Search Results (31)

The generalization of nautical charts remains crucial in geographic information science and cartography. Traditional geometry-based methods have contributed to the advancement of automated generalization to a certain extent, but they still exhibit significant limitations in handling complex marine spatial relationships. This paper proposes the Graph Neural Network (GNN) as a transformative solution. GNN excels at processing non-Euclidean geospatial data, addressing the following three critical problems in the generalization of submarine terrain data: geographic feature representation, data processing, and the generalization process. The review first systematically outlines the main operators and fundamental methods of chart generalization. It analyzes their specific performance in various elements such as soundings, depth contours, islands, and coastlines. Subsequently, the potential of GNN is explored in addressing the limitations of traditional generalization methods. Although GNN is not a panacea, it shows advantages through horizontal and vertical comparisons. Finally, the challenges encountered in applying GNN to cartographic generalization are discussed. Full article

The advancement of computational tools for cartometric analysis has opened new avenues for the identification and understanding of stemmatic relationships between historical maps through the analysis of their planimetric distortions. The 19th-century Western cartographic depiction of Jerusalem serves as an ideal case study in this context. The challenges of conducting comprehensive onsite surveys—due to limited time and local knowledge—combined with the fascination surrounding the area’s representation, resulted in a proliferation of maps marked by frequent errors, distortions, and extensive copying. How can planimetric similarities and differences between maps be measured, and what insights can be derived from these comparisons? This paper introduces a methodology aimed at detecting and segmenting regions of local planimetric similarity across maps, corresponding to the portions that were either copied between them or derived from a common source. To detect these areas, the ground control points from the georeferencing process are employed to deform a common lattice grid for each map. These grids, triangulated to maintain shape rigidity, can be partitioned under conditions of geometric similarity, allowing for the segmentation and clustering of locally similar regions that represent shared areas between the maps. By integrating this segmentation with a filter on the intensity of distortion, the areas of the grid that are almost non-deformed, and thus not relevant for the study, can be excluded. To showcase the support this methodology offers for close reading, it is applied to the maps in the dataset depicting the Russian Compound. The methodology serves as a tool to assist in constructing the genealogy of the area’s representation and uncovering new historical insights. A larger dataset of 50 maps from the 19th century is then used to identify all the local predecessors of a given map, showcasing another application of the methodology, particularly when working with extensive collections of maps. These findings highlight the potential of computational cartometry to uncover hidden layers of cartographic knowledge and to advance the digital genealogy of map collections. Full article

Decarbonization strategies aim at increasing renewable energy source (RES) capacity, including new photovoltaic (PV) systems. Utility-scale PV installations are often placed in agricultural areas, resulting in a reduction in agricultural land and affecting the environment. To balance agricultural and energy policies, PV development should not limit agricultural purposes, allowing sustainable exploitation under specific technological and environmental conditions, particularly in areas of actual or potential abandonment. Studying agricultural abandonment is complex due to its multifaceted nature, the lack of a clear definition, and challenges in acquiring cartographic data. This study introduces and compares two methodologies to identify abandoned agricultural areas, aiming to delineate macro-areas of potential abandonment and examine patterns for conversion to energy use, with a focus on Toscana, a region (NUTS-2) in central Italy, which has experienced cropland reduction unrelated to urbanization. The first, simplified approach analyses land cover changes from 2000 to 2018, while the second method provides a more detailed abandonment detection by means of medium spatial resolution satellite imagery from the Harmonized Landsat and Sentinel-2 dataset. A Random Forest classifier combined with Object-Based Image Analysis (OBIA) is applied to satellite data to map annual active/non-active croplands. Annual maps are then validated with a trajectory-based approach to detect agricultural land abandonment. This second methodology can help in providing spatially and timely meaning estimates of abandoned agricultural areas to be recovered for energy purposes and promote a sustainable growth of PV systems. Full article

