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The section Cryptogamia-Lichenes of the Herbarium Universitatis Taurinensis (TO) includes ca. 34,600 lichen specimens, organised in the historical (ca. 30,700 specimens, mostly from the 19th century) and modern (ca. 3,900 specimens collected from 1978, out of which ca. 3400 from Italy) collections. Specimens from the administrative regions of Piemonte and Valle d’Aosta (NW Italy) are the core of the modern collection, documenting floristic and vegetation studies, as well as biomonitoring campaigns and investigations on the biodeterioration of the stone cultural heritage.The dataset of the Italian materials of the modern lichenological collection of TO, with 3,365 samples, is fully georeferenced and accessible in the Global Biodiversity Information Facility (GBIF), in the Jointly Administered Herbarium Management System and Specimen Database (JACQ) and in the Information System of Italian Lichens (ITALIC). With regard to the historical collection, only a set of 59 recently revised specimens is available on the mentioned platforms, but most of the materials are accessible as digital images on the website of the project HERB-TO-CHANGE.

Brazil is among the world’s top beef producers and exporters, and the Montana breed of livestock has gained popularity due to its exceptional meat quality and ability to adapt to the tropical climate. This differentiates it from other breeds, such as the Zebu and Taurine. A methodology that mapped sixteen farms across five Brazilian states was adopted to investigate the link between SNP genetic data and animal collection location. The data was georeferenced using the Geographic Information System and the ArcGIS 10.3 software, considering a geographic coordinate system and the WGS 84 datum. The Alleles in Space (AIS) software was used to study the relationship between the SNP genetic data and the animal collection location. Various analyses were conducted, including the Mantel correlation, genetic barrier identification, and spatial autocorrelation. The results suggest that there is a correlation between genetic and geographical distances, supporting the idea that geographical distance can affect genetic diversity. This information is vital to understand the genetic structure of populations concerning geographical space and is crucial for optimizing Brazilian agricultural production. [ABSTRACT FROM AUTHOR]

This work shows the original projection of a 1:57,600 scale map of southern Germany at the end of the 18th century, produced under the direction of Karl-Heinrich von Schmitt (1743–1805). The sections of the map were scanned and georeferenced as part of the MAPIRE project, and the results are publicly available. In the present work, we use contemporary documents, in particular the books of César-Francois Cassini de Thury and manuscript sketches of the map found in the Military Archive of Vienna, to show that the overall projection of the map is identical to that used in Cassini's survey of France (first half of the 18th century). In the archive, we managed to find the overview sheet on which—in addition to the Paris Cassini coordinate system—the section grid of the Schmitt map was also constructed. This sketch served as the basis for the compilation and copying work, wherein the existing map works and survey sketches were inserted into 197 sections of the Schmitt map. Thus, the map coordinate system can be modeled in GIS systems using the Cassini (or Cassini-Soldner) projection, with the Paris Observatory as the projection origin. The georeferencing accuracy of using the pure Cassini projection is around 1–1.3 km (at the extremes, around 5 km), which is much more inaccurate than the one used in later topographic surveys. It is considered a combined result of the compilation of the different maps, presumably surveyed by graphic triangulation with measuring tables. [ABSTRACT FROM AUTHOR]

Aquatic ecosystems are crucial in preserving biodiversity, regulating biogeochemical cycles, and sustaining human life; however, their resilience against climate change and anthropogenic stressors remains poorly understood. Recently, unmanned aerial vehicles (UAVs) have become a vital monitoring tool, bridging the gap between satellite imagery and ground-based observations in coastal and marine environments with high spatial resolution. The dynamic nature of water surfaces poses a challenge for photogrammetric techniques due to the absence of fixed reference points. Addressing these issues, this study introduces an innovative, efficient, and accurate workflow for georeferencing and mosaicking that overcomes previous limitations. Using open-source Python libraries, this workflow employs direct georeferencing to produce a georeferenced orthomosaic that integrates multiple UAV captures, and this has been tested in multiple locations worldwide with optical RGB, thermal, and multispectral imagery. The best case achieved a Root Mean Square Error of 4.52 m and a standard deviation of 2.51 m for georeferencing accuracy, thus preserving the UAV's centimeter-scale spatial resolution. This open-source workflow represents a significant advancement in the monitoring of marine and coastal processes, resolving a major limitation facing UAV technology in the remote observation of local-scale phenomena over water surfaces. [ABSTRACT FROM AUTHOR]

