Combinando teselaciones de alta resolución y redes de transporte detalladas para el análisis de accesibilidad en áreas extensasIndicadores de presión humana en áreas costeras

  1. Borja Moya-Gómez 1
  2. José Ojeda-Zújar 2
  3. Juan Carlos García-Palomares 1
  4. Juan Pedro Pérez-Alcántara 2
  5. Javier Gutiérrez Puebla 1
  6. Esperanza Sánchez-Rodríguez 2
  1. 1 tGIS Research Group, Department of Geography, Complutense Universityof Madrid
  2. 2 Department of Geography, University of Seville, Sevilla
Journal:
Geofocus: Revista Internacional de Ciencia y Tecnología de la Información Geográfica

ISSN: 1578-5157

Year of publication: 2024

Issue: 33

Pages: 27-42

Type: Article

DOI: 10.21138 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

More publications in: Geofocus: Revista Internacional de Ciencia y Tecnología de la Información Geográfica

Abstract

Human pressure on coastal areas poses a serious threat to their conservation. This pressure can be measured using accessibility indicators. However, a detailed accessibility analysis, with highly spatially disaggregated information and complex transport networks, requires millions of optimal routes to be obtained. To reduce processing times, this paper uses the centroid of aregular tessellation representingtrip origins (square tileswith population and average income) and a layer of points associated with the coastline to represent destinations. Route calculations between all origins and all destinations are performed once, and then, depending on the objective of the study (accessibility to ports, beaches, lighthouses,or other points of interest), optimal route selections to the corresponding destination typecan be made. The study resultsshow the different degrees of human pressure on Andalusian beaches using different accessibility indicators