The understanding of species distribution in Peru is limited, in part due to cartographic representations that traditionally use political rather than biogeographical boundaries. The objective of this study was to determine the distribution of Arecaceae species in the department of Amazonas by representing them in biogeographical regions. To this end, geographic information systems and global databases were used to map and analyze the species in four categories: Ecosystems Map, Ecoregions Map, Peru Climate Classification Map, and Protected Natural Areas Map. Subsequently, diversity metrics were estimated, revealing high diversity in Amazonas, with 22 genera and 90 species of Arecaceae representing 51.16% and 41.28% of the records in Peru, respectively. In addition, predominant genera and species were identified, and diversity was evaluated in biogeographic units. Of a total of 336,029 records, 45 genera were found, with Geonoma and Bactris being the most representative, and of the 218 species found in total, the records that stood out the most varied according to biogeographical regions. For each Biogeographic unit by category, different responses were obtained, for example, for Index Margalef, between 0.000 (low in Agricultural Area), 7.2489 (medium in Eastern Cordillera Real Montane Forests), and 13.2636 (high in Non-protected Areas). Similarly, for the Shannon–Wiener diversity index ($\overline{H}$), where values were obtained between 0.000 (low in Jalca (Andean High Grasslands), (medium in Reserved Zonez) and 3.7054 (high in Non-protected Areas). The results suggest high under-recording, evidencing gaps in knowledge and information, as analyses based on detailed studies of diversity in specific biogeographic categories in these other families, as well as future research to determine, for example, genomes and Hill numbers, will be carried out. The conclusions highlight the high correlation between the diversity metrics analyzed, confirm the theoretical validity, and allow us to recommend species richness and the Margalef Index as useful and relevant metrics due to their applicability and ease of interpretation. This study offers key information for decision makers in policies for the conservation of Arecaceae diversity and motivates us to project research of this type in other families in Peru. Full article

The decline in the role of agriculture as the basis for the livelihood of rural residents has led to the development of new directions for rural transformation. In Poland, the concept of multifunctional development has gained the most popularity. However, it does not have a defined spatial development model. There has also been no research into how the development of non-agricultural functions affects spatial development and to what extent this development is sustainable. Therefore, the aim of this study is to show and compare the changes that have taken place over the last 40–50 years in the spatial arrangements of development in traditional agricultural villages and in villages with different non-agricultural functions (tourist, industrial, and service functions). At the same time, we want to indicate which of these functions have contributed to the development of the most sustainable spatial arrangements. To this end, we selected three indicators of sustainable development of rural space: compactness of buildings, continuation of traditional rural layouts, and availability of services, and then carried out an analysis of changes in these indicators on the basis of archival and current cartographic materials and data on service facilities. We conducted the research for four municipalities in eastern Poland (50 villages). The results indicate the predominance of negative spatial phenomena such as the deterioration of the accessibility of services and spatial development contrary to historical spatial layouts. There is a spillover of development in the form of discontinuous, chaotic clusters of buildings often having the character of suburbia and, consequently, the disappearance of village centres, worsening walkability, and blurring of village boundaries. The only positive change is an increase in the compactness of buildings—mainly in villages that previously had a dispersed character. It is difficult to identify village functions that would unequivocally favour spatial sustainability. The service villages showed slight advantages in terms of social (availability of services) and environmental (compactness of buildings) factors. In contrast, the development of agricultural villages was more favourable in cultural terms (traditional village layouts). In all aspects, negative changes were recorded in industrial villages and (the worst results) in tourist villages. However, the trends were similar in all municipalities, which draws attention primarily to the lack of a rational spatial policy related to multifunctional village development. Full article

The purpose of this article is to investigate the factors that influence the authenticity of heritage hotels in popular tourist destinations. Using the Greek island of Santorini as a case study, the following three (3) factors, which have not been systematically studied so far, are examined and appear to have a significant impact on authenticity in the conversion of a heritage architectural building into a heritage hotel: (a) its structural characteristics, (b) the influence of the star classification system and (c) the extent to which each business promotes authenticity elements and heritage identity. For the purposes of this study, a threefold methodological approach was conducted, which includes archival research in the registry of the Hellenic Chamber of Hotels for all the heritage hotels in Santorini (69 units), research in the accounting data of the island’s heritage hotels certified with the national star ranking system for their services and amenities and research analysis of the information regarding the promotion of the heritage hotels through their official websites. Additionally, a cartographic representation of the locations of these hotels was created and their positioning was compared to the boundaries of traditional or non-traditional settlements. The results validated the basic finding of the literature review, that the authenticity of a heritage hotel is a construction under constant negotiation, influenced by a multitude of factors. The conversion of a historic building into a heritage hotel is a multidimensional process that requires a delicate balance between preserving cultural value and adapting to the needs of modern tourism, as well as a continuous evaluation and review of the policies in place. Full article

