Relevant bibliographies by topics / Geospatial maps

Academic literature on the topic 'Geospatial maps'

Author: Grafiati
Published: 7 July 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Geospatial maps":

1

Kamimura, Kaito. "GSI Maps – Showcase of National Geospatial Data." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-158-2019.

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<p><strong>Abstract.</strong> Geospatial Information Authority of Japan (GSI), a special organization of the Ministry of Land, Infrastructure, Transport and Tourism (MLIT), operates web maps "GSI Maps" (https://maps.gsi.go.jp/) (Figure 1). GSI Maps is the showcase of geospatial information developed by GSI and can be used with various devices and web browsers. GSI Maps is one of GSI’s important efforts to realize a society that everyone can get and utilize geospatial information anytime, anywhere.</p>
2

Mogi, Hirosato. "The advancement of utilizing geospatial information via GSI Maps." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-252-2019.

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<p><strong>Abstract.</strong> The Geospatial Information Authority of Japan (GSI) is the national organization that has jurisdiction over the Survey Act, and develops geospatial information. We are also promoting utilization of them based on the Basic Act on the Advancement of Utilizing Geospatial Information. In addition, the Japanese government is promoting the Open Data initiative, in which the government widely discloses public data in machine-readable formats and allows secondary use of them. In accordance with these laws and initiative, we aim to realize a society where geospatial information can be widely and highly utilized by the disclosure of geospatial information. In order to achieve our mission, we are working on providing map data using “GSI Maps” (https://maps.gsi.go.jp/) which is a web map developed by using open source software (OSS) as the basis (Figure 1a). In this paper, we introduce “Three Open Policies” to promote utilizing geospatial information provided via GSI Maps.</p>
3

Xu, Haijiang, Tinghua Ai, Qingsheng Guo, and Yi Xiao. "From Maps to Geospatial Knowledge Graph: Geospatial Knowledge Representation and Reasoning." Abstracts of the ICA 6 (August 12, 2023): 1–2. http://dx.doi.org/10.5194/ica-abs-6-279-2023.

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Le, Phuong-Phi. "Patient access to opioid substitution treatment pharmacy and medical service providers in South Australia: geospatial mapping." Australian Journal of Primary Health 25, no. 2 (2019): 125. http://dx.doi.org/10.1071/py18099.

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This cross-sectional study geospatially maps patient access to opioid substitution treatment (OST) pharmacy and medical providers in South Australia (SA), Australia. De-identified data from a total of 2935 public and private OST patients (1092 public cases and 1843 private cases) were included in the study. Geospatial mapping of OST patient locations, their dosing community pharmacy and prescriber was undertaken. The geospatial modelling methods used in this study presents an application whereby information about patient travel patterns to reach OST providers can be used as a tool for treatment service planning.
5

Muthu, Sabarish Senthilnathan, Eleni Gkadolou, and Emmanuel Stefanakis. "Historical Map Collections on Geospatial Web." GEOMATICA 67, no. 3 (September 2013): 163–71. http://dx.doi.org/10.5623/cig2013-035.

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The Provincial Archives of New Brunswick (PANB) and the University of New Brunswick Archives (UNBA) maintain a rich collection of historical maps and plans of the City of Fredericton dating back to the 17th Century. This content is in the form of microfiches and paper maps, which are difficult to be accessed and used by researchers and educators. Recently, a series of microfiches and maps have been scanned and are already available in digital form. Going a step further, the advancements in geospatial web technology have been applied to make this digital content a valuable resource of historical information for the endusers. A prototype system has been developed and tested for a set of representative historical maps and plans. The system provides the following functionality: (a) geo-referenced scanned maps can be archived into a geospatial catalog; (b) appropriate metadata can be attached to them; (c) the maps can be superimposed and visualized on top of recent base maps (e.g., Google Maps, Bing Maps, Open Street Map); and (d) the catalog content can be searched and disseminated on the web using geospatial standards. End-users have been exposed to the prototype and evaluated its functionality. Their comments highlight the potential of the prototype in the study of cultural heritage and historical documentation.
6

Kong, Ningning Nicole. "One store has all? - the backend story of managing geospatial information toward an easy discovery." IASSIST Quarterly 42, no. 4 (February 22, 2019): 1–14. http://dx.doi.org/10.29173/iq927.

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Geospatial data includes many formats, varying from historical paper maps, to digital information collected by various sensors. Many libraries have started the efforts to build a geospatial data portal to connect users with the various information. For example, GeoBlacklight and OpenGeoportal are two open-source projects that initiated from academic institutions which have been adopted by many universities and libraries for geospatial data discovery. While several recent studies have focused on the metadata, usability and data collection perspectives of geospatial data portals, not many have explored the backend stories about data management to support the data discovery platform. The objective of this paper is to provide a summary about geospatial data management strategies involved in the geospatial data portal development by reviewing case studies. These data management strategies include managing the historical paper maps, scanned maps, aerial photos, research generated geospatial information, and web map services. This paper focuses on the data organization, storage, cyberinfrustracture configuration, preservation and sharing perspectives of these efforts with the goal to provide a range of options or best management practices for information managers when curating geospatial data in their own institutions.
7

Cherif, Mohamed Abderrazak, Sebastien Tripodi, Yuliya Tarabalka, Isabelle Manighetti, and Lionel Laurore. "Novel Approaches for Aligning Geospatial Vector Maps." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2-2024 (June 11, 2024): 55–64. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-2024-55-2024.

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Abstract. The surge in data across diverse fields presents an essential need for advanced techniques to merge and interpret this information. With a special emphasis on compiling geospatial data, this integration is crucial for unlocking new insights from geographic data, enhancing our ability to map and analyze trends that span across different locations and environments with more authenticity and reliability. Existing techniques have made progress in addressing data fusion; however, challenges persist in fusing and harmonizing data from different sources, scales, and modalities. This research presents a comprehensive investigation into the challenges and solutions in vector map alignment, focusing on developing methods that enhance the precision and usability of geospatial data. We explored and developed three distinct methodologies for polygonal vector map alignment: ProximityAlign, which excels in precision within urban layouts but faces computational challenges; the Optical Flow Deep Learning-Based Alignment, noted for its efficiency and adaptability; and the Epipolar Geometry-Based Alignment, effective in data-rich contexts but sensitive to data quality. In practice, the proposed approaches serve as tools to benefit from as much as possible from existing datasets while respecting a spatial reference source. It also serves as a paramount step for the data fusion task to reduce its complexity.
8

Hochmair, Hartwig, and Adam Benjamin. "Spatial Measurements on USGS Topo Maps." EDIS 2021, no. 1 (February 16, 2021): 7. http://dx.doi.org/10.32473/edis-fr433-2021.

