10.30486/gcr.2020.1901102.1019

The Increasing Need for Geographical Information Technology (GIT) Tools in Geoconservation and Geotourism

HTML PDF
  • Mark Williams1,
  • Melinda McHenry1,
  1. Geography and Spatial Sciences, School of Environments, Technology and Design,The University of Tasmania, Clarks Road, Sandy Bay 7005 Tasmania, Australia
Cover Image

Published in Issue 2020-07-01

Copyright (c) -1 Mark Williams, Melinda McHenry (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Williams, M., & McHenry, M. (2020). The Increasing Need for Geographical Information Technology (GIT) Tools in Geoconservation and Geotourism. Geoconservation Research, 3(1). https://doi.org/10.30486/gcr.2020.1901102.1019
Crossref
Scopus
Google Scholar
Europe PMC

HTML views: 46

PDF views: 181

Abstract

The use of GIS, remote sensing, and other geographic tools in geoconservation and geotourism is increasing. These tools – hereafter referred to as ‘Geographic Information Technology’ (GIT) tools – have the potential to simplify workflow in geoconservation assessment and inventory, be employed as decision support and decision making tools for complex decisions, or be used to enhance communication and user experience in geotourism. In this paper, we review the progress on the use of GIT tools in geoheritage and geotourism to date, highlighting current gaps in practice. By way of an interview of prominent global geoconservation and geotourism professionals conducted in 2018, we show that approximately 25% of the surveyed workforce use some type of GIT tool to aid in decision support, decision making, or for communication(s) of inventory elements and features of interest. Upon review of the literature, it appears that the vast majority of tools are used for communications of inventory, features and site maps. Opportunities for further improvement in the field will most likely be realised when more sophisticated decision-making tools become available for geoconservationists and geotourism professionals, especially in the use of GIS Multi-Criteria Decision Analysis (GIS-MCDA) to rank and curate inventory, geosites or geotouristic experiences. We conclude our discussion with a case study demonstrating the use of selected GIT tools in the process of decision support, decision making, and communications. We show that at each step in the process of geoconservation, there is a GIT tool that can simplify workflow, and be used to cross-collaborate with other users or platforms. With further refinement, GIT tools should be able to support geoconservationists and geotouristic professionals in global decision making – for assessment, inventory, and standardisation of interpretations of landscape values and potential use.

Keywords

  • Degradation,
  • Drone,
  • Education,
  • Mobile app,
  • Scientific value,
  • Tourism,
  • Web map
HTML PDF