Mato Grosso state is the biggest maize producer in Brazil, with the predominance of cultivation concentrated in the second harvest. Due to the need to obtain more accurate and efficient data, agricultural intelligence is adapting and embracing new technologies such as the use of satellites for remote sensing and geographic information systems. In this respect, this study aimed to map the second harvest maize cultivation areas at Canarana-MT in the crop year 2019/2020 by using geographic object-based image analysis (GEOBIA) with different spatial, spectral, and temporal resolutions. MSI/Sentinel-2, OLI/Landsat-8, MODIS-Terra and MODIS-Aqua, and PlanetScope imagery were used in this assessment. The maize crops mapping was based on cartographic basis from IBGE (Brazilian Institute of Geography and Statistics) and the Google Earth Engine (GEE), and the following steps of image filtering (gray-level co-occurrence matrix—GLCM), vegetation indices calculation, segmentation by simple non-iterative clustering (SNIC), principal component (PC) analysis, and classification by random forest (RF) algorithm, followed finally by confusion matrix analysis, kappa, overall accuracy (OA), and validation statistics. From these methods, satisfactory results were found; with OA from 86.41% to 88.65% and kappa from 81.26% and 84.61% among the imagery systems considered, the GEOBIA technique combined with the SNIC and GLCM spectral and texture feature discriminations and the RF classifier presented a mapping of the corn crop of the study area that demonstrates an improved and aided the performance of automated multispectral image classification processes. Full article

In this paper, two syntactic configurations are considered that involve V-to-C movement in present-day German: Verb Second in run-of-the-mill declarative clauses and Verb Second in non-assertive embedded contexts. Along the lines of the cartographic approach and on the basis of syntactic and semantic evidence, it is proposed that in both constructs, the finite verb targets neither Force° nor the head of any other projection hosting a moved constituent in its specifier, but, rather, that it moves into the lowest head in the extended CP layer, namely Fin°. As a result of this, (at least) two types of verb raising to Fin° are to be postulated in this language: one that is triggered by discourse/information structure (V2₁) and one that results from mechanical movement to C elicited by an otherwise lacking lexicalization of the relevant left-peripheral head (V2₂). Full article

To provide the population with food, it is very important to re-cultivate “abandoned lands” that have been retired from agricultural use. The conversion of arable land into agricultural abandoned lands in the south of Kazakhstan is, first of all, primarily associated with salinity. For the purposes of sustainable development, there is a need to develop proposals for re-mastering by studying their current state and reviewing world studies on the reclamation of salt-affected soils. Therefore, this study is devoted to the study of the current environmental and reclamation conditions of the abandoned areas of the Otyrar region in southern Kazakhstan. The proposed directions of changes in their development were also presented. In the course of the research, the historical method is used in the study of the emergence and formation of abandoned lands; the method of geographical analysis during the territorial analysis of the research object; the statistical and comparison methods in showing the complexity and intensity of the problems; the cartographic, geo-informational and field research (reconnaissance) methods in the study of the condition of the abandoned lands in the research object and methods of grouping and analysis were used in the work with scientific data on the topic of research. Using Sentinel-2 images, the GIS program created phenological dynamics of crops based on NDVI vegetation indices during the vegetation period of the irrigated range. By classifying them, abandoned lands due to salinization were separated from fields. By deciphering space images with the help of geoinformation technologies, it was revealed that the area of abandoned lands in the research object is 13,688.9 ha, including the area of non-saline soils—83.9 ha, weakly saline soils—984.4 ha, medium saline soils—2398.3 ha, and highly saline soils—10,222.1 ha. A review of the methods and technologies proposed by scientists for the development and amelioration of salt-affected lands was made. Taking into account the ecological and reclamation state of the object of research along with the material and technical capabilities of farms, two methods of developing abandoned lands (organic and agro-innovative) in the research object are proposed and the need for their use in case of soil salinization has been scientifically justified. Full article

