Geospatial Location Research Articles

Quantifying architectural uniqueness of Scots pine trees using terrestrial laser scanning: toward individual tree fingerprinting

Abstract Tree architecture reflects a hierarchical growth pattern shaped by the interplay between genetics and the environment. Environmental variation leads to unique resource availability, resulting in each tree developing distinct structural features, akin to the uniqueness of a human fingerprint. In this study, we propose a nondestructive method for quantifying this architectural uniqueness using terrestrial laser scanning for tree identification. While tree identification is commonly based on their precise geospatial location, this information may not always be available. Instead, we hypothesized that a tree’s stem profile (diameters along the stem) and branching arrangement (locations of branch origins on the stem surface) could distinguish individuals within a population. The experimental setup included 65 Scots pine (Pinus sylvestris L.) trees in a managed boreal forest stand, scanned with terrestrial laser scanning in September 2021 (T1) and November 2022 (T2). We investigated whether individual trees could be identified based on architectural similarities between their point cloud reconstructions from T1 and T2. In total, 52 trees (80.0%) were identified based on their architectural characteristics. The results supported our hypothesis, showing that identifying ≥10 branch origins from independent reconstructions was sufficient to establish architectural uniqueness, resulting in 100% identification accuracy (n = 20 trees). These findings suggest that the complex three-dimensional tree architecture can be condensed into a two-dimensional pattern of points representing branch arrangement, which we term the “tree fingerprint.” These architectural characteristics, which can be reconstructed from the lower half of the tree, are well suited for acquisition via ground-based sensing techniques such as terrestrial or mobile laser scanning. If point cloud data capable of characterizing individual branches is acquired during forest operations, the proposed methodology can facilitate tree identification for applications such as wood tracking, even without geospatial coordinates.

Prevalence and determinants of vulnerability among Sundarbans mangrove forest resource-dependent communities in cyclone-prone southwestern coastal districts of Bangladesh

Vulnerability assessment is crucial for reducing the impact of natural disasters on marginalized coastal communities. In Bangladesh, studies have addressed the vulnerability of coastal populations, but they often overlook the Sundarbans mangrove forest resource-dependent communities (SMFRDCs). These marginalized groups, reliant on the forest, frequently face natural disasters such as cyclones, increasing their vulnerability. This study seeks to assess the extent of vulnerability among SMFRDCs and uncover the critical risk factors contributing to it. This cross-sectional survey was conducted in three southwestern coastal districts of Bangladesh: Satkhira, Khulna, and Bagerhat. Data were collected from 782 SMFRDCs in three Upazila (sub-district) of selected coastal districts using a structured interview schedule (SIS) and following a multistage stratified random sampling approach. The data were analyzed using IBM SPSS Statistics v27 for Windows. A one-sample binomial test was performed to assess the prevalence of vulnerability. Additionally, bivariate analyses (Pearson’s Chi-square [χ2], Yates’s Correction for Continuity [χ2Yates], Phi [φ], and Cramer’s V [φc]), and multivariable binary logistic regression (MBLR) were conducted to identify the associated risk factors. The findings of the one-sample binomial indicate that among the coastal Upazila, the vulnerability prevalence was highest in Mongla (53.4 %; 95 % CI: 47.4 % - 59.3 %). Additionally, honey collectors were found to be more vulnerable to natural disasters, with a prevalence of 60.8 % (95 % CI: 52.7 % - 68.6 %) among the SMFRDCs. The MBLR findings indicate that SMFRDCs with over 31 years of experience and involvement in multiple occupations were less vulnerable to natural disasters. Likewise, SMFRDCs with better household materials, transport, and livestock assets were less vulnerable to natural disasters. In contrast, those with medium-to-high domestic assets were more at risk. Additionally, having land and access to loans reduced the likelihood of vulnerability. SMFRDCs with better natural, physical, and political capital were also less vulnerable. The findings show that vulnerability among SMFRDCs varied by geospatial location and occupation. Socio-demographics, household resources, and livelihood capitals were key predictors of the household vulnerability of SMFRDCs. To reduce this vulnerability, it is recommended that organizations – governmental and non-governmental – work together to create comprehensive plans involving SMFRDCs in both planning and implementing disaster risk reduction strategies by addressing individual and community-level factors.

