Seasonal trend analysis (STA) of MODIS vegetation index time series for the mangrove canopy of the Teacapan-Agua Brava lagoon system, Mexico

References

• Alongi, D. M. 2002. “Present State and Future of World’s Mangrove Forests.” Environmental Conservation 23 (3): 331–349. doi:10.1017/S0376892902000231.
   Google Scholar
• Arief, M. C. W., and A. Itaya. 2017. “A Brief Description of Recovery Process of Coastal Vegetation after Tsunami: A Google Earth Time-Series Remote Sensing Data.” Journal Manajemen Hutan Tropika 23 (2): 81–89. doi:10.7226/jtfm.23.2.81.
   Web of Science ®Google Scholar
• Ball, M. C., and J. B. Passioura. 1995. “Mangrove Gain in Relation to Wáter Use: Photosynthesis in Mangroves.” Ecophysiology of Photosynthesis edited by E. D. Schulze and M. M. Caldwell 247–259. Berlin: Springer. . 10.1007/978-3-642-79354-7_12.
   Google Scholar
• Baserra, L. N. G., and E. Galvani. 2013. “Mangrove Microclimate: A Case Study from Southeastern Brazil.” Earth Interactions 17 (2): 1–16. doi:10.1175/2012EI000464.1.
   Google Scholar
• Berlanga, R. C. A. 2006. “Characterization of the Coastal Landscapes of Sinaloa and North of Nayarit, Mexico through the Analysis of Land Cover Patterns. [Caracterización De Los Paisajes Costeros De Sinaloa Y Norte De Nayarit, México a Través Del Análisis De Los Patrones De Cobertura Del Terreno].” PhD Diss. Universidad Nacional Autónoma de México, México. 204 p.
   Google Scholar
• Berlanga-Robles, C. A., and A. Ruiz-Luna. 2002. “Land Use Mapping and Change Detection in the Coastal Zone of Northwest Mexico Using Remote Sensing Techniques.” Journal of Coastal Research 18 (3): 514–522. ORCID: 0000-0001-6878-0929.
   Web of Science ®Google Scholar
• Berlanga-Robles, C. A., and A. Ruiz-Luna. 2007. “Analysis of change trends of the mangrove forest in Teacapan-Agua Brava lagoon system, Mexico. An approximation using Landsat satellite images [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].” Universidad y Ciencia 23 (1): 29–46.
   Google Scholar
• Bernini, E., and C. E. Rezende. 2010. “Litterfall in Mangroves in Southeast Brazil.” Pan-American Journal of Aquatic Sciences 5 (4): 508–519.
   Google Scholar
• Blanco, C. M., F. Flores, M. A. Ortiz, G. De la Lanza, J. Lopez-Portillo, I. Valdéz, C. Agraz, et al. 2011. Diagnostico Funcional De Marismas Nacionales [Functional Diagnosis of Marismas Nacionales. México: Universidad Autónoma de Nayarit, Comisión Nacional Forestal.
   Google Scholar
• Chen, B., X. Xiao, X. Li, L. Pan, R. Doughty, J. Ma, J. Dong, et al. 2017. “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 Journal of Photogrammetry and Remote Sensing 131 :104–120. doi:10.1016/j.isprsjprs.2017.07.011.
   Web of Science ®Google Scholar
• Chétet, V., and J. P. Denux. 2011. “Analysis of MODIS NDVI Time Series to Calculate Indicators of Mediterranean Forest Fire Susceptibility.” GIScience & Remote Sensing 48 (2): 171–194. doi:10.2747/1548-1603.48.2.171.
   Web of Science ®Google Scholar
• Cintron, G., and Y. Schaeffer-Novelli. 1985. “Características y desarrollo estructural de los manglares de Norte y Sur América.” Ciencia Interamericana 25 (1–4): 4–15.
