Abstract: Reality often challenges the effectiveness of environmental policy and its instruments, as is evident for Marine Ecological Territory Instruments in the Mexican Coastal Zone (MCZ), known as Ecological Territory Management Programs (POET, from the Spanish acronym). The primary function of POETs is to guide the allocation of coastal uses within the ecosystem boundaries of 265 municipalities, encompassing 24,945 km of coastline and 10,570 km2 of the continental shelf. The POETs operate through a public management system involving over 500 legal instruments and at least 300 personnel, comprising both municipal and state officials. Its goal is to protect the rights of more than 25 million inhabitants to enjoy a healthy environment and equitable access to resources. However, this remains a challenging and often unresolved task partially explained by various adverse and complex operational conditions that include the diverse population distributions among coastal municipalities, which average 96528.8 ± 203842.5; inaccuracies in coastline measurements, and the absence of a unified system for monitoring, collecting, and disseminating coastal data. Considering operability as an important POETs characteristic that enable them to activate other functions, we identify 47 essential conditions for effectively operating marine POETs within the Mexican Coastal Zone management public system.

Abstract: The decline of forests in many countries has prompted governments to adopt conservation measures for forest resources. In the total and partial wildlife reserves of Bontioli, forest conservation appears difficult to implement despite the state's adoption of so-called participatory management approaches. Forest cover loss persists due to the combined effects of natural and human factors. Authorities are attempting to preserve the forest in a context of growing local needs, driven—though not exclusively—by demographic pressure. Using a mixed-methods approach combining qualitative and quantitative data, we mapped this forest retreat and analyzed its underlying causes. We also examined local perceptions of forest conservation. While forest decline is widely acknowledged and lamented, it highlights divergent views between authorities and local populations regarding concepts such as deforestation and conservation. The diversity of perceptions, depending on place of residence and the level of dependence on the land resources of the Bontioli reserves, also plays a key role in the acceptance of policies aimed at forest preservation. For sustainable forest management, the development of socio-economic infrastructure, the transformation of a part of the reserve into an agroforestry park, and the ongoing consultation of local communities emerge as effective solutions for safeguarding the forest.

Abstract: Urban environments are complex systems shaped by diverse factors such as land-use patterns and service structures, which constitute an important asset to urban living. The relatively high living standards and economic opportunities they bring about are frequently characterized as a centripetal factor attracting people to urban areas. However, the need for urban services and a diversity of land uses is increasing competition for land. Unequal land-use also makes it more difficult for poor residents to acquire essential services such as nutritious food sources, thereby aggravating health disparities. Lack of sufficient mobility and widespread urbanization may also hinder inner-city inhabitants’ access to food. Therefore, understanding the current practice and policy regarding land-use and urban services structure and the intricate linkages between land-use and service allocation is key to addressing systemic health inequities affecting the urban poor. Furthermore, eliminating these gaps is critical to developing equitable urban environments that benefit everyone. Nonetheless, managing increasing competition for land-use and the supply of urban services while accounting for increasing population and diverse stakeholders’ interests requires efficient allocation and use of urban land. The review findings show a close relationship between urban planning and community well-being. For instance, the analysis of findings shows an African urban system, which is often associated with chaotic life, informal development, and environmental deterioration as a result of a lack of strict adherence to statutory land-use planning requirements and regulations. The review findings also suggest that efficient land-use may improve service accessibility and inhabitants’ health outcomes, indicating the need for policies that give integrated planning a top priority.

Abstract: This study aims to examine the spatiotemporal distribution of air temperature in a Mediterranean region with rugged topography, dominated by anabatic and katabatic breezes. The thermal breeze is studied using data from four fixed Davis-type stations installed in 2022 and 2023, as well as air temperature data from Tinytag sensors. This network allows us to spatialize the thermal breeze on a half-hourly temporal scale. Thermal inversion is measured in the Zahlé Valley, where an average inversion layer of 400 m is observed at the valley floor. The urban heat island (UHI) is studied using satellite imagery, along with fixed and mobile air temperature measurements conducted in 2022 and 2023. A mean difference reaching a maximum of 7.7ºC between urban and rural areas is observed. This difference is confirmed by satellite, fixed, and mobile measurements.

