This paper presents a case study focused on the measurement of horizontal deformations occurring above an active coal seam extraction site in the Upper Silesian Coal Basin. The investigation of ground surface deformation effects was carried out along a randomly selected 48-meter test section located above a mining panel. Within the defined segment, the deformation index values were determined using measurements based on varying base lengths, ranging from 1 to 24 meters. The primary objective of the study was to identify the actual magnitudes of horizontal deformations that developed within these bases during the course of the deformation process. The main source of data consisted of measurements of distances between permanently stabilized survey points positioned at 1-meter intervals along the observation line. These measurements were obtained using a specially designed and constructed instrument. The values of the deformation index, depending on the length of the measurement base, resulted in significant differences in the assessment of surface stability and potential hazard within the same area. The horizontal deformations determined from 6-meter and standard 24-meter bases did not fully capture the actual deformation hazard affecting the ground surface. The presented case study demonstrates an irregular spatial distribution of horizontal deformations within bases of 6 meters and longer. The maximum deformation index values recorded over shorter segments considerably exceeded the averaged values, leading to changes in the evaluation of the mining area’s deformation risk at the study site.
In daily life there are many relationships between human being and the local space. A typical feature of the state register (cadastre) is stability in time. But in other relationships to the local space – the role of time can be crucial.In this paper the task of defining the relationships to the space in a formal way was undertaken. The method of making the conditions (facts) for the selected examples of relations was applied, and then the procedures (algorithms) were carried out, building the relationships to the local space, making it active for an individual or a group.As examples, at first the relationships to 2D objects was presented, regarding the addressed fragment of the local space and the defined time when the relationship is active. Then the hierarchic structure of the space was taken into account by dividing it into smaller final units using a developed address recorded in the set of base conditions.A reverse case was discussed – hierarchic increase of the area in subsequent steps of the procedure of defining the relationships between the activity and space. In this case the access to the subsequent larger and larger areas is the function of the eligibilities of individuals or social groups to the subsequent stage of extending the area up to its final maximal form. Such relationships take place in industrial companies, where the gradation of eligibilities is a form of protecting the production details.Another relationship to the space is the relationship of the individual or group to linear objects, for example to the network of roads and marked trails. The example of the relationship to the network of trails and the complex case of the relationship, regarding additional conditions were presented.The next section developing direct relationships to multistep relationships is discussed. It extends the feature only for the sequence of pedestrian movements combined with the traffic. In this case two relationships occur: the relationship to a spatial object and relationship to a linear object (the route of the vehicle).In almost all the cases the time factor plays an important role in the relation to space, which is defined as one of the conditions in the set of base facts.The contemporary time is the era of digitalisation of data and processes. The space we live, is a unique good. This good should be managed in a sustainable way Hence the need to explore, analyse and formalise various relationships to the space.
Rapid urbanization has significantly transformed the landscape of Tirana County over the past three decades, reducing natural vegetation and altering land cover composition. This study employs multi-temporal Landsat imagery and the Google Earth Engine platform to quantify vegetation change between 2000 and 2025 through the Normalized Difference Vegetation Index (NDVI) analysis. Summer season composites were generated for both years to minimize phenological effects, and NDVI differencing was used to identify areas of significant greenness loss. Additional analysis of the Normalized Difference Built-up Index (NDBI) allowed the distinction between vegetation decline caused by urban expansion and other land degradation processes. Results indicate a marked decrease in vegetated areas within the Tirana metropolitan region, primarily in the western and southern zones, where built-up surfaces have expanded. In contrast, higher-elevation zones toward Dajti Mountain retained stable vegetation cover. The findings demonstrate the value of cloud-based remote-sensing tools for long-term environmental monitoring and provide evidence of the spatial footprint of urban growth in Albania’s fastest-developing county.
