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Articles

Using geovisual analytics to enrich conservation science: a review of interactive visualization of wildlife and environmental spatial data across ecosystems

ORCID Icon & ORCID Icon
Pages 286-318 | Received 17 Jul 2022, Accepted 10 Mar 2023, Published online: 28 May 2023

References

  • Alberti, K. (2013). Web-based visualization of uncertain spatio-temporal data. A MSc. Thesis by Koen Alberti, Earth Surface and Water Programme at Utrecht University, 1–101.
  • Andrienko, G., Andrienko, N., Demsar, U., Dransch, D., Dykes, J., Fabrikant, S. I., Jern, M., Kraak, M.-J., Schumann, H., & Tominski, C. (2010). Space, time and visual analytics. International Journal of Geographical Information Science, 24(10), 1577–1600. https://doi.org/10.1080/13658816.2010.508043
  • Andrienko, G., Andrienko, N., Dykes, J., Kraak, M. J., Robinson, A., & Schumann, H. (2016). GeoVisual analytics: Interactivity, dynamics, and scale. Cartography and Geographic Information Science, 43(1), 1–2. https://doi.org/10.1080/15230406.2016.1095006
  • Andrienko, G., Andrienko, N., Jankowski, P., Keim, D., Kraak, M-J, MacEachren, A., & Wrobel, S. (2007). Geovisual analytics for spatial decision support: Setting the research agenda. International Journal of Geographical Information Science, 21(8), 839–857. https://doi.org/10.1080/13658810701349011
  • Arciniegas, G., Janssen, R., & Omtzigt, N. (2011). Map-based multicriteria analysis to support interactive land use allocation. International Journal of Geographical Information Science, 25(12), 1931–1947. https://doi.org/10.1080/13658816.2011.556118
  • Bakker, K., & Ritts, M. (2018). Smart Earth: A meta-review and implications for environmental governance. Global Environmental Change, 52, 201–211. https://doi.org/10.1016/j.gloenvcha.2018.07.011
  • Benke, K. K., Sheth, F., Betteridge, K., Pettit, C. J., & Aurambout, J.-P. (2012). A geo-visual analytics approach to biological shepherding: Modelling animal movements and impacts. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, I–2, 117–122. https://doi.org/10.5194/isprsannals-I-2-117-2012
  • Benke, K. K., Sheth, F., Betteridge, K., Pettit, C. J., & Aurambout, J.-P. (2015). Application of geovisual analytics to modelling the movements of ruminants in the rural landscape using satellite tracking data. International Journal of Digital Earth, 8(7), 579–593. https://doi.org/10.1080/17538947.2013.872703
  • Bernasocchi, M., Coltekin, A., & Gruber, S. (2012). An open source geovisual analytics toolbox for multivariate spatio-temporal data in environmental change modelling. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, I–2, 123–128. https://doi.org/10.5194/isprsannals-I-2-123-2012
  • Boukherroub, T., D’amours, S., & Rönnqvist, M. (2018). Sustainable forest management using decision theaters: Rethinking participatory planning. Journal of Cleaner Production, 179, 567–580. https://doi.org/10.1016/j.jclepro.2018.01.084
  • Burns, R., & Skupin, A. (2013). Towards qualitative geovisual analytics: A case study involving places, people, and mediated experience. Cartographica: The International Journal for Geographic Information and Geovisualization, 48(3), 157–176. https://doi.org/10.3138/carto.48.3.1691
  • Chapman, A. D. (2020). Current best practices for generalizing sensitive species occurrence data. Copenhagen: GBIF Secretariat. https://doi.org/10.15468/doc-5jp4-5g10.
  • Chen, J., Roth, R. E., Naito, A. T., Lengerich, E. J., & MacEachren, A. M. (2008). Geovisual analytics to enhance spatial scan statistic interpretation: An analysis of U.S. cervical cancer mortality. International Journal of Health Geographics, 7(1), 57. https://doi.org/10.1186/1476-072X-7-57
  • Conserve.IO. (n.d.). Sharktivity. Retrieved March 21, 2021, from http://conserve.io/sharktivity.