Analyzing geospatial and geopolitical influences on airline competition: A Finnair case study

AbstractFor many years Helsinki has served as a key air transport hub connecting Asia and Europe primarily through Finland's national carrier, Finnair. Yet, in February of 2022 the closure of Russian airspace ended the Siberian corridor, at least in the near term that had long served as the most efficient air transport pathway between Asia and Europe. This study examines Helsinki's historical role as a key transport hub within the theoretical context of geographic centrality and intermediacy. The optimum geospatial location of Helsinki relative to key Asian cities is explored through both marketing and operational advantages that Finnair once leveraged. The networked route structure of Finnair before and during the twin shocks of the global pandemic and subsequent Russian–Ukrainian conflict is juxtaposed against a comparison set of hub‐and‐spoke airlines yielding key insights about the evolving competitive dynamics in the region. Moreover, a key component of Finnair's Asian strategy, dubbed the 24‐h single aircraft roundtrip rotation, is elucidated with respect to its benefits for aircraft utilization and crew scheduling efficiency. This unique characteristic allows for a special expression of intermediacy that can serve as an accelerant in air transport hub development. Finally, the current challenges facing Finnair due to the geopolitical turmoil are placed within a managerial context and avenues for future research are offered.

Using surrogate modeling to predict storm surge on evolving landscapes under climate change

Planners managing coastal flood risk under a constrained computational budget face a tradeoff. Simulating many time periods or scenarios limits how many storm simulations can be run on each landscape. In this analysis, we present a deep learning model to predict storm surge as a function of storm parameters but also landscape features and boundary conditions (e.g., sea level). It is trained on peak surge elevations from Advanced Circulation (ADCIRC) hydrodynamic simulations of coastal Louisiana in a 2020 baseline and decadal periods from 2030 to 2070 under two morphological and climate scenarios. Leave-one-landscape-out cross-validation yielded a 0.086-m RMSE and 0.050-m MAE over 90 storms per landscape and 94,013 geospatial locations. A two-sided Kolmogorov-Smirnov test comparing annual exceedance probability (AEP) estimates from the model predictions to ADCIRC simulations rejected the null hypothesis that the predicted and ADCIRC AEP values were drawn from the same distribution only 1.1% of the time.

Geolocation of Fixed Emission Sources Produced by Artisan Brick Kilns in the Atmospheric Basin of the City of Juliaca, Peru

Objective: The study objective is to investigate the application of georeferencing systems to identify the geospatial location of fixed sources of atmospheric emissions produced by artisanal brickyards in the air basin of Juliaca city-Peru. Theoretical Framework: Previous studies have shown that artisanal brickyards are a significant source of air pollution in developing urban and on the outskirts. Emissions of fine particles, nitrogen oxides and other pollutants from the burning of traditional fuels, such as firewood and coal contribute to the degradation of air quality and can have adverse effects on human health and the environment. The georeferencing application and geospatial analysis techniques in the atmospheric pollution study have allowed a better understanding of the spatial distribution of emission sources and their impact on the environment. These tools are essential to identify and map the artisanal brickyard locations and to evaluate their contribution to air pollution in urban and on the outskirts. Method: The methodology adopted for this research includes data collection and compilation of existing information; georeferencing of brickyards through the use of geographic information systems (GIS); analysis of geospatial data for the identification of spatial patterns; preparation of thematic and spatial distribution maps; and the interpretation of results. Results and Discussion: The study results highlight the importance of locating the fixed sources of emissions produced by artisanal brick factories in the Juliaca air basin. This precise spatial identification provides a solid basis for the formulation of policies and mitigation strategies aimed at reducing air pollution in the region, in addition to representing fundamental data for the use and exploitation of GIS for environmental protection and modelling, among others. Research Implications: The results can be applied or influence practices in the environmental and forestry engineering field, the ICTs application, modelling and simulation, and territorial planning, among others. Originality/Value: This study contributes to the literature using georeferencing techniques for environmental modelling purposes. The relevance and value of this research are evident in obtaining georeferenced points for the estimation of emission factors for the predictive calculation of volumes, flows and dispersion of pollutants in an air basin.