Albania is increasingly exposed to natural and anthropogenic hazards, including recurrent floods in the Shkodra basin, forest fires in mountainous protected areas, and ongoing deforestation linked to land-use change. Effective monitoring of these processes is challenged by fragmented datasets, delayed reporting, and the limited integration of advanced analytical methods into operational geoinformation systems. This article proposes a hybrid AI-GIS pipeline that combines semantic image classification with quantitative geospatial analysis to support hazard detection and management. The approach integrates the Contrastive Language–Image Pretraining (CLIP) model for zero-shot classification of hazard-related imagery with pixel-level segmentation and spectral indices derived from remote sensing data. CLIP enables the automatic labeling of images and tiles according to natural language prompts such as “flooded farmland”, “burned forest” or “deforested hillside” providing semantic context without the need for retraining. Segmentation methods and indices, including NDWI for floods, NDVI for vegetation loss, and dNBR for burn severity, are then applied to quantify the spatial extent of affected areas. The resulting outputs are structured in a PostGIS database, where hazard layers and attributes are stored and linked to spatial queries. A Web GIS environment built with Leaflet provides interactive visualization, dashboards, and temporal comparisons for end users. Three scenarios are presented: flood extent mapping in Shkodra, wildfire impact in Lurë National Park, and deforestation monitoring in Tropoja. Results demonstrate that the integration of semantic classification and quantitative extraction enhances both the interpretability and accuracy of hazard assessments. The framework highlights the potential of combining AI and GIS technologies to create scalable, reproducible, and policy-relevant observatories for environmental risk monitoring in Albania.
Urban biodiversity, although often underestimated, plays a key role in providing vital ecosystem services such as climate regulation, air purification and others. However, anthropogenic pressures, including rapid urbanization and land use changes, exacerbate the effects of climate change, and seriously threaten these services. This bibliometric review aims to analyze research conducted between 1990 and 2024 on urban biodiversity assessment and management, ecosystem services, and the impacts of climate change. The Publish or Perish 8 (PoPe) software is used because of its information and its flexibility of use for the different analyses, which are processed with the Excel 2013 software. Out of 1,644 publications with PoPe, 345 are select after clearance and subsequently analyze. The year 2017 marks the most prolific year of publication of articles for the mixing of concepts: “biodiversity”, “ecosystem services”, “urban dynamics” and “climate change”. From 1990 to 1996, we noted a low rate of articles according to these concepts throughout the world and it was in 2019 and 2020 that scientific research gained momentum in the Asian continent (128 publications) and more precisely in China (22.33 %) and India (7.86 %). Through these publications (articles, books, conferences and others), the publisher having been cited the most is Elsevier (17,359 citations). From the sampled publications, researchers in the assessment and management of biodiversity (33.41 %), the mapping and modeling of ecosystem services (27.27 %) as well as the dynamics of land use in urban areas (21.13 %) and the impacts of climate change (18.19 %) used various methods. These different methodological approaches were chosen based on the objective and year of the research, the availability of resources and the reliability of the results. This review has a capital importance in the sense that it provides a range of information regarding urban ecology.
The escalating challenges of climate change, biodiversity loss, land degradation, and urban expansion have amplified the need for reliable, high-resolution, and timely environmental data. Geographic Information Systems (GIS) and Remote Sensing (RS) technologies have become indispensable tools for environmental monitoring, enabling the systematic collection, analysis, and visualization of spatial data across diverse ecosystems. This review synthesizes recent innovations in GIS and RS that are transforming environmental surveillance and decision-making. Key developments include the integration of artificial intelligence (AI) and machine learning (ML) for enhanced image classification, cloud-based platforms like Google Earth Engine (GEE) for scalable analysis, and the increasing use of Unmanned Aerial Vehicles (UAVs) and hyperspectral sensors for high-resolution monitoring. Furthermore, the convergence of geospatial analytics with big data, the Internet of Things (IoT), and participatory approaches such as citizen science is expanding the accessibility and impact of environmental data. Case studies from Africa, Asia, and global initiatives highlight practical applications in land use change detection, water resource assessment, hazard risk mapping, urban heat island analysis, and biodiversity conservation. While the potential of these tools is vast, persistent challenges include data interoperability, technical capacity gaps, policy integration barriers, and ethical concerns related to surveillance and data equity. This review calls for greater investment in open-source tools, interdisciplinary collaboration, and inclusive data governance to realize the full potential of GIS and RS in achieving environmental resilience and sustainability. Future directions emphasise real-time monitoring, ethical frameworks, and the democratisation of spatial intelligence.