Geoinformation and aerial data collection are essential during post-earthquake emergency response. This research focuses on the long-lasting spatial impacts of temporary solutions, which have persisted in regions of Central Italy affected by catastrophic seismic events over the past 25 years, significantly and permanently altering their landscapes. The paper analyses the role of geomatic and photogrammetric tools in documenting the emergency process and projects in post-disaster phases. An Atlas of Temporary Architectures is proposed, which defines a common semantic and geometric codification for mapping temporary housing from territorial to urban and building scales. The paper presents an implementation of attribute specification in existing official cartographic data, including geometric entities in a 3D GIS data model platform for documenting and digitalising these provisional contexts. To achieve this platform, UAV point clouds are integrated with non-metric data to ensure a complete description in a multiscalar approach. Accurate topographic modifications can be captured by extracting very high-resolution orthophotos and elevation models (DSM and DTM). The results have been validated in Visso (Macerata), a small historical mountain village in Central Italy which was heavily damaged by the seismic events of 2016/2017. The integrated approach overcomes the existing gaps and emphasizes the importance of managing heterogeneous geospatial emergency data for classification purposes. It also highlights the need to enhance an interoperable knowledge base method for post-disaster temporary responses. By combining geomatic tools with architectural studies, these visualization techniques can support national and local organizations responsible for post-earthquake management through a 3D modelling method to aid future transformations or interventions following other natural disasters. Full article

Physical urban boundaries (PUBs) are basic geographic information data for defining the spatial extent of urban landscapes with non-agricultural land and non-agricultural economic activities. Accurately mapping PUBs provides a spatiotemporal database for urban dynamic monitoring, territorial spatial planning, and ecological environment protection. However, traditional extraction methods often have problems, such as subjective parameter settings and inconsistent cartographic scales, making it difficult to identify PUBs objectively and accurately. To address these problems, we proposed a self-supervised learning approach for PUB extraction. First, we used nighttime light and OpenStreetMap road data to map the initial urban boundary for data preparation. Then, we designed a pretext task of self-supervised learning based on an unsupervised mutation detection algorithm to automatically mine supervised information in unlabeled data, which can avoid subjective human interference. Finally, a downstream task was designed as a supervised learning task in Google Earth Engine to classify urban and non-urban areas using impervious surface density and nighttime light data, which can solve the scale inconsistency problem. Based on the proposed method, we produced a 30 m resolution China PUB dataset containing six years (i.e., 1995, 2000, 2005, 2010, 2015, and 2020). Our PUBs show good agreement with existing products and accurately describe the spatial extent of urban areas, effectively distinguishing urban and non-urban areas. Moreover, we found that the gap between the national per capita GDP and the urban per capita GDP is gradually decreasing, but regional coordinated development and intensive development still need to be strengthened. Full article

The think-aloud method is a widely used method for evaluating the usability of websites and software. However, it can also be used with cartographic products, an area which has been neglected up to now. It is a method in which test participants verbalise all their thought processes aloud. The participants are given a test scenario containing tasks to be completed. The method aims to reveal the participants’ subjective attitudes toward a product in order to evaluate its usability. The present paper describes the use of the think-aloud method to evaluate the usability of a cartographic work—the regional atlas of the Moravian-Silesian Region. The study includes (I) a complete review of the method, based on the studies conducted; (II) testing tools for working with recorded data; (III) designing an experiment for evaluating the usability of the atlas; and (IV) the resulting qualitative and quantitative evaluation of the atlas based on the obtained results. During the study, three approaches were proposed to process and analyse the audio recordings. The first option was to separate the audio recordings into individual annotations and analyse them. The second option was to convert the recordings to text and perform a linguistic analysis. The third supplementary option was to use all the material produced and to analyse it subjectively and retrospectively, from the researcher’s perspective. All three options were used in the final assessment of the atlas. Based on the participants’ statements, any shortcomings in the studied atlas were identified for each topic (e.g., non-dominant maps or exceedingly complex infographics), and recommendations for their elimination were proposed. Full article