  • Conserve.IO, International Fund for Animal Welfare, & U.S. National Marine Sanctuaries. (n.d.). WhaleAlert. Retrieved March 19, 2021, from http://www.whalealert.org/.
  • Cooperation & development Center at EPFL (CODEV). (2014). SAVMAP. https://www.epfl.ch/labs/lasig/research/projects/savmap/.
  • Copernicus Marine Service. (2021). Ocean data visualisation tools. Copernicus Marine Environment Monitoring Service. https://marine.copernicus.eu/access-data/ocean-visualisation-tools.
  • Dawidowicz, A., & Kulawiak, M. (2018). The potential of web-GIS and geovisual analytics in the context of marine cadastre. Survey Review, 50(363), 501–512. https://doi.org/10.1080/00396265.2017.1328331
  • Deitrick, S., & Wentz, E. A. (2015). Developing implicit uncertainty visualization methods motivated by theories in decision science. Annals of the Association of American Geographers, 105(3), 531–551. https://doi.org/10.1080/00045608.2015.1012635
  • Demšar, U. (2007). Knowledge discovery in the environmental sciences: Visual and automatic data mining for radon problems in groundwater. Transactions in GIS, 11(2), 255–281. https://doi.org/10.1111/j.1467-9671.2007.01044.x
  • Demšar, U., Buchin, K., Cagnacci, F., Safi, K., Speckmann, B., Van de Weghe, N., Weiskopf, D., & Weibel, R. (2015). Analysis and visualisation of movement: An interdisciplinary review. Movement Ecology, 3(1), 5. https://doi.org/10.1186/s40462-015-0032-y
  • Díaz, S., Settele, J., Brondízio, E. S., Ngo, H. T., Guèze, M., Agard, J., Arneth, A., Balvanera, P., Brauman, K. A., Butchart, S. H. M., Chan, K. M. A., Garibaldi, L. A., Ichii, K., Liu, J., Subramanian, S. M., Midgley, G. F., Miloslavich, P., Molnár, Z., Obura, D., … Zayas, C. N. (Eds.) (2019). IPBES (2019): Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental science-policy platform on biodiversity and ecosystem services. IPBES Secretariat, Bonn, Germany, 56. https://doi.org/10.5281/zenodo.3553579.
  • Douglas, K. (2021). The nature fix. New Scientist, 249(3327), 36–40. https://doi.org/10.1016/S0262-4079(21)00522-4
  • Dreiss, L. M., Lacey, L. M., Weber, T. C., Delach, A., Niederman, T. E., & Malcom, J. W. (2022). Targeting current species ranges and carbon stocks fails to conserve biodiversity in a changing climate: Opportunities to support climate adaptation under 30 × 30. Environmental Research Letters, 17(2), 024033. https://doi.org/10.1088/1748-9326/ac4f8c
  • Dykes, J., MacEachren, A. M., & Kraak, M.-J. (2005). Introduction: Exploring geovisualization. In Exploring Geovisualization. https://www.sciencedirect.com/book/9780080445311/exploring-geovisualization.
  • EarthNC. (2016). EarthNC: Next generation navigation. http://earthnc.com/apps/shark-net-app.