Increasing productivity without jeopardizing the network's operation, consumers' experience, and the safety and integrity of procedures, is a major goal for all utilities. Scheduling of work has a direct impact on productivity, especially in the case of utilities that cover a wide geographical area using a limited number of employees. In the case of power utilities, however, scheduling has to consider, apart from the location of issues, the type and technical characteristics of each issue as well as its priority has to be considered in order to produce an optimum schedule. This paper focuses on the impact on productivity of a geospatial ticket management system considering the experience from such a system applied on network studies performed by HEDNO, the Greek Distribution Network Operator, in Patras Area. The term "network studies" is used to describe the study of all expansion and alteration works, ranging from a single Low Voltage (LV) pole installation to major Medium Voltage (MV) network rearrangements/expansion, and includes visits and measurements on the actual location as well as in-door calculations. In Patras Area, the local HEDNO division implemented in 2021-2022 a geospatial ticket managing system, based on available network data and custom Google Maps, aiming to increase its productivity by optimizing the scheduling process. Initial results published in February 2022, showed a significant productivity increase (up to 42%). However, the initial results considered a time span of only one month and thus could easily be misleading. This paper revisits the issue considering a larger time span (more than two years) that should provide more trustworthy results. It also briefly presents the latest updates and improvements made to the system. Results show that the increase in the number of studies and their predicted costs are similar to the initial results, with the increase in productivity being around 41%. In September 2022, HEDNO set the very ambitious goal of significantly increasing the overall production of network studies (more than double in terms of predicted costs) and the use of such a system can provide valuable help towards achieving this goal. [ABSTRACT FROM AUTHOR]

The "Herbarium Universitatis Tergestinae" (TSB), with a total of ca. 50,000 specimens, includes the largest modern collection of lichens in Italy, with 25,796 samples collected from all over the country since 1984, representing 74% of all taxa known to occur in Italy. Almost all specimens have been georeferenced “a posteriori”. The dataset is available through GBIF, as well as in ITALIC, the Information System of Italian Lichens.The TSB Herbarium hosts the largest modern lichen collection in Italy, with a total of ca. 50,000 specimens. This dataset contains all of the 25,796 specimens collected within the administrative borders of Italy. Amongst them, 98% are georeferenced and 87% have the date of collection. The dataset includes several type specimens (isotypes and holotypes) and exsiccata.

Map mosaics of the First Military Survey showing Lower Austria and Hungary (two separate zones and coordinate systems of 1:28,800 survey sections) were georeferenced. Compared to the previous fitting carried out in the framework of the publicly available MAPIRE project, an attempt was made here to determine the true native projections, despite the assumption, according to the literature, that these map works have no real geodetic basis and no real cartographic projection. In the case of Lower Austria, the native coordinate system of the Brno–Wien–Varaždin degree measurement of Father Joseph Liesganig, the Cassini projection centred on Stephansdom in Vienna, proved to be the survey's own projection. In Hungary, in addition to the centre of a similar degree measurement, a fundamental point of the also documented Budapest-surrounding network of Colonel Neu proved to be a possible starting point of the Cassini projection used. Thus, with these centres, the Cassini projection is a good mathematical model for the native coordinate system of the surveys in these provinces. This achievement opens the possibility of better georeferencing of old maps of the survey, providing a database of land use and environmental change analyses and a step forward in understanding the survey technology of the 18th century. [ABSTRACT FROM AUTHOR]