References

  1. Aldighieri B, Testa B, Bertini A (2016). 3D exploration of the San Lucano Valley: virtual geo-routes for everyone who would like to understand the landscape of the Dolomites. Geoheritage. 8(1):77-90. https://doi.org/10.1007/s12371-015-0164-x
  2. Araujo AM, Pereira DI (2018). A New Methodological Contribution for the Geodiversity Assessment: Applicability to Ceará State (Brazil). Geoheritage. 10(4):591–605. https://doi.org/10.1007/s12371-017-0250-3
  3. Bailey JJ, Boyd DS, Hjort J, Lavers, CP, Field, R (2017). Modelling native and alien vascular plant species richness: At which scales is geodiversity most relevant? Global Ecology and Biogeography. 26(7):763–776. https://doi.org/10.1111/geb.12574
  4. Banjac N, Savić L, Maran A, Cukavac, M, Ganic, M, Nikic, Z (2011). The Geology in Digital Age. In Proceedings of the 17th Meeting of the Association of European Geological Societies. Serbia: Serbian Geological Society.
  5. Benito-Calvo A, Pérez-González A, Magri O, Meza P (2009). Assessing regional geodiversity: the Iberian Peninsula. Earth Surface Processes and Landforms. 34(10):1433–1445. https://doi.org/10.1002/esp.1840
  6. Bishop M (2013). Remote Sensing and GIScience in Geomorphology: Introduction and Overview. Treatise on Geomorphology. 3:1–24. https://doi.org/10.1016/B978-0-12-374739-6.00040-3
  7. Brandolini P, Pelfini M (2010). Mapping geomorphological hazards in relation to geotourism and hiking trails. In Mapping Geoheritage, pp. 31-45, Lausanne, Institut de géographie, Géovisions n°35.
  8. Bratton A, Smith B, McKinley J, Lilley K (2013). Expanding the Geoconservation Toolbox: Integrated Hazard Management at Dynamic Geoheritage Sites. Geoheritage 5(3):173–183. https://doi.org/10.1007/s12371-013-0082-8
  9. Brilha J (2016). Inventory and Quantitative Assessment of Geosites and Geodiversity Sites: a Review. Geoheritage. 8(2):119–134. https://doi.org/10.1007/s12371-014-0139-3
  10. Carn SA (1999). Application of synthetic aperture radar (SAR) imagery to volcano mapping in the humid tropics: a case study in East Java, Indonesia. Bulletin of Volcanology. 61(1-2):92–105
  11. Carrión MP, Herrera FG, Briones J, Domínguez-Cuesta M, Berrezueta, E (2018). Geotourism and Local Development Based on Geological and Mining Sites Utilization, Zaruma-Portovelo, Ecuador. Geosciences. 8(6):205. https://doi.org/10.3390/geosciences8060205
  12. Cartoscope (n.d.) Geological sites of NSW. http://www.geomaps.com.au/scripts/centralwest.php. Retrieved 18 Jun, 2018
  13. Casals-Carrasco P, Kubo S, Madhavan BB (2000). Application of spectral mixture analysis for terrain evaluation studies. International Journal of Remote Sensing. 21(16):3039–3055. https://doi.org/10.1080/01431160050144947
  14. Cayla N (2014). An Overview of New Technologies Applied to the Management of Geoheritage. Geoheritage. 6(2):91–102. https://doi.org/10.1007/s12371-014-0113-0
  15. Chen RF, Chang KJ, Angelier J, Chan Y, Deffontaines B, Lee C, Lin , M (2006) Topographical changes revealed by high-resolution airborne LiDAR data: The 1999 Tsaoling landslide induced by the Chi–Chi earthquake. Engineering geology. 88(3-4):160–172
  16. Corsini A, Borgatti L, Cervi F, Dahne A, Ronchetti F, Sterzai P (2009). Estimating mass-wasting processes in active earth slides–earth flows with time-series of High-Resolution DEMs from photogrammetry and airborne LiDAR. Natural Hazards and Earth System Sciences. 9(2):433–439
  17. Cracknell MJ, Reading AM (2014). Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and the use of explicit spatial information. Computers & Geosciences. 63:22–33. https://doi.org/10.1016/j.cageo.2013.10.008