Abstract: This work combines geomorphological and historical research to decode the landscape in the world's most famous painting: the Gioconda. The background of the painting was analysed in detail, and numerous morphological correspondences with the Montefeltro area in central Italy were found. The upper valley of the Senatello Stream features the Fumaiolo Massif, renowned for its springs that feed the Tiber River. The region is composed of the limestones and sandstones of the San Marino and Monte Fumaiolo Formations, alongside clay formations from the "Valmarecchia Nappe". This lithological variety, the intense fracturing of the limestone rocks, and climatic and tectonic events during the Middle to Upper Pleistocene produced a complex and varied geomorphology. The landscape is marked by large landslides and significant debris deposits reflecting its recent evolution. The painting, as well as historical documents and Leonardo’s drawings from his time in the Romagna Region, provide evidence of a large lake beneath Mount Aquilone. The area was affected by a significant change in the morphology of the slopes, probably caused by a landslide that occurred in the period 1500-1700, a period characterised by climatic and tectonic upheavals, which may have led to the disappearance of the lake.

Abstract: This study investigates the Holocene evolution of the Laraquete-Carampangue strandplain (LCS) on the tectonically active coast of south-central Chile using Ground Penetrating Radar (GPR) and LiDAR data. Laraquete-Carampangue strandplain (LCS), on the tectonically active coast of south-central Chile, is a rare accretionary feature in a region dominated by rocky shorelines and limited sediment supply. LiDAR-derived digital elevation model reveals a complex geomorphology comprising 52 beach ridges, aeolian dunes, and fluvial paleochannels, while GPR radargrams uncover marine and aeolian facies influenced by past seismic and climatic events. We interpret these units in the frame of past seismic and climatic events. Our geomorphological and stratigraphic findings suggest that the strandplain progradation was driven by relative sea-level changes associated with past seismic cycles and Holocene climate change. We propose that the transition from drier to humid conditions in the late Holocene triggered the onset of dune formation at the end of the Little Ice Age. This integrated approach highlights the interplay of tectonic and climatic forcings in shaping coastal landforms, offering insights into their long-term response to environmental change.

Abstract: Reforestation is widely promoted as a nature-based solution for climate change, yet little attention is given to its potential unintended consequences: deforestation leakage, where agricultural activities are displaced rather than reduced. This study provides a empirical quantification of reforestation-induced leakage in Brazil, using panel data and spatial econometric models to estimate both the magnitude and geographic extent of displaced deforestation. We estimate 12% of deforestation leakage due to reforestation displacing agricultural areas, with effects propagating up to 150 km. We also test whether livestock intensification mitigates this spillover effect - without significant effects on offset leakage. Our results suggest that carbon credit accounting methodologies could improve their statistical evidence to avoid inflate or miscalculate net carbon benefits of reforestation projects. These findings have direct implications for carbon offset standards (e.g., Verra, ART-TREES) and the design of reforestation projects worldwide.

Abstract:

Marine litter (ML), encompassing human-made objects in marine ecosystems, poses significant threats to the coasts of some Adriatic islands, despite their remoteness and sparse populations. These islands, reliant on tourism, are particularly vulnerable to ML pollution. This study hypothesized that the natural features of the islands influence ML distribution. It employes an integrated geographic approach combining the results of field survey (via sea kayaking) with various indicators which include: (1) coastal orientation and number density of bays, (2) vegetation exposure and biomass share, (3) island area and number density of bays, (4) bay openness and ML quantity, and (5) bay openness and plastic prevalence in ML.Focusing on islands of Lošinj, Pašman, Vis, and the Kornati and Elaphiti archipelago, the study analyzed data collected over six years (2018–2023). Results highlighted that NW-SE and W-E coastal orientations are particularly susceptible to ML accumulation, especially in the southern Adriatic. Linear Regression analyses revealed a stronger correlation between number density of polluted bays and the surface area of smaller islands (<10 km²) compared to larger islands (>10 km²). The following findings underscore the need for international collaboration and stringent policies to mitigate ML pollution, ensuring the protection of Adriatic marine ecosystems and the sustainability of local communities.

Abstract: Amidst the backdrop of the fossil fuel energy crisis, the development of renewable energy sources is experiencing an unprecedented acceleration in Spain and focusing in metropolitan areas. This study investigates the potential for photovoltaic energy development in Spanish metropolitan areas, specifically Madrid and its surrounding region. Recognizing the inherent challenges of land use and material scarcity associated with this development, the research aims to quantify the maximum achievable photovoltaic capacity for the region, along with the corresponding land occupation and material consumption requirements. A Material Flow Analysis (MFA) methodology is employed to project these parameters to 2050. The analysis estimates a potential production capacity of 32,163 GWh/year, representing 76.81% of the projected electricity consumption in 2050 (and 39.94% of final energy consumption). This capacity would necessitate the utilization of 32,169 hectares of land (4.01% of the regional area), including 7,139 hectares of rooftop space. Critically, 48% of the suitable land is classified as agricultural land, highlighting potential land-use competition. Furthermore, the study extrapolates the material requirements to a global scale, estimating the percentage of global mineral reserves required for a comparable energy transition. The analysis yields an estimate of 0.75% for aluminum, 17.69% for copper, and 34.89% for silver. These findings provide crucial insights into the material and geographical constraints impacting the feasibility of urban energy transitions.