   Google Scholar
• Congalton, R. G., and K. Green. 1999. Assessing the Accuracy of Remote Sensed Data: Principles and Practices.” Boca Raton: Lewis Publishers.
   Google Scholar
• De la Lanza, E. G., and S. Hernández. 2017. “Natural and Induced Space/Time Environmental Changes in the Teacapán-Agua Brava Lagoon System, NW Mexico.” Journal of Aquaculture & Marine Biology 5 (6): 00140.
   Google Scholar
• De la Lanza, E. G., S. Sánchez, V. Sorani, and T. Bojórquez. 1996. “Geological, Hydrological, and Mangrove Features in the Coastal Plain of Nayarit, Mexico. [Características Geológicas, Hidrológicas, Y Del Manglar En La Planicie Costera De Nayarit, México].” Boletín de Investigaciones Geográficas 32: 33–54.
   Google Scholar
• Eastman, J. R. 2016. “TerrSet. Geospatial Monitoring and Modelling System. Tutorial.” Massachusetts: Clark Labs.
   Google Scholar
• Eastman, J. R., F. Sangermano, B. Ghimire, H. L. Zhu, H. Chen, N. Neeti, Y. M. Cai, et al. 2009. “Seasonal Trend Analysis of Images Time Series.” International Journal of Remote Sensing 30 (10): 2721–2726. doi:10.1080/01431160902755338.
   Web of Science ®Google Scholar
• Eastman, J. R., F. Sangermano, E. A. Machado, J. Rogan, and A. Anyamba. 2013. “Global Trends in Seasonality of Normalized Difference Vegetation Index (NDVI), 1982-2011.” Remote Sensing 5 (10): 4799–4818. doi:10.3390/rs5104799.
   Web of Science ®Google Scholar
• Flores-Verdugo, F., F. González-Farías, O. Ramírez-Flores, F. Amezcua-Linares, A. Yañeez-Arancibia, M. Alvarez, and J. W. Day. 1990. “Mangrove, Aquatic Primary Productivity, and Fish Community Dynamics in Teacapán-Agua Brava Lagoon-Estuarine System (Mexican Pacific).” Estuaries 13: 219–230. doi:10.2307/1351591.
   Google Scholar
• Friess, D. A., and E. L. Webb. 2014. “Variability in Mangrove Change Estimates and Implications for the Assessment of Ecosystem Service Provision.” Global Ecology and Biogeography 23 (7): 715–725. doi:10.1111/geb.12140.
   Web of Science ®Google Scholar
• Giri, C. 2016. “Observation and Monitoring of Mangrove Forests Using Remote Sensing: Opportunities and Challenges.” Remote Sensing 8 (9): 1–8. doi:10.3390/rs8090783.
   Web of Science ®Google Scholar
• Giri, C., E. Ocheieng, L. L. Tieszen, Z. Zhu, A. Singh, T. Loveland, J. Masek, and N. Duke. 2011. “Status and Distribution of Mangrove Forests of the World Using Earth Observation Satellite Data.” Global Ecology and Biogeography 20 (1): 154–159. doi:10.1111/j.1466-8238.2010.00584.x.
   Web of Science ®Google Scholar
• Giri, C., J. Long, S. Abbas, R. M. Murali, F. M. Qamer, B. Pengra, and D. Thau. 2015. “Distribution and Dynamics of Mangrove Forests of South Asia.” Journal Environmental Management 148: 101–111. doi:10.1016/j.jenvman.2014.01.020.
   PubMed Web of Science ®Google Scholar
• Hall-Beyer, M. 2003. “Comparison of Single-Year and Multiyear NDVI Time Series Principal Components in Cold Temperate Biomes.” IEEE Transactions on Geoscience and Remote Sensing 41 (11): 1–8. doi:10.1109/TGRS.2003.817274.
   Web of Science ®Google Scholar
• Heumann, B. W. 2011. “Satellite Remote Sensing of Mangrove Forests: Recent Advances and Future Opportunities.” Progress in Physical Geography: Earth and Environment 35 (1): 87–108. doi:10.1177/0309133310385371.