Baobab (Adansonia digitata L.) is a multiple-use species of high socio-economic importance in tropical Africa. It faces anthropogenic, climatic and parasitic pressures that are likely to affect its sustainability. This study provides new elements for more effective baobab management in the context of climate and global change in Togo. Specifically, it aims to: (i) determine the impact of climate change on the spatial distribution of A. digitata and A. trifasciata, and (ii) identify priority areas for the conservation and sustainable use of A. digitata co-products in the face of climate change and parasitism in Togo. The algorithm based on the maximum entropy of the baobab was developed in order to model potential habitats. Modelling was based on 17 environmental variables and occurrences of A. digitata and its parasite, Analeptes trifasciata in West Africa. The algorithm of maximum entropy (MaxEnt) was used. Forecasts were performed for SSP 126 and SSP 585 scenarios. Habitats were prioritised for conservation by combining current and future models using Zonation software. Currently, A. digitata and to A. trifasciata are predicted to occupy about 80.1 % and 91 % of the Togolese territory, respectively. By 2055, about 50 % of the highly favourable habitat for A. digitata will have been lost due to unfavourable habitat. This decline is greater in the SSP 585 scenario than SSP 126 scenario. It is recommended to implement an integrated pest management strategy and to introduce A. digitata in the most favourable areas, considering the spatial distribution of the parasite. Conservation of A. digitata must take into account areas suitable for its growth, development and reproduction. In situ conservation in agroforestry systems and home gardens should be promoted for the sustainable use of A. digitata by-products in Togo.
The ground-penetrating radar (GPR) method is one of the geophysical electromagnetic methods. The standard technique of the GPR surveys is the short-offset reflection profiling (SORP) technique, which can theoretically be described in the same way as the zero-offset (ZO) measurements. During the surveys performed using the SORP technique, the offset (i.e. the separation between the transmitter and receiver antennae) is not adjusted to the depth of the objects located in an examined medium. In more advanced measurements, performed using the wide-offset reflection profiling (WORP) technique, the offset is adjusted to the supposed depth of the underground objects which should be detected using the GPR method. The theoretical background and comparison of the SORP and the WORP surveys were described in the paper. The article also presents theoretical analyses regarding to the shape of the radiation pattern generated by the GPR antennas located on the ground surface, i.e. on the border of two media (i.e. air and geological medium) with different electromagnetic properties. The variability of shapes of the radiation patterns as well as the variability of the reflection coefficients for electromagnetic waves with transverse electric (TE) and transverse magnetic (TM) polarizations for different offsets, affect the quality of GPR recordings, which was analysed in the paper theoretically as well as through the field tests. The terrain measurements were performed on a selected part of the Vistula river flood levee in Krakow (Poland), where geotechnical sounding indicated the existence of the loose zones. In order to increase the detection possibilities of the GPR method, surveys were performed after precipitation, which created a temporary two-layer medium, i.e. near-surface, water-saturated zone and deeper located, dry zone. The results of the WORP surveys confirmed the theoretical analysis and allowed to record more readable radargrams for larger offsets than in the case of the short offset, which facilitated further interpretation of the recordings.
The Crown of Polish Mountains is a list of mountain peaks that has long attracted significant interest, with all included summits being considered worthy conquering. The proposal to expand this list with additional peaks, termed the “New Crown of Polish Mountains” by historian Krzysztof Bzowski, served as the impetus for a study of examining the accuracy of LiDAR (Light Detection and Ranging) point clouds in the areas of the newly proposed peaks. The primary data source analyzed in this study is the LiDAR point cloud with a density of 4 points per square meter, obtained from the ISOK project. As a secondary LiDAR data source, a self-generated point cloud was utilized, created by using the integrated LiDAR sensor in the iPhone 13 Pro and the free 3dScannerApp mobile application within terrestrial scanning. These datasets were compared against RTK GNSS measurements obtained with a Leica GS16 receiver and mobile measurements conducted using Android smartphones. In addition to analyzing the raw point clouds, the study also involved the visualization of the analyzed areas by the creation of Digital Terrain Models in two software programs: ArcGIS Pro and QGIS Desktop. The research confirmed the known accuracy of ALS point clouds and revealed that the integrated LiDAR sensor in the iPhone 13 Pro demonstrates surprising accuracy. The potential for laser scanning with a smartphone, combined with the capability of conducting mobile GNSS measurements, could revolutionize geodetic surveying and simplify the acquisition of point cloud data.