Abstract:

A model for rapid detection of coastal mangrove cover was devised. The idea is that it can be applied by users with basic knowledge of remote sensing and GIS. The model is based on calculating the principal components (PC) from bands corresponding to the visible, near infrared, and shortwave infrared regions in Landsat Level-2 images. The model was tested for RAMSAR sites located Mexico: Laguna Guasima on the upper Gulf of California coast, Puerto Arista on the Pacific Ocean coast, and Laguna Madre on the Gulf of Mexico. It was found that the first PC in the three RAMSAR sites explains 80 to 90% of the variation and corresponds mainly to areas that include crop fields or urban infrastructure. The second PC, with cumulative variance of 8 to 14%, corresponds mainly to mangrove cover, and the PC with the lowest percentage of cumulative variance (< 5.0%) is invariably open water. The advantage of using Landsat Collection Level 2 is that there is an archive managed by the USGS of imagery from virtually all over the world that is over 50 years old.

Abstract: Urban planning has become increasingly complex, necessitating the use of digitized data, large-scale city scans, and advanced tools for planning and development. Recent advancements in open-source 3D modeling software – Blender, have introduced powerful procedural editing tools like geometry nodes, alongside robust mesh and curve manipulation capabilities. These features position Blender as a viable and cost-effective alternative to proprietary solutions in urban planning workflows. This study identifies common requirements, tasks, and workflows associated with cityscape transformation and visualization, implementing them within Blender’s environment. Documented working examples are provided, including procedural editing, cloud painting, and mesh transformation operations, demonstrating Blender’s versatility. To evaluate its practicality and performance, we conducted a comparative analysis with Rhinoceros Grasshopper, a widely used tool in urban planning. Metrics such as computational efficiency, workflow adaptability, and user experience were analyzed across multiple scenarios involving point cloud processing, mesh editing, and visualization tasks. Finally, we suggest further potential improvements aided by Blender’s powerful scripting framework.

Abstract:

Rapid urbanization and climate impacts have raised concerns about the emergence and aggravation of urban heat island effects. In Africa, studies have focused more on big cities due to their growing populations and high socio-economic functions, while mid-sized cities remain understudied, with limited comparative insights into their distinct characteristics. This study therefore provided a spatiotemporal analysis of land use land cover change (LULCC) and surface urban heat islands (SUHI) effects in the Nigerian mid-sized cities of Akure and Osogbo from 2014 to 2023. This study used Landsat 8 and 9 imagery (2014 and 2023) and analyzed data via Google Earth Engine and ArcGIS Pro 3.4. Results showed that Akure increased significantly from 164.026 km² to 224.191 km² in the built areas while Osogbo witnessed a smaller expansion from 41.808 km² to 58.315 km² in built areas. This study identified Normalized Difference Vegetation Index (NDVI) and emissivity patterns associated with vegetation and thermal emissions and a positive association between LST and urbanization. The findings across Akure and Osogbo cities established that the LULCC had a different impact on SUHI effects. As a result, evidence from a mid-sized city might not be extended to other cities of similar size and socioeconomic characteristics without caution.

Abstract:

Balancing regional disparities in non-grainization at the prefecture level is vital for stable grain production and sustainable urbanization. This study employs geospatial analysis to examine the spatiotemporal patterns and driver factors of non-grainization in Jiangsu Province from 2001 to 2020. By integrating geospatial data from 77 county-level units and employing spatial autocorrelation analysis, multiple linear regression, and Mixed Geographically Weighted Regression (MGWR), this study reveals the spatial heterogeneity and key driving factors of non-grainization. The results indicate that despite cyclical fluctuations in the provincial non-grainization rate, significant regional differences persist. High–high clusters are evident in economically developed southern and coastal areas, while low–low clusters are observed in less developed northern regions, indicating strong spatial dependence. Furthermore, the analysis reveals that rural residents' per capita disposable income and total agricultural output contribute to the process of non-grainization, emphasizing the impact of economic development on land use decisions. These findings highlight the importance of geoinformation tools in managing regional disparities. Integrating spatial and socioeconomic analysis offers practical insights for policymakers to develop targeted strategies that balance food security with agricultural diversification. This study provides valuable insights for policymakers seeking to optimize land-use planning in rapidly urbanizing agricultural regions.