Disrupting the Neoliberal Capitalist Media Agenda in South Africa:

Neoliberalism has been described as the most successful ideology in world history (Anders-son 2000). This has, in turn, impacted the modern media by dumbing down its public interest role, through cultivating concentrated media ownership patterns, which has produced hyper-commercial and elitist-driven content. This paper has the broad aim of provoking discussions and debates both for the Global South and Global North geospatial locations grappling with these neoliberal consequences, by considering what systemic alternative(s) to capitalist me-dia can be considered. It specifically explores the return of the anti-capitalist alternative media to South Africa’s print media terrain to function in a developmental role. With the aim to dilute the neoliberal capitalist nature of its media that has effectively perpetuated the dominance of the elite class at the expense of citizen-oriented and public interest imperatives (Govenden 2022). It furthers this argument by also comparatively drawing on two BRICS country case studies from Asia i.e. China and India.

Assessing de facto wastewater reuse and its implications for water quality in Yangtze Basin (2014–2021)

De facto wastewater reuse is the incidental presence of treated wastewater in a water supply source. Unplanned indirect wastewater reuse, which is also called de facto reuse, occurs when wastewater is discharged into surface water upstream of the intakes of suitable drinking water treatment plants. Although this discharged wastewater may increase the water quality risks for downstream water supplies, they contribute to the water supply source as an additional in-stream flow. Therefore, proper wastewater management is crucial to ensure access to safe water and address the challenges due to urbanization and population growth. There are detailed data on the infrastructure and river flows in some countries, but this study examined the use of a more limited dataset in other countries and specifically assessed the de facto reuse in the Yangtze River Basin in China. GIS modelling was used to calculate the streamflow of Yangtze River from the DEM, while macro water consumption data was used to estimate the wastewater discharges, and this methodology solved the problem that the outcome was limited by the lack of gauging stations at more locations and lack of precise geospatial location of drinking water intakes or wastewater discharges. Under an average-flow condition, Chongqing in the upper reaches had de facto reuses that increased from 0.57 % in 2014 to 0.60 % in 2021; Wuhan in the middle reaches had de facto reuses, which increased from 1.56 % in 2014 to 1.64 % in 2021; Shanghai, which is located in the estuary of the Yangtze River, increased its de facto reuse from 2.35 % in 2014 to 2.51 % in 2021. Under low-flow conditions, the de facto reuse of Chongqing, Wuhan, and Shanghai in 2021 was 1.7 %, 4.9 %, and 7.4 %, respectively. This relatively high level of de facto reuse is consistent with the estimation of unintended treated wastewater contributions to streams and growing risk of drinking water quality in the Yangtze River Basin. This research estimated de facto reuse in the Yangtze River Basin and showed the feasibility of using limited infrastructure datasets to assess de facto reuse and the modeling methods allow identification of river reaches most impacted by wastewater, and perhaps suggest prioritization for investments in additional wastewater treatment in reaches with high de facto reuse.

Research on the Method of Managing Personal Massive Photos Using Geodatabase

Abstract. In view of the limitations of the existing methods for personal massive photos management and browsing, a method of using geodatabase to manage and browse massive personal photos is proposed. Firstly, vector geodatabase is created and defined based on geographic information technology. Then, attribute information including the file name, photo date and time, photo point longitude, photo point latitude, location name, photo storage path and so on of each photo in the file system are extracted. Finally, based on the longitude and latitude of the photo point, the geospatial location data of each photo is generated, and written into the vector geodatabase together with the attribute information. Based on the storage path of photos in the file system, the links between the geospatial database and photos are established. Furtherly realize the attribute information and geographical space location management of massive photos, as well as the browsing and viewing of photos. Take personal photos as an example to introduce the data processing and verify the practicability of the method. The result shows that this method uses the idea of geodatabase to manage massive personal photos, which is conducive to reflect the geographical spatial distribution and density characteristics of the photos, and can use the time axis to connect the track of personal history, which is convenient for browsing and analyzing the experience.