  • Enguehard, R. A., Devillers, R., & Hoeber, O. (2013). Comparing interactive and automated mapping systems for supporting fisheries enforcement activities–a case study on vessel monitoring systems (VMS). Journal of Coastal Conservation, 17(1), 105–119. https://doi.org/10.1007/s11852-012-0222-3
  • Enguehard, R. A., Hoeber, O., & Devillers, R. (2013). Interactive exploration of movement data: A case study of geovisual analytics for fishing vessel analysis. Information Visualization, 12(1), 65–84. https://doi.org/10.1177/1473871612456121
  • Fabrikant, S. I., & Lobben, A. (2009). Introduction: Cognitive issues in geographic information visualization. Cartographica: The International Journal for Geographic Information and Geovisualization, 44(3), 139–143. https://doi.org/10.3138/carto.44.3.139
  • Fetissov, M., Aps, R., Goerlandt, F., Jänes, H., Kotta, J., Kujala, P., & Szava-Kovats, R. (2021). Next-generation smart response web (NG-SRW): An operational spatial decision support system for maritime oil spill emergency response in the Gulf of Finland (Baltic Sea). Sustainability, 13(12), 6585. https://doi.org/10.3390/su13126585
  • Gadsden, D. (2019, September 18). African parks uses tracking to combat poaching and protect animals. Esri Blog. https://www.esri.com/about/newsroom/blog/african-parks-track-animals/.
  • Getto, G., & Moore, C. (2017). Mapping personas: Designing UX relationships for an online coastal atlas. Computers and Composition, 43, 15–34. https://doi.org/10.1016/j.compcom.2016.11.008
  • Global Forest Watch. (2021). Global forest watch map. https://www.globalforestwatch.org/map/.
  • Goltz, S. (2014a, July 2). Persona grata: Welcoming users into the interaction design process. UX Magazine. http://uxmag.com/articles/persona-grata.
  • Goltz, S. (2014b, August 6). A closer look at personas: What they are and how they work (part 1). Smashing Magazine. http://www.smashingmagazine.com/2014/08/06/a-closer-look-at-personas-part-1/.
  • Green, K. (2011). Comparison of DMC, UltraCam, and ADS40 imagery for benthic habitat and propeller scar mapping. Photogrammetric Engineering & Remote Sensing, 77(6), 589–599. https://doi.org/10.14358/PERS.77.6.589
  • Hampton, S. E., Strasser, C. A., Tewksbury, J. J., Gram, W. K., Budden, A. E., Batcheller, A. L., Duke, C. S., & Porter, J. H. (2013). Big data and the future of ecology. Frontiers in Ecology and the Environment, 11(3), 156–162. https://doi.org/10.1890/120103
  • Han, X., Smyth, R. L., Young, B. E., Brooks, T. M., Sánchez de Lozada, A., Bubb, P., Butchart, S. H. M., Larsen, F. W., Hamilton, H., Hansen, M. C., & Turner, W. R. (2014). A biodiversity indicators dashboard: Addressing challenges to monitoring progress towards the aichi biodiversity targets using disaggregated global data. PLoS ONE, 9(11), e112046. https://doi.org/10.1371/journal.pone.0112046
  • Hansson, M., & Håkansson, B. (2007). The Baltic Algae watch system - a remote sensing application for monitoring cyanobacterial blooms in the Baltic Sea. Journal of Applied Remote Sensing, 1(1), 011507. https://doi.org/10.1117/1.2834769
  • Hart, D. A., Prestby, T., & Roth, R. E. (2022). Design and evaluation of coastal web atlases: Best practices and future opportunities for map representation, interaction, and usability. Coastal Management, 50(6), 514–548. https://doi.org/10.1080/08920753.2022.2126271
  • Helbig, C., Dransch, D., Böttinger, M., Devey, C., Haas, A., Hlawitschka, M., Kuenzer, C., Rink, K., Schäfer-Neth, C., Scheuermann, G., Kwasnitschka, T., & Unger, A. (2017). Challenges and strategies for the visual exploration of complex environmental data. International Journal of Digital Earth, 10(10), 1070–1076. https://doi.org/10.1080/17538947.2017.1327618
  • Ho, Q. V. (2013). Architecture and applications of a geovisual analytics framework. Department of Science and Technology Linkoping University.
