Academic literature on the topic 'Mapping QGIS'
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Journal articles on the topic "Mapping QGIS"
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Vikhot, Yuriy, Solomiia Kril, and Ihor Bubniak. "DIGITAL GEOLOGICAL MAPPING AND GEODATA ANALYSIS USING TOOLS AND PLUGINS OF QGIS." SCIENTIFIC PAPERS OF DONNTU Series: “The Mining and Geology”, no. 1(27)-2(28)2022 (2022): 122–35. http://dx.doi.org/10.31474/2073-9575-2022-1(27)-2(28)-122-135.
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Purpose. The article aims is to demonstrate the possibilities, methods and advantages of using Quantum GIS (QGIS) plugins and mobile applications for digital geological mapping, input and primary analysis of field geodata in Earth Sciences – Structural Geology, Engineering Geology, Hydrogeology, Ecology, Geophysics, etc. Methodology. The most important tools and plugins of QGIS, an open source GIS program, that works on the most widespread platforms – Windows, MacOS X, Linux and applications on Android, iOS for digital mapping, structural geodata analysis, and visualization are used. Results. The most important tools and plugins of QGIS (Georeferencer GDAL, GarminCustomMap, Profile Tool, VoGIS-ProfilTool, qProf, qgSurf, Stereonet, qgis2web, and QField mobile application) are analyzed. Their using for digital geological mapping, input and analysis of structural and other geodata, construction of 2D topographic profiles, visualization of geodata in web browsers are briefly described. Scientific novelty. Tools and plugins of QGIS, which are necessary for certain purposes for working with various types of data on geological maps, their analysis, and construction of geological and geophysical profiles are defined. QGIS software applications allow to add new plugins, create your own notations for digital mapping that can be used to solve specific geological tasks and analyze geospatial and geological data, or add ready-made specialized geological notations according to geological standards. Practical significance. Complex using of basic, additional external plugins of QGIS and specialized geological markings contributes to effective field digital mapping, modern visualization of various types of geological maps with spatial reference, creation of new digital electronic and complex demonstration maps for printing and visualization in web browsers, construction topographic and geological 2D profiles, GIS analysis of structural geodata, slope analysis, etc. Data obtained in QGIS can be imported into such specialized programs as Petrel Exploration & Production Software Platform (Shlumberger), MOVE Software (Midland Valley), etc. Keywords: Quantum GIS or QGIS, QGIS tools and plugins, digital geological mapping, QField, GIS analysis of structural geodata, slope analysis.
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Fang, Zhe, Guoyan Jiang, Caijun Xu, and Shuai Wang. "A tectonic geodesy mapping software based on QGIS." Geodesy and Geodynamics 11, no. 1 (January 2020): 31–39. http://dx.doi.org/10.1016/j.geog.2019.08.001.
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Stuckey, Owen. "A Comparison of ArcGIS and QGIS for Animation." Cartographic Perspectives, no. 85 (June 22, 2017): 23–32. http://dx.doi.org/10.14714/cp85.1405.
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I compare two GIS programs which can be used to create cartographic animations—the commercial Esri ArcGIS and the free and open-source QGIS. ArcGIS implements animation through the “Time Slider” while QGIS uses a plugin called “TimeManager.” There are some key similarities and differences as well as functions unique to each plugin. This analysis examines each program’s capabilities in mapping time series data. Criteria for evaluation include the number of steps, the number of output formats, input of data, processing, output of a finished animation, and cost. The comparison indicates that ArcGIS has more control in input, processing, and output of animations than QGIS, but has a baseline cost of $100 per year for a personal license. In contrast, QGIS is free, uses fewer steps, and enables more output formats. The QGIS interface can make data input, processing, and output of an animation slower.
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Kelly, Brett. "Review of Unclassed Choropleth Mapping." Cartographic Perspectives, no. 86 (November 14, 2017): 30–35. http://dx.doi.org/10.14714/cp86.1424.
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Although unclassed choropleth maps lead to a more accurate representation of data, grouping of data into classes is still common. Commonly-used data classification techniques such as equal-interval, quantiles, and natural breaks produce very different and possibly misleading representations. An unclassed map creates a distinct color for each unique value. The method was introduced by Tobler in 1973 using an x, y coordinate plotter that created crossed-line shadings. Tobler’s unclassed proposal used grayscale values because color displays were not yet available. Current color monitors have the ability to display 16.7 million colors, while most GIS software packages have limits to their color ramps. QGIS defines color ramps with up to 999 classes. It is also possible to define up to 1000 classes in ArcMap, and ArcGIS Pro has an “Unclassed” option when styling choropleth maps. Utilizing more color classes results in a more truthful map due to minimizing error from the grouping of data. The unclassed method is examined here along with color ramps and classification schemes in QGIS and Esri’s ArcMap/ArcGIS Pro. It is demonstrated that it is usually impossible to create a truly unclassed choropleth map using the default color schemes in these programs.
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Singh, Manmohan, Alex Thomas, Vinay Khalko, and Vinay Kumar. "Flood hazard mapping using HEC-RAS and QGIS for Meja dam." International Journal of Chemical Studies 8, no. 5 (September 1, 2020): 2044–47. http://dx.doi.org/10.22271/chemi.2020.v8.i5ab.10604.