Mapping Population Densities and Waste Management Systems in Mombasa County: A Literature Review of GIS and Remote Sensing Techniques

Mombasa County is one of the five counties along the coastline of Kenya. Currently, Mombasa County has a human population of 1.2 million people, and the population is rapidly increasing through rural-urban immigration and natural births. However, the inadequacy of well-established waste management systems on the mainland and coastlines of the County is a threat to the well-being of the local residents. Poorly disposed of wastes both on land and at sea can lead to health problems not only for humans and terrestrial animals but also for aquatic animals such as fish, with the latter being one of the main sources of affordable proteins for poor coastal communities. This paper aimed to conduct a review of the spatial human population density of Mombasa County and the geospatial location of waste dumping sites and their proximity to settled areas. This literature review synthesized existing research on the application of Geographic Information Systems (GIS) and Remote Sensing techniques in mapping population densities and assessing waste management systems. The review began by examining studies that investigate population distribution patterns in urban and rural areas, utilizing GIS to analyze demographic data and satellite imagery. It explored methodologies used to estimate population densities, including dasymetric mapping, spatial interpolation, and land use classification techniques. Key findings were that limited studies have utilized GIS technologies to assess the population in Kenya. GRASP and Random Forest (RF) were the main techniques previously used to assess population densities in the rural Taita Hills area and along the coastal region. The population has exponentially increased in Mombasa County since the 1950s and is projected to increase further. Additionally, waste management in Mombasa County is majorly controlled by the county government. Ten geo-tagged waste collection spots were identified during the review, spread across the residential areas. In conclusion, the county should endeavor to employ GIS techniques to assess the rapid population change within the county and have targeted interventions to address the disparities in waste collection systems against population increase.

Environmental injustice in the air quality for digital platform delivery workers in Bogotá, Colombia, 2021

Air quality is a matter of interest for public health due to its rapid deterioration in low- and middle-income countries and the effects of polluted air on the health of populations. To explore the air quality conditions in which digital platform delivery workers carry out their work, evaluating the localities of Kennedy and Usaquén in Bogotá, 2021. We developed a mixed parallel convergent study based on four sources of information: 1) Ethnographic observation in five commercial locations of the two localities; 2) Monitoring of PM10 and PM2.5 in 56 delivery routes using a low-cost sensor; 3) Daily logs of the routes to support the device data interpretation, and 4) A semi-structured interview applied to the drivers to explore their danger perception during the routes. We identified elements causing environmental injustice among digital platform delivery workers between the two study locations. The routes made by the delivery drivers in the locality of Kennedy registered higher concentrations of PM10 and PM2.5, compared to the values observed in Usaquén. The sources of air pollution identified by the delivery drivers through ethnographic observation and the router logbook showed the worst parameters in Kennedy. We evidenced that air quality, urban equipment, road infrastructure, mobile sources, and geospatial location are elements that mark the presence of environmental injustice for the digital platform delivery drivers in the studied localities. To reduce this inequity, it is necessary for digital delivery platforms and the district government to implement strategies that reduce the exposure and emission of air pollutants to protect the health of digital platform delivery workers.

Examining inequalities in spatial access to national health insurance fund contracted facilities in Kenya.