Archival aerial photographs are among the most common, voluminous, and frequently used collections in map and geography libraries because of the unique and important spatial information that they contain. They are, however, an underutilized resource because they are challenging to work with and due to misconceptions about their quality. Therefore, developing efficient workflows to convert archival aerial photographs into research-quality digital spatial data is an important next step in making them accessible to a broad range of potential users. The present study tested three software to georeference, orthorectify, and mosaic 15 digitized archival photographs. Using positional accuracy and aesthetics of output mosaics as measures of software performance, all three completed the task impressively well. Output image spatial resolution and positional accuracy were found to be comparable to common public-domain contemporary aerial photography datasets like those produced by the National Agricultural Imagery Program. We also assessed software ease of use by geospatial professionals who were not trained photogrammetrists and found all three to be accessible with care and training resources. The software tools to efficiently convert archival aerial photographs into research-quality digital spatial data have finally matured to the point where collection managers can reasonably consider collection scale conversion projects. [ABSTRACT FROM AUTHOR]

In this research, we investigated the variability of soil moisture on two slopes of opposite aspect (a northern slope and a southern slope) but with the same soil type. To identify the spatial disposal of the soil type on both slopes, we georeferenced the paper-based soil map of Sfântu Gheorghe, using the QGIS platform. In order to use the correct slope aspect, we used a numerical model of the terrain (relief). The research plot was soil sampled at the depth of 10 cm on two different dates: on 7 November 2019 and on 3 March 2020, using a Buerkle soil sampler.

The need to ensure the long-term ability of power distribution systems to meet demands means that upgrades and alterations/expansions, as well as inspection and maintenance works, are constantly necessary. This paper presents an approach to use custom Google Maps as a ticket management system for scheduling and monitoring such works. A geospatial representation is rather useful in networks that are great in length and follow irregular routes (which is typically the case for power distribution networks). However, acquiring a representation of such networks, especially for the Low Voltage side, is an enormous task. This paper presents a cost-free and easy-to-implement approach that can be used in the absence of a full geospatial representation of the network. This approach utilizes an assign-to-the-feeding-transformer (for all Low Voltage issues) and assign-one-indicating-point (for each Middle Voltage issue) scheme, thus, requiring a minimum amount of data easily retrieved from the network. This approach provides a georeferenced ticket management system that can be employed for improved monitoring and scheduling through a user-friendly and free-to-use web-based application which use requires no additional costs or training. The presented approach has been applied in the area of Patras, Greece and initial results, showing a significant improvement in productivity, ranging from 10% to 42%, are further presented and discussed in this paper along with background information. [ABSTRACT FROM AUTHOR]

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The article concerns the transformation of the nineteenth--century cadastral map in the cadastral coordinate system to the current Polish national coordinate system (PL-1992, EPSG:2180). This map provides source information on land ownership and shows the state of topography nearly 200 years ago. The task of changing the georeferencing was performed for its sections covering the area of Krakow, using information on the cadastral system in Western Galicia and the Krakow local coordinate system (ULK). A single-step algorithm is proposed and can be used to transform coordinates from the Krakow area. In particular, it can be used to georeference sections of a cadastral map. The advantage is its independence from unchanged topographic points. These points are either difficult to determine or there are few of them in that area. The accuracy of the coordinate transformation model is at the level of 30 cm and the actual accuracy – is about 1 m. [ABSTRACT FROM AUTHOR]

Photogrammetry with unmanned aerial vehicles (UAVs) has become a source of data with extensive applications. The accuracy is of utmost significance, yet the intention is also to find the best possible solutions for data acquisition in economic terms. The objective of the research was the analysis of various variants of the bundle block adjustment. The analysis concerns data which is diversified with respect to the type of shutter (rolling/global), the measurement of external orientation elements, the overlap and the number of ground control points (GCPs). [ABSTRACT FROM AUTHOR]