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United States Geological Survey topographic maps provide a variety of geospatial measurement tools thanks to their built-in georeferencing capabilities. Georeferencing facilitates display of geographic coordinates and measurement of distances, perimeters, and areas on PDFs using the measure tools built into Adobe Reader and Adobe Acrobat. This 7-page fact sheet written by Hartwig H. Hochmair and published by the UF/IFAS School of Forest Resources and Conservation explains and showcases the use of these geospatial readout functions. It also provides background information about and assistance with estimating point coordinates on the Universal Transverse Mercator grid cast on USGS topographic maps as an optional layer.
9

Chuan Yin, Chuan Yin, Yanhui Wang Chuan Yin, Duoduo Yin Yanhui Wang, Wanzeng Liu Duoduo Yin, Hao Wu Wanzeng Liu, and Kexin Liu Hao Wu. "Rapid Production Method of Massive Thematic Maps Based on Geospatial Knowledge Extraction." 電腦學刊 35, no. 2 (April 2024): 285–301. http://dx.doi.org/10.53106/199115992024043502018.

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<p>Geospatial knowledge in massive academic papers can provide knowledge services such as location-based research hotspot analysis, spatio-temporal data aggregation, research results recommendation, etc. However, geospatial knowledge often exists implicitly in literature resources in unstructured form, which is difficult to be directly accessed and mined and utilized for rapid production of massive thematic maps. In this paper, we take the geospatial knowledge of the area studied as an example and introduce its extraction method in detail. An integrated feature template matching and random forest classification algorithm is proposed for accurately identifying research areas from the abstract texts of academic papers and producing thematic maps. Firstly, the precise recognition of geographical names is achieved step by step based on BiLSTM-CRF algorithm and improved heuristic disambiguation method; then, the area studied is extracted by the designed integrated feature recognition template of area studied using random forest classification algorithm, and a fast thematic map is designed for the knowledge of area studied, topic and literature. The experimental results show that the area studied recognition accuracy can reach 97%, the F-value is 96%, and the recall rate reaches 96%, achieving high accuracy and high efficiency of area studied extraction in text. Based on the geospatial knowledge, the thematic map can achieve the effect of fast map formation and accurate expression.</p> <p>&nbsp;</p>
10

Gaata, Methaq Talib. "Robust Watermarking Scheme for GIS Vector Maps." Ibn AL- Haitham Journal For Pure and Applied Science 31, no. 1 (May 10, 2018): 277. http://dx.doi.org/10.30526/31.1.1835.

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With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data. The digital map is separated into the isolated parts.Watermark data are embedded within the nominated magnitudes in each part when satisfied the definite criteria. The efficiency of proposed watermarking scheme is assessed within statistical measures based on two factors which are fidelity and robustness. Experimental results demonstrate the proposed watermarking scheme representing ideal trade off for disagreement issue between distortion amount and robustness. Also, the proposed scheme shows robust resistance for many kinds of attacks.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Geospatial maps":

1

Norwood, Carla Michele Holt Flora L. "Making maps that matter? the role of geospatial information in addressing rural landscape change /." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2009. http://dc.lib.unc.edu/u?/etd,2546.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2009.
Title from electronic title page (viewed Oct. 5, 2009). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Curriculum for the Environment and Ecology." Discipline: Anthropology; Department/School: Anthropology.
2

Kasperi, Johan. "Occlusion in outdoor Augmented Reality using geospatial building data." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204442.

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Creating physical simulations between virtual and real objects in Augmented Reality (AR) is essential for the user experience. Otherwise the user might lose sense of depth, distance and size. One of these simulations is occlusion, meaning that virtual content should be partially or fully occluded if real world objects is in the line-of-sight between the user and the content. The challenge for simulating occlusion is to construct the geometric model of the current AR environment. Earlier studies within the field have all tried to create realistic pixel-perfect occlusion and most of them have either required depth-sensing hardware or a static predefined environment. This study proposes and evaluates an alternative model-based approach to the problem. It uses geospatial data to construct the geometric model of all the buildings in the current environment, making virtual content occluded by all real buildings in the current environment. This approach made the developed function compatible with non depth-sensing devices and in a dynamic outdoor urban environment. To evaluate the solution it was implemented in a sensor-based AR application visualizing a future building in Stockholm. The effect of the developed function was that the future virtual building was occluded as expected. However, it was not pixel-perfect, meaning that the simulated occlusion was not realistic, but results from the conducted user study said that it fulfilled its goal. A majority of the participants thought that their AR experience got better with the solution activated and that their depth perception improved. However, any definite conclusions could not be drawn due to issues with the sensor-based tracking. The result from this study is interesting for the mobile AR field since the great majority of smartphones are not equipped with depth sensors. Using geospatial data for simulating occlusions, or other physical interactions between virtual and real objects, could then be an efficient enough solution until depth-sensing AR devices are more widely used.
För att uppnå en god användarupplevelse i Augmented Reality (AR) så är det viktigt att simulera fysiska interaktioner mellan de virtuella och reella objekten. Om man inte gör det kan användare uppfatta saker som djup, avstånd och storlek felaktigt. En av dessa simulationer är ocklusion som innebär att det virtuella innehållet ska vara delvis eller helt ockluderat om ett reellt objekt finns i siktlinjen mellan användaren och innehållet. För att simulera detta är utmaningen att rekonstruera den geometriska modellen av den nuvarande miljön.Tidigare studier inom fältet har försökt att uppnå en perfekt simulation av ocklusion, men majoriteten av dem har då krävt antingen djupavkännande hårdvara eller en statisk fördefinierad miljö. Denna studie föreslår och utvärderar en alternativ modellbaserad lösning på problemet. Lösningen använder geospatial data för att rekonstruera den geometriska modellen av alla byggnader i den nuvarande omgivningen, vilket resulterar i att det virtuella innehållet blir ockluderat av alla reella byggnader i den nuvarande miljön. Den utvecklade funktionen blev i och med det kompatibel på icke djupavkännande enheter och fungerande i en dynamisk urban miljö. För attutvärdera denna funktion så var den implementerad i en sensorbaserad AR applikation som visualiserade en framtida byggnad i Stockholm. Resultatet visade att den utvecklade funktionen ockluderade den virtuella byggnaden som förväntat. Dock gjorde den ej det helt realistiskt, men resultatet från den utförda användarstudien visade att den uppnådde sitt mål. Majoriteten av deltagarna ansåg att deras AR upplevelse blev bättre med den utvecklade funktionen aktiverad och ett deras uppfattning av djup förbättrades. Dock kan inga definitiva slutsatser dras eftersom AR applikationen hade problem med den sensorbaserade spårningen. Resultaten är intressant för det mobila AR fältet eftersom majoriteten av alla smartphones ej har stöd för djupavkänning. Att använda geospatial data för att simulera ocklusion, eller någon annan fysisk interaktion mellan virtuella och reella objekt, kan då vara en tillräckligt effektiv lösning tills djupavkännande AR enheter används mer.
3

Virinchi, Billa. "Data Visualization of Telenor mobility data." Thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13951.