  18. de Carvalho O, Guimarães R, Montgomery D, Gillespie A, Trancoso Gomes R, de Souza Martins E, Silva N (2013). Karst Depression Detection Using ASTER, ALOS/PRISM and SRTM-Derived Digital Elevation Models in the Bambuí Group, Brazil. Remote Sensing. 6(1):330–351. https://doi.org/10.3390/rs6010330
  19. Department of Primary Industries, Parks, Water and Environment (DPIPWE) (n.d.). Tasmanian Geoconservation Database (TGD). https://dpipwe.tas.gov.au/conservation/geoconservation/tasmanian-geoconservation-database. Retrieved 27 May, 2020
  20. Dewitte O, Jasselette J-C, Cornet Y, Van Den Eeckhaut M, Collignon A, Poesen J, Demoulin A (2008). Tracking landslide displacements by multi-temporal DTMs: A combined aerial stereophotogrammetric and LIDAR approach in western Belgium. Engineering Geology. 99(1-2):11–22
  21. dos Santos DS, Mansur KL, de Arruda Jr ER, Dantas M, Shinzato E (2018). Geodiversity Mapping and Relationship with Vegetation: A Regional-Scale Application in SE Brazil. Geoheritage. 11(2):399-415. https://doi.org/10.1007/s12371-018-0295-y
  22. Eeckhaut MVD, Poesen J, Verstraeten G, Vanacker V, Nyssen J, Moeyersons J, Beek LPH, Vandekerckhove L (2007). Use of LIDAR‐derived images for mapping old landslides under forest. Earth Surface Processes and Landforms. 32(5):754–769
  23. Fernández-Lozano J, Gutiérrez-Alonso G (2017). The Alejico Carboniferous Forest: a 3D-Terrestrial and UAV-Assisted Photogrammetric Model for Geologic Heritage Preservation. Geoheritage. 9(2):163–173. https://doi.org/10.1007/s12371-016-0193-0
  24. Fiore GM (2013). Monitoring and valuing the European geological heritage: operational uses of satellite applications. https://www.eurisy.org/data_files/publications-documents/18/publications_document-18.pdf?t=1392914887. Retrieved 29 Jun, 2020
  25. Forte JP, Brilha J, Pereira DI, Nolasco M (2018). Kernel Density Applied to the Quantitative Assessment of Geodiversity. Geoheritage. 10(2):205–217. https://doi.org/10.1007/s12371-018-0282-3
  26. Fuertes-Gutiérrez I, Fernández-Martínez E (2012). Mapping Geosites for Geoheritage Management: A Methodological Proposal for the Regional Park of Picos de Europa (León, Spain). Environmental Management. 50(5):789–806. https://doi.org/10.1007/s00267-012-9915-5
  27. Gallerini G, Susini S, Bruciatelli L, Donatis M de (2011). Geomatics and geo-tourism: San Bartolo Natural Park case study (Pesaro, Italy). GeoActa. Special Publication 3:167–178
  28. Geological Survey of Brazil (2006). Geodiversity Map of Brazil. http://rigeo.cprm.gov.br/jspui/handle/doc/16854. Retrieved 27 May, 2020, from
  29. Ghiraldi L, Giordano E, Perotti L, Giardino M (2014). Digital Tools for Collection, Promotion and Visualisation of Geoscientific Data: Case Study of Seguret Valley (Piemonte, NW Italy). Geoheritage. 6(2):103–112. https://doi.org/10.1007/s12371-014-0115-y
  30. Gomez C, Hayakawa Y, Obanawa H (2015). A study of Japanese landscapes using structure from motion derived DSMs and DEMs based on historical aerial photographs: New opportunities for vegetation monitoring and diachronic geomorphology. Geomorphology. 242:11–20. https://doi.org/10.1016/j.geomorph.2015.02.021
  31. González-Delgado JA, Martínez-Graña AM, Civis J, Sierro FJ, Goy JL, Dabrio CJ, Ruiz F, González-Regalado ML, Abad M (2015). Virtual 3D tour of the Neogene palaeontological heritage of Huelva (Guadalquivir Basin, Spain). Environmental Earth Sciences. 73(8):4609–4618. https://doi.org/10.1007/s12665-014-3747-y
  32. Gupta R (2018). Remote Sensing Geology (3rd Ed). Berlin: Springer Berlin Heidelberg
  33. Hackney C, Clayton AI (2015). Section 1.7 Unmanned Aerial Vehicles (UAVs) and their application in geomorphic mapping. In Geomorphological Techniques. London: British Society of Geomorphology
