Abstract
In the coastal tropics and subtropical regions, fragile ecosystems such as deltas, mangrove forests, and swamps are common, whose ecological stability strictly depends on the quality management of hydrological resources at the basin level. The National Hydrographic Basin Council in Cuba, protect the hydrographic basins, considered as the reference unit for the integrated management of water resources. Moreover, the council aims at preventing negative impacts on of these vital ecosystems for their key services to the overall social and economic wellbeing. As an example, the Zaza River basin in the of Province of Sancti Spiritus, the mangrove forest is suffering from significant decay, in particular on the southern coasts. A significant improvement of the water resources sustainable management in Cuba, is a more reliable and timely monitoring. Considering the extreme conditions and the limited accessibility of mangroves, remote sensing and others earth observations techniques represents a suitable tool for monitoring the mangrove forest in coastal areas. In our study, we used a set of 10 multispectral Landsat – 8 OLI images from November 2014 to December 2015.
By collecting campaigns on mangroves’ phenology, we have: 1) studied the relationships between phenology and spectral behavior of species; and, 2) set up a classification framework to assess the forests composition remotely, with special attention to mangroves. The methodology here implemented could be effectively applied in all coastal natural ecosystems of this island to improve the knowledge about the critical issues of these very fragile ecosystems.
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References
E.C.: Directive 2000/60/EC: European parliament and of the European union (2000)
Gain, A.K., Rouillard, J.J., Benson, D.: can integrated water resources management increase adaptive capacity to climate change adaptation? a critical review. J. Water Resour. Prot. 5, 11–20 (2013)
GWP.: Integrated Water Resources Management. TAC background paper No. 4, GWP, Stockholm, Sweden (2000)
Feller, I.C., Sitnik, M. (eds.).: Mangrove Ecology Workshop Manual. Smithsonian Institution, Washington, DC, USA (1996)
Menéndez, L,. Priego, A.: Los manglares de Cuba: Ecología. En El ecosistema de manglar en América Latina y la Cuenca del Caribe: su manejo y conservación (D. Suman, ed.), Rosenstiel School of Marine and Atmospheric Science & The Tinker Foundation, pp. 64–75 (1994)
Blasco, F., Gauquelin, T., Rasolofoharinoro, M., Denis, J., Aizpuru, M., Caldairou, V.: Recent advances in mangrove studies using remote sensing data. Mar. Freshwater Res. 49, 287–296 (1998)
Kovacs, J.M., Wang, J., Blanco-Correa, M.: Mapping disturbances in a mangrove forest using multi-data Landsat TM imagery. Environ. Manag. 27(5), 763–776 (2001)
Modica, G., Solano, F., Merlino, A., Di Fazio, S., Barreca, F., Laudari, L., Fichera, C.R.: Using Landsat 8 imagery in detecting cork oak (Quercus suber L.) woodlands: a case study in Calabria Italy. J. Agric. Eng. 47(4), 205–215 (2016). https://doi.org/10.4081/jae.2016.571
Melaas, E.K., et al.: Multisite analysis of land surface phenology in North American temperate and boreal deciduous forests from Landsat. Remote Sens. Environ. 186, 452–464 (2016)
Krause, G., Bock, M., Weiers, S., Braun, G.: mapping land-cover and mangrove structures with remote sensing techniques: a contribution to a synoptic gis in support of coastal management in North Brazil. Environ. Manag. 34(3), 429–440 (2004)
Vaiphasa, C., Omsongwang, S., Vaiphasa, T., Skidmore, A.K.: tropical mangrove species discrimination using hyperspectral data: a laboratory study. Estuar. Coast. Shelf Sci. 65, 371–379 (2006)
Vogelmann, J.E., Xian, G., Homer, C., Tolk, B.: monitoring gradual ecosystem change using landsat time series analyses: case studies in selected forest and rangeland ecosystems. Remote Sens. Environ. 122, 92–105 (2012)
Kovacs, J.M., Zhang, C., Flores-Verdugo, F.J.: mapping the condition of mangroves of the Mexican pacific using c-band ENVISAT ASAR and landsat optical data. Cienc. Mar. 34(4), 407–418 (2008)
Berlanga-Robles, Ruiz-Luna, A.: Análisis de las tendencias de cambio del bosque de mangle del sistema lagunar Teacapán-Agua brava, México. Una aproximación con el uso de imágenes de satélite Landsat. Publicaciones UCiencia. 23(1), 29–46 (2007)
Adam, E., Mutanga, O., Rugege, D.: Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wetlands Ecol. Manage. 18, 281–296 (2010)
Kasawani, I., Norsaliza, U., Mohd, H.I.: analysis of spectral vegetation indices related to soil-line for mapping mangrove forest using satellite imagery. Appl. Remote Sens. J. 1(1), 25–31 (2010)
Kuenzer, C., Bluemel, A., Gebhardt, S., Vo, Q.T., Dech, S.: remote sensing of mangrove ecosystems: a review. Remote Sens. 3, 878–928 (2011)
Giri, C., Pengra, B., Zhu, Z., Singh, A., Tiszen, L.L.: monitoring mangrove forest dynamics of the sundarsban in bangladesh nd india using multi-temporal satellite data from 1973 to 2000. Estuar. Coast. Shelf Sci. 73, 91–100 (2007)