   Google Scholar
• Jia, M., Z. Wang, L. L., . K. Song, C. Ren, B. Liu, and D. Mao. 2014. “Mapping China’s Mangroves Based on an Object-Oriented Classification of Landsat Imagery.” Wetlands 34 (2): 277–283. doi:10.1007/s13157-013-0449-2.
   Web of Science ®Google Scholar
• Jiang, Z. Y., A. R. Huete, J. Chen, Y. H. Chen, J. Li, G. J. Yan, and X. Y. Zhang. 2006. “Analysis of NDVI and Scaled Difference Vegetation Index Retrieval of Vegetation Fraction.” Remote Sensing of Environment 101 (3): 366–378. doi:10.1016/j.rse.2006.01.003.
   Web of Science ®Google Scholar
• Kamal, M., S. Phinn, and K. Johansen. 2014. “Characterizing the Spatial Structure of Mangrove Features for Optimizing Image-Based Mangrove Mapping.” Remote Sensing 6 (2): 984–1006. doi:10.3390/rs6020984.
   Web of Science ®Google Scholar
• Kathiresan, K., and B. L. Bingham. 2001. “Biology of Mangrove Ecosystem.” Marine Biology 40: 81–251.
   Web of Science ®Google Scholar
• Kovacs, J. M., F. Flores-Verdugo, J. Wang, and L. Aspden. 2004. “Estimating Leaf Area Index of a Degraded Mangrove Forest Using High Spatial Resolution Satellite Data.” Aquatic Botany 80 (1): 13–22. doi:10.1016/j.aquabot.2004.06.001.
   Web of Science ®Google Scholar
• Kovacs, J. M., J. Wang, and F. Flores-Verdugo. 2005. “Mapping Mangrove Leaf Area Index at the Species Level Using IKONOS and LAI-2000 Sensors for the Agua Brava Lagoon, Mexican Pacific.” Estuarine Coastal and Shelf Science 62: 377–384. doi:10.1016/j.ecss.2004.09.027.
   Web of Science ®Google Scholar
• Kovacs, J. M., J. Wang, and M. Blanco-Correa. 2001. “Mapping Disturbances in a Mangrove Forest Using Multi-Date Landsat TM Imagery.” Environmental Management 27 (5): 763–776. doi:10.1007/s002670010186.
   PubMed Web of Science ®Google Scholar
• Kovacs, J. M., M. Blanco-Correa, and F. Flores-Verdugo. 2001. “A Logistic Regression Model of Hurricane Impacts in A Mangrove Forest of the Mexican Pacific.” Journal of Coastal Research 17 (1): 30–37. ORCID: 0000-0002-0520-3996.
   Web of Science ®Google Scholar
• Kuenzer, C., A. Bluemel, S. Gebhardt, T. V. Quoc, and S. Dech. 2011. “Remote Sensing of Mangrove Ecosystems: A Review.” Remote Sensing 3: 878–928. doi:10.3390/rs3050878.
   Web of Science ®Google Scholar
• Landis, J. R., and G. G. Koch. 1977. “The Measure of Observer Agreement for Categorical Data.” Biometrics 33 (1): 159–174.
   PubMed Web of Science ®Google Scholar
• Langner, A., J. Miettine, and F. Siegert. 2007. “Land Cover Change 2002–2005 in Borneo and the Role of Fire Derived from MODIS Imagery.” Global Change Biology 13 (11): 2329–2340. doi:10.1111/j.1365-2486.2007.01442.x.
   Web of Science ®Google Scholar
• Long, J. B., and C. Giri. 2011. “Mapping the Philippines´ Mangrove Forest Using Landsat Imagery.” Sensors 11 (3): 2972. doi:10.3390/s110302972.