  • Hoeber, O., & Ul Hasan, M. (2015). Supporting event-based geospatial anomaly detection with geovisual analytics: Proceedings of the 6th International Conference on Information Visualization Theory and Applications, 17–28. https://doi.org/10.5220/0005268000170028.
  • Hoeber, O., & Ul Hasan, M. (2018). A geovisual analytics approach for analyzing event-based geospatial anomalies within movement data. Information Visualization, 17(2), 91–107. https://doi.org/10.1177/1473871617693040
  • Hoeber, O., Wilson, G., Harding, S., Enguehard, R., & Devillers, R. (2011). Exploring geo-temporal differences using GTdiff. 2011 IEEE Pacific Visualization Symposium, 139–146. https://doi.org/10.1109/PACIFICVIS.2011.5742383
  • Huang, J., Lucash, M. S., Scheller, R. M., & Klippel, A. (2021). Walking through the forests of the future: Using data-driven virtual reality to visualize forests under climate change. International Journal of Geographical Information Science, 35(6), 1155–1178. https://doi.org/10.1080/13658816.2020.1830997
  • Huang, J., Lucash, M. S., Simpson, M. B., Helgeson, C., & Klippel, A. (2019). Visualizing natural environments from data in virtual reality: Combining realism and uncertainty. 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), 1485–1488. https://doi.org/10.1109/VR.2019.8797996
  • Jern, M. (2009). Collaborative web-enabled geoanalytics applied to OECD regional data. In Y. Luo (Ed.), Cooperative design, visualization, and engineering (Vol. 5738, pp. 32–43). Springer. https://doi.org/10.1007/978-3-642-04265-2_5.
  • Jern, M., Brezzi, M., & Lundblad, P. (2010). Geovisual analytics tools for communicating emergency and early warning. In Geographic Information and Cartography for Risk and Crisis Management (pp. 379–394).
  • Jern, M., Brezzi, M., & Thygesen, L. (2009). A web-enabled Geovisual Analytics tool applied to OECD Regional Data. Eurographics (Areas Papers), 19–26.
  • Jones, B. (2022, January 21). This map may make you feel better about the state of the planet. Vox. https://www.vox.com/down-to-earth/22870194/restor-map-nature-healing-forest-restoration.
  • Kantartzis, A., Malesios, C., Stergiadou, A., Theofanous, N., Tampekis, S., & Arabatzis, G. (2021). A geographical information approach for forest maintenance operations with emphasis on the drainage infrastructure and culverts. Water, 13(10), 1408. https://doi.org/10.3390/w13101408
  • Katz, B. (2020). Vulnerability and adaptation of pacific northwest shellfisheries to ocean acidification. Oregon State University.
  • Khan, K. A., Akhter, G., & Ahmad, Z. (2011). Integrated geoscience databanks for interactive analysis and visualization. International Journal of Digital Earth, 1–9. https://doi.org/10.1080/17538947.2011.638990
  • Kinkeldey, C. (2014a). Incorporating uncertainty information into exploratory land cover change analysis: A geovisual analytics approach. A Dissertation by Christoph Kinkeldey, HafenCity Universitat Hamburg, 178.
  • Kinkeldey, C. (2014b). A concept for uncertainty-aware analysis of land cover change using geovisual analytics. ISPRS International Journal of Geo-Information, 3(3), 1122–1138. https://doi.org/10.3390/ijgi3031122
  • Kinkeldey, C. (2014c). Development of a prototype for uncertainty-aware geovisual analytics of land cover change. International Journal of Geographical Information Science, 28(10), 2076–2089. https://doi.org/10.1080/13658816.2014.891037
  • Kinkeldey, C., & Schiewe, J. (2014). Expert interviews about the use of visually depicted uncertainty for analysis of remotely sensed land cover change. https://doi.org/10.13140/2.1.2516.3523.
