A spatial approach for the identification the family orchards areas in rural areas: the case of Sinincay -Cuenca – Ecuador
DOI:
https://doi.org/10.37135/ns.01.11.09Keywords:
Cropland, Sentinel-2, Remote sensing, Land useAbstract
Mapping land use and delimiting study areas in the peripheral zones of cities has been one of the central themes of the literature on urban and territorial studies in Latin American countries with difficult access to data where transformation processes are accelerated. The objective of this study was to propose an applicable methodology for the detection of home garden areas in rural areas of Cuenca. It was based on the use of Sentinel-2 satellite images and unsupervised classification processes to identify possible cultivation areas. Based on this, spatial criteria were defined to classify and identify home gardens, based on the characteristics of the gardens themselves. A total of 699 gardens were identified in the field. Therefore, this study is a first approximation to the identification of home gardens in rural areas and constitutes very useful information for local governments, who are responsible for promoting these activities and in turn improving the production, mobilization, and marketing conditions of the vulnerable group that engages in subsistence agriculture. Thus, this research can be replicated in different localities and geographical contexts.
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ArcGIS. (s.f.). Herramienta Clasificación no supervisada de clúster Iso. Obtenido Enero 13, 2023, de https://desktop.arcgis.com/es/arcmap/latest/extensions/spatial-analyst/image-classification/executing-the-iso-cluster-unsupervised-classification-tool.htm
Buendía-Martínez, I., & Carrasco, I. (2013). Mujer, actividad emprendedora y desarrollo rural en América Latina y el Caribe. Cuadernos de Desarrollo Rural. Cuadernos de desarrollo rural, 10(72), 21-45. Obtenido de http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0122-14502013000300003
Brown, M. E., & McCarty, J. L. (2017). Is remote sensing useful for finding and monitoring urban farms? Applied Geography, 80, 23-33. DOI: https://doi.org/10.1016/j.apgeog.2017.01.008
Flores, E. (2022, Enero 12). La movilidad desde las zonas rurales como medio de desarrollo de la población. Obtenido a partir de https://www.ucuenca.edu.ec/component/content/article/309-espanol/investigacion/blog-de-ciencia/ano-2022/junio-2022/2683-capsula-la-movilidad-desde-las-zonas-rurales-como-medio-de-desarrollo-de-la-poblacion
Baldini, C., Marasas, M. E., Tittonell, P., & Drozd, A. A. (2022). Urban, periurban and horticultural landscapes – Conflict and sustainable planning in La Plata district, Argentina. Land Use Policy, 117, 106120. DOI: https://doi.org/10.1016/J.LANDUSEPOL.2022.106120
Caballero, I., Ruiz, J., & Navarro, G. (2019). Sentinel-2 satellites provide near-real time evaluation of catastrophic floods in the West Mediterranean. Water (Switzerland), 11(12). DOI: https://doi.org/10.3390/w11122499
Clavijo Palacios, C. E., & Cuvi, N. (2017). La Sustentabilidad de huertas urbanas y periurbanas con base agroecológica en Quito. Letras Verdes. Revista Latinoamericana de Estudios Socioambientales, (21), 68-91. DOI: https://doi.org/10.17141/LETRASVERDES.21.2017.2608
Cattivelli, V. (2021). Planning peri-urban areas at regional level: The experience of Lombardy and Emilia-Romagna (Italy). Land Use Policy, 103, 105282. https://doi.org/10.1016/j.landusepol.2021.105282
Donoso, M. (2016). Análisis crítico de la planificación urbana de la Ciudad de Cuenca. Maskana, 7(1), 107–122. https://doi.org/https://doi.org/10.18537/mskn.07.01.11
Echeverri, R., & Ribero, M. P. (2002). Nueva ruralidad: Visión del territorio en América Latina y el Caribe (Interamericano Instituto de Cooperación para la Agricultura, ed.). Obtenido de http://www.cusur.udg.mx/fodepal/Articulos referentes de Des Susr/Construyendo el desarrollo rural_archivos_ArturoSC/Nueva_ruralidad.pdf
ESA. (2021). Processing Levels -User Guides - Sentinel-2A MSI. Obtenido enero 13, 2023, de https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/processing-levels
ESA. (2019). Spatial Resolutions - Sentinel-2 MSI - User Guides. Recuperado Enero 13, 2023, de Copernicus Obtenido de https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/resolutions/spatial
Frere, M., & Popov, G. F. (1979). Agrometeorological crop monitoring and forecasting.
Ferrelli, F., Brendel, A. S., Miguel, G., Perillo, E., & Piccolo, M. C. (2020). Validación de productos satelitales a partir de mediciones in situ para el monitoreo de coberturas del suelo en el sur de la Región Pampeana (Argentina). Caminhos de Geografia, 21(76), 190–207. https://doi.org/10.14393/RCG217654051
Follmann, A., Willkomm, M., & Dannenberg, P. (2021). As the city grows, what do farmers do? A systematic review of urban and peri-urban agriculture under rapid urban growth across the Global South. Landscape and Urban Planning, Vol. 215, p. 104186. https://doi.org/10.1016/j.landurbplan.2021.104186
FAO. (2014). Ciudades más verdes en América Latina y el caribe. Un informe de la FAO sobre la agricultura urbana y periurbana en la región. Obtenido de www.fao.org/
Forkuor, G., Dimobe, K., Serme, I., & Tondoh, J. E. (2018). Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2’s red-edge bands to land-use and land-cover mapping in Burkina Faso. GIScience & remote sensing, 55(3), 331-354. DOI: https://doi.org/10.1080/15481603.2017.1370169
Flores, G., Mora, E., & Chica, J. (2020). Una mirada a la planificación de las infraestructuras nodales de transporte terrestre en las cercanías al centro urbano de Cuenca Ecuador. Quid 16: Revista Del Área de Estudios Urbanos, (14), 269–282. Obtenido de https://publicaciones.sociales.uba.ar/index.php/quid16/article/view/4537
Güneralp, B., Reba, M., Hales, B. U., Wentz, E. A., & Seto, K. C. (2020). Trends in urban land expansion, density, and land transitions from 1970 to 2010: a global synthesis. Environmental Research Letters, 15(4), 044015. DOI: https://doi.org/10.1088/1748-9326/AB6669
Gielen, E., Flores Juca, E., Palencia, J., Balseca, M., López Chofre, I., Sarmiento Moscoso, S., … Chica, J. (2019). Retos para el desarrollo de una ciudad sostenible en Cuenca (Ecuador). Análisis del crecimiento urbano entre 2008 y 2018. In J. Poyatos Sebastián, L. García Soriano, & J. L. Baró Zarzo (Eds.), Fundamentos y practica de la ciudad sostenible. Valencia, España (pp. 297–309). Valencia, España: Universitat Politècnica de València.