With the rapid development of technology and the increasing amount of data being processed, smart cities use real-time information processing to optimise various processes, including navigation and traffic management. In this context, spatial data on traffic incidents plays a key role, enabling drivers to bypass congestion and navigate safely and efficiently through the city. This study focuses on assessing the quality and availability of spatial data on road obstructions provided by the General Directorate for National Roads and Motorways (pl.: Generalna Dyrekcja Dróg Krajowych i Autostrad, GDDKiA) in Poland. In order to analyse this data, a web application was developed to visualise the data on a map to identify problems related to the accuracy of locations and the lack of key information. During the study, it was found that many of the points that were supposed to represent the locations of road incidents were at a significant distance from the actual road axes, indicating errors in geolocalisation. To improve accuracy, additional algorithms were applied that automatically corrected the position of the points to match the nearest roads. Additionally, in cases where geographic coordinates were missing, a geocoding method based on OpenStreetMap data was used. The analysis showed that the data from the General Directorate for National Roads and Motorways is partly incomplete and problematic, which limits its usefulness in further spatial analyses. In addition, the irregular updating of the data at 10-minute intervals and the low number of reported incidents further affect their quality and usefulness. Furthermore, comparison of the visualisation results with the GDDKiA road information map revealed significant discrepancies in the location of obstructions, suggesting that data sources or processing methods may differ. The results suggest the need to improve the accuracy and completeness of the spatial data provided so that it can effectively support cartographic analyses and visualisations.
In addition to the commonly known stable legal relationships between persons or institutions and fragments of the Earth's surface (real estate), there are widely applied ad hoc relationships to real space, with significantly varying durations. They are a function of acquired rights and remain valid for a strictly defined period of time. They are common in everyday life and take on diverse forms, the basic attribute of which is a reference to a broadly understood fragment of geographical space. Emerging technological achievements, such as digitisation of payments, algorithmisation of procedures, identification of documents and people, autonomous traffic and artificial intelligence - pose a challenge to provide ad hoc relationships to space with formalised notation. The problem of formal notation of legal rules applicable in local space will be presented on the example of the right of entry to the university campus, together with local traffic and parking rules. The space is divided into zones and then into smaller units – parking spaces, according to the hierarchical structure. Social groups that have relationships with these zones are also formed into hierarchical sets. Individual groups have different rights to space – hierarchically – at the zone level. The established hierarchy is the first factor considered. The second factor is variability over time. Relationships to local space change over time, most often in a cyclical form. It can therefore be concluded that in this case the law is a function of time. Parking spaces, as objects in spatial sets, are occupied randomly and subsequent users must start the procedure of searching the remaining objects belonging to the set. This procedure has been written in the form of a flowchart and graph. Objects removed from the set (as they are occupied) may randomly return, so for the purposes of effective searching, this process is presented as repeatable – as a whole or locally (cascading search). The third aspect considered are differences in the way users move around the local road network and in elementary spatial fields. The network structure is represented by intersections, which are noted as node matrices. In order to define how to behave in the local space, a list of rules was prepared and standardised. From a practical point of view, a form of prohibition is advantageous because it can be logically linked to a list (set) of consequences. Following these assumptions, the general form of the behavioural test algorithm was formulated. The presented issues demonstrate complex relationships to space and its integrating rule in relation to legal rules. This approach to law allows for space management using IT methods. The notation of the spatial structure and of legal relationships related to time enable the definition of rules of conduct for diverse groups of local societies. Dissimilarity from equality of law for all and stability over time, occurs in local environments and raises the relationships between community, space and time to a higher level of generality.
Surveys using LiDAR technology have become very popular over the past several years due to their high accuracy, speed of acquisition and completeness of space capture. Due to the progressive ease of use, these measurements are increasingly being carried out by less skilled field workers. On the other hand, however, more and more knowledge and ‘know-how’ is emerging in the processing stages of the data collected in the field. If both parts of this process are properly organised and supported by technology, satisfactory results can be obtained at the level of efficiency gains in both field work and automatic LiDAR data processing. This analysis presents the results of the work on the SITEPLANNER application developed by 3Deling.