Kenya aims to achieve universal health coverage (UHC) by 2030 and has selected the National Health Insurance Fund (NHIF) as the 'vehicle' to drive the UHC agenda. While there is some progress in moving the country towards UHC, the availability and accessibility to NHIF-contracted facilities may be a barrier to equitable access to care. We estimated the spatial access to NHIF-contracted facilities in Kenya to provide information to advance the UHC agenda in Kenya. We merged NHIF-contracted facility data to the geocoded inventory of health facilities in Kenya to assign facility geospatial locations. We combined this database with covariates data including road network, elevation, land use, and travel barriers. We estimated the proportion of the population living within 60- and 120-minute travel time to an NHIF-contracted facility at a 1-x1-kilometer spatial resolution nationally and at county levels using the WHO AccessMod tool. We included a total of 3,858 NHIF-contracted facilities. Nationally, 81.4% and 89.6% of the population lived within 60- and 120-minute travel time to an NHIF-contracted facility respectively. At the county level, the proportion of the population living within 1-hour of travel time to an NHIF-contracted facility ranged from as low as 28.1% in Wajir county to 100% in Nyamira and Kisii counties. Overall, only four counties (Kiambu, Kisii, Nairobi and Nyamira) had met the target of having 100% of their population living within 1-hour (60min) travel time to an NHIF-contracted facility. On average, it takes 209, 210 and 216min to travel to an NHIF-contracted facility, outpatient and inpatient facilities respectively. At the county level, travel time to an NHIF-contracted facility ranged from 10min in Vihiga County to 333min in Garissa. Our study offers evidence of the spatial access estimates to NHIF-contracted facilities in Kenya that can inform contracting decisions by the social health insurer, especially focussing on marginalised counties where more facilities need to be contracted. Besides, this evidence will be crucial as the country gears towards accelerating progress towards achieving UHC using social health insurance as the strategy to drive the UHC agenda in Kenya.

Accounting and Monitoring System of Electricity Expenditures Based on Geospatient Data Consumers Location

The purpose of the research is considers the development and implementation of a system of accounting and monitoring of electricity costs with visualization of geospatial location data by consumers, which provides technical accounting and analysis of the structure of electricity consumption, estimation of electricity consumption for the tasks of planning production volumes and purchasing electricity from producing companies based on consumer expenditure statistics, prevention of losses associated with unauthorized electricity extraction.Methods. When creating a project and software implementation of a system for monitoring and controlling energy consumption, methods of system analysis, methods of designing software for information systems, a unified object-oriented modeling language Unified Modeling Language (UML), DBMS SQLServer, development environment Microsoft Visual Studio Code (VS Code.) were used.Results. During the project, software for a monitoring and control system for electricity consumption with visualization of geospatial data on the location of consumers was developed and implemented.Тhe project was implemented, tested and introduced into the activities of JSC АtomЕnergoSbyt when planning and accounting for electricity supplies to consumers.Тhe testing results showed that the software system fully satisfies the functional requirements, is ready for use and was demonstrated at the exhibition center.Conclusion. А system for recording energy consumption data with visualization of the territorial location of consumers has been developed in order to control consumption and payments. Тhe developed system will solve the problem of delay in receiving readings from metering devices in the data collection system. Visualization of energy resource con- sumption data by objects and their territorial location with linked personal accounts, meters and consumption volumes will allow you to quickly control the volume of supplies and energy consumers. availability of payment, which will reduce unproductive losses and unauthorized connections.For the company JSC Аtomenergosbyt, operational visualization of consumer data makes it possible to analyze the coverage of consumers by territorial basis and plan new connections.

EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question Answering

Earth vision research typically focuses on extracting geospatial object locations and categories but neglects the exploration of relations between objects and comprehensive reasoning. Based on city planning needs, we develop a multi-modal multi-task VQA dataset (EarthVQA) to advance relational reasoning-based judging, counting, and comprehensive analysis. The EarthVQA dataset contains 6000 images, corresponding semantic masks, and 208,593 QA pairs with urban and rural governance requirements embedded. As objects are the basis for complex relational reasoning, we propose a Semantic OBject Awareness framework (SOBA) to advance VQA in an object-centric way. To preserve refined spatial locations and semantics, SOBA leverages a segmentation network for object semantics generation. The object-guided attention aggregates object interior features via pseudo masks, and bidirectional cross-attention further models object external relations hierarchically. To optimize object counting, we propose a numerical difference loss that dynamically adds difference penalties, unifying the classification and regression tasks. Experimental results show that SOBA outperforms both advanced general and remote sensing methods. We believe this dataset and framework provide a strong benchmark for Earth vision's complex analysis. The project page is at https://Junjue-Wang.github.io/homepage/EarthVQA.