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Nowadays with the rapid development of cities, understanding the human mobility patterns of subscribers is crucial for urban planning and for network infrastructure deployment. Today mobile phones are electronic devices used for analyzing the mobility patterns of the subscribers in the network, because humans in their daily activities they carry mobile phones for communication purpose. For effective utilization of network infrastructure (NI) there is a need to study on mobility patterns of subscribers.   The aim of the thesis is to simulate the geospatial Telenor mobility data (i.e. three different subscriber categorized segments) and provide a visual support in google maps using google maps API, which helps in decision making to the telecommunication operators for effective utilization of network infrastructure (NI).    In this thesis there are two major objectives. Firstly, categorize the given geospatial telenor mobility data using subscriber mobility algorithm. Secondly, providing a visual support for the obtained categorized geospatial telenor mobility data in google maps using a geovisualization simulation tool.    The algorithm used to categorize the given geospatial telenor mobility data is subscriber mobility algorithm. Where this subscriber mobility algorithm categorizes the subscribers into three different segments (i.e. infrastructure stressing, medium, friendly). For validation and confirmation purpose of subscriber mobility algorithm a tetris optimization model is used. To give visual support for each categorized segments a simulation tool is developed and it displays the visualization results in google maps using Google Maps API.   The result of this thesis are presented to the above formulated objectives. By using subscriber mobility algorithm and tetris optimization model to a geospatial data set of 33,045 subscribers only 1400 subscribers are found as infrastructure stressing subscribers. To look informative, a small region (i.e. boras region) is taken to visualize the subscribers from each of the categorized segments (i.e. infrastructure stressing, medium, friendly).    The conclusion of the thesis is that the functionality thus developed contributes to knowledge discovery from geospatial data and provides visual support for decision making to telecommunication operators. Nowadays with the rapid development of cities, understanding the human mobility patterns of subscribers is crucial for urban planning and for network infrastructure deployment. Today mobile phones are electronic devices used for analyzing the mobility patterns of the subscribers in the network, because humans in their daily activities they carry mobile phones for communication purpose. For effective utilization of network infrastructure (NI) there is a need to study on mobility patterns of subscribers.   The aim of the thesis is to simulate the geospatial Telenor mobility data (i.e. three different subscriber categorized segments) and provide a visual support in google maps using google maps API, which helps in decision making to the telecommunication operators for effective utilization of network infrastructure (NI).    In this thesis there are two major objectives. Firstly, categorize the given geospatial telenor mobility data using subscriber mobility algorithm. Secondly, providing a visual support for the obtained categorized geospatial telenor mobility data in google maps using a geovisualization simulation tool.    The algorithm used to categorize the given geospatial telenor mobility data is subscriber mobility algorithm. Where this subscriber mobility algorithm categorizes the subscribers into three different segments (i.e. infrastructure stressing, medium, friendly). For validation and confirmation purpose of subscriber mobility algorithm a tetris optimization model is used. To give visual support for each categorized segments a simulation tool is developed and it displays the visualization results in google maps using Google Maps API.   The result of this thesis are presented to the above formulated objectives. By using subscriber mobility algorithm and tetris optimization model to a geospatial data set of 33,045 subscribers only 1400 subscribers are found as infrastructure stressing subscribers. To look informative, a small region (i.e. boras region) is taken to visualize the subscribers from each of the categorized segments (i.e. infrastructure stressing, medium, friendly).    The conclusion of the thesis is that the functionality thus developed contributes to knowledge discovery from geospatial data and provides visual support for decision making to telecommunication operators.
4

Weiss, Jeremy, and Michael Crimmins. "DroughtView: Satellite-based Drought Monitoring and Assessment." College of Agriculture, University of Arizona (Tucson, AZ), 2017. http://hdl.handle.net/10150/625291.

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6 pp.
Remotely sensed data are valuable for monitoring, assessing, and managing impacts to arid and semi-arid lands caused by drought or other changes in the natural environment. With this in mind, we collaborated with scientists and technologists to redevelop DroughtView, a web-based decision-support tool that combines satellite-derived measures of surface greenness with additional geospatial data so that users can visualize and evaluate vegetation dynamics across space and over time. To date, users of DroughtView have been local drought impact groups, ranchers, federal and state land management staff, environmental scientists, and plant geographers. Potential new applications may include helping to track wildland fire danger. Here, we present the functionality of DroughtView, including new capabilities to report drought impacts and share map information, as well as the data behind it.
5

Hollinger, David L. "Crop Condition and Yield Prediction at the Field Scale with Geospatial and Artificial Neural Network Applications." Kent State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=kent1310493197.

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Kobakian, Stephanie Rose. "New algorithms for effectively visualising Australian spatio-temporal disease data." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/203908/1/Stephanie_Kobakian_Thesis.pdf.

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This thesis contributes to improvements in effectively communicating population related cancer distributions and the associated burden of cancer on Australian communities. This thesis presents a new algorithm for creating an alternative map displays of tessellating hexagons. Alternative map displays can emphasise statistics in countries that contain densely populated cities. It is accompanied by a software implementation that automates the choice of one hexagon to represent each geographic unit, ensuring the statistic for each is equitably presented. The case study comparing a traditional choropleth map to the alternative hexagon tile map contributes to a growing field of visual inference studies.
7

Palacios, Castro Harold Jesús Alberto, and Elias Kevin Jorge Pérez. "Implementación de bases geoespaciales para la vulnerabilidad sísmica de edificios de concreto armado." Bachelor's thesis, Universidad Ricardo Palma, 2015. http://cybertesis.urp.edu.pe/handle/urp/1323.