Abstract: Land use conflicts pose a growing challenge to sustainable development, particularly in regions experiencing rapid urbanization. This study examines the spatiotemporal dynamics of land use conflicts and their ecological implications in Tianshui City from 1980 to 2020. The objectives are to identify patterns of spatial heterogeneity, explore the driving factors behind land use conflicts, and analyze their relationship with ecological risks.The natural breaks (Jenks) classification method was employed to categorize land use conflicts into five levels, ranging from no conflict to severe conflict, with classification accuracy evaluated using the Kappa coefficient, achieving a minimum value of 0.83. Semivariance geostatistical analysis was applied to assess spatial heterogeneity, revealing that structural factors such as topography and climate dominated in the early years, while stochastic factors, including urbanization and socio-economic development, became increasingly influential over time. Bivariate LISA clustering analysis highlighted a strong spatial correlation between high land use conflicts and ecological risks, particularly in areas undergoing rapid transitions, such as the conversion of arable land to urban uses.The results indicate a significant expansion of high-conflict and severe-conflict zones, particularly in urban and agriculturally fertile regions, accompanied by a decline in conflict-free areas. The aggregation of high-risk activities, such as urban sprawl and industrial development, has further exacerbated ecological risks. These findings underscore the need for integrated land use policies that prioritize ecological protection, promote sustainable urban expansion, and mitigate the impacts of land use conflicts. Future research should incorporate emerging drivers, such as climate variability, and develop advanced models to improve the prediction and management of land use conflicts and their ecological consequences.

Abstract: Understanding lagoon behavior is crucial for both scientific research and engineering, especially in delicate Arctic environments. Lagoons are vital to coastal areas, often bol-stering infrastructure resilience. Since Spring 2019, we've monitored the Longyearbyen lagoon (Spitsbergen), vital for coastal erosion defense and serving as a natural laboratory. The location's well-developed infrastructure and accessible logistics make it an ideal testing site available at any time. It can be used for many natural scientific studies. Spanning 400x50m, the lagoon continually shifts due to waves and tides, with a maximum tidal range of 2m. This article focuses on gravel spit movement, accelerating in recent years to several meters monthly. Through methods like aerial and satellite images, laser scanning and hydrodynamic measurements, we've delineated processes, rates, and mechanisms behind this movement. Bed-load transport along the spit, coupled with gravel slides, primarily drives expansion and lagoon growth. Modeling these processes aids in forecasting lagoon system development, crucial for informed management and engineering decisions in Arctic coastal regions.

Abstract: A tsunami disaster can cause significant economic losses for a tourism area like Batukaras Village, which is located on the southern coast of Java Island. This paper tries to elaborate on the calculation of economic losses in tourism areas due to the damage to buildings, loss of land production and loss of income based on high-resolution geospatial data. The data are derived from UAV photogrammetry surveys and high-resolution tsunami run-up models. The tsunami worst-case scenario run-off model provides an inundation area of 43 ha with 185 buildings and 24.4 ha of productive land. The estimated losses from the tsunami disaster amounted to IDR 208.79 billion, consisting of 49.63 billion from building damage, 6.73 billion from productive land and 152.43 billion from the tourism sector. This result shows that the tsunami disaster will severely affect tourism areas because the tourism sector contributes 73% of the total economic losses. Reduction of the economic loss, in addition to spatial planning near the coastline to reduce the number of impacted buildings and productive land, can be achieved by accelerating the recovery period so that economic activities after the tsunami disaster can be carried out immediately, including in the tourism sector.

Abstract:

This study investigated recent climate changes in Ghana and the relationships between climate and malaria case rates. for 2008–2022. These were analysed at three spatial scales: national; regional; and ‘climate zone’ (i.e., coastal, savannah and forest zones that are roughly horizontal zones that move south to north across Ghana). Descriptive statistics and qualitative discussion were used to identify possible relationships between the climate variability and the malaria case rates. A correlation analysis was used to provide a quantitative framing for the discussion of the results. The climate analysis identified a general warming over the period with a mid-2010s maximum temperature peak in the forest and savannah zones, also associated with changes in the annual temperature cycle. Malaria case rates increased between 2008 and 2013, decreased sharply in 2014, and then decreased steadily from 2015 to 2022 for all spatial scales. The sharp decline was broadly coincident with a change in the temperature regime that would provide a less favourable environment for the malaria vectors. This was particularly so for an increase in maximum temperatures in the savannah and coastal climate zones in the key months for malaria transmission after 2014. The correlation analysis showed statistically significant (p<0.05) relationships between malaria case rates and mean and maximum temperatures at the national scale, and malaria case rates and mean, maximum and minimum temperatures for the coastal climate zone.