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Ioan Cimpianu, Catalin, and Alin Mihu-Pintilie. "OPEN SOURCE FLOOD MAPPING TOOLS – QGIS, RIVER GIS AND HEC-RAS." Acta Geobalcanica 6, no. 1 (September 1, 2019): 35–41. http://dx.doi.org/10.18509/agb.2020.04.
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Wijayanthi, Kanthi, Ahmad Basuki, and Frans Tohom. "Efektivitas Pemanfaatan QGIS Dalam Pembuatan Peta Inventarisasi Perlengkapan Jalan." Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) 8, no. 2 (November 25, 2021): 145–55. http://dx.doi.org/10.46447/ktj.v8i2.315.
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In the field of road traffic and transportation, road inventory activities are needed to monitor or monitor the condition of road equipment. The proper data collection will facilitate evaluation and supervision by managers or supervisors of traffic and road transportation. The data collection of road equipment inventory data can be compiled manually or electronically, which is integrated with the road equipment information system. One of the electronic data collections is by utilizing QGIS, which is one part of the Geographic Information System (GIS). This study aims to measure the effectiveness of using QGIS in making road equipment inventory maps using survey data and questionnaires to determine the difference between manual inventory data collection and WebGIS-based inventory data collection. Data analysis used SPSS calculation to test data validity, reliability, normality, Wilcoxon test and N-Gain Score test. From this data, it is found that the use of QGIS in road equipment inventory mapping has an average effectiveness of 60.26%, with the interpretation criteria being quite effective.
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G, Pradeepa, Sudha R.V., Dhivya Dharshini N, Niroja K, and Sri Praba S. "Network Coverage Mapping." Irish Interdisciplinary Journal of Science & Research 06, no. 02 (2022): 110–12. http://dx.doi.org/10.46759/iijsr.2022.6215.
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Mobile signal strength (coverage) maps are of great importance to cellular operators for network planning and operation are expensive to obtain, imperfectly reflective of call quality outcomes, and potentially constructed from biased samples. Users of smartphones utilize high-speed network services while commuting on public transit and hope to have a consistent, high-quality connection. Measuring and monitoring coverage and quality of service mean being able to assess reality and its representation. Data collection is a vital ingredient in this process. Finding Mobile signal strength and Mapping the Coverage areas using GIS through differentiating the Network. Due to the massive load demand on cellular networks and frequent changes in the underlying radio channel, users often experience sudden unexpected variations in the connection quality. To overcome variations, we create a Map to differentiate the signal strength with a regular update through the Received Signal Strength Indicator (RSSI) in QGIS Software using Python and XML plugins.
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Ollivier, Chloé, Yoann Lecomte, Konstantinos Chalikakis, Naomi Mazzilli, Charles Danquigny, and Christophe Emblanch. "A QGIS Plugin Based on the PaPRIKa Method for Karst Aquifer Vulnerability Mapping." Groundwater 57, no. 2 (January 31, 2019): 201–4. http://dx.doi.org/10.1111/gwat.12855.
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Agus, F., Ramadiani, W. Silalahi, A. Armanda, and Kusnandar. "Mapping urban green open space in Bontang city using QGIS and cloud computing." IOP Conference Series: Earth and Environmental Science 144 (April 2018): 012032. http://dx.doi.org/10.1088/1755-1315/144/1/012032.
Full textDissertations / Theses on the topic "Mapping QGIS"
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Ollivier, Chloé. "Caractérisation et spatialisation de la recharge des hydrosystèmes karstiques : Application à l'aquifère de Fontaine de Vaucluse, France A QGIS Plugin Based on the PaPRIKa Method for Karst Aquifer Vulnerability Mapping Challenges and Limitations of Karst Aquifer Vulnerability Mapping Based on the PaPRIKa Method—Application to a Large European Karst Aquifer (Fontaine de Vaucluse, France)." Thesis, Avignon, 2019. http://www.theses.fr/2019AVIG0056.