Monitoring solutions for remote locations: A data gathering approach for remote nature-based solution sites

Nature-based solutions have gained popularity as an approach to tackling hydro-meteorological hazards (HMHs) in both urban and rural settings. Despite this popularity, challenges persist regarding the evidence base for their effectiveness and data scarcity at the feature or site scale. Flood modelling is a common approach to quantifying the effectiveness of NbS; however, the accuracy of these models heavily depends on the accuracy of the DEM, land cover, and hydraulic/hydrological data utilised. Remote and rural settings often face data scarcity due to the challenging nature of data collection, and insufficient funding for monitoring. Additionally, NbS features vary in size and scale, with many being small (<1 m in width), posing challenges for accurate representation in national LiDAR datasets. Technological advancements in remote sensing technologies, such as unmanned aerial vehicles, handheld LiDAR, and GPS-GNSS, offer opportunities to gather high-resolution, high-accuracy data in these challenging locations. This article proposes a methodological framework for collecting elevation data at remote NbS sites that can tackle areas affected by both sparse and dense vegetation cover. This approach proves valuable in both pre-NbS implementation, through facilitating NbS opportunity and environmental risk identification, and post-NbS implementation, through aiding in geo-spatial feature location, improving existing DEM data for flood modelling, and monitoring temporal changes.

Development of a community severance index for urban areas in the United States: A case study in New York City

Background and aimsTraffic-related exposures, such as air pollution and noise, have a detrimental impact on human health, especially in urban areas. However, there remains a critical research and knowledge gap in understanding the impact of community severance, a measure of the physical separation imposed by road infrastructure and motorized road traffic, limiting access to goods, services, or social connections, breaking down the social fabric and potentially also adversely impacting health. We aimed to robustly quantify a community severance metric in urban settings exemplified by its characterization in New York City (NYC). MethodsWe used geospatial location data and dimensionality reduction techniques to capture NYC community severance variation. We employed principal component pursuit, a pattern recognition algorithm, combined with factor analysis as a novel method to estimate the Community Severance Index. We used public data for the year 2019 at census block group (CBG) level on road infrastructure, road traffic activity, and pedestrian infrastructure. As a demonstrative application of the Community Severance Index, we investigated the association between community severance and traffic collisions, as a proxy for road safety, in 2019 in NYC at CBG level. ResultsOur data revealed one multidimensional factor related to community severance explaining 74% of the data variation. In adjusted analyses, traffic collisions in general, and specifically those involving pedestrians or cyclists, were nonlinearly associated with an increasing level of Community Severance Index in NYC. ConclusionWe developed a high spatial-resolution Community Severance Index for NYC using data available nationwide, making it feasible for replication in other cities across the United States. Our findings suggest that increases in the Community Severance Index across CBG may be linked to increases in traffic collisions in NYC. The Community Severance Index, which provides a novel traffic-related exposure, may be used to inform equitable urban policies that mitigate health risks and enhance well-being.

Assessing Acceptability: The Role of Understanding Participant, Neighborhood, and Community Contextual Factors in Designing a Community-Tailored Cooking Intervention.