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Nuestro país se encuentra ubicado en una zona de alta actividad sísmica, por ello es importante que los ingenieros civiles tengan una adecuada capacidad para realizar análisis de vulnerabilidad sísmica y comprendan la importancia de la prevención. En la presente tesis analizamos los diferentes escenarios de daño sísmico para edificios de concreto armado organizados por tipología de número de pisos. Para el desarrollo de la presente investigación utilizamos dos Software, el primer software de simulación sísmica, en el cual modelamos la muestra de edificaciones de concreto armado que representan el distrito de Santiago de Surco, para luego analizarlo con un sismo de tiempo historia que simula varias magnitudes del mismo sismo amplificado con aceleraciones del suelo que varían de 0.1g a 1.0g, con el objetivo de obtener cada vez mayores desplazamientos, y de esa manera mayores niveles de daño mediante la metodología Hazus M-H. Luego estos valores expresarlos en cuadros de curvas de fragilidad sísmica con cuatro tipos de niveles de daño. El Segundo Software que utilizamos es el Sistema de Información Geográfica (SIG), con este programa sistematizamos los datos obtenido de la curva de fragilidad para mostrar mapas de niveles de daño para distintos escenarios sísmicos que muestren el comportamiento de los edificios al ocurrir un evento sísmico. Our country is located in a zone of high seismic activity, it is important that civil engineers have adequate capacity for analysis of seismic vulnerability and understand the importance of prevention. In this thesis we analyze the different scenarios of seismic damage to reinforced concrete buildings organized by type of number of floors. For the development of this research we use two software, the first seismic simulation software, which model the sample of reinforced concrete buildings representing Santiago de Surco, and then scan it with an earthquake simulating various weather history amplified earthquake magnitudes thereof with ground accelerations ranging from 1.0g 0.1ga, in order to obtain increasing displacement, and thus higher levels of damage by HAZUS MH methodology. Then these values express them in boxes seismic fragility curves with four types of damage levels. The second software we use is the Geographic Information System (GIS), with this program systematize data obtained fragility curve to display maps for different levels of damage scenarios showing the seismic performance of buildings to a seismic event occur.
8

Cherif, Mohamed Abderrazak. "Alignement et fusion de cartes géospatiales multimodales hétérogènes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ5002.

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L'augmentation des données dans divers domaines présente un besoin essentiel de techniques avancées pour fusionner et interpréter ces informations. Avec une emphase particulière sur la compilation de données géospatiales, cette intégration est cruciale pour débloquer de nouvelles perspectives à partir des données géographiques, améliorant notre capacité à cartographier et analyser les tendances qui s'étendent à travers différents lieux et environnements avec plus d'authenticité et de fiabilité. Les techniques existantes ont progressé dans l'adresse de la fusion des données ; cependant, des défis persistent dans la fusion et l'harmonisation des données de différentes sources, échelles et modalités. Cette recherche présente une enquête complète sur les défis et les solutions dans l'alignement et la fusion des cartes vectorielles, se concentrant sur le développement de méthodes qui améliorent la précision et l'utilisabilité des données géospatiales. Nous avons exploré et développé trois méthodologies distinctes pour l'alignement des cartes vectorielles polygonales : ProximityAlign, qui excelle en précision dans les agencements urbains; l'Alignement Basé sur l'Apprentissage Profond du Flux Optique, remarquable pour son efficacité ; et l'Alignement Basé sur la Géométrie Épipolaire, efficace dans les contextes riches en données. De plus, notre étude s'est penchée sur l'alignement des cartes de géometries linéaires, soulignant l'importance d'un alignement précis et du transfert d'attributs des éléments, pointant vers le développement de bases de données géospatiales plus riches et plus informatives en adaptant l'approche ProximityAlign pour des géometries linéaires telles que les traces de failles et les réseaux routiers. L'aspect fusion de notre recherche a introduit un pipeline sophistiqué pour fusionner des géométries polygonales en se basant sur le partitionnement d'espace, l'optimisation non convexe de la structure de données de graphes et les opérations géométriques pour produire une carte fusionnée fiable qui harmonise les cartes vectorielles en entrée, en maintenant leur intégrité géométrique et topologique. En pratique, le cadre développé a le potentiel d'améliorer la qualité et l'utilisabilité des données géospatiales intégrées, bénéficiant à diverses applications telles que la planification urbaine, la surveillance environnementale et la gestion des catastrophes. Cette étude avance non seulement la compréhension théorique dans le domaine mais fournit également une base solide pour des applications pratiques dans la gestion et l'interprétation de grands ensembles de données géospatiales
The surge in data across diverse fields presents an essential need for advanced techniques to merge and interpret this information. With a special emphasis on compiling geospatial data, this integration is crucial for unlocking new insights from geographic data, enhancing our ability to map and analyze trends that span across different locations and environments with more authenticity and reliability. Existing techniques have made progress in addressing data fusion; however, challenges persist in fusing and harmonizing data from different sources, scales, and modalities.This research presents a comprehensive investigation into the challenges and solutions in vector map alignment and fusion, focusing on developing methods that enhance the precision and usability of geospatial data. We explored and developed three distinct methodologies for polygonal vector map alignment: ProximityAlign, which excels in precision within urban layouts but faces computational challenges; the Optical Flow Deep Learning-Based Alignment, noted for its efficiency and adaptability; and the Epipolar Geometry-Based Alignment, effective in data-rich contexts but sensitive to data quality. Additionally, our study delved into linear feature map alignment, emphasizing the importance of precise alignment and feature attribute transfer, pointing towards the development of richer, more informative geospatial databases by adapting the ProximityAlign approach for linear features like fault traces and road networks. The fusion aspect of our research introduced a sophisticated pipeline to merge polygonal geometries relying on space partitioning, non-convex optimization of graph data structure, and geometrical operations to produce a reliable fused map that harmonizes input vector maps, maintaining their geometric and topological integrity.In practice, the developed framework has the potential to improve the quality and usability of integrated geospatial data, benefiting various applications such as urban planning, environmental monitoring, and disaster management. This study not only advances theoretical understanding in the field but also provides a solid foundation for practical applications in managing and interpreting large-scale geospatial datasets
9

Liu, Yung-I. "The Influence of Communication Context on Political Cognition in Presidential Campaigns: A Geospatial Analysis." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1211994930.

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Fombuena, Valero Arnau. "Geospatial Social Network lnnovation Assessment of the Spanish Higher Education." Doctoral thesis, Universitat Politècnica de València, 2018. http://hdl.handle.net/10251/107943.