A crucial risk governance priority of the Greek forest managers is to reduce damages in the wildland–urban interface (WUI) by controlling wildfire behavior through fuel management practices. To support decisions for where management should be applied and how, this study experimented with new methods for fuel treatments allocation over a typical Mediterranean fire-prone landscape in the peninsula of Kassandra (an area of 350 km²), northern Greece. The Minimum Travel Time (MTT) fire simulation algorithm and the Treatment Optimization Model were used to produce eight spatial exclusionary and non-exclusionary datasets that were used as criteria for the spatial optimization of fuel management interventions. We used the Multicriteria Decisions Analysis method with Geographical Information Systems to cartographically intersect the criteria to produce two priority maps for two forest management scenarios (i.e., a control and a realistic one). The results revealed that 48 km² of the study area was characterized as high-priority locations in the control scenario (i.e., with equally weighted management priorities), while 60 km² was assigned to the high-priority class in the realistic scenario (i.e., with different weighted management priorities). Further analysis showed a substantial variation in treatment priority among the four major forest land cover types (broadleaves, sparse Mediterranean shrublands, conifers, and dense Mediterranean shrublands), revealing that the latter two had the highest selection values. Our methodological framework has already been operationally used by the Greek Forest Service branch of Kassandra to decide the most effective landscape fuel treatment allocation. Full article

Solid waste management represents a challenge for municipalities, particularly at the collection stage. The high costs involved in its operation make it difficult to provide the service in all its communities, which results in bad practices (burning, burying, or dumping into a river) and the proliferation of open dumps. Collection efficiency is aggravated by poor route planning, narrow road networks, and irregular scheduling. This research proposes and develops the following objectives: (1) an analysis of the technical and logistical conditions of a town, (2) an improved municipal route for waste collection, and (3) the practical implications identified in the optimization of the service (challenges, strategies, and perspectives). During the study period (2018, 2019 and 2021), the following steps were carried out: (1) field trips to monitor the formal and informal routes, georeferencing each stop with a global positioning system, (2) semi-structured interviews to route personnel to learn about technical and logistical aspects, (3) the downloading of cartographic data for digitization, and (4) a network analysis aimed at designing an optimal route for formal collection and the spatial scope of the informal routes. The current technical and logistical analysis detected inefficiency in collection due to weak municipal operational planning and the irregular frequency of visits to the locality. The locality produces an average of 2.8 tons per day and its largest volume is organic waste (68.3%), followed by non-recyclable inorganic waste (21.2%), and recyclable waste (10.5%). In terms of results for the optimization of the municipal collection route, it is estimated that there will be an improvement in the time of the day of approximately 2 h less, going through 95 points when its schedule is 60 collection points, while the distance factor does not suffer changes due to the fact that there are no alternate routes between the departure and destination route. Among the main challenges faced by the municipalities are the limited budgets for basic sanitation services, which is why technological strategies and trained human resources are required for better municipal solid waste management. From a technical perspective, geographic information systems are a current trend to model and optimize service routes, with which a better scenario can be proposed. From a social perspective, community participation works as a key factor to carry out activities focused on finding solutions to the problems related to municipal solid waste management. Full article

The selection of appropriative geomedia attributes for constructing natural and suggestive perspective visualizations of historical non-cartometric manuscript topographic works is investigated, to enable an intuitive perception of relief landforms. The main objective of the study is to demonstrate geomedia parameters for representing the third dimension in topographic watercolor maps from the eighteenth century, using cartographic rules and geoinformation operations for transforming graphic means of expression. The following methods were used: the choice of representative map fragments with specific painterly means of expression; the analysis of main relief forms on historical and modern maps; the rectification; vectorization of contour lines, and the transformation to a GRID model; the use of parameter variations: elevation rise, azimuth and altitude, contrast of illumination; and the creation of the final bird’s-eye-view visualization, with appropriate parameters. It is found that the parameters for the visualization of the non-cartometric water-colored topographic image on a 3D model can be selected in turn. However, what matters is maintaining their complementarity. The proposed parameters for the three maps work well for creating the general static bird’s-eye-view visualization, with the natural and suggestive perception of the landscapes’ relief. Full article