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La recharge des hydrosystèmes karstiques dépend des conditions climatiques, de la transpiration de la végétation, de l’évaporation des sols, des propriétés du sol et de l’hétérogénéité du karst. Elle dépend donc de nombreux facteurs variables dans le temps et dans l’espace, nous souhaitons caractériser et localiser les variations de la recharge d’hydrosystèmes karstiques à l’échelle régionale (plurikilométrique). La recharge peut être diffuse ou concentrée selon l’hétérogénéité du karst, ce qui limite à la fois les possibilités de mesures et de modélisations. Bien que l’évapotranspiration conditionne fortement la recharge du karst, l’évaluation de sa dynamique spatiotemporelle est souvent simplifiée. La calibration des paramètres du modèle hydrogéologique peut compenser les erreurs d’estimation de l’évapotranspiration et de la recharge donc, sans contrainte extérieure, la validation des simulations reste difficile. Afin de connaitre la distribution spatiotemporelle de la recharge du karst nous proposons un modèle conceptuel semi-distribué de l’hydrosystème (KaRaMel) associé à un modèle conceptuel semi-distribué de l’évapotranspiration (SimpKcET). Les outils développés sont appliqués au vaste hydrosystème de la Fontaine de Vaucluse (Sud-Est de la France). Les résultats montrent que (1) l’utilisation des indices de végétation, fournis par les mesures satellites, permet une estimation réaliste de la dynamique spatiotemporelle de l’évapotranspiration pour tous les types de végétations ; (2) la distribution spatiale des paramètres du modèle conceptuel semi-distribué du karst peut facilement être contrainte avec des informations sur les sols (réserve utile) et sur l’hydrosystème (vulnérabilité intrinsèque) ; (3) une boite à outils pour le système d’information géographique (QGIS) a été développée afin de faciliter la cartographie de la vulnérabilité intrinsèque des aquifères karstiques avec la méthode PaPRIKa ; (4) KaRaMel + SimpKcET permet à la fois de connaître la répartition spatiotemporelle des stocks et une estimation fiable des débits de l’exutoire de l’aquifère; (5) la recharge journalière, mensuelle et annuelle varie considérablement dans l’espace et dans le temps, les zones les plus contributives évoluant d’une année à l’autre ; (6) les débits de la Fontaine de Vaucluse sont sensibles à la distribution spatiale de la rechargeThe recharge of karst hydrosystems depends on climatic conditions, vegetation transpiration, soil evaporation, soil properties and karst heterogeneity. Recharging therefore depends on many factors that vary in time and space, and we wish to characterize and locate variations in the recharge of karst hydrosystems on a regional scale. The recharge can be diffuse or concentrated depending on the heterogeneity of the karst, which limits both measurement and modelling possibilities. Although evapotranspiration strongly influences the recharge of karst, the assessment of its spatiotemporal dynamics is often simplified. Calibration of the hydrogeological model parameters can compensate errors in estimating evapotranspiration and recharge and without external constraints, validation of the simulations remains difficult. In order to know the spatial and temporal distribution of karst recharge we propose a semi-distributed conceptual model of the hydrosystem (KaRaMel) associated with a semi-distributed conceptual model of evapotranspiration (SimpKcET). The tools developed are applied to the vast hydrosystem of the Fontaine de Vaucluse (South-East France). The results show that (1) the use of vegetation indices, provided by remote sensing, provides a realistic estimate of the spatiotemporal dynamics of evapotranspiration for all types of vegetation; (2) the spatial distribution of the parameters of the semi-distributed model can easily be constrained with information on soils (soil available water capacity) and on the hydrosystem (intrinsic vulnerability); (4) A toolbox for geographic information systems has been developed to facilitate the mapping of the intrinsic vulnerability of karst aquifers using the PaPRIKa method; (3) KaRaMel + SimpKcET provides both the spatial and temporal distribution of stocks and a reliable estimate of the aquifer discharges ; (4) daily, monthly and annual recharges change considerably in space and time, the most contributing areas varying from one year to the next; (5) the discharges of the Fontaine de Vaucluse are sensitive to the spatial distribution of the recharge
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CHOUDHURY, MD ABDUL MUEED. "Remote sensing approaches in carbon stock (CS) mapping considering the dominant tree species in urban areas." Doctoral thesis, 2021. http://hdl.handle.net/11566/290836.
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Recentemente, Negli ultimi anni, il preoccupante incremento del contributo del carbonio atmosferico al cambio climatico ha sollevato con forza il dibattito. In area urbana, le misure di mitigazione si stanno concentrando, tra le altre, sul ruolo delle infrastrutture verdi. In particolare, gli approcci improntati a sistemi di pianificazione e gestione del verde urbano sostenibili sembrano essere promettenti. Informazioni esplicite e tempestive sulla composizione strutturale e funzionale delle infrastrutture verdi e sulle singole strutture o aggregati di alberi urbani, in merito al loro ruolo nella cattura del carbonio atmosferico
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(CS), sono essenziali affinché i responsabili delle amministrazioni locali adottino azioni immediate per mitigare il peggioramento dell’impatto delle attività antropiche.