Renewable energy sources play a crucial role in reducing global reliance on fossil fuels. Advancements in technology has en- abled harnessing of renewable energy from solar, wind, and ocean tides to be viable. Solar energy, in particular, has gained significant global recognition as a renewable energy alternative. This study integrates Multi-Criteria Evaluation (MCE) and Geographic Information Systems (GIS) to assess Solar Photovoltaic Farms (SPVFs) suitability in Nakuru County, Kenya. The study considered seven criteria including; slope, solar radiation, aspect, land use land cover, proximity to roads, power transmission lines, and settlements. These were evaluated using the Analytical Hierarchy Process (AHP) to generate weights for each decision criterion. The weights were used to overlay independent criteria maps that were formed as a result of the re- classification of each criterion from which a composite rated map was developed. Similarly, a composite restriction map was created by leveraging on constraint criteria including; protected ecosystems, water bodies, settlement areas, slope over 20%, proximity to roads, proximity to the transmission line, and land use land cover. Results obtained from overlaying the composite rated and restricted maps reveal Nakuru County’s general suitability for SPVFs, except for Kuresoi North and Kuresoi South divisions which exhibit low solar radiation. Extremely-suitable areas ac- counted for 3.00% (224.14 km²), very-suitable areas 34.05% (2541.45 km2), moderately-suitable areas 7.76% (579.55 km2), marginally-suitable areas 1.47% (109.77 km2) while least-suitable areas covered 0.02% (1.39 km2). The study provides valuable data and information for government agencies and investors to identify potential Photovoltaic (PV) system sites. Furthermore, the government is encouraged to establish a favorable framework for solar PV exploration and provide incentives to the private sector to facilitate the establishment of SPVFs.
This bibliographic analysis focused on various methods for estimating net primary productivity, vegetation indices and their various applications, as well as vulnerability assessment and management strategies for protected areas. To do this, a bibliography on the different topics collected using search engines Scopus, Science Direct, ResearchGate, and Google Scholar via the Publish or Perish portal was analyzed. Of the 1128 scientific papers on the selected topic after refining the database, 978 were journal articles, 59 were books, 52 were reports, 20 were conference proceedings, and 19 were theses. These documents detail numerous methods for estimating net primary productivity, a key parameter for assessing ecosystem performance. Methods using remote sensing data, especially vegetation indices, appear to be the easiest, least costly, and least labor-intensive today, ensuring reliable results. These innovative methods are best suited for assessing fragile ecosystems. This is the case for protected areas which have been facing the combined effects of anthropogenic actions and climate change in recent years. Considering the challenges posed by the management of Togolese protected areas, particularly since the socio-political disturbances of the 1990s, it is urgent to assess the health status of these specific ecosystems, focusing on their performance.
The article refers to the engineering thesis. This study describes the behavior of bedload transport and bed morphology in the Wloclawek Reservoir, simulated with the PTM model. Through numerical simulations, the interaction between flow dynamics, material transport and deposition was investigated. This analysis was carried out based on two variables: the height of sediment bedforms and the change in the bed level. The results were obtained for medium to high Vistula River discharges: 780, 1143, 1630 and 2990 m3·s–1.
Nutrition depends on diet, which consists of various articles of food. Hence, balanced and nutritious food is the most important single factor in connection with attainment and maintenance of health [1]. An individual’s health is largely determined by nutrition, and it is determined by diet, which consists of a variety of food items. A total of 115 villages were chosen, and 23 villages from the list of (ITDP) villages were randomly chosen in each tehsil (administrative unite in India). By using a probability proportional to the size of the various tribes, a total of 10 households from each chosen village were covered. For this reason, households in each village were divided into groups based on tribe and the necessary numbers of households (HH) from each tribe were included in the survey. The total amount of share in terms of weightage of assuming food item was calculated and using the allocated weightage. As a result, eating a well-balanced and healthy diet is the single most significant element in achieving and maintaining good health of an individual depends largely on nutrition. Tribal populations are malnourished and as a result of food deficiencies, they are at risk of developing dietary deficiency diseases.
Nowadays the amount of gathered raw data emphasizes the importance of further data processing done by skilled engineers aided by computer algorithms. Researchers develop new algorithms for the automated determination of geometrical features, such as symmetry and main axes, skeleton lines, etc. This paper presented a new algorithm to compute an unbranched axis. It was based on the Curve of Minimal Radii (CMR) algorithm, and it overcomes its significant limitations depending on the shape of the input data. To define the accuracy of the results the threshold parameter was introduced. The described approach is more comprehensive than CMR in terms of the object shape. The tests were conducted on several planar objects, and the results were compared with the original CMR axes and Medial Axis.