  • Koylu, C., Larson, R., Dietrich, B. J., & Lee, K.-P. (2019). CarSenToGram: Geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter. Cartography and Geographic Information Science, 46(1), 57–71. https://doi.org/10.1080/15230406.2018.1510343
  • Kulawiak, M. (2016). Operational algae bloom detection in the Baltic Sea using GIS and AVHRR data. Baltica, 29(1), 3–18. https://doi.org/10.5200/baltica.2016.29.02
  • Kulawiak, M., & Chybicki, A. (2018). Application of Web-GIS and geovisual analytics to monitoring of seabed evolution in south baltic Sea coastal areas. Marine Geodesy, 41(4), 405–426. https://doi.org/10.1080/01490419.2018.1469557
  • Kveladze, I., Kraak, M.-J., & Van Elzakker, C. P. J. M. (2015). The space-time cube as part of a GeoVisual analytics environment to support the understanding of movement data. International Journal of Geographical Information Science, 29(11), 2001–2016. https://doi.org/10.1080/13658816.2015.1058386
  • Lloyd, D., Dykes, J., & Radburn, R. (2008). Mediating geovisualization to potential users and prototyping a geovisualization application. 8.
  • Lundquist, C. J., & Granek, E. F. (2005). Strategies for successful marine conservation: Integrating socioeconomic, political, and scientific factors. Conservation Biology, 19(6), 1771–1778. https://doi.org/10.1111/j.1523-1739.2005.00279.x
  • MacEachren, A. M., Jaiswal, A., Robinson, A. C., Pezanowski, S., Savelyev, A., Mitra, P., Zhang, X., & Blanford, J. (2011). SensePlace2: GeoTwitter analytics support for situational awareness. 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), 181–190. https://doi.org/10.1109/VAST.2011.6102456.
  • MacEachren, A. M., & Kraak, M.-J. (2001). Research challenges in geovisualization. Cartography and Geographic Information Science, 28(1), 3–12. https://doi.org/10.1559/152304001782173970
  • MacEachren, A. M., Robinson, A., Hopper, S., Gardner, S., Murray, R., Gahegan, M., & Hetzler, E. (2005). Visualizing geospatial information uncertainty: What We know and what we need to know. Cartography and Geographic Information Science, 32(3), 139–160. https://doi.org/10.1559/1523040054738936
  • Maggi, S., Fabrikant, S. I., Imbert, J.-P., & Hurter, C. (2016). How do display design and user characteristics matter in animations? An empirical study with Air traffic control displays. Cartographica: The International Journal for Geographic Information and Geovisualization, 51(1), 25–37. https://doi.org/10.3138/cart.51.1.3176
  • Marek, L., Tuček, P., & Pászto, V. (2015). Using geovisual analytics in Google Earth to understand disease distribution: A case study of campylobacteriosis in the Czech Republic (2008–2012). International Journal of Health Geographics, 14(1), 7. https://doi.org/10.1186/1476-072X-14-7
  • McCarthy, D. P., Donald, P. F., Scharlemann, J. P. W., Buchanan, G. M., Balmford, A., Green, J. M. H., Bennun, L. A., Burgess, N. D., Fishpool, L. D. C., Garnett, S. T., Leonard, D. L., Maloney, R. F., Morling, P., Schaefer, H. M., Symes, A., Wiedenfeld, D. A., & Butchart, S. H. M. (2012). Financial costs of meeting global biodiversity conservation targets: Current spending and unmet needs. Science, 338(6109), 946–949. https://doi.org/10.1126/science.1229803
  • Merten, W., Amos, J., Reyer, A., Woods, P., Savitz, J., & Sullivan, B. (2016). Global fishing watch: Bringing transparency to global commercial fisheries. arXiv preprint. arXiv:1609.08756
  • Miller, H. J., Dodge, S., Miller, J., & Bohrer, G. (2019). Towards an integrated science of movement: Converging research on animal movement ecology and human mobility science. International Journal of Geographical Information Science, 33(5), 855–876. https://doi.org/10.1080/13658816.2018.1564317
  • Morstatter, F., Kumar, S., Liu, H., & Maciejewski, R. (2013). Understanding Twitter data with TweetXplorer. Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1482–1485. https://doi.org/10.1145/2487575.2487703
  • Naidoo, R., Balmford, A., Ferraro, P., Polasky, S., Ricketts, T., & Rouget, M. (2006). Integrating economic costs into conservation planning. Trends in Ecology & Evolution, 21(12), 681–687. https://doi.org/10.1016/j.tree.2006.10.003
  • NatureServe. (2018). Homepage: Biodiversity Dashboard. https://dashboard.natureserve.org/.