Many studies in air, soil, and water research involve observations and sampling of a specific location. Knowing where studies have been previously undertaken can be a valuable addition to future research, including understanding the geographical context of previously published literature and selecting future study sites. Here, we introduce Literature Mapper, a Python QGIS plugin that provides a method for creating a spatial bibliography manager as well as a specification for storing spatial data in a bibliography manager. Literature Mapper uses QGIS' spatial capabilities to allow users to digitize and add location information to a Zotero library, a free and open-source bibliography manager on basemaps or other geographic data of the user's choice. Literature Mapper enhances the citations in a user's online Zotero database with geo-locations by storing spatial coordinates as part of traditional citation entries. Literature Mapper receives data from and sends data to the user's online database via Zotero's web API. Using Zotero as the backend data storage, Literature Mapper benefits from all of its features including shared citation Collections, public sharing, and an open web API usable by additional applications, such as web mapping libraries. To evaluate Literature Mapper's ability to provide insights into the spatial distribution of published literature, we provide a case study using the tool to map the study sites described in academic publications related to the biogeomorphology of California's coastal strand vegetation, a line of research in which air movement, soil, and water are all driving factors. The results of this exercise are presented in static and web map form. The source code for Literature Mapper is available in the corresponding author's GitHub repository: https://github.com/MicheleTobias/LiteratureMapper [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of this study was to explore spatial genetic structure patterns in cattle breeds adapted to local conditions in Brazil. We georeferenced 876 animals of ten breeds raised in Brazil kept in the Genebank of Brazilian Agricultural Research Corporation (Embrapa) by sample locations using the QGIS 2.4.0 software. The Mantel tests, spatial autocorrelation, and Monmonier tests were performed. The distances for spatial correlation tests ranged from 5 to 15 classes. The results indicated genetic discontinuities in cattle breeds from the Midwest, South, and Southeast of the country. Correlation between genetic and geographic distance was low, but significant. The Monmonier Maximum Distance Algorithm indicated an initial subdivision of Curraleiro and then Pantaneiro from the other breeds. In another subdivision, Criollo, Mocho Nacional, and Caracu were grouped. Genetic discontinuity was observed beyond 431 km, the minimum sampling distance between populations for conservation purposes.

Detecting traffic events and their locations is important for an effective transportation management system and better urban policy making. Traffic events are related to traffic accidents, congestion, parking issues, to name a few. Currently, traffic events are detected through static sensors e.g., CCTV camera, loop detectors. However they have limited spatial coverage and high maintenance cost, especially in developing regions. On the other hand, with Web 2.0 and ubiquitous mobile platforms, people can act as social sensors sharing different traffic events along with their locations. We investigated whether Twitter – a social media platform can be useful to understand urban traffic events from tweets in India. However, such tweets are informal and noisy and containing vernacular geographical information making the location retrieval task challenging. So far most authors have used geotagged tweets to identify traffic events which accounted for only 0.1%-3% or sometimes less than that. Recently Twitter has removed precise geotagging, further decreasing the utility of such approaches. To address these issues, this research explored how ungeotagged tweets could be used to understand traffic events in India. We developed a novel framework that does not only categorize traffic related tweets but also extracts the locations of the traffic events from the tweet content in Greater Mumbai. The results show that an SVM based model performs best detecting traffic related tweets. While extracting location information, a hybrid georeferencing model consists of a supervised learning algorithm and a number of spatial rules outperforms other models. The results suggest people in India, especially in Greater Mumbai often share traffic information along with location mentions, which can be used to complement existing physical transport infrastructure in a cost-effective manner to manage transport services in the urban environment. [ABSTRACT FROM AUTHOR]