In questo studio, è stata adottata una metodologia dettagliata per la calibrazione e mappatura del CS delle alberature in due aree urbane. Uno studio è stato condotto a Sassuolo (MO), una città italiana di dimensioni medie. L'altro, è stato condotto nella regione della capitale del Belgio (Bruxelles), dove sono state anche valutate ed analizzate in modo comparativo le due diverse fonti di dati di telerilevamento (LiDAR e WorldView 3 (WV3)) ed i rispettivi risultati di mappatura. A Sassuolo, la mappatura del CS è stata eseguita utilizzando solo dati da immagini WV3 per un'area di studio alla scala locale di dettaglio. In particolare, alla scala di parco urbano, sono state selezionate 22 parcelle (10 m × 10 m ciascuna) di cui 7 per la validazione dei risultati della classificazione delle specie arboree e della calibrazione e mappatura del CS. In un secondo esperimento, a Bruxelles, l'approccio è stato replicato per un'area di studio più ampia, alla scala di città metropolitana. In questo caso, 75 parcelle (10 m × 10 m ciascuna) sono state utilizzate, di cui 20 per la convalida della calibrazione dei risultati della mappatura del CS. In entrambi i casi, sia a Sassuolo sia a Bruxelles, le specie arboree dominanti sono state identificate e classificate utilizzando immagini WV3 ad alta risoluzione. L'approccio di classificazione OBIA (Object-Based Image Analysis) è stato impiegato con successo ottenendo una precisione complessiva (Overall Accuracy) del 78% e del 71%, rispettivamente, per le relative specie arboree. Le stime del CS per ciascun caso sono state computate, a livello del singolo plot, utilizzando un modello allometrico basato su dati dendrometrici rilevati in campo, ad esempio altezza della pianta (H) e diametro del fusto all'altezza del petto (DBH). Successivamente il CS calcolato in base ai dati dicampo, insieme alle variabili derivate dall’elaborazione dei dati WV3 (NDVI) e LiDAR (CHM), sono stati mappati usando il sistema informativo geografico QGIS. I risultati ottenuti per entrambe le città hanno permesso di validare l'approccio, quale metodo efficiente e conveniente per mappare alla scala urbana, sia media che metropolitana, il contributo delle specie arboree dominanti nella cattura del carbonio atmosferico (CS). Questo studio aiuterà sicuramente urbanisti e pianificatori a meglio comprendere e meglio progettare la pianificazione delle infrastrutture verdi urbane, basandosi su dati provenienti da fonti telerilevate da remoto, e ove possibile prossimali, in base alla loro disponibilità ed al livello di opportunità, al fine di implementare un sistema sostenibile di gestione del verde urbano.Recently, severe intensification of atmospheric carbon recognizes the importance of urban tree contributions in atmospheric carbon mitigation in city areas considering a sustainable urban green planning and management system. Explicit and timely information on urban trees and their roles in atmospheric Carbon Stock (CS) are essential for the policymakers to take immediate actions to recover the effects of deforestation and their worsening outcomes. This doctoral study will be a way out for the policymakers in CS mapping for the dominant tree species in their cities based on Remote Sensing (RS) data sources. The mapping approach could be a useful tool especially for developing countries, where hyperspectral data could be a better solution over the hardly available LiDAR data. In this study, a detailed methodology on the urban tree CS calibration and mapping was done for two urban areas one of which was in Sassuolo (MO), a smaller city in Italy. The other one was conducted in the capital region of Belgium (Brussels), where also the comparative analysis of the two different remote sensing data sources (LiDAR and WorldView 3 (WV3)) and their mapping outcomes were assessed to define the convenience and applicability of the data sources. In Sassuolo, CS mapping was done utilizing only the WV3 image data for a smaller study area of 22 plots (10m×10m each) where the 7 plots were utilized to validate the results of tree species classification and the CS calibration and mapping. Later in Brussels, the approach was implied for a larger study area of 75 plots (10m×10m each) where 20 plots were utilized for the validation of CS calibration and mapping outcomes. In all cases, either in Sassuolo or in Brussels, dominant tree species were identified and classified utilizing the high-resolution WV3 image. The Object-Based Image Analysis (OBIA) classification approach was successfully employed to attain the overall accuracy of 78% and 71% for the tree species in Sassuolo and Brussels respectively. The field estimations of CS for each plot were done utilizing an allometric model based on the field data on tree dendrometry i.e. Height (H) and Diameter at Breast Height (DBH). Later the computed CS based on the field data along with the WV3 (NDVI) and LiDAR (CHM) data derived variables, had been mapped in QGIS. The results were found quite evident for both cities which did approve the approach as an efficient and convenient way of mapping, certainly recognizing the dominant tree species contributions in atmospheric CS. No doubt, this study will assist the city planners to understand and decide the applicability of remote sensing data sources based on their availability and the level of expediency, ensuring a sustainable urban green management system.
Books on the topic "Mapping QGIS"
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Westra, Erik. Building Mapping Applications with QGIS. Packt Publishing, Limited, 2014.
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Pandey, C. B., Priyabrata Santra, Mahesh Kumar, and N. R. Panwar. Soil Resources and Its Mapping Through Geostatistics Using R and Qgis. Taylor & Francis Group, 2019.
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QGIS for Hydrological Appllications: Recipes for Catchment Hydrology and Water Management. Locate Press, 2019.
Find full textBook chapters on the topic "Mapping QGIS"
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El Hajj, Mohammad, Mehrez Zribi, Nicolas Baghdadi, and Michel Le Page. "Mapping of Drought." In QGIS and Applications in Water and Risks, 185–214. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119476726.ch6.
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Thierion, Vincent, and Marc Lang. "Object-Based Classification for Mountainous Vegetation Physiognomy Mapping." In QGIS and Applications in Agriculture and Forest, 283–339. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119457107.ch9.
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Aval, Josselin, and Thierry Erudel. "Airborne Optical Remote Sensing Potential for Pool Mapping in an Urban Environment." In QGIS and Applications in Territorial Planning, 93–123. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119457121.ch4.
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Ose, Kenji. "Detection and Mapping of Clear-Cuts with Optical Satellite Images." In QGIS and Applications in Agriculture and Forest, 153–80. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119457107.ch5.