Abstract: Precise Point Positioning with real-time kinematic (PPP-RTK) technology, which relies on Global Navigation Satellite Systems (GNSS), encounters difficulties in achieving high-precision and rapid convergence during ionospheric scintillation events such as those occurring in thunder-storms. Most existing research on PPP-RTK has primarily focused on calm ionospheric conditions, with limited analysis of its performance under ionospheric anomalies. This study analyzes 13-day data collected from 305 Australian stations, encompassing both ionospheric anomalies (from May 10th to 13th, 2024) and calm periods. We evaluated the residuals of uncalibrated phase delay (UPD), the accuracy of atmospheric modeling, as well as the positioning accuracy and convergence time of PPP-RTK. The results reveal that during ionospheric anomalies, com-pared to calm conditions, the accuracy of wide-lane and narrow-lane UPDs decreases by 2.4% and 1.4%, respectively. Meanwhile, the accuracy of estimated ionospheric and tropospheric de-lays deteriorates by 167.1% and 17.3%, respectively. In terms of PPP-RTK services, for the hori-zontal component, the convergence times increase by 25.0%, 44.4%, and 55.6% for the GPS-only, GPS+Galileo, and GPS+Galileo+BDS solutions, respectively. For the vertical component, the in-creases are 56.9%, 81.6%, and 87.2%, respectively. Regarding the positioning accuracies, for the horizontal component, they decline by 5.5%, 7.4%, and 10.4% for the GPS-only, GPS+Galileo, and GPS+Galileo+BDS solutions, respectively. For the vertical component, the declines are 11.8%, 13.0%, and 18.5%, respectively. This indicates that ionospheric anomalies significantly disrupt PPP-RTK services, mainly due to the degradation of ionospheric delay estimates, which directly affects positioning results. Although the ionosphere can lead to significant degradation in posi-tioning performance, the positioning performance can still be substantially improved with an in-crease in the number of satellites. This study thus offers new insights into the performance of PPP-RTK during ionospheric disturbances.

Abstract: Flash floods, driven largely by climate and land-use changes, are among the most destructive natural hazards globally, causing significant damage and loss of life. This study employs the Flash Flood Potential Index (FFPI) to assess flood-prone areas in North Macedonia's catchments, utilizing GIS and advanced geospatial analytics. The average FFPI values for the main and subcatchments range from 5.34 to 6.46. Across the country's territory, 24.7% of the subcatchments are identified as very highly vulnerable to flash floods (torrential catchments). Correspondingly, the FFPI model ranges from 2.1 to 15.1, with an average value of 5.9, revealing significant spatial variability in flash flood risks across the country. The model classifies vulnerability into five categories, from 1 (very low) to 5 (very high). The Treska, Kriva Reka, and Pčinja River catchments exhibit the highest flood-prone susceptibility, with average FFPI values of 3.36, 3.30, and 3.22, respectively. Nationwide, 25.6% of the area is categorized as highly vulnerable to flash floods. The FFPI model was validated using intense precipitation data and historical flash flood events, ensuring a robust assessment of flood susceptibility. This research addresses the challenges of flash flood forecasting and management in North Macedonia, particularly in regions with limited observational data. By integrating factors such as slope, lithology, land use, vegetation, and the Bare Soil Index (BSI), alongside rainfall, peak discharges, and response times, this study aims to inform improved flood risk management strategies.

Abstract:

Statistical modelling approaches which produce fine spatial resolution population estimates have been developed to fill data gaps in resource-poor countries where census data are either outdated or incomplete. These population modelling methods often draw upon recent georeferenced sample population enumeration datasets to predict population density and distribution at both sampled and non-sampled locations, based on their correlation with a set of carefully selected geospatial covariates. These modelled population estimates are increasingly used to support governance, health surveillance, equitable resource allocation, and humanitarian response. However, methodological challenges remain. For example, the georeferenced sample enumeration data are usually disparate and patchy in their distributions, with a high proportion of non-sampled locations that result in highly uncertain estimates. Here, we present a model-based Bayesian geostatistical small area population estimation approach which simultaneously · Combines multiple sample population enumeration datasets and· Explicitly integrates spatial autocorrelation within a single modelling framework. Findings from a simulation study show varying levels of accuracy in the posterior parameter estimates over different levels of spatial variance and data missingness. The methodology, which was further validated using five nationally representative household listing datasets in Cameroon, provides a valuable methodological development in small area population estimation modelling from sparsely distributed sample enumeration data.