  34. Harmon B, Viles H (2013). Beyond geomorphosites: trade-offs, optimization, and networking in heritage landscapes. Environment Systems and Decisions. 33(2):272–285. https://doi.org/10.1007/s10669-013-9448-3
  35. Hjort J, Luoto M (2012). Can geodiversity be predicted from space? Geomorphology. 153–154:74–80. https://doi.org/10.1016/j.geomorph.2012.02.010
  36. Hoblea F, Delannoy J, Jaillet S, Ployon E, Sadier B (2014). Digital Tools for Managing and Promoting Karst Geosites in Southeast France. Geoheritage. 6(2):113–127. https://doi.org/10.1007/s12371-014-0112-1
  37. Ilić M, Stojković S, Rundić L, Ćalić J, Sandić D (2016). Application of the geodiversity index for the assessment of geodiversity in urban areas: an example of the Belgrade city area, Serbia. Geologia Croatica. 69(3):325–336. https://doi.org/10.4154/gc.2016.27
  38. Kaskela AM, Kotilainen AT (2017). Seabed geodiversity in a glaciated shelf area, the Baltic Sea. Geomorphology 295:419–435. https://doi.org/10.1016/j.geomorph.2017.07.014
  39. Kasprzak M, Jancewicz K, Michniewicz A (2018). UAV and SfM in detailed geomorphological mapping of granite tors: an example of Starościńskie Skały (Sudetes, SW Poland). Pure and Applied Geophysics. 175(9):3193-3207
  40. Kiernan K (1995). An atlas of Tasmanian karst: Volumes 1-2. Hobart, Australia: Tasmanian Forest Research Council.
  41. Kozlowski S (2004). Geodiversity. The concept and scope of geodiversity. Przeglad Geologiczny. (8)52:5
  42. Kruse S (2013). 3.5 Near-Surface Geophysics in Geomorphology. In Treatise on Geomorphology, pp 103–129. San Diego: Elsevier
  43. Litwin L (2008). Atlas of karst area based on Web GIS technology. Environmental Geology. 54(5):1029–1036. https://doi.org/10.1007/s00254-007-0892-6
  44. Lombardo V, Piana F, Fioraso G, Irace A, Mimmo D, Mosca P, Tallone S, Barale L, Morelli M, Giardino M (2016). The classification scheme of the piemonte geological map and the ontogeonous initiative. Rend. Online Soc. Geol. It. 39:117-120 https://doi.org/10.3301/ROL.2016.61
  45. Lombardo V, Piana F, Mimmo D (2018). Semantics–informed geological maps: Conceptual modeling and knowledge encoding. Computers & Geosciences. 116:12–22. https://doi.org/10.1016/j.cageo.2018.04.001
  46. Lugeri FR, Farabollini P, Lugeri N, Amadio V, Baiocco F (2017). “LANDSCApp”: a friendly way to share the Italian geo-heritage. Acta Geoturistica. 8(2):79-86 https://doi.org/10.1515/agta-2017-0008
  47. Luo X (2015). An Integrated WebGIS-Based Management Platform of Geopark. The Open Construction and Building Technology Journal. 9(1):287–291. https://doi.org/10.2174/1874836801509010287
  48. Martin S (2014). Interactive Visual Media for Geomorphological Heritage Interpretation. Theoretical Approach and Examples. Geoheritage. 6(2):149–157. https://doi.org/10.1007/s12371-014-0107-y
  49. Martin S, Reynard E, Pellitero Ondicol R, Ghiraldi L (2014). Multi-scale Web Mapping for Geoheritage Visualisation and Promotion. Geoheritage. 6(2):141–148. https://doi.org/10.1007/s12371-014-0102-3
  50. Martinez-Graña AM, Goy JL, Cimarra C (2015). 2D to 3D geologic mapping transformation using virtual globes and flight simulators and their applications in the analysis of geodiversity in natural areas. Environmental Earth Sciences. 73(12):8023–8034. https://doi.org/10.1007/s12665-014-3959-1
  51. Martínez-Graña AM, Legoinha P, González-Delgado JA, Dabrio CJ, Pais J, Goy JL, Zazo C, Civis J, Armenteros I, Alonso-Gavilan G, Dias R, Cunha T (2017). Augmented Reality in a Hiking Tour of the Miocene Geoheritage of the Central Algarve Cliffs (Portugal). Geoheritage. 9(1):121–131. https://doi.org/10.1007/s12371-016-0182-3
  52. Masron T, Mohamed B, Marzuki A (2015). GIS base tourism decision-support system for Langkawi Island, Kedah, Malaysia. Theoretical and Empirical Researches in Urban Management. 10(2):21–35