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Leroux, Louise, Luca Congedo, Beatriz Bellón, Raffaele Gaetano, and Agnès Bégué. "Land Cover Mapping Using Sentinel-2 Images and the Semi-Automatic Classification Plugin: A Northern Burkina Faso Case Study." In QGIS and Applications in Agriculture and Forest, 119–51. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119457107.ch4.
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Hisaindee, Muhammad Nadiim, Abdel Isker Mudhawo, and E. S. M. Suresh. "Vulnerability Mapping of Residential Buildings with Respect to Cyclonic Wind in Mauritius Using Remote Sensing and QGIS." In Lecture Notes in Civil Engineering, 15–27. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4715-5_2.
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Magembe-Mushi, Dawah, and Ramadhani Matingas. "Contributions of Local Authorities to Community Adaptive Capacity to Impacts of Climate Change; A Case Study of Sea Level Rise in Pangani Division, Pangani District." In The Urban Book Series, 143–66. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06550-7_8.
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AbstractCommunities around the world are facing tremendous climate change impacts, among others, sea level rise. Local authorities try to respond to the impacts of climate change by implementing localised adaptive measures to improve capacity. Impacts of climate change are worse in developing countries especially the Sub-Saharans due to inabilities to implement adaptive measures with inadequate resources; hence hindering the ability of communities to adapt to the impacts of climate change. It is the purpose of this chapter to explore the contributions of a local authority as one of the corresponding authorities responsible for enhancing a community’s adaptive capacity and its behaviour to climate change impacts. Interviews, mapping, observation and photographing, were conducted in the Pangani division in Tanzania. SPSS and QGIS software were used for analysis. It was found that sea level rise caused communities to suffer beach erosion, land inundation, saltwater intrusion, changes in fish availability, destruction of infrastructure and vegetation. The local authority implemented localised adaptive measures which improved adaptive capacity. These measures included construction and maintenance of seawall, planting and protecting mangroves and preparation of land-use plans. Also, an institutional arrangement involved different departments, committees and the community at large, with actors collaborating through the local authority in developing community adaptive capacity. This chapter recommends that the local authority should; enhance coordination among actors, make use of spatial analysis tools, mobilise resources and enhance community participation.
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"Visualizing Data in Geographic Information Systems with QGIS." In Using Geodata and Geolocation in the Social Sciences: Mapping our Connected World, 176–210. 1 Oliver’s Yard, 55 City Road London EC1Y 1SP: SAGE Publications Ltd, 2017. http://dx.doi.org/10.4135/9781473983267.n11.
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M. Mugaviri, Blessing, Gilbert H. Moyo, Ezra Pedzisai, and Cuthbert Maravanyika. "Spatio-Temporal Distribution of the Black Rhino (Diceros bicornis L.) in the Midlands Black Rhino Conservancy, Zimbabwe." In Environmental Sciences. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.106715.
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Geographic Information System (GIS) and Remote Sensing (RS) technologies have many attributes that are beneficial in detecting, mapping, and, monitoring change in Land use/Land cover (LULC). This study used the technology with the aim to evaluate the Spatio -temporal impacts of Land use/Land cover Changes (LULCC) on Black Rhino distribution in Midlands Black Rhino Conservancy (MBRC), Zimbabwe. The study used time series satellite data. Landsat images were downloaded for the month of May at five-year intervals from 2000 to 2020. LULC and Normalized Differences Vegetation Index (NDVI) maps obtained were used in change detection. The images were classified using QGIS software on the maximum likelihood classifier algorithm. Presents and absence data for Black Rhino was used for distribution mapping. Quantum Geographic Information System (QGIS) and, R studio software were used for analysis. Results indicated that, a big percentage cover change was the bare land which increased by over 160%. Woodland decreased by about 46% within the same space of time. LULCC showed a significant positive relationship with black rhino distribution (p = 0.0381). MOLUSCE plugin was used for Prediction of LULCC for the year 2030, results indicated the highest increase in bare land 16.59%.
Conference papers on the topic "Mapping QGIS"
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Martín, Belén, Ramón Molinero-Parejo, Nikolai Shurupov, Amor Ariza-Álvarez, Emilio Ortega, Miguel Navarro-Ligero, María Eugenia López-Lambas, Francisco Aguilera-Benavente, and Julio Alberto Soria-Lara. "IMPROVING SKILLS OF PROCESSING AND MAPPING CADASTRAL INFORMATION BY AN INNOVATIVE QGIS PLUGIN WITH TEACHING PURPOSES." In 14th International Conference on Education and New Learning Technologies. IATED, 2022. http://dx.doi.org/10.21125/edulearn.2022.2271.
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Snytko, V. A., Yu M. Semenov, M. Yu Semenov, A. V. Silayev, and G. I. Lysanova. "КАРТОГРАФИЧЕСКОЕ ОБЕСПЕЧЕНИЕ ГЕОЭКОЛОГИЧЕСКОГО МОНИТОРИНГА БАССЕЙНА ОЗЕРА БАЙКАЛ." In Geosistemy vostochnyh raionov Rossii: osobennosti ih struktur i prostranstvennogo razvitiia. ИП Мироманова Ирина Витальевна, 2019. http://dx.doi.org/10.33833/tig.2019.27.11.010.