   PubMed Web of Science ®Google Scholar
• Mehlig, U. 2006. “Phenology of Red Mangrove, Rhizophora Mangle L, in the Caeté Estuary, Pará, Equatorial Brazil.” Aquatic Botany 84 (2): 158–164. doi:10.1016/j.aquabot.2005.09.007.
   Web of Science ®Google Scholar
• Miller, P. C. 1972. “Bioclimate Leaf Temperature, and Primary Production in Red Mangrove Canopies in South Florida.” Ecology 53 (1): 22–45. doi:10.2307/1935708.
   Web of Science ®Google Scholar
• Nagelkerken, I., S. J. M. Blaber, S. Bouillon, P. Green, M. Haywood, L. G. Kirton, J. O. Meynecke, et al. 2008. “The Habitat Function of Mangroves for Terrestrial and Marine Fauna: A Review.” Aquatic Botany 89 (2): 155–185. doi:10.1016/j.aquabot.2007.12.007.
   Web of Science ®Google Scholar
• Pastor-Guzman, J., J. Dash, and P. Atkinson. 2018. “Remote Sensing of Mangrove Forest Phenology and Its Environmental Drivers.” Remote Sensing of Environment 205: 71–84. doi:10.1016/j.rse.2017.11.009.
   Web of Science ®Google Scholar
• Rahman, A. F., D. Dragoni, K. Didan, A. Barreto, and J. A. Hutabarat. 2013. “Detecting Large Scale Conversion of Mangroves to Aquaculture with Change Point and Mixed-Pixel Analyses of High-Fidelity MODIS Data.” Remote Sensing of Environment 30: 96–107. doi:10.1016/j.rse.2012.11.014.
   Google Scholar
• Rodríguez-Zuñiga, M. T., C. Troche-Souza, A. D. Márquez-Mendoza, J. D. Vázquez-Balderas, L. Valderrama-Landeros, S. Velázquez-Salazar, M. I. Cruz-López, et al. 2013. “Manglares De México. Extensión, Distribución Y Monitoreo [Mangroves of Mexico. Extension, Distribution and Monitoring].” Mexico: Comisión Nacional para el conocimiento y Uso de la Biodiversidad.
   Google Scholar
• Rogan, J., L. Schneider, Z. Christman, M. Millones, D. Lawrence, and B. Schmook. 2011. “Hurricane Disturbance Mapping Using MODIS EVI Data in the Southeastern Yucatán, Mexico.” Remote Sensing Letters 2 (3): 259–267. doi:10.1080/01431161.2010.520344.
   Web of Science ®Google Scholar
• Rossi, E., J. Rogan, and L. Schneider. 2013. “Mapping Forest Damage in Northern Nicaragua after Hurricane Felix (2007) Using MODIS Enhanced Vegetation Index Data.” GIScience & Remote Sensing 50 (4): 171–194. doi:10.1080/15481603.2013.820066.
   Web of Science ®Google Scholar
• Ruiz-Luna, A., J. Acosta-Velázquez, and C. A. Berlanga-Robles. 2008. “On the Reliability of the Data of Extent of Mangroves, a Case Study in Mexico.” Ocean and Coastal Management 51 (4): 342–351. doi:10.1016/j.ocecoaman.2007.08.004.
   Web of Science ®Google Scholar
• Sharma, S., A. T. M. R. Hoque, K. Analuddin, and A. Hagihara. 2012. “Litterfall Dynamics in Overcrowded Mangrove Kandelia Obovate (S., L.) Yong Stand over Five Years.” Estuarine, Coastal and Shelf Science 98: 31–41. doi:10.1016/j.ecss.2011.11.012.
   Web of Science ®Google Scholar
• Tuyholske, C. C., Z. Tane, D. Lopez-Carillo, D. Roberts, and S. Cassels. 2017. “Thirty Years of Land Use/Cover Change in the Caribbean: Assessing the Relationship between Urbanization and Mangrove Loss in Roatan, Honduras.” Applied Geography 88: 84–93. doi:10.1016/j.apgeog.2017.08.018.