  53. Melelli L, Vergari F, Liucci L, Del Monte M (2017). Geomorphodiversity index: Quantifying the diversity of landforms and physical landscape. Science of The Total Environment. 584–585:701–714. https://doi.org/10.1016/j.scitotenv.2017.01.101
  54. Mwaniki M (2016). Geology mapping and lineament visualization using image enhancement techniques: comparison of Landsat 8 (OLI) and Landsat 7 (ETM+). Dissertation. Jomo Kenyatta University of Agriculture and Technology
  55. Najwer A, Borysiak J, Gudowicz J, Mazurek M, Zwoliński Z (2016). Geodiversity and Biodiversity of the Postglacial Landscape (Dębnica River Catchment, Poland). Quaestiones Geographicae. 35(1):5–28. https://doi.org/10.1515/quageo-2016-0001
  56. Najwer A, Reynard E, Zwolinski Z (2014). GIS and Multi-criteria evaluation (MCE) for landform geodiversity assessment. In Proceedings of the EGU General Assembly 2014 (Volume 16). Austria: Copernicus.
  57. Năpăruş-Aljančič M, Pătru-Stupariu I, Stupariu MS (2017). Multiscale wavelet-based analysis to detect hidden geodiversity. Progress in Physical Geography. 41(5):601–619. https://doi.org/10.1177/0309133317720835
  58. Napieralski J, Barr I, Kamp U, Kervyn M (2013). 3.8 Remote Sensing and GIScience in Geomorphological Mapping. In Treatise on Geomorphology. pp 187–227. San Diego: Elsevier
  59. Nex F, Remondino F (2014). UAV for 3D mapping applications: a review. Applied Geomatics. 6(1):1–15. https://doi.org/10.1007/s12518-013-0120-x
  60. Ng Y (2016). Drones: Their applications in geopark and geoheritage management. http://www.leisuresolutions.com.au/wp-content/uploads/2015/02/dronesapplication_ggn2016.pdf. Retrieved 27 May, 2020
  61. Nichols W, Killingbeck K, August P (1998). The Influence of Geomorphological Heterogeneity on Biodiversity: II. A Landscape Perspective. Conservation Biology. 12(2):371–379
  62. Otto J-C, Prasicek G, Blöthe J, Schrott L (2018). 2.05 - GIS Applications in Geomorphology. In Comprehensive Geographic Information Systems. pp 81–111. Elsevier: Oxford https://doi.org/10.1016/B978-0-12-409548-9.10029-6
  63. Pál M, Albert G (2019). Digital cartography for geoheritage: turning an analogue geotourist map into digital. In Proceedings of the ICA (pp. 1–7). https://doi.org/10.5194/ica-proc-2-96-2019
  64. Piras M, Taddia G, Forno MG, Gattiglio M, Aicardi I, Dabove P, Russo SL, Lingua A (2017). Detailed geological mapping in mountain areas using an unmanned aerial vehicle: application to the Rodoretto Valley, NW Italian Alps. Geomatics, Natural Hazards and Risk. 8(1):137–149. https://doi.org/10.1080/19475705.2016.1225228
  65. Poiraud A, Chevalier M, Claeyssen B, Biron P-E, Joly B (2016). From geoheritage inventory to territorial planning tool in the Vercors massif (French Alps): Contribution of statistical and expert cross approaches. Applied Geography. 71:69–82. https://doi.org/10.1016/j.apgeog.2016.04.012
  66. Qiu J-T, Li P-J, Yu Z-F, Li P (2015). Petrology and Spectroscopy Studies on Danxia Geoheritage in Southeast Sichuan Area, China: Implications for Danxia Surveying and Monitoring. Geoheritage. 7(4):307–318. https://doi.org/10.1007/s12371-015-0160-1
  67. Regolini-Bissig G, Reynard E (Eds) (2010). Mapping geoheritage. Lausanne: Institut de Géographie, Géovisions.
  68. Rutherford J, Kobryn H, Newsome D (2015). A Case Study in the Evaluation of Geotourism Potential Through Geographic Information Systems: Application in a Geology-Rich Island Tourism Hotspot. Current Issues in Tourism. 18(3):267–285. https://doi.org/10.1080/13683500.2013.873395