Bibliographic References

  • Boisjoly, G., El-Geneidy, A. (2016). Daily fluctuations in transit and job availability: A comparative assessment of time-sensitive accessibility measures. Journal of transport geography, 52, 73-81.
  • Cascetta, E., Cartenì, A., Montanino, M. (2016). A behavioral model of accessibility based on the number of available opportunities. Journal of Transport Geography, 51, 45-58.
  • Condeço-Melhorado, A., Gutiérrez Puebla, J., García Palomares, J. C. (2013). Influence of distance decay on the measurement of spillover effects of transport infrastructure: a sensitivity analysis. GeoFocus. International Review of Geographical Information Science and Technology, (13_1), 22-47.
  • de Souza, G. N., Oliveira, C. A., Tardem, A. S., Soares-Gomes, A. (2017). Counting and measuring ghost crab burrows as a way to assess the environmental quality of beaches. OceanCoastal Management, 140, 1-10.
  • Defeo, O., McLachlan, A., Schoeman, D. S., Schlacher, T. A., Dugan, J., Jones, A., ... Scapini, F. (2009). Threats to sandy beach ecosystems: a review. Estuarine, coastal and shelf science, 81(1), 1-12.
  • Farber, S., Morang, M. Z., Widener, M. J. (2014). Temporal variability in transit-based accessibility to supermarkets. Applied Geography, 53, 149-159.
  • García-Albertos, P., Picornell, M., Salas-Olmedo, M.H., Gutiérrez, J., 2019. Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis. Transportation Research A, 125, pp. 294-307.
  • Gutiérrez, J. (2001). Location, economic potential and daily accessibility: an analysis of the accessibility impact of the high-speed line Madrid–Barcelona–French border. Journal of transport geography, 9(4), 229-242.
  • Gutiérrez, J., García-Palomares, J.C. (2020). "Transport and Accessibility". In: Kobayashi, A. (Ed.), International Encyclopedia of Human Geography, 2nd edition. vol. 13, pp. 407–414.
  • Handy, S. L., Niemeier, D. A. (1997). Measuring accessibility: an exploration of issues and alternatives. Environment and planning A, 29(7), 1175-1194.
  • Hansen, W.G., 1959. How accessibility shapes land-use. Journal of American Institute of Planners, 25 (2), pp. 73–76
  • Huff, D. L. (1963). A probabilistic analysis of shopping center trade areas. Land economics, 39(1), 81-90.
  • Huff, D. L. (1964). Defining and estimating a trading area. Journal of marketing, 28(3), 34-38.
  • IECA (2020): Distribución espacial de la población en Andalucía.https://www.juntadeandalucia.es/institutodeestadisticaycartografia/VisorGrid/visor.htm
  • INE (2019): Atlas de Distribución Rentas de los Hogares. "https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736177088&menu=ultiDatos&idp=1254735976608"
  • Kapatsila, B., Palacios, M. S., Grisé, E., El-Geneidy, A. (2023). Resolving the accessibility dilemma: Comparing cumulative and gravity-based measures of accessibility in eight Canadian cities. Journal of Transport Geography, 107, 103530.
  • Kelly, J. F. (2014). Effects of human activities (raking, scraping, off-road vehicles) and natural resource protections on the spatial distribution of beach vegetation and related shoreline features in New Jersey. Journal of Coastal Conservation, 18, 383-398.
  • Kelobonye, K., Zhou, H., McCarney, G., Xia, J. C. (2020). Measuring the accessibility and spatial equity of urban services under competition using the cumulative opportunities measure. Journal of Transport Geography, 85, 102706.
  • Kim, J., Nicholls, S. (2018). Access for all? Beach access and equity in the Detroit metropolitan area. Journal of Environmental Planning and Management, 61(7), 1137-1161.
  • Kim, J., Lyu, S. O., Song, H. (2019). Environmental justice and public beach access. City Community, 18(1), 49-70.
  • Kim, J., Jang, S. (2023). Assessing equity in public beach access with spatial intersectionality. The Professional Geographer, 75(4), 636-641.
  • Langford, M., Higgs, G., Radcliffe, J., White, S. (2008). Urban population distribution models and service accessibility estimation. Computers, Environment and Urban Systems,32.1, 66-80.
  • Martínez, A., Eckert, E. M., Artois, T., Careddu, G., Casu, M., Curini-Galletti, M., Gazale, V.,Gobert, S.,Ivanenko, V. N., Jondelius,U.,Marzano,M.,Pesole,G.,Zanello,A.,TodaroM. A.,Fontaneto, D. (2020). Human access impacts biodiversity of microscopic animals in sandy beaches. Communications Biology, 3(1), 175.
  • Montgomery, M. C., Chakraborty, J., Grineski, S. E., Collins, T. W. (2015). An environmental justice assessment of public beach access in Miami, Florida. Applied Geography, 62, 147-156.
  • Morris, J. M., Dumble, P. L., and Wigan, M. R. (1979). Accessibility indicators for transport planning. Transportation Research A, 13A, 91-109.
  • Moura, T. G. Z., Garcia-Alonso, L., Salas-Olmedo, M. H. (2017). Delimiting the scope of the hinterland of ports: proposal and case study. Journal of Transport Geography, 65, 35-43.
  • Moya-Gómez, B. García-Palomares, J.C., 2017. The impacts of congestion on automobile accessibility. What happens in the largest European cities? Journal of Transport Geography,62, pp. 148-159
  • Nakaya, T. (2000). An information statistical approach to the modifiable areal unit problem in incidence rate maps. Environment and Planning A, 32, 91–109.
  • Omer, I. (2006). Evaluating accessibility using house-level data: A spatial equity perspective. Computers, environment and urban systems, 30(3), 254-274.
  • Ojeda, J., Paneque, P., Rodríguez, E. S., Alcántara, J. P. P. (2021). Geografía de la renta de los hogares en España a nivel municipal: nuevos datos y nuevas posibilidades de geovisualización, exploración y análisis espacial en entornos cloud. Investigaciones Geográficas, (76), 9-30.
  • Openshaw, S. (1984). The modifiable aerial unit problem. Concepts and techniques in modern geography. Norwich: Geo Books.
  • Peña-Alonso, C., Hernández-Calvento, L., Pérez-Chacón, E., Ariza-Solé, E. (2017). The relationship between heritage, recreational quality and geomorphological vulnerability in the coastal zone: A case study of beach systems in the Canary Islands. Ecological Indicators, 82, 420-432.
  • Pérez-Fernández, O. (2021). Modelos de localización asignación utilizando redes dinámicas a partir de ficheros GTFS y datos de TomTom. GeoFocus. International Review of Geographical Information Science and Technology, (28), 59-81.
  • Prieto, A and Ojeda, J (in press): Metodología de levantamiento de datos y cálculo de las tasas de erosión en el litoral: la evolución de la línea de costa andaluza en las playas expuestas para el S.XXI (2001-2019). Investigaciones Geográficas.
  • Pritchard, J. P., Tomasiello, D. B., Giannotti, M., Geurs, K. (2019). Potential impacts of bike-and-ride on job accessibility and spatial equity in São Paulo, Brazil. Transportation research part A: policy and practice, 121, 386-400.
  • Seer, F. K., Irmler, U., Schrautzer, J. (2016). Beaches under pressure–effects of human access on vegetation at Baltic Sea beaches. Applied Vegetation Science, 19(2), 225-234.
  • Stępniak, M., Pritchard, J. P., Geurs, K. T., Goliszek, S. (2019). The impact of temporal resolution on public transport accessibility measurement: Review and case study in Poland. Journal of transport geography, 75, 8-24.
  • Taylor, C., Gorard, S., Fitz, J. (2003). The modifiable areal unit problem: segregation between schools and levels of analysis. International Journal of Social Research Methodology, 6(1), 41–60.
  • Tomasiello, D. B., Giannotti, M. (2022). Unfolding time, race and class inequalities to access leisure. Environment and Planning B: Urban Analytics and City Science, 23998083221111405.
  • Vallés, S. M., Gallego Fernández, J. B., Dellafiore, C. M. (2011). Dune vulnerability in relation to tourism pressure in central Gulf of Cádiz (SW Spain), a case study. Journal of Coastal Research, 27(2), 243-251.
  • Wegener, M., Eskelinnen, H., Fürst, F., Schürmann, C.,Spiekermann, K. (2000). Indicators of Geographical Position. Final Report of the Working Group "Geographical Position"of the Study Programme on European Spatial Planning. Dortmund, IRPUD.
  • Weng, J., Zhu, X., Li, X. (2020). Impact of high-speed rail on destination accessibility: a case study of China. Journal of China Tourism Research, 16(4), 494-509.
  • Wessel, N., Farber, S. (2019). On the accuracy of schedule-based GTFS for measuring accessibility. Journal of Transport and Land Use, 12(1), 475-500.
  • Yu, Siqi, Xigang Zhu, and Qian He. (2020). An assessment of urban park access using house-level data in urban China: Through the lens of social equity. International journal of environmental research and public health,17.7: 2349.
  • Zhang, M., Kukadia, N. (2005). Metrics of urban form and the modifiable areal unit problem. Transportation Research Record, 1902(1), 71-79.
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