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El contexto actual es el de una crisis en la Unión Europea, especialmente en los países del sur. Para acabar con la crisis, la Unión Europea elaboró la estrategia Horizon2020 que se centra en la innovación para abordar los desafíos socio-económicos. La innovación tiene un impacto en la sociedad y por tanto también sobre el territorio en el que habitan las personas que forman dicha sociedad. El empleo de la perspectiva geoespacial permite llevar a cabo un tipo de análisis que es raramente utilizado por los expertos en Educación Superior que suelen centrarse en metodologías puramente estadísticas. El objetivo principal de esta tesis es el desarrollo de un modelo que utiliza los Sistemas de Información Geográfica para evaluar la innovación desde el punto de vista de las universidades y el territorio. Además, a través de la aplicación de ese modelo para el caso específico de la innovación producida por las universidades españolas que forman parte de la Conferencia de Rectores de las Universidades Españolas en el año 2015, un segundo objetivo es identificar patrones y tendencias que puedan revelar nueva información. Los resultados muestran dichos patrones así como la posibilidad de mejorar los métodos actuales de evaluación de la innovación. El modelo presentado en esta tesis provee una solución para entender mejor las redes de innovación y su efecto en el territorio. En el caso específico estudiado, la evaluación provee una solución que es fácil de entender para las personas responsables de la toma de decisiones en cada una de las provincias españolas. Estas personas pueden identificar qué tipo de instituciones promueven la innovación y dónde se encuentran, qué conexiones tienen y cómo mejorar los resultados de innovación a través de la identificación de socios significativos. Además, la financiación de investigación e innovación podría dirigirse mejor hacia aquellas instituciones con mayor potencial de innovación.
The current context is one of crisis in the European area, especially in the southern countries. To put an end to the crisis, the European Union elaborated the Horizon 2020 strategy focusing on innovation to tackle the socio-economic challenges. Innovation has an impact on society and, as a result on the territory inhabited by the people forming such society. Employing a geospatial perspective allows performing a type of analysis that is seldom approached by higher education experts, who tend to focus on purely statistical methodologies. The main goal of this dissertation is the development of a model that uses GIS for innovation assessment from the perspective of universities and the territory. Then, through application of the model for the case of the assessment of innovation produced by the Spanish universities listed in CRUE in the year 2015, the secondary goal is to identify patterns that may unearth new significant information. The results show spatial patterns and the potential of improving the current methods of assessing innovation. The model presented in this thesis does provide an innovative solution to better understand innovation networks and their effect on the territory. In the specific case studied, the assessment provides an easy-to-understand solution for decision makers in the different provinces. The decision makers can then identify what type of institutions are driving innovation and where they are located, what connections they have and how to improve their innovation results through the identification of significant partners. Furthermore, the funding for research and innovation could be better directed towards those institutions with the higher potential.
El context actual és el d'una crisi a la Unió Europea, especialment als països del sud. Per acabar amb la crisi, la Unió Europea va elaborar l'estratègia Horizon2020 que es centra en la innovació per afrontar els desafiaments socio-econòmics. La innovació té un impacte en la societat i per tant també sobre el territori en el que habiten les persones que formen eixa societat. L'ús de la perspectiva geoespacial permet realitzar un tipus d'anàlisi que és rarament utilitzat pels experts en Educació Superior que solen centrar-se en metodologies purament estadístiques. L'objectiu principal d'aquesta tesi és el desenvolupament d'un model que utilitza els Sistemes d'Informació Geogràfica per avaluar la innovació des del punt de vista de les universitats i el territori. A més, a través de l'aplicació d'aquest model per al cas específic de la innovació produïda per les universitats espanyoles que formen part de la Conferència de Rectors de les Universitats Espanyoles durant l'any 2015, un segon objectiu és identificar patrons i tendències que puguen mostrar nova informació. Els resultats mostren aquests patrons així com la possibilitat de millorar els mètodes actuals de l'avaluació de la innovació. El model presentat en aquesta tesi proveeix una solució per comprendre millor les xarxes d'innovació i el seu efecte sobre el territori. Al cas específic estudiat, l'avaluació ofereix una solució que és fàcil de comprendre per a les persones responsables de la presa de decisions en cadascuna de les províncies espanyoles. Aquestes persones poden identificar quins tipus d'institucions promouen la innovació i on es troben, quines connexions tenen i com millorar els resultats d'innovació a través de la identificació de socis significatius. A més, el finançament d'investigació podria dirigir-se millor cap aquelles institucions amb major potencial d'innovació.
Fombuena Valero, A. (2018). Geospatial Social Network lnnovation Assessment of the Spanish Higher Education [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/107943
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Books on the topic "Geospatial maps":

1

Ohio Geographically Referenced Information Program., ed. Contacts for geospatial data sets of Ohio, 1997. Columbus: Ohio Geographically Referenced Information Program, 1997.

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Baker, Nancy T. National Stream Quality Accounting Network and National Monitoring Network Basin Boundary Geospatial Dataset, 2008-13. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2011.

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Stefanakis, Emmanuel. An introduction to web mapping & geospatial web services. North Charleston: CreateSpace Independent Publishing Platform, 2015.

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Rogerson, Peter. Statistical detection and surveillance of geographic clusters. Boca Raton: Chapman & Hall/CRC, 2009.

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Workshop National Geospatial Data Infrastructure: Towards a Road Map for India (2001 New Delhi, India). Workshop National Geospatial Data Infrastructure: Towards a Road Map for India, 5-6 February 2001, New Delhi India. Noida: Centre for Spatial Database Management and Solutions, 2001.

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Foody, Giles, Peter Mooney, Cidália Costa Fonte, Ana Maria Olteanu Raimond, Steffen Fritz, and Linda See, eds. Mapping and the Citizen Sensor. London, United Kingdom: Ubiquity Press, 2017.

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Anthamatten, Peter. How to Make Maps. Taylor & Francis Group, 2020.

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Anthamatten, Peter. How to Make Maps. Taylor & Francis Group, 2020.

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Anthamatten, Peter. How to Make Maps: An Introduction to Theory and Practice of Cartography. Taylor & Francis Group, 2020.

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Anthamatten, Peter. How to Make Maps: An Introduction to Theory and Practice of Cartography. Taylor & Francis Group, 2020.

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Book chapters on the topic "Geospatial maps":

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Del Rio, Nicholas, Paulo Pinheiro da Silva, Ann Q. Gates, and Leonardo Salayandia. "Semantic Annotation of Maps Through Knowledge Provenance." In GeoSpatial Semantics, 20–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-76876-0_2.

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Cartwright, William. "An Investigation of Maps and Cartographic Artefacts of the Gallipoli Campaign 1915: Military, Commercial and Personal." In Geospatial Visualisation, 19–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-12289-7_2.

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Kraak, Menno-Jan. "Maps of time." In The Routledge Handbook of Geospatial Technologies and Society, 541–53. London: Routledge, 2023. http://dx.doi.org/10.4324/9780367855765-44.

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Idrissi, Nisrine, Fatimazahra ElMadani, Meryem Idrissi, Mohammed Ben Abbou, Mustapha Taleb, and Zakia Rais. "The Effect of Surface Water Pollution on the Incidence of Viral Hepatitis: A Spatial Assessment Using GIS Maps." In Geospatial Technology, 69–81. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24974-8_5.

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Chiang, Yao-Yi, Muhao Chen, Weiwei Duan, Jina Kim, Craig A. Knoblock, Stefan Leyk, Zekun Li, et al. "GeoAI for the Digitization of Historical Maps." In Handbook of Geospatial Artificial Intelligence, 217–47. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003308423-11.

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Langran, Elizabeth, and Janine DeWitt. "Place-Based Learning, Geospatial Literacy, and Maps." In Navigating Place-Based Learning, 1–24. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55673-0_1.