  • Nelson, J., Quinn, S., Swedberg, B., Chu, W., & MacEachren, A. (2015). Geovisual analytics approach to exploring public political discourse on twitter. ISPRS International Journal of Geo-Information, 4(1), 337–366. https://doi.org/10.3390/ijgi4010337
  • North, C. (2006). Toward measuring visualization insight. IEEE Computer Graphics and Applications, 26(3), 6–9. https://doi.org/10.1109/MCG.2006.70
  • Nukavarapu, N., & Durbha, S. (2017). GEO-Visual analytics for healthcare critical infrastructure simulation model. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 6106–6109. https://doi.org/10.1109/IGARSS.2017.8128402
  • Pezanowski, S., MacEachren, A. M., Savelyev, A., & Robinson, A. C. (2018). SensePlace3: A geovisual framework to analyze place–time–attribute information in social media. Cartography and Geographic Information Science, 45(5), 420–437. https://doi.org/10.1080/15230406.2017.1370391
  • Pontius, J., & Duncan, J. (2018). Linking science and management in a geospatial, multi- criteria decision support tool. In H. F. dos S. Viana, & F. A. G. Morote (Eds.), New perspectives in forest science. InTech. https://doi.org/10.5772/intechopen.73083.
  • Pörtner, H.-O., Roberts, D. C., Poloczanska, E. S., Mintenbeck, K., Tignor, M., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., & Rama, B. (eds.). (2022). IPCC, 2022: Summary for Policymakers In: Climate change 2022: Impacts, adaptation, and vulnerability. Contribution of working group II to the sixth assessment report of the intergovernmental panel on climate change. Cambridge University Press.
  • Prestby, T. J., Robinson, A. C., McLaughlin, D., Dudas, P. M., & Grozinger, C. M. (2023). Characterizing user needs for Beescape: A spatial decision support tool focused on pollinator health. Journal of Environmental Management, 325, 116416. https://doi.org/10.1016/j.jenvman.2022.116416
  • Randazzo, G., Italiano, F., Micallef, A., Tomasello, A., Cassetti, F. P., Zammit, A., D’Amico, S., Saliba, O., Cascio, M., Cavallaro, F., Crupi, A., Fontana, M., Gregorio, F., Lanza, S., Colica, E., & Muzirafuti, A. (2021). Webgis implementation for dynamic mapping and visualization of coastal geospatial data: A case study of BESS project. Applied Sciences, 11(17), 8233. https://doi.org/10.3390/app11178233
  • Restor: Your home for nature restoration. (n.d.). Restore.Eco. Retrieved February 12, 2022, from https://restor.eco/.
  • Riehmann, P., Hanfler, M., & Froehlich, B. (2005). Interactive Sankey diagrams. IEEE Symposium on Information Visualization, 2005. INFOVIS 2005, 233–240. https://doi.org/10.1109/INFVIS.2005.1532152
  • Robinson, A. C. (2017). Geovisual analytics. Geographic Information Science & Technology Body of Knowledge, 2017(Q3), https://doi.org/10.22224/gistbok/2017.3.6
  • Robinson, A. C., Peuquet, D. J., Pezanowski, S., Hardisty, F. A., & Swedberg, B. (2017). Design and evaluation of a geovisual analytics system for uncovering patterns in spatio-temporal event data. Cartography and Geographic Information Science, 44(3), 216–228. https://doi.org/10.1080/15230406.2016.1139467
  • Roth, R. E., & MacEachren, A. M. (2014). Geovisual Analytics & the Science of Interaction: A Case Study. 5.
