Remote Sensing of Salinity in Agroecosystem of Mayarí, at Holguín Province, Cuba
Main Article Content
Abstract
Article Details
Those authors that have publications with this journal accept the following terms:
1. They will retain their copyright and guarantee the journal the right of first publication of their work, which will be simultaneously subject to the License Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) that allows third parties to share the work whenever its author is indicated and its first publication this journal. Under this license the author will be free of:
• Share — copy and redistribute the material in any medium or format
• Adapt — remix, transform, and build upon the material
• The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
• Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
• NonCommercial — You may not use the material for commercial purposes.
• No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
2. The authors may adopt other non-exclusive license agreements to distribute the published version of the work (e.g., deposit it in an institutional telematics file or publish it in a monographic volume) whenever the initial publication is indicated in this journal.
3. The authors are allowed and recommended disseminating their work through the Internet (e.g. in institutional telematics archives or on their website) before and during the submission process, which can produce interesting exchanges and increase the citations of the published work. (See the Effect of open access).
References
ALDABAA, A.A.; WEINDORF, D.C.; CHAKRABORTY, S.; SHARMA, A.B.; LI, B.: “Combination of proximal and remote sensing methods for rapid soil salinity quantification”, Geoderma, 239: 34-46, 2015, ISSN: 0016-7061, DOI: https://dx.doi.org/10.1016/j.geoderma.2014.09.011.
AL-KHAIER, F.: Soil salinity detection using satellite remote sensing, International Institute for Geo-Information Science and Earth observation ITC, MSc. Thesis in Geo-Information Science and Earth Observation, Enscheda, the Netherlands, 2003.
ALLBED, A.; KUMAR, L.; ALDAKHEEL, Y.Y.: “Assessing soil salinity using soil salinity and vegetation indices derived from IKONOS high-spatial resolution imageries: Applications in a date palm dominated region”, Geoderma, 230: 1-8, 2014, ISSN: 0016-7061, DOI: https://dx.doi.org/10.1016/j.geoderma.2014.03.025.
ASFAW, E.; SURYABHAGAVAN, K.V.; ARGAW, M.: “Soil salinity modeling and mapping using remote sensing and GIS: The case of Wonji sugar cane irrigation farm, Ethiopia”, Journal of the Saudi Society of Agricultural Sciences, 17(3): 250-258, 2018, ISSN: 1658-077X, DOI: https://dx.doi.org/10.1016/j.jssas.2016.05.003.
ÁVILA, S.E.; GARCÍA, S.J.A.; VALTIERRA, P.E.; GARCÍA, M.R.; HOYOS, F.G.: “Producción de biodiesel derivado de la Jatropha: un estudio de competitividad en el estado de Chiapas, México”, Revista Fitotecnia Mexicana, 41(4): 461-468, 2018, ISSN: 0187-7380.
BAQUERO, G.; ESTEBAN, B.; PUIG, R.; RIBA, J.; RIUS, A.: “Characterization of physical properties of vegetable oils to be used as fuel in diesel engines”, 2010.
CHEN, D.; HUANG, J.; JACKSON, T.J.: “Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near-and short-wave infrared bands”, Remote Sensing of Environment, 98(2-3): 225-236, 2005, ISSN: 0034-4257, DOI: https://dx.doi.org/10.1016/j.rse.2005.07.008.
DEHNI, A.; LOUNIS, M.: “Remote sensing techniques for salt affected soil mapping: application to the Oran region of Algeria”, Procedia Engineering, 33: 188-198, 2012, ISSN: 1877-7058, DOI: https://dx.doi.org/10.1016/j.proeng.2012.01.1193.
ELHAG, M.: “Evaluation of different soil salinity mapping using remote sensing techniques in arid ecosystems, Saudi Arabia”, Journal of Sensors, : 1-8, 2016, ISSN: 1687-725X, DOI: https://dx.doi.org/10.1155/2016/7596175.
GORJI, T.; SERTEL, E.; TANIK, A.: “Monitoring soil salinity via remote sensing technology under data scarce conditions: A case study from Turkey”, Ecological Indicators, 74: 384-391, 2017, ISSN: 1470-160X, DOI: https://dx.doi.org/10.1016/j.ecolind.2016.11.043.
GU, Y.; BROWN, F.J.; VERDIN, P.J.; WARDLOW, B.: “A five‐year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States”, Geophysical research letters, 34(6): 1-6, 2007, ISSN: 0094-8276, DOI: https://dx.doi.org/10.1029/2006GL029127.
HEIDINGER, A.H.: Detección de salinidad de los suelos en el Antiplano Peruano-Boliviano mediante percepción remota, inducción electromagnética y sistemas de información geográfica, Universidad Nacional Agraria La Molina, Facultad de Ciencias …, Tesis de Licenciatura, Lima, Perú, 2008.
KHAN, N.M.; GUEVARA, V.V.; SATO, Y.; SHIOZAWA, S.: “Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators”, Agricultural Water Management, 77(1-3): 96-109, 2005, ISSN: 0378-3774, DOI: https://dx.doi.org/10.1016/j.agwat.2004.09.038.
MARTÍNEZ, N.; LÓPEZ, C.; BASURTO, M.; PÉREZ, R.: “Efectos por salinidad en el desarrollo vegetativo. Tecnociencia. 5, 156-161”, 2011.
MULLER, S.J.: Indirect soil salinity detection in irregated areas using earth observation methods, Stellenbosch University, Faculty of Science, Master of Science Thesis, Stellenbosch, Sud Africa, 2017.
OLIVA, M.A.; RINCÓN, R.; ZENTENO, E.; PINTO, A.; DENDOOVEN, L.; GUTIÉRREZ, F.: “Rol del vermicompost frente al estrés por cloruro de sodio en el crecimiento y fotosíntesis en plántulas de tamarindo (Tamarindus indica L.)”, Revista Gayana. Botánica, 65(1): 10-17, 2011, ISSN: 0717-6643, e-ISSN: 0016-5301.
PLATONOV, A.; NOBLE, A.; KUZIEV, R.: “Soil salinity mapping using multi-temporal satellite images in agricultural fields of Syrdarya province of Uzbekistan”, En: Developments in soil salinity assessment and reclamation: Innovative thinking and use of marginal soil and water resources in irrigated agriculture, Ed. Springer, Shahid SA, Abdelfattah MA, and Taha FK ed., Dordrecht, Netherlands, pp. 87-98, 2013.
ROUSE, J.; HAAS, R.; SCHELL, J.; DEERING, D.: “Monitoring Vegetation Systems in the Great Plains with ERTS Proceeding”, En: Third Earth Reserves Technology Satellite Symposium, Greenbelt: NASA SP-351, USA, 1974, ISBN: 30103017.
SOCA, R.: Identificación de las tierras degradadas por la salinidad del suelo en los cultivos de caña de azúcar mediante imágenes de satélite, Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Físicas, Tesis para optar el Grado Académico de Magíster en Física con mención en Geofísica, Lima, Perú, 2015.
WANG, J.; DING, J.; YU, D.; AKIYAMA, D.M.; HE, B.; CHEN, X.; GE, X.; ZHANG, Z.; WANG, Y.; YANG, X.: “Machine learning-based detection of soil salinity in an arid desert region, Northwest China: A comparison between Landsat-8 OLI and Sentinel-2 MSI”, Journal Science of The Total Environment, 707: 1-11, 2020, ISSN: 0048-9697, DOI: https://dx.doi.org/10.1016/j.scitotenv.2019.136092.