In the paper, non-standard signal and image processing applied for the GPR (Ground Penetrating Radar) data record for various antennae orientations was presented and discussed. The terrain surveys were carried out in the post-mining region in Poland where numerous sinkholes and subsidence areas were observed on the surface due to the former mining activity. The GPR surveys were conducted between two existing sinkholes and the aim of measurements was detection of loose zones in the ground created by suffosion process which caused the formation of the mentioned two sinkholes. In the paper, the Author proposed a new way of processing and analysis of radargrams based on three steps, i.e. 1D more advanced processing of signals/traces, 2D more advanced image processing of combined radarogram, visualisation and analysis of selected signal attributes.
The application of various petrophysical and elastic metrics has advanced reservoir characterization and provided critical geological formation information. Porosity declines with depth, according to sonic, neutron, and density logs. Lithology, pressure, and hydrocarbons all contribute to this. Formation resistivity and fluid saturation are used to identify hydrocarbon-bearing zones. Because oil and gas are non-conductive, hydrocarbon-containing rocks are more resistant than water. In lithological categorization, gamma logs and the Vp/Vs ratio have helped classify reservoirs as Agbada Formation sand-shale reservoirs. Reservoir elastic characteristics, specifically sandstones, have been studied at various depths. These discoveries have an impact on their brittleness, strength, and failure risk in a variety of scenarios. Hydrocarbon accumulation has been influenced by diagenetic compaction equilibrium in pressure-exposed shale source beds. The research advances our understanding of the geological formations of the Niger Delta and gives practical insights for exploration and production. Decisions on oil and gas are based on hydrocarbon reservoir assessments at various depths, including porosity, fluid saturation, and lithology. Well logs from Wells B001, B002, and B003 revealed the diverse properties of several Niger Delta reservoirs. These discoveries have benefited hydrocarbon exploration and production decision-making significantly.
Of Yemen’s Mesozoic basins, the Sab’atayn Basin offers the most significant potential for oil and gas exploration. The key consideration in the evaluation of source rocks to hydrocarbon exploration is the quantity and nature of the organic materials in sedimentations. Using organic geochemistry and total organic carbon content, organic-rich sediments from the Meem (Lower) and Lam (Upper) members from four wells in the NW Sab’atayn Basin were evaluated. The information gained reveals that the Meem source rocks have a total organic carbon content (TOC) value between 0.2–1.68 wt%, therefore suggests fair to very good source rocks. Only two samples in the Kamaran-01 well had values greater than 3 wt%, compared to the Lam source rocks’ values, which range from 0.2 to 3.81 wt%, which suggest excellent source rocks. The majority of the samples are made up of reworked organic debris, with no possibility for interesting source rocks, according to the Rock-Eval pyrolysis data. The majority of the Meem and Lam source rocks samples under study have Tmax values below 440 °C, placing them in the immature to marginally mature and on the main periphery of main phases of hydrocarbon formation. Based on the results of the Meem source rocks’ generative potential (GP), it may be inferred that non-generative rocks status of Meem source rocks due to GP values less than 2 mg HC/gm rock. Additionally, if the burial depth is sufficient to generate the necessary temperature and pressure, source rocks with extraordinarily high GP values of more than 10 mg Hc/g rock may serve as an efficient source rock for the Dahamr Ali-01 well. On the other hand Lam source rock is classified as moderate source rocks. Non-generative potential has been reported from Lam source rock in Himyar-01 well where the GP is less than 1 mg HC/g rock. The cross-plots of pyrolysis characteristics, such as HI versus Tmax (modified van Krevelen diagram) and TOC vs S2, which are most likely the result of deposition of more terrigenous type III organic materials derived from terrestrial in the study area, can be used to determine the kerogen type for Lam and Meem source units. The analysis of Meem source rocks demonstrated that they are typically plotted in the mature zone; however samples of Lam source rocks proved that they have been still immature, merely marginally mature in the Dahamr Ali-01 and Saba-01 wells.