Modern techniques for the map analysis allow for the creation of full or partial geometric reconstruction of its content. The projection is described by the set of estimated constant values: transformed pole position, standard parallel latitude, longitude of the central meridian, and a constant parameter. Analogously the analyzed map is represented by its constant values: auxiliary sphere radius, origin shifts, and angle of rotation. Several new methods denoted as M6-M9 for the estimation of an unknown map projection and its parameters differing in the number of determined parameters, reliability, robustness, and convergence have been developed. However, their computational demands are similar. Instead of directly measuring the dissimilarity of two projections, the analyzed map in an unknown projection and the image of the sphere in the well-known (i.e., analyzed) projection are compared. Several distance functions for the similarity measurements based on the location as well as shape similarity approaches are proposed. An unconstrained global optimization problem poorly scaled, with large residuals, for the vector of unknown parameters is solved by the hybrid BFGS method. To avoid a slower convergence rate for small residual problems, it has the ability to switch between first- and second-order methods. Such an analysis is beneficial and interesting for historic, old, or current maps without information about the projection. Its importance is primarily referred to refinement of spatial georeference for the medium- and small-scale maps, analysis of the knowledge about the former world, analysis of the incorrectly/inaccurately drawn regions, and appropriate cataloging of maps. The proposed algorithms have been implemented in the new version of the detectproj software.

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks’ distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

Child well-being is described as a social problem, such that in most cases social indicators defined by experts are used, without much input from local and heterogeneous communities. This article makes the case for an innovative way to monitor and explore child well-being globally, while also critiquing currently used indices. Based on Nussbaum’s Capabilities approach, we propose to formulate indices by using GIS and a comprehensive list of relevant geospatial datasets, using uniquely designed meta-layers and feature catalogues. Moreover, we argue that these geospatial data can be collected and mapped by the local communities, through participatory approaches, thus not relying on authoritative engagement and data. This will contribute to the empowerment of communities, making them relevant stakeholders with valued contribution to the process. This paper outlines preliminary work related to concepts and ideas, whereas future work is planned to develop an elaborate and comprehensive GIS model, and conduct further spatial analysis in the framework of a small scale campaign. [ABSTRACT FROM AUTHOR]

Advancements in computing capabilities over the last decade have allowed for the routine creation of Structure from Motion-Multiview Stereo (SfM-MVS) terrain models that can serve as base for high resolution geologic mapping. Outcrops models developed from these systems are high-resolution, photo-realistic 3D base providing unprecedented capability for geometric analysis. Yet, before this technology becomes a mainstay of field geology, the potential errors associated with it must be well understood. Here, we compare orientation measurements from multi-point analyses on the SfM-MVS point clouds to those taken in the field with the objective of resolving the geometry of complex folds within the outcrop. We also analyzed two point clouds of the same exposure created from different ground-based cameras to compare the ranges of error. We found that the point clouds produced from ground-based photos exhibited significant rigid-body rotation relative to the real world despite well distributed ground control, yet the models maintained a realistic scale and internal geometry. To correct the error the model values were rotated and the discrepancy reassessed. The two point clouds produced similar results, however, the Sony compact-digital-camera-based point cloud ultimately corresponded more closely to field values. We suggest that the primary cause of the error in the point clouds was GPS-based and was enhanced by the lack of significant topographic relief in our camera positions, allowing rigid-body rotations along the axis of the photographic array. This outcome suggests that care must be taken when GPS errors are a significant fraction of the outcrop size and relatively 2D outcrops imaged by a relatively 1D image array are subject to rotation errors that are difficult to remove without high-resolution ground control. Short of using a UAV and/or RTK-GPS we show how this can be resolved simply by collecting several known orientations in the field, which can then be used to orient the model more accurately, akin to ground control points. This addition is a key step if this method is to be used for more thorough analysis and is a general method that could be used to orient virtual outcrops with no geographic reference. [ABSTRACT FROM AUTHOR]

The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. Therefore, a near-real-time rapid georeference method for UAV remote sensing disaster data is proposed in this paper. The UAV images are achieved georeference combined with the position and attitude data collected by UAV flight control system, and the georeferenced data is organized by means of world file which is developed by ESRI. The C # language is adopted to compile the UAV images rapid georeference software, combined with Geospatial Data Abstraction Library (GDAL). The result shows that it can realize rapid georeference of remote sensing disaster images for up to one thousand UAV images within one minute, and meets the demand of rapid disaster response, which is of great value in disaster emergency application. [ABSTRACT FROM AUTHOR]