  • Sacha, D., Senaratne, H., Kwon, B. C., Ellis, G., & Keim, D. A. (2016). The role of uncertainty, awareness, and trust in visual analytics. IEEE Transactions on Visualization and Computer Graphics, 22(1), 240–249. https://doi.org/10.1109/TVCG.2015.2467591
  • Sanchez, G. M., Eaton, M. J., Garcia, A. M., Keisman, J., Ullman, K., Blackwell, J., & Meentemeyer, R. K. (2022). Integrating principles and tools of decision science into value-driven watershed planning for compensatory mitigation. Ecological Applications, 33. https://doi.org/10.1002/eap.2766
  • Savelyev, A., & MacEachren, A. M. (2020). Advancing the theory and practice of system evaluation: A case study in geovisual analytics of social media. International Journal of Cartography, 6(2), 202–221. https://doi.org/10.1080/23729333.2019.1637488
  • Tapia-McClung, R., & Silván-Cárdenas, J. L. (2021). Exploring spatiotemporal urbanization through a hybrid remote sensing-geovisual analytics approach. IEEE, 021 Mexican International Conference on Computer Science (ENC), 1–8.
  • Thomas, J. J., & Cook, K. A. (2005). Illuminating the path: The research and development agenda for visual analytics. National Visualization and Analytics Ctr.
  • Tomaszewski, B. (2011). Situation awareness and virtual globes: Applications for disaster management. Computers & Geosciences, 37(1), 86–92. https://doi.org/10.1016/j.cageo.2010.03.009
  • Tomaszewski, B. M., Robinson, A. C., Weaver, C., Stryker, M., & MacEachern, A. M. (2009). GeoVisual Analytics and Crisis Management. Proceedings of the 4th International ISCRAM Conference, 8, 173–179.
  • Tomaszewski, B., & MacEachren, A. M. (2012). Geovisual analytics to support crisis management: Information foraging for geo-historical context. Information Visualization, 11(4), 339–359. https://doi.org/10.1177/1473871612456122
  • Tracey, J. A., Sheppard, J., Zhu, J., Wei, F., Swaisgood, R. R., & Fisher, R. N. (2014). Movement-Based estimation and visualization of space use in 3D for wildlife ecology and conservation. PLoS ONE, 9(7), e101205. https://doi.org/10.1371/journal.pone.0101205
  • Turdukulov, U., & Moncrieff, S. (2016). Enabling geovisual analytics of health data using a server-side approach. Cartography and Geographic Information Science, 43(1), 16–29. https://doi.org/10.1080/15230406.2015.1065762
  • Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: Can it facilitate? International Journal of Human-Computer Studies, 57(4), 247–262. https://doi.org/10.1006/ijhc.2002.1017
  • U.S. Department of the Interior. (n.d.). America the Beautiful: Our Work to Conserve at Least 30% of Lands and Waters by 2030. Retrieved April 1, 2022, from https://www.doi.gov/priorities/america-the-beautiful.
  • U.S. Fish and Wildlife Service (2021). U.S. Fish and Wildlife Service Proposes Delisting 23 Species from Endangered Species Act Due to Extinction. https://www.fws.gov/press-release/2021-09/us-fish-and-wildlife-service-proposes-delisting-23-species-endangered-species.
  • Urbano, F., Cagnacci, F., Calenge, C., Dettki, H., Cameron, A., & Neteler, M. (2010). Wildlife tracking data management: A new vision. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1550), 2177–2185. https://doi.org/10.1098/rstb.2010.0081
  • Vatin, G., & Napoli, A. (2013). Guiding the controller in geovisual analytics to improve maritime surveillance. GEOProcessing 2013: The Fifth International Conference on Advanced Geographic Information Systems, Applications, and Services, 7, 26–31.