   Web of Science ®Google Scholar
• Valderrama-Landeros, L., F. Flores-de Santiago, J. M. Kovacs, and F. Flores-Verdugo. 2018. “An Assessment of Commonly Employed Satellite-Based Remote Sensors for Mapping Mangrove Species in Mexico Using an NDVI-based Classification Scheme.” Environmental Monitoring and Assessment 190 (1): 23. doi:10.1007/s10661-017-6399-z.
   Web of Science ®Google Scholar
• Valderrama-Landeros, L. H., M. T. Rodríguez-Zúñiga, and C. Troche-Souza, S. Velázquez-Salazar, S., E. Villeda-Chávez, J. A. Alcántara-Maya, B. Vázquez-Balderas, et al. 2017. “Manglares de México: actualización y exploración de los datos del sistema de monitoreo 1970/1980–2015. [Mangroves of Mexico: Update and exploration of the monitoring data system 1970/1980-2015]”. México: Comisión Nacional para el Conocimiento y Uso de la Biodiversidad
   Google Scholar
• Vo, Q. T., C. Kuenzer, Q. M. Vo, F. Moder, and N. Oppelt. 2012. “Review of Valuation Methods for Mangrove Ecosystem Services.” Ecological Indicators 23: 431–446. doi:10.1016/j.ecolind.2012.04.022.
   Web of Science ®Google Scholar
• Westermark, P. O. 2015. “Package ‘Harmonicregresion’.” April 1. https://cran.r-project.org/web/packages/HarmonicRegression/HarmonicRegression.pdf
   Google Scholar
• Wheater, C. P., and P. A. Cook. 2000. Using Statistics to Understand the Environment. New York: Routledge.
   Google Scholar
• Wilkie, M. L., and S. Fortuna. 2003. “Status and Trends in Mangrove Area Extent Worldwide.” Food and Agriculture Organization of the United Nations, December.http://www.fao.org/docrep/007/j1533e/J1533E00.htm#TopOfPage
   Google Scholar
• Younes, C. N., K. E. Joyce, and S. W. Maier. 2017. “Monitoring Mangrove Forests: Are Taking Full Advantage of Technology.” International Journal of Applied Earth Observation and Geoinformation 63: 1–14. doi:10.1016/j.jag.2017.07.004.
   Web of Science ®Google Scholar
• Zhang, H., W. Wenping, W. Dong, and S. Liu. 2014. “Seasonal Patterns of Litterfall in Forest Ecosystem Wordwide.” Ecological Complexity 20: 240–247. doi:10.1016/j.ecocom.2014.01.003.
   Web of Science ®Google Scholar
• Zhang, X., M. A. Friedl, C. B. Schaaf, A. H. Strahler, J. Hodges, F. Gao, B. C. Reed, and A. Huete. 2003. “Monitoring Vegetation Phenology Using MODIS.” Remote Sensing of Environment 84 (3): 471–475. doi:10.1016/S0034-4257(02)00135-9.
   Web of Science ®Google Scholar
• Zhang, X., P. M. Treitz, D. Chen, C. Quan, L. Shi, and X. Li. 2017. ““Mapping Mangrove Forest Using Multi-Tidal Remotely-Sensed Data and Decision-Tree-Based Procedure.” International Journal of Applied Earth Observation and Geoinformation.” 62: 201–214. doi:10.1016/j.jag.2017.06.010.
   Web of Science ®Google Scholar
• Zhu, Y. H., K. Liu, L. Liu, S. W. Myint, S. G. Wang, H. X. Liu, and Z. He. 2017. “Exploring the Potential of WorldView-2 Red-Edge Band-Based Vegetation Indices for Estimation of Mangrove Leaf Area Index with Machine Learning Algorithms.” Remote Sensing 9 (10): 1060. doi:10.3390/rs9101060.
   Web of Science ®Google Scholar