  69. Saadi NM, Aboud E, Saibi H, Watanabe K (2008). Integrating data from remote sensing, geology and gravity for geological investigation in the Tarhunah area, Northwest Libya. International Journal of Digital Earth. 1(4):347–366. https://doi.org/10.1080/17538940802435844
  70. Santos I, Henriques R, Mariano G, Pereira DI (2018). Methodologies to Represent and Promote the Geoheritage Using Unmanned Aerial Vehicles, Multimedia Technologies, and Augmented Reality. Geoheritage. 10(2):143–155. https://doi.org/10.1007/s12371-018-0305-0
  71. Serrano E, Ruiz-Flaño P, Arroyo P (2009). Geodiversity assessment in a rural landscape: Tiermes-Caracena area (Soria, Spain). Memorie Descrittive Della Carta Geoligica d’Italia. 87:173–180
  72. Simon N, Ali CA, Mohamed KR, Sharir K (2016). Best band ratio combinations for the lithological discrimination of the Dayang Bunting and Tuba Islands, Langkawi, Malaysia. Sains Malaysiana. 45(5):659–667
  73. Slama T, Turki MM (2015). 3D Cartography and Geovisualization based on GIS and Geovrml for an open access landform investigation and analysis within an Open web platform (Owp). In Proceedings of 15th International Multidisciplinary Scientific GeoConference (pp. 619–626). Bulgaria: SGEM
  74. Stepišnik U, Trenchovska A (2018). A New Quantitative Model for Comprehensive Geodiversity Evaluation: the Škocjan Caves Regional Park, Slovenia. Geoheritage. 10(1):39–48. https://doi.org/10.1007/s12371-017-0216-5
  75. Suma A, Cosmo PD (2011). Geodiv Interface: An Open Source Tool for Management and Promotion of the Geodiversity of Sierra De Grazalema Natural Park (andalusia, Spain). GeoJournal of Tourism and Geosites. 8(2):309-318
  76. Suma A, Gracia F, Cosmo PD (2010). Detection and mapping of karst depressions through remote sensing approach: an example from Sierra de Líbar (Málaga, SW Spain). In A. Mihevc, M. Prelovšek, N-Z. Hajna (Eds.). In Proceedings of the 18th International Karstological School" Classical Karst"- Dinaric Karst (pp. 63-63). Slovenia: Speleological Association of Slovenia.
  77. van der Meer FD, van der Werff HMA, van Ruitenbeek FJA, et al (2012). Multi- and hyperspectral geologic remote sensing: A review. International Journal of Applied Earth Observation and Geoinformation. 14(1):112–128. https://doi.org/10.1016/j.jag.2011.08.002
  78. Waldhoff G, Bubenzer O, Bolten A, Koppe W, Bareth G (2008). Spectral analysis of ASTER, Hyperion, and Quickbird data for geomorphological and geological research in Egypt (Dakhla Oasis, Western Desert). Int Arch Photogramm Remote Sens Spat Inf Sci. 37:1201–1206
  79. Westoby MJ, Brasington J, Glasser NF, Hambrey MJ, Reynolds JM (2012). ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology 179:300–314. https://doi.org/10.1016/j.geomorph.2012.08.021
  80. Williams MA, McHenry MT (2020). Application of Geographic Information Technologies (GIT) to geosite and geodiversity site assessment in Tasmania, Australia. Manuscript submitted for publication.
  81. Williams, MA, McHenry MT. Boothroyd A (2020). Geoheritage and Geotourism: challenges and unifying themes. Geoheritage. 12(63). https://doi.org/10.1007/ s12371-020-00492-1
  82. Yürür MT, Saein AF, Kaygısız N (2018). What a Geologist May Do When the Geological Heritage Is in Danger? Geoheritage. 11(2):301-308. https://doi.org/10.1007/s12371-018-0284-1
  83. Zatserkovnyi V, Oberemok N, Berezina P (2017). Geoportal as a means to popularize geological heritage of Ukraine. Pidvodni tehnologii. 7:18–27. https://doi.org/10.26884/1707.1201
  84. Zwolinski Z, Najwer A, Giardino M (2016). Methods of geodiversity assessment and theirs application. In Proceedings of the EGU General Assembly 2016. Austria: Copernicus.
  85. Zwolinski Z, Najwer A, Giardino M (2018). Chapter 2 - Methods for Assessing Geodiversity. In Geoheritage, pp 27–52. Amsterdam: Elsevier.