  • Vitolo, C., Elkhatib, Y., Reusser, D., Macleod, C. J. A., & Buytaert, W. (2015). Web technologies for environmental Big Data. Environmental Modelling & Software, 63, 185–198. https://doi.org/10.1016/j.envsoft.2014.10.007
  • von Schuckmann, K., Le Traon, P.-Y., Alvarez-Fanjul, E., Axell, L., Balmaseda, M., Breivik, L.-A., Brewin, R. J. W., Bricaud, C., Drevillon, M., Drillet, Y., Dubois, C., Embury, O., Etienne, H., Sotillo, M. G., Garric, G., Gasparin, F., Gutknecht, E., Guinehut, S., Hernandez, F., … Verbrugge, N. (2016). The Copernicus Marine Environment Monitoring Service Ocean State Report. Journal of Operational Oceanography, 9(sup2), s235–s320. https://doi.org/10.1080/1755876X.2016.1273446
  • Walter, T., & Couzin, I. D. (2021). TRex, a fast multi-animal tracking system with markerless identification, and 2D estimation of posture and visual fields. ELife, 10, e64000. https://doi.org/10.7554/eLife.64000
  • Weisse, M. J., Noguerón, R., Vicencio, R. E. V., & Soto, D. A. C. (2019). Use of near-real-time deforestation alters: A case study from Peru. World Resources Institute. https://files.wri.org/d8/s3fs-public/use-near-real-time-deforestation-alerts.pdf.
  • White, J. J. D., & Roth, R. E. (2010). TwitterHitter: Geovisual Analytics for Harvesting Insight from Volunteered Geographic Information. 8.
  • Willis, K. S. (2015). Remote sensing change detection for ecological monitoring in United States protected areas. Biological Conservation, 182, 233–242. https://doi.org/10.1016/j.biocon.2014.12.006
  • World Resources Institute. (n.d.). Forest Monitoring, Land Use & Deforestation Trends. Global Forest Watch. Retrieved March 20, 2021, from https://www.globalforestwatch.org/.
  • Xu, H., Demir, I., Koylu, C., & Muste, M. (2019). A web-based geovisual analytics platform for identifying potential contributors to culvert sedimentation. Science of The Total Environment, 692, 806–817. https://doi.org/10.1016/j.scitotenv.2019.07.157
  • Xu, H., Windsor, M., Muste, M., & Demir, I. (2020). A web-based decision support system for collaborative mitigation of multiple water-related hazards using serious gaming. Journal of Environmental Management, 255, 109887. https://doi.org/10.1016/j.jenvman.2019.109887
  • Yao, F., & Wang, Y. (2020). Towards resilient and smart cities: A real-time urban analytical and geo-visual system for social media streaming data. Sustainable Cities and Society, 63, 102448. https://doi.org/10.1016/j.scs.2020.102448
  • Zhang, D., Wang, H., Wang, X., & Lü, Z. (2020). Accuracy assessment of the global forest watch tree cover 2000 in China. International Journal of Applied Earth Observation and Geoinformation, 87, 102033. https://doi.org/10.1016/j.jag.2019.102033
  • Zhang, T., Hua, G., & Ligmann-Zielinska, A. (2015). Visually-driven parallel solving of multi-objective land-use allocation problems: A case study in Chelan, Washington. Earth Science Informatics, 8(4), 809–825. https://doi.org/10.1007/s12145-015-0214-6
  • Zurita-Milla, R., Blok, C., & Retsios, V. (2012). Geovisual analytics of satellite image time series. International Congress on Environmental Modelling and Software, 392, 1–8. https://scholarsarchive.byu.edu/iemssconference/2012/Stream-B/392

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