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Разрабатываемая методология геоэкологического мониторинга основана на выявлении антропогенных источников вещества и наблюдении связей между ними и объектами среды путем рассмотрения объектов в качестве смесей, а источников в качестве их компонентов, с использованием подходов ландшафтного мониторинга. Обоснованы методические подходы к разработке картографического обеспечения мониторинга структуры загрязнения и распределения загрязнителей в бассейне озера Байкал. Для обоснования сети наблюдений и контроля, экстраполяции результатов мониторинга на территории, не охваченные непосредственными наблюдениями, показа оперативной информации о состоянии геосистем и экосистем требуется картографическая основа. Методика картографирования базируется на основных положениях учения о геосистемах В.Б. Сочавы. Методические приемы геоинформационного картографирования были адаптированы применительно к бассейну оз. Байкал. Модель SRTM 4й версии, взятая за основу для получения изолиний рельефа, была преобразована и приведена к масштабу 1:5 000000, а все цифровые слои были интегрированы в единую картографическую проекцию и систему координат (WGS 84). Сопоставление пространственно привязанных слоев рельефа и гидрографической сети в QGIS позволило разграничить бассейны крупных, средних и малых притоков Байкала. Инструментами выявления структуры хозяйственной деятельности служат методы ландшафтногеохимического синтеза, картографирования агроландшафтов, ландшафтного планирования и ретроспективного картографического анализа геосистем с длительной историей хозяйственного освоения. Выявление структуры загрязнения Байкала, его притоков и водосборного бассейна в целом осуществляется путем анализа пространственного и временного распределения загрязнителей в компонентах природной среды. Картографирование дифференциации загрязнителей проводится с использованием современных методов геоинформационного анализа и моделирования, которые реализованы в программе ArcGIS 10. Расчет составов выбросов неизвестных источников проводится с применением методов многомерного анализа. Проанализированы основные параметры ландшафтногеохимической дифференциации бассейна озера Байкал, составлена карта дифференциации поверхностных вод по способности вод к самоочищению, разработана схема районирования территории по способности обеспечивать тот или иной состав вод. The developed methodology of geoenvironmental monitoring is based on identification of anthropogenic sources of substance and the observation of communications between them and the objects of the environment by consideration of the objects as mixes, and the sources as their components, with use of approaches of landscape monitoring. Methodical approaches to development of cartographic ensuring of monitoring of pollution and distribution of pollutants in the basin of Lake Baikal are proved. The cartographic basis is necessary for justification of the network of observations and monitoring, extrapolation of results of monitoring on the territories which are not captured by immediate observations, display of operational information on a condition of geosystems and ecosystems. The technique of mapping is based on original positions of V.B. Sochava doctrine about geosystems. Methodical techniques of geoinformation mapping were adapted in relation to the basin of Lake Baikal. The SRTM model of the 4th version taken as a basis for receiving isolines of a relief was transformed and scaled by 1:5,000,000. All digital layers were integrated into a uniform cartographic projection and a frame (WGS 84). Comparison of spatially attached layers of a relief and a hydrographic network in QGIS allowed us to differentiate the pools of the large, average and small inflows of Baikal. The methods of landscapegeochemical synthesis, mapping of agrolandscapes, landscape planning and the retrospective cartographic analysis of geosystems with the long history of economic development served as the instruments of identification of the structure of economic activity. Identification of pollution structure of Lake Baikal, its inflows and a catchment basin in general is carried out by the analysis of spatial and temporary distribution of pollutants in environment components. Mapping of pollutants differentiation is carried out with use of the modern methods of the geoinformational analysis and the model operation, which are realized in the ArcGIS 10 program. Calculation of compositions for the emissions of unknown sources is carried out with application of methods of the multidimensional analysis. Key parameters of landscapegeochemical differentiation of the basin of Lake Baikal are analyzed. The map of differentiation of the surface water on ability of waters to selfcleaning has been compiled. The scheme of regionalization for the territory on ability to provide this or that composition of waters has been developed.
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Snytko, V. A., Yu M. Semenov, M. Yu Semenov, A. V. Silayev, and G. I. Lysanova. "КАРТОГРАФИЧЕСКОЕ ОБЕСПЕЧЕНИЕ ГЕОЭКОЛОГИЧЕСКОГО МОНИТОРИНГА БАССЕЙНА ОЗЕРА БАЙКАЛ." In Geosistemy vostochnyh raionov Rossii: osobennosti ih struktur i prostranstvennogo razvitiia. ИП Мироманова Ирина Витальевна, 2019. http://dx.doi.org/10.35735/tig.2019.27.11.010.