Cooking is an identified dietary strategy that is positively associated with optimal diet quality. Prior to initiating cooking interventions, evaluating the prospective acceptability of the intervention among community members living within low food access areas and understanding geospatial food shopping locations may aid in designing community-tailored interventions. A sequential mixed methods study was conducted to determine the prospective acceptability of a planned community-located cooking intervention among African American adults living in a low food access area and with at least one cardiovascular disease risk factor. A semi-structured guide was used to conduct five virtual focus groups. Qualitative data were analyzed using thematic analysis and validated through participant check-in interviews. Survey responses were analyzed based on descriptive data. Geospatial analysis of participant locations that were reported for food shopping was conducted to show food environment utilization. Focus groups with study participants (n = 20, all female, mean age 60.3, SD 9.3, mean cooking frequency per week 4.0, food insecure n = 7) were conducted between March and April, 2021. Thematic analysis of the focus group transcripts identified five main themes as follows: (A) Barriers to Cooking (family and caregiving, transportation, COVID-19 pandemic, time availability, household composition); (B) Motivators for Cooking (family, caregiving, health, enjoyment, COVID-19 pandemic); (C) Strategies (food shopping, social support, social media, meal planning); (D) Neighborhood (gentrification, perceived safety, stigmatization, disparities in grocery stores); (E) and Acceptability of the Intervention (reasons to participate, barriers, recruitment, intervention delivery). Participant validation interviews confirmed the themes and subthemes as well as the illustrative quotes. Geospatial analysis showed a majority of locations were outside of the participants' residential areas. Prospective acceptability of a community-tailored cooking intervention found that the planned intervention could be modified to address individual level factors, such as caregiving and health, community contextual factors, such as perceived safety, and the general health needs of the community.

Geospatial conditions of landslide formation on the territory of Sakhalin Island

The paper considers the conditions for the formation of landslide-prone areas of Sakhalin Island, the intensity of development and the main characteristics of landslides of various types common on the territory of Sakhalin Island. Sakhalin Island, determined by the geospatial location of the territory. It is due to the geospatial location of the territory as a result of the tectonic and geological history of its development that the present relief, in addition to extensive sedimentation basins, is represented by steeply sloping erosion-denudation and abrasion forms of macro and mesorelief with high potential energy, overlain by layered significantly dislocated and structurally disturbed terrigenous strata represented by relatively weak rocks, the accumulation of which occurred as a result of cyclic sedimentation. The tectonic and accompanying seismic activity, as well as the geologic history of the terrane formation, have led to the formation of complex engineering, geological, and hydrogeological conditions of the territory. Furthermore, the marginal position of the region determines its monsoon climate with high cyclonic activity, leading to a general high moisture content of the territory and activation of exogenous processes. Thus, due to the geospatial position of Sakhalin in the transition zone, a whole complex of natural factors of landslide formation was formed in the territory, including global factors (tectonic, climatic) and their subordinate determinants, as well as secondary (trigger) factors (geomorphologic, geological, hydrogeological, seismic), contributing to the widespread development of modern active landslides of different scales, characteristics, as well as types of landslide process and mechanism of mountain displacement.

Strategic Minerals for Climate Change and the Energy Transition: The Mining Contribution of Colombia

To transition to carbon neutrality by the year 2050, copper, lithium, rare earths, cobalt, nickel, and silver are essential due to their use in the manufacture of electric cars, lithium batteries, wind turbines, solar panels, motors, and electrical wiring. The main goal of this study is to carry out a mining approach of the prospective areas of Colombia with strategic minerals for energy transition and climate change, analyzing the geospatial location, mining rights, mineral extraction, and royalty collection. Open data from SGC, ANM, and SIMCO geoportals were consulted. The prospective areas totaled 311,535.2 km2, equivalent to 27.3% of Colombia, and were located mainly in the Andes Mountains. The total area of mining rights and applications with strategic minerals for the energy transition is 112,802.2 km2 or 9.9% of Colombia, representing 5731 rights and 3939 applications. From 2012 to 2023, 448,330 tons of nickel, 172.9 tons of silver, and 171.6 tons of copper were mined in Colombia, which has contributed USD 513,140,286 as royalties to the state. No royalties have been earned from the extraction of rare earths, lithium, or cobalt. Fulfilling the Paris Agreement is possible with new sustainable mining projects of strategic minerals.