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Roosens, Dieter, Kris McGlinn, and Christophe Debruyne. "Using Maps for Interlinking Geospatial Linked Data." In Lecture Notes in Computer Science, 209–26. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33246-4_14.

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Chen, Yang. "Urban Green Space Maps Based on GeoAI." In Handbook of Geospatial Approaches to Sustainable Cities, 75–93. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003244561-7.

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Bock, Fabian, Jiaqi Liu, and Monika Sester. "Learning On-Street Parking Maps from Position Information of Parked Vehicles." In Geospatial Data in a Changing World, 297–314. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33783-8_17.

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Déri, Andrea. "Maps, Knowledge and Resilience: Application of ArcGIS in Building Small Islands’ Resilience to Climate Change." In Geospatial Technologies and Climate Change, 137–74. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01689-4_9.

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Conference papers on the topic "Geospatial maps":

1

Dahiya, Manjeet, Devendra Samatia, and Kabir Rustogi. "Learning locality maps from noisy geospatial labels." In SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3341105.3373933.

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"YouthMap 5020! What should youth-centred web maps look like?" In GI_Forum 2014 - Geospatial Innovation for Society. Vienna: Austrian Academy of Sciences Press, 2015. http://dx.doi.org/10.1553/giscience2014s285.

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Ji, Cuiling, Yongkang Xiao, and Tianhe Chi. "Research on the key technologies of mobile digital maps." In Geoinformatics 2006: GNSS and Integrated Geospatial Applications, edited by Deren Li and Linyuan Xia. SPIE, 2006. http://dx.doi.org/10.1117/12.712931.

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Lee, Saro. "Integration of mineral potential maps from various geospatial models." In the 2nd International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1999320.1999373.

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Zhang, Jingyuan, and Hao Shi. "Geospatial Visualization using Google Maps: A Case Study onConference Presenters." In Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007). IEEE, 2007. http://dx.doi.org/10.1109/imsccs.2007.4392646.

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Zhang, Jingyuan, and Hao Shi. "Geospatial visualization using google maps: a case study on conference presenters." In Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007). IEEE, 2007. http://dx.doi.org/10.1109/imsccs.2007.9.

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Johnson-Roberson, Matthew, Mitch Bryson, Bertrand Douillard, Oscar Pizarro, and Stefan B. Williams. "Out-of-Core Efficient Blending for Underwater Georeferenced Textured 3D Maps." In 2013 4th International Conference on Computing for Geospatial Research & Application (COM.Geo). IEEE, 2013. http://dx.doi.org/10.1109/comgeo.2013.3.

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Guo, Tao, Kaiyu Feng, Gao Cong, and Zhifeng Bao. "Efficient Selection of Geospatial Data on Maps for Interactive and Visualized Exploration." In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3183713.3183738.

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Boulmay, B., Y. Gubanov, and D. Tishechkin. "Visualize OSDU™ Data with Geospatial Consumption Zone and No Code Maps." In Third EAGE Digitalization Conference and Exhibition. European Association of Geoscientists & Engineers, 2023. http://dx.doi.org/10.3997/2214-4609.202332033.

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Bakula, Krzysztof. "THE EFFECTIVE APPLICATION OF GEOSPATIAL DATA IN FLOOD HAZARD AND RISK MAPS CREATION." In 13th SGEM GeoConference on WATER RESOURCES. FOREST, MARINE AND OCEAN ECOSYSTEMS. Stef92 Technology, 2013. http://dx.doi.org/10.5593/sgem2013/bc3/s12.048.

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Reports on the topic "Geospatial maps":

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Giles Álvarez, Laura, Juan Carlos Vargas-Moreno, and Leonardo Pacheco Tenório Cavalcanti. Maps for Gaps: A Geospatial Approach to Estimating Development Gaps in Haiti. Inter-American Development Bank, December 2021. http://dx.doi.org/10.18235/0003811.

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This paper presents the results of a development gap analysis for Haiti using a geospatial approach. Gaps are calculated and characterized by means of qualitative and quantitative techniques, including macroeconomic, microeconomic, and geospatial data analyses. The analysis identifies, presents, and discusses 16 sectoral gaps. It is then expanded by overlapping the sectoral gaps to identify possible relations and spillover effects between them. The results suggest that transportation, early childhood education, and crime and insecurity gaps are the most significant in terms of the area and population affected. Results also show that 24 percent of the area of the country and 9.9 percent of Haitians are affected by nine or more overlapping gaps, particularly in the Nord-Ouest, Artibonite, and Centre departments. In terms of the links between sectors, crime and insecurity gaps tend to overlap with gaps in early childhood education and employment opportunities.
2

Lawley, C. J. M., P. Giddy, L. Katz, N. Chu, A. Francis, J. Carvajal, M. Pinheiro, et al. Canada geological map compilation. Natural Resources Canada/CMSS/Information Management, 2024. http://dx.doi.org/10.4095/pf995j5tgu.

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The Canada Geological Map Compilation (CGMC) is a database of previously published bedrock geological maps sourced from provincial, territorial, and other geological survey organizations. The geoscientific information included within these source geological maps was standardized, translated to English, and combined to provide complete coverage of Canada and support a range of down-stream machine learning applications. Detailed lithological, mineralogical, metamorphic, lithostratigraphic, and lithodemic information was not previously available as one national-scale product. The source map data was also enhanced by correcting geometry errors and through the application of a new hierarchical generalized lithology classification scheme to subdivide the original rocks types into 35 classes. Each generalized lithology is associated with a semi-quantitative measure of classification uncertainty. Lithostratigraphic and lithodemic names included within the source maps were matched with the Lexicon of Canadian Geological Names (Weblex) wherever possible and natural language processing was used to transform all of the available text-based information into word tokens. Overlapping map polygons and boundary artifacts across political boundaries were not addressed as part of this study. As a result, the CGMC is a patchwork of overlapping bedrock geological maps with varying scale (1:30,000-1:5,000,000), publication year (1996-2023), and reliability. Preferred geological and geochronological maps of Canada are presented as geospatial rasters based on the best available geoscientific information extracted from these overlapping polygons for each map pixel. New higher resolution geological maps will be added over time to fill data gaps and to update geoscientific information for future applications of the CGMC.
3

Lawley, C. J. M., P. Giddy, L. Katz, N. Chu, A. Francis, J. Carvajal, M. Pinheiro, et al. Canada geological map compilation. Natural Resources Canada/CMSS/Information Management, 2024. http://dx.doi.org/10.4095/332596.