Full textAbstract:
Разрабатываемая методология геоэкологического мониторинга основана на выявлении антропогенных источников вещества и наблюдении связей между ними и объектами среды путем рассмотрения объектов в качестве смесей, а источников в качестве их компонентов, с использованием подходов ландшафтного мониторинга. Обоснованы методические подходы к разработке картографического обеспечения мониторинга структуры загрязнения и распределения загрязнителей в бассейне озера Байкал. Для обоснования сети наблюдений и контроля, экстраполяции результатов мониторинга на территории, не охваченные непосредственными наблюдениями, показа оперативной информации о состоянии геосистем и экосистем требуется картографическая основа. Методика картографирования базируется на основных положениях учения о геосистемах В.Б. Сочавы. Методические приемы геоинформационного картографирования были адаптированы применительно к бассейну оз. Байкал. Модель SRTM 4й версии, взятая за основу для получения изолиний рельефа, была преобразована и приведена к масштабу 1:5 000000, а все цифровые слои были интегрированы в единую картографическую проекцию и систему координат (WGS 84). Сопоставление пространственно привязанных слоев рельефа и гидрографической сети в QGIS позволило разграничить бассейны крупных, средних и малых притоков Байкала. Инструментами выявления структуры хозяйственной деятельности служат методы ландшафтногеохимического синтеза, картографирования агроландшафтов, ландшафтного планирования и ретроспективного картографического анализа геосистем с длительной историей хозяйственного освоения. Выявление структуры загрязнения Байкала, его притоков и водосборного бассейна в целом осуществляется путем анализа пространственного и временного распределения загрязнителей в компонентах природной среды. Картографирование дифференциации загрязнителей проводится с использованием современных методов геоинформационного анализа и моделирования, которые реализованы в программе ArcGIS 10. Расчет составов выбросов неизвестных источников проводится с применением методов многомерного анализа. Проанализированы основные параметры ландшафтногеохимической дифференциации бассейна озера Байкал, составлена карта дифференциации поверхностных вод по способности вод к самоочищению, разработана схема районирования территории по способности обеспечивать тот или иной состав вод. The developed methodology of geoenvironmental monitoring is based on identification of anthropogenic sources of substance and the observation of communications between them and the objects of the environment by consideration of the objects as mixes, and the sources as their components, with use of approaches of landscape monitoring. Methodical approaches to development of cartographic ensuring of monitoring of pollution and distribution of pollutants in the basin of Lake Baikal are proved. The cartographic basis is necessary for justification of the network of observations and monitoring, extrapolation of results of monitoring on the territories which are not captured by immediate observations, display of operational information on a condition of geosystems and ecosystems. The technique of mapping is based on original positions of V.B. Sochava doctrine about geosystems. Methodical techniques of geoinformation mapping were adapted in relation to the basin of Lake Baikal. The SRTM model of the 4th version taken as a basis for receiving isolines of a relief was transformed and scaled by 1:5,000,000. All digital layers were integrated into a uniform cartographic projection and a frame (WGS 84). Comparison of spatially attached layers of a relief and a hydrographic network in QGIS allowed us to differentiate the pools of the large, average and small inflows of Baikal. The methods of landscapegeochemical synthesis, mapping of agrolandscapes, landscape planning and the retrospective cartographic analysis of geosystems with the long history of economic development served as the instruments of identification of the structure of economic activity. Identification of pollution structure of Lake Baikal, its inflows and a catchment basin in general is carried out by the analysis of spatial and temporary distribution of pollutants in environment components. Mapping of pollutants differentiation is carried out with use of the modern methods of the geoinformational analysis and the model operation, which are realized in the ArcGIS 10 program. Calculation of compositions for the emissions of unknown sources is carried out with application of methods of the multidimensional analysis. Key parameters of landscapegeochemical differentiation of the basin of Lake Baikal are analyzed. The map of differentiation of the surface water on ability of waters to selfcleaning has been compiled. The scheme of regionalization for the territory on ability to provide this or that composition of waters has been developed.
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Nash, Susan Smith, Patrick L. Friend, and Marit Brommer. "A Fully Integrated and Updated Geothermal Gradient Atlas of the World." In Offshore Technology Conference. OTC, 2022. http://dx.doi.org/10.4043/32035-ms.
Full textAbstract:
Abstract Scope The energy transition offers multiple opportunities for traditional energy companies and their geoscience workforce to explore for new types of energy resources. In this paper. we report on new initiatives to develop fully integrated databases using GIS and AI to provide added value and new insights into the world's current and diversified existing data repositories. One such initiative, the Global Heat Flow Database (GHFD), seeks to create a geothermal gradient atlas of the world, combining existing maps and data into a searchable, georeferenced mapping format with layers reflecting temperatures, landforms, geological features, and other information for making decisions about exploring for geothermal energy, and siting and developing geothermal plants and infrastructure. The project scope is global and requires the mining and integration of large modern and archived data sets. We also list several diverse datasets that are complementary to creating a truly global database, and we provide examples of methods and workflows involved in the process of prospecting for geothermal resources and creating geothermal heat flow gradients and maps. Methods The global geothermal gradient atlas involves a team effort by geologists and data scientists to identify, QC, and classify relevant geothermal data from structured and unstructured sources, including public and commercial databases, maps and reports, and other repositories of georeferenced temperature and depth. The processes of combining databases, clean up and QC of data, and incorporation of different functional layers in a GIS system will involve several important steps: 1) creating a uniform standard for managing the data; 2) utilization of platforms that enable data acquisition, ingestion, cleaning, and application of various machine learning algorithms to assure quality and uniformity; and 3) including other useful and related data, which will be available as layers in the GIS system. Results The resulting database will be available as a searchable atlas for industry and academia use, and from which custom maps, studies, and data can be exported. The global geothermal atlas database will adhere to FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable). First deliverables will consist of the integrated geothermal gradient temperature and depth data for use with QGIS, ArcGIS or other GIS mapping software. Apps will allow the atlas users to compare the geothermal prospectivity by geographical location, and to rank in terms of amenability to development according to geothermal resource and proximity to end users and conveyance infrastructure. Discrete database layers will include geographic landforms, major infrastructure, and geological information including fault systems and major structural features. Novel information Several aspects make the project unique and differentiate it from others. First, is the fact that state of the art data management and machine learning systems will be used to ingest, classify, clean, and easily access the data. The results will be a geothermal gradient database and atlas that are significantly more accurate than those in use today. Second, is the fact that accessibility and front-end apps will make the data base multi-functional and suitable for a wide range of geothermal applications, including exploration for optimal sources near communities, siting and developing sedimentary and igneous geothermal plants, identifying prospects for shallow as well as deeper geothermal energy generation, and repurposing producing, declining, or abandoned oil and gas wells for use in geothermal energy production.