Monitoring and Mapping Winter Wheat Spring Frost Damage with MODIS Data and Statistical Data

Spring frost is an extreme temperature event that poses a significant threat to winter wheat production and consequently jeopardizes food security. In the context of climate change, the accelerated phenology of winter wheat due to global warming advances the frost-sensitive stage, thereby escalating the risk of spring frost damage. Present techniques for monitoring and assessing frost damage heavily rely on meteorological data, controlled field experiments and crop model simulations, which cannot accurately depict the actual disaster situation for winter wheat. In this study, we propose a novel method that utilizes remote sensing index and statistical data to ascertain the spatial distribution of spring frost damage to winter wheat and evaluate the extent of damage. This method was employed to monitor and assess the spring frost damage event that occurred in Shandong province from 3 to 7 April 2018. The result shows that beginning on 3 April, the daily minimum temperature in western Shandong Province dropped significantly (decreased by 17.93 °C), accompanied by precipitation. The daily minimum temperature reached the lowest on 7 April (−1.48 °C). The growth of winter wheat began to be inhibited on 3 April 2018, and this process persisted until 13 April. Subsequently, the impact of spring frost damage on winter wheat ceased and growth gradually resumed. The affected area of winter wheat spanned 545,000 mu with an accuracy rate of 89.72%. Severely afflicted areas are mainly located in the cities of Jining, Zaozhuang, Dezhou, Heze, Liaocheng, Jinan and Tai’an in western Shandong province, and the yield reduction rates were 5.27~12.02%. Our monitoring results were consistent with the distribution of county-level winter wheat yield in 2018 in Shandong province, the daily minimum temperature distribution during spring frost and severely afflicted areas reported by the news. This method proves effective in delineating the spatial distribution of agricultural disasters and monitoring the extent of disaster damage. Furthermore, it can provide reliable information of disaster area and geospatial location for the agricultural department, thereby aiding in disaster damage assessment and post-disaster replanting.

Exploring the role of canopy triangular units in analysing canopy effects on saplings

On the distribution and growth of saplings, canopy structure has a considerable influence. However, traditional canopy metrics are inadequate in irregular stands due to their inability to consider the heterogeneous horizontal and vertical distributions of canopy structure. To surmount this inherent limitation and achieve an advanced comprehension of the three-dimensional attributes characterizing the canopy, we introduce the innovative framework of canopy triangular units. This conceptual framework encapsulates a comprehensive array of multifaceted information, encompassing intricate forest layer intricacies such as tree height differentials, intricate competitive attributes exemplified by disparities in diameter at breast height and crown width, alongside precise geospatial location information. In this study, we formulated geometrically organized triangular networks based on precise tree coordinates, subsequently delineating ten distinct triangular unit categories predicated upon diameter at breast height measurements: DT (3,0,0), DT (2,1,0), DT (2,0,1), DT (1,2,0), DT (1,1,1), DT (1,0,2), DT (0,3,0), DT (0,2,1), DT (0,1,2), and DT (0,0,3). The values enclosed within parentheses represent the quantities of large trees, medium trees, and small trees contained within each respective triangular unit type. Our analytical framework commenced with an in-depth evaluation of the differences in quantities and areas across these diverse triangular unit types. Subsequent to this, these identified triangular unit categories underwent systematic classification into three distinct groups, thereby enabling meticulous investigation into variations within the spatial dispersion of sapling populations. Furthermore, a comprehensive suite of seven triangular unit variables encapsulating the multifaceted three-dimensional attributes of the canopy was established. This enabled a comprehensive investigation into their nuanced relationships with the growth patterns of saplings. Analyzing the triangular unit types in the three sample plots, a clear pattern emerged: maximum occurrences of DT (0,1,2) units alongside minimal DT (3,0,0) occurrences. Moreover, saplings show a clear preference for triangular unit types with low abundance of large trees. The correlation analysis revealed a significant positive link between the individual basal area increment of saplings and relevant parameters - opening area, triangular perimeter, and triangular area. As a practical implication, during the replanting of saplings, the selective choice of triangular units with fewer large trees can be prioritized to support their growth and development. To optimize sapling growth, selective tree cutting may be deemed necessary to create new triangular units and expand the opening area. These findings emphasize the significance of accounting for the framework of canopy triangular units in the development of management strategies aimed at improving both sapling quantity and growth.