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The Canada Geological Map Compilation (CGMC) is a database of previously published bedrock geological maps sourced from provincial, territorial, and other geological survey organizations. The geoscientific information included within these source geological maps was standardized, translated to English, and combined to provide complete coverage of Canada and support a range of down-stream machine learning applications. Detailed lithological, mineralogical, metamorphic, lithostratigraphic, and lithodemic information was not previously available as one national-scale product. The source map data was also enhanced by correcting geometry errors and through the application of a new hierarchical generalized lithology classification scheme to subdivide the original rocks types into 35 classes. Each generalized lithology is associated with a semi-quantitative measure of classification uncertainty. Lithostratigraphic and lithodemic names included within the source maps were matched with the Lexicon of Canadian Geological Names (Weblex) wherever possible and natural language processing was used to transform all of the available text-based information into word tokens. Overlapping map polygons and boundary artifacts across political boundaries were not addressed as part of this study. As a result, the CGMC is a patchwork of overlapping bedrock geological maps with varying scale (1:30,000-1:5,000,000), publication year (1996-2023), and reliability. Preferred geological and geochronological maps of Canada are presented as geospatial rasters based on the best available geoscientific information extracted from these overlapping polygons for each map pixel. New higher resolution geological maps will be added over time to fill data gaps and to update geoscientific information for future applications of the CGMC.
4

Cook, Samantha, Matthew Bigl, Sandra LeGrand, Nicholas Webb, Gayle Tyree, and Ronald Treminio. Landform identification in the Chihuahuan Desert for dust source characterization applications : developing a landform reference data set. Engineer Research and Development Center (U.S.), October 2022. http://dx.doi.org/10.21079/11681/45644.

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ERDC-Geo is a surface erodibility parameterization developed to improve dust predictions in weather forecasting models. Geomorphic landform maps used in ERDC-Geo link surface dust emission potential to landform type. Using a previously generated southwest United States landform map as training data, a classification model based on machine learning (ML) was established to generate ERDC-Geo input data. To evaluate the ability of the ML model to accurately classify landforms, an independent reference landform data set was created for areas in the Chihuahuan Desert. The reference landform data set was generated using two separate map-ping methodologies: one based on in situ observations, and another based on the interpretation of satellite imagery. Existing geospatial data layers and recommendations from local rangeland experts guided site selections for both in situ and remote landform identification. A total of 18 landform types were mapped across 128 sites in New Mexico, Texas, and Mexico using the in situ (31 sites) and remote (97 sites) techniques. The final data set is critical for evaluating the ML-classification model and, ultimately, for improving dust forecasting models.
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Baldos, Uris Lantz. Development of GTAP 9 Land Use and Land Cover Data Base for years 2004, 2007 and 2011. GTAP Research Memoranda, August 2017. http://dx.doi.org/10.21642/gtap.rm30.

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Understanding the challenges of achieving environmental sustainability goals given future demand for food, fiber and fuel requires economic models and databases that incorporate spatially explicit information on land use and land cover (LULC). The GTAP LULC database and its variants have been extensively used in a wide variety of applications aimed at examining the land-environment-energy nexus. Looking back the development of the first GTAP LULC was no simple task as it required the expertise of several researchers to identify and process relevant geospatial information. And because of this, succeeding updates of the GTAP LULC database (namely v.7 for 2004 and v.8 for 2004, 2007) relied heavily on AEZ-region level data from GTAP LULCv.6 in order to update land cover and land use as well as share-out land rents. This memorandum documents the development of the GTAP LULC v.9 database. In keeping with the multi-year release of GTAP v.9, the GTAP LULC v.9 data is developed for each benchmark year (i.e. 2004, 2007 and 2011). But unlike previous releases, GTAP LULCv.9 is created directly from publicly available high-resolution (i.e. 5-minute grid) spatial land cover and land use maps. Since these maps can be readily downloaded online, it is possible to replicate GTAP LULCv.9 if users know how to handle spatial data and if they follow the methods outlined in this document. Furthermore, by developing the capacity to handle spatial data within the Center, new spatial LULC information can be easily incorporated in future releases of the GTAP LULC.
6

Zandiatashbar, Ahoura, Jochen Albrecht, and Hilary Nixon. A Bike System for All in Silicon Valley: Equity Assessment of Bike Infrastructure in San José, CA. Mineta Transportation Institute, October 2023. http://dx.doi.org/10.31979/mti.2023.2162.

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Investing in sustainable, multimodal infrastructure is of increasing importance throughout the United States and worldwide. Cities are increasingly making strategic capital investment decisions about bicycle infrastructure—decisions that need planning efforts that accurately assess the equity aspects of developments, achieve equitable distribution of infrastructures, and draw upon accurate assessment methods. Toward these efforts, this project uses a granular bike network dataset with statistical and geospatial analyses to quantify a bike infrastructure availability score (i.e., bike score) that accounts for the safety and comfort differences in bike path classes in San José, California. San José is the 10th largest U.S. city and a growing tech hub with a booming economy, factors that correlate with increased traffic congestion if adequate multimodal and active transportation infrastructure are not in place. Therefore, San José has been keen on becoming “one of the most bike-friendly communities in North America.” The City’s new plan, which builds on its first bike plan adopted in 2009, envisions a 557-mile network of allages-and-abilities bikeways to support a 20% bicycle mode split (i.e., 20% of all trips to be made by bike) by 2050. Hence, San José makes a perfect study area for piloting this project’s methodology for accurately assessing the equity of urban bike plans and infrastructures. The project uses the above-mentioned bike score (representing the bike infrastructure supply status) and San José residents’ bike travel patterns (to show bike trip demand status) utilizing StreetLight data to answer the following questions: (1) Where are San José's best (bike paradise) and worst (bike desert) regions for cycling? (2) How different are the socioeconomic attributes of San José’s bike desert and paradise residents? (3) Has San José succeeded in achieving an equitable infrastructure distribution and, if so, to what extent? And, (4) has the availability of infrastructure attracted riders from underserved communities and, if so, to what extent? Using the bike infrastructure availability score, this research measures and maps the City of San José's best and worst regions for cycling through geospatial analyses to answer Question 1 above. Further spatial and statistical analyses including t-tests, Pairwise Pearson correlation analysis, descriptive analysis, spatial visualization, principal component analysis (PCA), and multiple regression models to answer Questions 2, 3, and 4. In addition to this report, the findings are used to develop an open access web-tool, the San José Bike Equity Web Map (SJ-BE iMap). This research contributes to the critical assessment and planning efforts of sustainable, multimodal infrastructure in California and beyond.
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Mbani, Benson, Timm Schoening, and Jens Greinert. Automated and Integrated Seafloor Classification Workflow (AI-SCW). GEOMAR, May 2023. http://dx.doi.org/10.3289/sw_2_2023.

