetlands in Tianjin, China

Coastal wetlands are one of the world’s most threatened ecosystems and the influences of climate change and anthropogenic factors on changes in coastal wetland distribution have been the subject of active research in recent years. However, the multi-year intergenerational trends in coastal wetland areas, and the factors influencing them in China have not been fully studied using geographic spatial data during the past 30 years. The relative contributions of climate change and anthropogenic factors to spatio-temporal variations in coastal wetland area also remain to be described. In this study, we discuss changes in the coastal wetland areas and the reasons behind them in Tianjin, which is one of China’s fastest developing regions, using remote sensing and geographic information system technology, Pearson correlation analysis, the relative weight method and the land expansion extraction module, the land expansion analysis strategy (LEAS) model of the Patch-generated Land Use Simulation (PLUS) model. The results showed that the total wetland area declined from 2233.59 km2 in 1984 to 1742.73 km2 in 2020. We conclude that the expansion of non-wetland land types is the main driver of natural wetland area decrease, with 830.86 km2 of natural wetlands having been converted to non-wetlands during this period. The large areas of shallow water and tidal marsh that have been converted to construction and bare land particularly emphasize the primary importance of urbanization and coastal reclamation in driving wetland reduction. The results showed that the temporal variation of natural wetlands area was correlated with population density (PD), total gross domestic product (GDP), annual mean temperature (AMT), average relative humidity (ARH), and primary (PI), secondary (SI), and tertiary industrial development (TI). PD, PI, TI, GDP, SI, AMT, and ARH contributed to 24.47 %, 18.21 %, 15.74 %, 14.16 %, 12.77 %, 7.09 %, and 4.86 % of the wetland area decrease, respectively. PD, distance to settlements (DS), distance to railways (DRW), AMT, distance to rivers (DR), and GDP contributed 17.61 %, 14.27 %, 13.83 %, 13.62 %, 12.07 %, and 10.92 % of the spatial variations of natural wetland area, respectively, which showing the predominant effects of anthropogenic variables on the spatio-temporal natural wetland areas. Our results are valuable in identifying the dynamic spatio-temporal variations in coastal wetlands to improve our understanding of the impacts of climate change and human activities on coastal wetlands to help in the future protection and restoration of wetlands.

Enhancing Geographic Information System Skills through Boundary Mapping Training at Pesantren Rahmatullah, Lempake, Samarinda

This program designed to enhance the skills and knowledge of students and teaching staff at Pesantren Rahmatullah (Islamic boarding school) regarding the use of Geographic Information System (GIS) technology in boundary mapping. The initiative was launched recognizing the importance of understanding territorial boundaries in the context of natural resource management, development planning, and disaster mitigation in the surrounding areas. The training includes a series of theoretical sessions and field practices. The first stage involves learning how to gather coordinate points in the field using the Garmin 60 CSX GPS device. The second stage focuses on field data processing and coordinate data correction, covering basic GIS knowledge, introduction to GIS software, and usage of Autodesk Map software and Arc GIS 10.8. The third stage is the scaled printing of processed field data. The duration of the training is one semester, following the curriculum set by the Rahmatullah Islamic boarding school. This training aims to equip participants with the necessary skills to produce accurate and informative boundary maps, which will later serve as tools for decision-making and strategic planning at Rahmatullah Lempake Islamic boarding school in Samarinda. Additionally, this activity also aims to enhance the boarding school’s awareness and capacity in utilizing geographic information technology for educational and environmental management purposes.

Applying GIS in Blue-Green Infrastructure Design in Urban Areas for Better Life Quality and Climate Resilience

The expansion of urban centers and peri-urban zones significantly impacts both the natural world and human well-being, leading to issues such as increased air pollution, the formation of urban heat islands, and challenges in water management. The concept of multifunctional greening serves as a cornerstone, emphasizing the interconnectedness of ecological, social, and health-related factors. This study aimed to identify potential locations for three specific types of blue-green infrastructure (BGI): bioswales, infiltration trenches, and green bus stops. Leveraging geospatial datasets, Geographic Information System (GIS) technology, and remote sensing methodologies, this study conducted a comprehensive analysis and modeling of spatial information. Initial cartographic representations were developed to identify specific locations within Olsztyn, a city in Poland, deemed appropriate for the implementation of the designated blue-green infrastructure (BGI) components. Following this, these models were combined with two additional models created by the researchers: a surface urban heat island (SUHI) model and a demographic model that outlined the age structure of the city’s population. This synergistic approach resulted in the development of a detailed map, which identified potential locations for the implementation of blue-green infrastructure. This was achieved by utilizing vector data acquired with a precision of 1 m. The high level of detail on the map allows for an extremely accurate representation of geographical features and infrastructure layouts, which are essential for precise planning and implementation. This infrastructure is identified as a key strategy for strengthening ecosystem resilience, improving urban livability, and promoting public health and well-being.