Alatorre, L.C., Sanchez-Andres, R., Cirujano, S., Begueria, S., Sanchez-Carrillo, S.: identification of mangrove areas by remote sensing: the roc curve technique applied to northwestern Mexico Coastal zone using landsat imagery. Remote Sens. 3, 1568–1583 (2011)
Chen, B., et al.: a mangrove forest map of china in 2015: analysis of time series landsat 7/8 and sentinel-1a imagery in google earth engine cloud computing platform. ISPRS J. Photogramm. Remote Sens. 131, 104–120 (2017)
Somers, B., Verbesselt, J., Ampe, E.M., Sims, N., Verstraeten, W.W., Coppin, P.: spectral mixture analysis to monitor defoliation in mixed-aged Eucalyptus globulus Labill plantations in southern Australia using landsat 5-TM and EO-1 hyperion data. Int. J. Appl. Earth Obs. Geoinf. 12(4), 270–277 (2010)
Praticò, S., Solano, F., Di Fazio, S., Modica, G.: machine learning classification of mediterranean forest habitats in google earth engine based on seasonal sentinel-2 time-series and input image composition optimisation. Remote Sens. 13, 586 (2021). https://doi.org/10.3390/rs13040586
Modica, G., Merlino, A., Solano, F., Mercurio, R.: an index for the assessment of degraded Mediterranean forest ecosystems. For. Syst. 24, 5 (2015). https://doi.org/10.5424/fs/2015243-07855
FAO.: The world’s mangroves 1980–2005. FAO FORESTRY PAPER 153, Rome. ISBN 978–92–5–105856–5 (2007)
Tomlinson, P.B.: The botany of mangroves. Cambridge University Press, Cambridge, United Kingdom (1986)
Choudhury, M.A.M., et al.: urban tree species identification and carbon stock mapping for urban green planning and management. Forests 11, 1226 (2020). https://doi.org/10.3390/f11111226
Giri, C., et al.: status and distribution of mangrove forests of the world using earth observation satellite data. Glob. Ecol. Biogeogr. 20, 154–159 (2011)
Wang, L., Silván-Cárdenas, L., Sousa, W.P.: neural network classification of mangrove species from multi-seasonal Ikonos imagery. Photogram. Eng. Remote Sens. 2008(74), 921–927 (2008)
Kanniah, K.D., Wai, N.S., Shin, A.L., Rasib, A.W.: per pixel and sub-pixel classifications of high-resolution satellite data for mangrove species mapping. Appl. GIS 3, 1–22 (2007)
Somers, B., Asner, G.P.: multi-temporal hyperspectral mixture analysis and feature selection for invasive species mapping in rainforest. Remote Sens. Environ. 136, 14–27 (2013)
Howland, W.G.: multispectral aerial photography for wetland vegetation mapping. Photogram. Eng. Remote Sens. 46, 87–99 (1980)
Verheyeden, A., Dahdouh-Guebas, F., Thomaes, K., De Genst, W., Hettiarachch, S., Koedam, N.: High-resolution vegetation dat for mangrove research as obtained from aerial photography. Environ. Dev. Sustain. 4, 113–133 (2002)
Menéndez, L., Guzmán, J.M., Capote, R.T., Rodríguez, L.F., González, A.V.: Situación Ambiental de los Manglares del Archipiélago Cubano. Casos de estudios: archipiélago Sabana Camagüey, franja sur de la Habana y costa norte de Ciudad Habana. En Memorias IV Convención Internacional sobre medio ambiente y desarrollo, 2 al 6 de junio de 2003, La Habana, pp. 435–451 (2003)
Menéndez, L., Guzmán, J.M.: Los manglares del archipiélago cubano: aspectos generales. In: L. Menéndez, J.M. Guzmán (eds.) Ecosistema de Manglar en el Archipiélago Cubano. UNESCO, Ciudad de la Habana, pp. 329 (2006)
Menéndez, J.M.G., Menéndez Carrera, L.: Protocolo para el monitoreo del ecosistema de manglar. Proyecto GEF/PNUD, Application de un enfoque regional al manejo de las àreas marino-costeras protegida en la Regiòn Archipiélagos del Sur de Cuba, La Habana (2013). ISBN: 978-959-287-042-0
Hesketh, M., Sanchez-Azofeifa, G.A.: the effect of seasonal spectral variation on species classification in the Panamanian Tropical Forest. Remote Sens. Environ. 118, 73–82 (2012)
Roberts, D.A., Gardner, M., Church, R., Ustin, S., Scheer, G., Green, R.O.: mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sens. Environ. 65, 267–279 (1998)
Roberts, D.A., Halligan, K., Dennison, P.: VIPER Tools User Manual Version 1.5 (2007)
Plaza, A.: Proposición, validación y prueba de una metodología para el análisis de datos hiperespectrales que integra información espacial y espectral. Tesis doctoral (2002)
Menéndez, L., et al.: Informe de proyecto de investigación: Bases ecológicas para la restauración de manglares en áreas seleccionadas del Archipiélago cubano y su relación con los cambios globales. Informe final del proyecto. Programa Nacional de Cambios Globales y Evolución del Medio Ambiente Cubano. IES. CITMA, pp 153 (2000)
Meza Diaz, B., Blackburn, G.A.: remote sensing of mangrove biophysical properties: evidence from a laboratory simulation of the possible effects of background variation on spectral vegetation indices. Int. J. Remote Sens. 24, 53–73 (2003)
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Marcheggiani, E. et al. (2021). Monitor Mangrove Forest Dynamics from Multi-temporal Landsat 8-OLI Images in the Southern Coast of Sancti Spíritus Province (Cuba). In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12955. Springer, Cham. https://doi.org/10.1007/978-3-030-87007-2_13
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