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Nash, Susan Smith, Patrick L. Friend, and Marit Brommer. "A Fully Integrated and Updated Geothermal Gradient Atlas of the World." In Offshore Technology Conference. OTC, 2022. http://dx.doi.org/10.4043/32035-ms.
Full textAbstract:
Abstract Scope The energy transition offers multiple opportunities for traditional energy companies and their geoscience workforce to explore for new types of energy resources. In this paper. we report on new initiatives to develop fully integrated databases using GIS and AI to provide added value and new insights into the world's current and diversified existing data repositories. One such initiative, the Global Heat Flow Database (GHFD), seeks to create a geothermal gradient atlas of the world, combining existing maps and data into a searchable, georeferenced mapping format with layers reflecting temperatures, landforms, geological features, and other information for making decisions about exploring for geothermal energy, and siting and developing geothermal plants and infrastructure. The project scope is global and requires the mining and integration of large modern and archived data sets. We also list several diverse datasets that are complementary to creating a truly global database, and we provide examples of methods and workflows involved in the process of prospecting for geothermal resources and creating geothermal heat flow gradients and maps. Methods The global geothermal gradient atlas involves a team effort by geologists and data scientists to identify, QC, and classify relevant geothermal data from structured and unstructured sources, including public and commercial databases, maps and reports, and other repositories of georeferenced temperature and depth. The processes of combining databases, clean up and QC of data, and incorporation of different functional layers in a GIS system will involve several important steps: 1) creating a uniform standard for managing the data; 2) utilization of platforms that enable data acquisition, ingestion, cleaning, and application of various machine learning algorithms to assure quality and uniformity; and 3) including other useful and related data, which will be available as layers in the GIS system. Results The resulting database will be available as a searchable atlas for industry and academia use, and from which custom maps, studies, and data can be exported. The global geothermal atlas database will adhere to FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable). First deliverables will consist of the integrated geothermal gradient temperature and depth data for use with QGIS, ArcGIS or other GIS mapping software. Apps will allow the atlas users to compare the geothermal prospectivity by geographical location, and to rank in terms of amenability to development according to geothermal resource and proximity to end users and conveyance infrastructure. Discrete database layers will include geographic landforms, major infrastructure, and geological information including fault systems and major structural features. Novel information Several aspects make the project unique and differentiate it from others. First, is the fact that state of the art data management and machine learning systems will be used to ingest, classify, clean, and easily access the data. The results will be a geothermal gradient database and atlas that are significantly more accurate than those in use today. Second, is the fact that accessibility and front-end apps will make the data base multi-functional and suitable for a wide range of geothermal applications, including exploration for optimal sources near communities, siting and developing sedimentary and igneous geothermal plants, identifying prospects for shallow as well as deeper geothermal energy generation, and repurposing producing, declining, or abandoned oil and gas wells for use in geothermal energy production.
Reports on the topic "Mapping QGIS"
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Metz, L., and A. N. Bear-Crozier. Landslide susceptibility mapping: a remote sensing based approach using QGIS 2.2 (Valmiera): technical manual. Geoscience Australia, 2014. http://dx.doi.org/10.11636/record.2014.056.
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Stewart, Gerard, David Craven, Sam Dawson, Luke Wallace, and Baskaran Sundaram. GIS methods for hydrogeology mapping in Timor-Leste, QGIS version (free software) : vulnerability assessment of climate change impacts on groundwater resources in Timor-Leste. Geoscience Australia, 2012. http://dx.doi.org/10.11636/record.2012.057.
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Stewart, Gerard, David Craven, Sam Dawson, Luke Wallace, and Baskaran Sundaram. GIS methods for hydrogeology mapping in Timor-Leste, QGIS version (free software): vulnerability assessment of climate change impacts on groundwater resources in Timor-Leste. Geoscience Australia, 2012. http://dx.doi.org/10.11636/record.2012/057.
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