Hao, Z., AghaKouchak, A., Nakhjiri, N., & Farahmand, A. (2014). Global integrated drought monitoring and prediction system. Scientific data, 1(1), 1-10. DOI: https://doi.org/10.1038/sdata.2014.1
Kassis, G., Bertrand, N., & Pecqueur, B. (2021). Rethinking the place of agricultural land preservation for the development of food systems in planning of peri-urban areas: Insights from two French municipalities. Journal of Rural Studies, 86, 366-375. DOI: https://doi.org/10.1016/J.JRURSTUD.2021.07.003
Kennedy, E., & Payongayong, E. (1992). Inventory of food and nutrition monitoring systems. Final report to the United States Agency for International Development, Office of Nutrition. International Food Policy Research Institute, Washington, DC.
Masoud, K. M., Persello, C., & Tolpekin, V. A. (2020). Delineation of agricultural field boundaries from sentinel-2 images using a novel super-resolution contour detector based on fully convolutional networks. Remote Sensing, 12(1) 59. DOI: https://doi.org/10.3390/RS12010059
Manzanal, M. A. (2017). Desarrollo, territorio y políticas públicas. Una perspectiva desde el desarrollo rural y territorial. Revista Interdisciplinaria de Estudios Agrarios, 46, 5-31. Obtenido de https://ri.conicet.gov.ar/handle/11336/76287
Persello, C., V. A. Tolpekin, J. R. Bergado, and R. A. de By. (2019). Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping. Remote sensing of environment, 231, 111253. DOI: https://doi.org/10.1016/j.rse.2019.111253
Ruiz López, C. F., Vieyra, A., & Méndez-Lemus, Y. (2021a). Segregación y singularidades en el periurbano de ciudades medias mexicanas. En A. Carrión Hurtado & M. F. Sandoval López (Eds.), Ciudades intermedias y nueva ruralidad (pp. 114-135). DOI: https://doi.org/doi.org/10.46546/202010savia
Ruiz-López, C., Vieyra, A., & Méndez-Lemus, Y. (2021b). Spatial segregation in Tarimbaro, municipality in the periurban of Morelia, Michoacán, México. Revista de Geografia Norte Grande, 2021(78), 237–257. https://doi.org/10.4067/S0718-34022021000100237
Salcedo, S., & Guamán, L. (Eds.). (2014). Agricultura Familiar en América Latina y El Caribe: Recomendaciones de Política. Obtenido de www.fao.org/publications
Sonobe, R., Yamaya, Y., Tani, H., Wang, X., Kobayashi, N., & Mochizuki, K. I. (2018). Crop classification from Sentinel-2-derived vegetation indices using ensemble learning. Journal of Applied Remote Sensing, 12(2):1. DOI: https://doi.org/10.1117/1.jrs.12.026019
Unganai, L. S., & Kogan, F. N. (1998). Drought monitoring and corn yield estimation in Southern Africa from 440 AVHRR data. Remote sensing of environment, 63(3), 219-232. DOI: https://doi.org/10.1016/S0034-4257(97)00132-6
Waldner, F., Fritz, S., Di Gregorio, A., Plotnikov, D., Bartalev, S., Kussul, N., … Defourny, P. (2016). A unified cropland layer at 250 m for global agriculture monitoring. Data, 1(1), 3. https://doi.org/10.3390/data1010003
Weiss, M., F. Jacob, & Duveiller, G. (2020). Remote sensing for agricultural applications: A meta-review. Remote Sensing of Environment, 236, 111402. https://doi.org/10.1016/j.rse.2019.111402
Wójtowicz, M. (2014). Crecimiento de la población, cambios espaciales y cambios sociales en la ciudad de Curitiba. In V. Mercedes Di & M. Perelman (Eds.), Ciudades Latinoamericanas. Desigualdad, segregación y tolerancia. CLACSO, (pp. 203–219). Obtenido de www.biblioteca.clacso.edu.ar
You, N., Dong, J., Huang, J., Du, G., Zhang, G., He, Y., ... & Xiao, X. (2021). The 10-m crop type maps in Northeast China during 2017–2019. Scientific data, 8(1), 1-11. DOI: https://doi.org/10.1038/s41597-021-00827-9
Yu, L., J. Wang, N. Clinton, Q. Xin, L. Zhong, Y. Chen, and P. Gong. (2013). FROM-GC: 30 m global cropland extent derived through multisource data integration. International Journal of Digital Earth, 6(6), 521-533. DOI: https://doi.org/10.1080/17538947.2013.822574