Dynamic Regionalization of the Island Santo Domingo through remote sensors products of the type espectroradiometers
DOI:
https://doi.org/10.26640/22159045.269Keywords:
dynamic regionalization, Island of Santo Domingo, satellite reflectance, mesoscale structure, seasonal variabilityAbstract
The dynamic regionalization of the island of Santo Domingo was determined with satellite reflectance derived from MODIS-Aqua sensor. To determine the temporal variability seasonal scenarios (not hurricane season and hurricane season) were established. Daily images were used from June 2002 to November 2013. To define the dynamic regions empirical orthogonal function first standardized (SEOF1) that guarantees the best combination of numerical variables Rrs412 nm satellite reflectances and Rrs488 nm was used. On the island of Santo Domingo 24 dynamic regions were identified in 2 domains Atlantic and Caribbean. In the domain of the Atlantic were identified 1 oceanic province with 2 dymanic regions, 1 coastal province and 2 coastal subprovince in which 8 dynamic regions were distributed, 1 coastal province and 2 coastal subprovince in which 8 dynamic regions were distributed. In the domain of the Caribbean were identified 1 oceanic province with1 dynamic region, 4 coastal province and 3 coastal subprovinces in which 13 dynamic regions were distributed. Based on the concentration of chlorophyll-a (Chla) Satellite average 7 regions were classified as oligotrophic, 5 as mesotrophic, and 12 eutrophic distributed in the Atlantic and Caribbean domains. The study of the temporal variability showed that the spatial dimension of the dynamic regions is modulated by the seasonal influence of each proposed scenario. The dynamic regionalization of the island of Santo Domingo allowed to identify surface mesoscale oceanographic structures as eddies and filaments for the month of February 2005.Downloads
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References
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[2] Millán-Núñez R, Santamaría del Ángel E, González-Silvera A. Methods for the regionalization of the ocean zone through biologic aspects. 2006. In: Córdova, Rosete, Enríquez y Fernández (Comp.). Marine ecologic ordering. Thematic vision of regionalization.
[3] Santamaría del Ángel, González-Silvera A, Millán-Núñez R, Callejas-Jiménez ME, Cajal-Medrano R. Determining Dynamic Biogeographic Regions using Remote Sensing Data. En prensa; 2011. 19 pp.
[4] Callejas-Jiménez A. Regionalización dinámica mediante radianzas normalizadas. Tesis que cubre parcialmente los requisitos de tesis doctoral. Universidad Autónoma de Baja California. Facultad de Ciencias Marinas 2010. ISSN 0278-4343.
[5] Santamaria del Ángel E, Álvarez-Borrego S, Müller-Karger FE. Gulf of California biogeographic regions based on coastal zone color scanner imagery. J Geophys Res Oceans 1978–2012. 1994;99(C4):7411–21.
[6] González-Silvera A, Santamaría del Ángel VMT, García CAE, García R, Millán-Núñez R, Muller-Karger F. Biogeographically regions of de tropical and subtropical Atlantic Ocean of South America; Clasification based on pigment (CZCS and chlorophyll-a (SeaWIFS) variability 2004. Continental Shelf Research. 24:983-1000.
[7] González-Silvera A, Santamaría del Ángel E, Millán-Núñez R. Spatial and temporal variability of the Brazil-Malvinas confluence and the La Plata Pluma as seen by SeaWiFS/NASA and AVHRR imagery. En: Journal of Geophysical Research 2006;111:C06010.
[8] Flores de Santiago FJ, Santamaría de Ángel E, González-Silvera A, Martínez-Díaz de León A, Millán-Núñez R, Kovacs J. Assessing dynamics micro-regions in the Great Islands of the Gulf of California based on MODIS aqua imagery products. En: Coastal Ocean Remote Sensing, edited by Robert J. Frouin, Zhong Ping Lee, Proc. of SPIE Vol. 6680, 668010-1. 2007. DOI: 10.1117/12.732574.
[9] Callejas-Jiménez M, Santamaría del Ángel E, González-Silvera A, Millán-Núnez R, Cajal-Medrano R. Dynamic Regionalization of the Gulf of Mexico based on normalized radiances (nLw) derived from MODIS-Aqua. Cont Shelf Res 2012;37:8–14.
[10] Cañón-Páez A. Regionalización dinámica del Gran Caribe basada en productos espectro-radiométricos satelitales. Tesis de Maestría. Escuela Naval Almirante padilla. Oceanografía Física. 2010.
[11] IOCC. Guide to the Creation and Use of Ocean-Colour, Level-3, Binned Data Products. Antoine D (ed.), Reports of the International Ocean-Colour Coordinating Marine Ecosystem Characterization.Dynamic Biogeographic Regions Using Remote Group, No. 4, IOCCG, Dartmouth, Canada; 2004. Pp. 23-29.
[12] NOAA NW Service. Hurricane Season Summaries and Reports. [internet] NOAA, National Weather Service. 2014 [Citado mayo 8 2014]; Disponible en http://www.nhc.noaa.gov/.
[13] Unisys Weather. Hurricane/Tropical Data for Atlantic. [internet]. Unisys. 2009 [Citado mayo 11 2014]. Disponible en http://weather.unisys.com/hurricane/atlantic/2009/.
[14] Marcano J. Mi País [Internet]. República Dominicana. 2009 [Citado mayo 22 2014]. Disponible en: http://www.jmarcano.com/mipais/geografia/hispaniola.html.
[15] Herrera-Moreno A, Betancourt L. Especies de equinodermos recientes (Echinodermata: Crinoidea, Asteroidea, Ophiuroidea, Echinoidea y Holothuroidea) conocidas para La Hispaniola. Cienc Soc Univ INTEC St Domingo. 2004;29:506–33
[16] Ministerio de Medio Ambiente y Recursos Naturales. IV Informe Nacional de Biodiversidad República Dominicana. Perspectivas de la situación, tendencias y amenazas a la diversidad biológica. Sistema Nacional de Áreas Protegidas. Febrero 2010. Pp. 26- 31.
[17] Ministerio de Medio Ambiente y Recursos Naturales. Medio ambiente en cifras 2005-2011. [Internet] Mixtli Grafika EIRL, 2012. Disponible en http://www.ambiente.gob.do/IA/Presentacion/Documents/
MA-EN-CIFRAS-2005-2011-Dic2013.pdf
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Published
2014-12-07
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How to Cite
Dynamic Regionalization of the Island Santo Domingo through remote sensors products of the type espectroradiometers. (2014). CIOH Scientific Bulletin, 32, 149-161. https://doi.org/10.26640/22159045.269