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The Automated and Integrated Seafloor Classification Workflow (AI-SCW) is a semi-automated underwater image processing pipeline that has been customized for use in classifying the seafloor into semantic habitat categories. The current implementation has been tested against a sequence of underwater images collected by the Ocean Floor Observation System (OFOS), in the Clarion-Clipperton Zone of the Pacific Ocean. Despite this, the workflow could also be applied to images acquired by other platforms such as an Autonomous Underwater Vehicle (AUV), or Remotely Operated Vehicle (ROV). The modules in AI-SCW have been implemented using the python programming language, specifically using libraries such as scikit-image for image processing, scikit-learn for machine learning and dimensionality reduction, keras for computer vision with deep learning, and matplotlib for generating visualizations. Therefore, AI-SCW modularized implementation allows users to accomplish a variety of underwater computer vision tasks, which include: detecting laser points from the underwater images for use in scale determination; performing contrast enhancement and color normalization to improve the visual quality of the images; semi-automated generation of annotations to be used downstream during supervised classification; training a convolutional neural network (Inception v3) using the generated annotations to semantically classify each image into one of pre-defined seafloor habitat categories; evaluating sampling strategies for generation of balanced training images to be used for fitting an unsupervised k-means classifier; and visualization of classification results in both feature space view and in map view geospatial co-ordinates. Thus, the workflow is useful for a quick but objective generation of image-based seafloor habitat maps to support monitoring of remote benthic ecosystems.
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Evans, Julie, Kendra Sikes, and Jamie Ratchford. Vegetation classification at Lake Mead National Recreation Area, Mojave National Preserve, Castle Mountains National Monument, and Death Valley National Park: Final report (Revised with Cost Estimate). National Park Service, October 2020. http://dx.doi.org/10.36967/nrr-2279201.

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Vegetation inventory and mapping is a process to document the composition, distribution and abundance of vegetation types across the landscape. The National Park Service’s (NPS) Inventory and Monitoring (I&M) program has determined vegetation inventory and mapping to be an important resource for parks; it is one of 12 baseline inventories of natural resources to be completed for all 270 national parks within the NPS I&M program. The Mojave Desert Network Inventory & Monitoring (MOJN I&M) began its process of vegetation inventory in 2009 for four park units as follows: Lake Mead National Recreation Area (LAKE), Mojave National Preserve (MOJA), Castle Mountains National Monument (CAMO), and Death Valley National Park (DEVA). Mapping is a multi-step and multi-year process involving skills and interactions of several parties, including NPS, with a field ecology team, a classification team, and a mapping team. This process allows for compiling existing vegetation data, collecting new data to fill in gaps, and analyzing the data to develop a classification that then informs the mapping. The final products of this process include a vegetation classification, ecological descriptions and field keys of the vegetation types, and geospatial vegetation maps based on the classification. In this report, we present the narrative and results of the sampling and classification effort. In three other associated reports (Evens et al. 2020a, 2020b, 2020c) are the ecological descriptions and field keys. The resulting products of the vegetation mapping efforts are, or will be, presented in separate reports: mapping at LAKE was completed in 2016, mapping at MOJA and CAMO will be completed in 2020, and mapping at DEVA will occur in 2021. The California Native Plant Society (CNPS) and NatureServe, the classification team, have completed the vegetation classification for these four park units, with field keys and descriptions of the vegetation types developed at the alliance level per the U.S. National Vegetation Classification (USNVC). We have compiled approximately 9,000 existing and new vegetation data records into digital databases in Microsoft Access. The resulting classification and descriptions include approximately 105 alliances and landform types, and over 240 associations. CNPS also has assisted the mapping teams during map reconnaissance visits, follow-up on interpreting vegetation patterns, and general support for the geospatial vegetation maps being produced. A variety of alliances and associations occur in the four park units. Per park, the classification represents approximately 50 alliances at LAKE, 65 at MOJA and CAMO, and 85 at DEVA. Several riparian alliances or associations that are somewhat rare (ranked globally as G3) include shrublands of Pluchea sericea, meadow associations with Distichlis spicata and Juncus cooperi, and woodland associations of Salix laevigata and Prosopis pubescens along playas, streams, and springs. Other rare to somewhat rare types (G2 to G3) include shrubland stands with Eriogonum heermannii, Buddleja utahensis, Mortonia utahensis, and Salvia funerea on rocky calcareous slopes that occur sporadically in LAKE to MOJA and DEVA. Types that are globally rare (G1) include the associations of Swallenia alexandrae on sand dunes and Hecastocleis shockleyi on rocky calcareous slopes in DEVA. Two USNVC vegetation groups hold the highest number of alliances: 1) Warm Semi-Desert Shrub & Herb Dry Wash & Colluvial Slope Group (G541) has nine alliances, and 2) Mojave Mid-Elevation Mixed Desert Scrub Group (G296) has thirteen alliances. These two groups contribute significantly to the diversity of vegetation along alluvial washes and mid-elevation transition zones.
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Russell, David P., Todd Krokowski, and Chris Lawrence. Map Based Interface for Geospatial Product Library (MAP-GPL). Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada439954.

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Baldos, Uris Lantz, and Erwin Corong. Development of GTAP 10 Land Use and Land Cover Data Base for years 2004, 2007, 2011 and 2014. GTAP Research Memoranda, November 2020. http://dx.doi.org/10.21642/gtap.rm36.

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Abstract:
Understanding the challenges of achieving environmental sustainability goals given future demand for food, fiber and fuel requires economic frameworks that incorporate spatially explicit information on land use and land cover (LULC). The GTAP LULC Data Base and its variants have been extensively used in a wide variety of applications aimed at examining the land-environment-energy nexus (Golub et al., 2012; Hertel et al., 2010; Johnson et al., 2019; Liu et al., 2014; Peña-Lévano et al., 2019; Stevenson et al., 2013; Taheripour et al., 2010; Taheripour & Tyner, 2012). The first release of the GTAP LULC Data Base combines geospatial data on land use and land cover into GTAP 6 Data Base – benchmarked to year 2001 (GTAP LULC v6). The methodology for creating and using this database is well documented (Lee et al., 2009; C. Monfreda et al., 2009; Sohngen et al., 2008). Succeeding updates of the GTAP LULC Data Base (namely v7 and v8 for 2004 and v8 for 2004, 2007) relied on readily available but aggregated GTAP LULC v6, albeit using national-level data from FAOSTAT (2020) (Avetisyan et al., 2010; Baldos & Hertel, 2012). Starting with GTAP 9, LULC was created directly from the latest, high-resolution (i.e. 5-minute) spatial land cover and land use maps in combination with national-level statistics (Baldos, 2017). This memorandum documents the development of the GTAP LULC version10A which is based on the GTAP v10A Data Base for years 2004, 2007, 2011 and 2014 (Aguiar et al., 2019). This update heavily relies on the methodology for creating GTAP LULC v9 which downscales national-level land cover and crop production statistics from FAOSTAT (2020) using publicly available spatial data (see Appendix I).

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