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Cambios en la producción primaria bruta (GPP) de la vegetación natural en la Comunidad Valenciana (2001-2018)

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Cambios en la producción primaria bruta (GPP) de la vegetación natural en la Comunidad Valenciana (2001-2018)

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dc.contributor.author Martínez, Beatriz es_ES
dc.contributor.author Sánchez-Ruiz, Sergio es_ES
dc.contributor.author Campos-Taberner, Manuel es_ES
dc.contributor.author García-Haro, Francisco Javier es_ES
dc.contributor.author Gilabert, María Amparo es_ES
dc.coverage.spatial east=-0.7532808999999999; north=39.4840108; name=Comunidad Valenciana, Espanya es_ES
dc.date.accessioned 2023-02-07T08:32:52Z
dc.date.available 2023-02-07T08:32:52Z
dc.date.issued 2023-01-30
dc.identifier.issn 1133-0953
dc.identifier.uri http://hdl.handle.net/10251/191684
dc.description.abstract [EN] This work analyzes the vegetation changes in the Comunidad Valenciana observed during the period 2001-2018, using the daily GPP (Gross Primary Production) time series at 1-km spatial resolution derived from Earth observation-based (EO) data. The GPP time series have been obtained from EO-based data (e.g., MODIS/Terra-Aqua and SEVIRI/MSG) and meteorological (e.g., precipitation and temperature) data using the light use efficiency model proposed by Monteith. The carbon fluxes detection has been performed by means of a multi-resolution analysis (MRA) based on the wavelet transform (WT). This analysis allows to decomposing the signal into different temporal resolution components. The interanual trend determines the vegetation change, positive (greening) or negative (browning) of vegetation photosynthetic activity over long-term scales. The negative long-term changes observed in natural vegetation reveal the presence of areas characterized by high degradated conditions. This is the case of Natural Pack of Serra d Espadà in Castellon province, which is also controlled by a local ecosystem conservation program. To identify more precisely these areas, the areas affected by abrupt changes (associated to forest fires) in which vegetation has not been yet recovered have been removed. In this case, the results show a good agreement with the official burnt areas from the local government. es_ES
dc.description.abstract [ES] Este trabajo analiza los cambios en la vegetación natural de la Comunidad Valenciana experimentados durante el periodo 2001-2018. Para ello se utiliza un producto de GPP (Gross Primary Production) diario a 1 km de resolución espacial obtenido con el modelo de eficiencia en el uso de la radiación propuesto por Monteith, combinando datos de observación de la Tierra (EO) (e.g., MODIS/Terra-Aqua y SEVIRI/MSG) y datos meteorológicos (e.g., precipitación y temperatura). La detección de cambios se ha llevado a cabo aplicando un análisis multi-resolución (AMR) basado en la transformada wavelet (TW) a las series temporales de GPP. Este análisis permite descomponer la serie en varias componentes con resoluciones temporales diferentes. La tendencia, positiva o negativa, de la componente que se asocia con la variabilidad interanual es la que determina el cambio, positivo (greening) o negativo (browning) de la actividad fotosintética a largo plazo. Los cambios graduales negativos detectados en la vegetación natural ponen de manifiesto la existencia de zonas caracterizadas con un cierto nivel de degradación y que, además, coinciden con zonas incluidas dentro de programas de conservación, como por ejemplo el Parque Natural de la serra d' Espadà en Castellón. Para poder identificar estas zonas se han eliminado previamente las zonas con cambios bruscos negativos que son consecuencia de incendios en los que la regeneración de la vegetación es muy lenta o todavía no se ha completado. Estas zonas presentan un buen acuerdo con la cartografía de incendios proporcionada por la Generalitat Valenciana. es_ES
dc.description.sponsorship Trabajo financiado por los proyectos LSA SAF (EUMETSAT), ESCENARIOS (CGL2012–35831) y ECCE EO (ayuda PID2020-18036RB-I00 financiada por MCIN/AEI/ 10.13039/501100011033 y por “FEDER Una manera de hacer Europa”). es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista de Teledetección es_ES
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Gross primary production es_ES
dc.subject Changes es_ES
dc.subject Forest fires es_ES
dc.subject Wavelets es_ES
dc.subject Producción primaria bruta es_ES
dc.subject Cambios es_ES
dc.subject Incendios forestales es_ES
dc.title Cambios en la producción primaria bruta (GPP) de la vegetación natural en la Comunidad Valenciana (2001-2018) es_ES
dc.title.alternative Gross primary production (GPP) changes of natural vegetation in the Comunidad Valenciana (2001-2018) es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/raet.2023.18659
dc.relation.projectID info:eu-repo/grantAgreement/AEI/ESCENARIOS/CGL2012–35831 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/ECCE EO/PID2020-18036RB-I00 es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Martínez, B.; Sánchez-Ruiz, S.; Campos-Taberner, M.; García-Haro, FJ.; Gilabert, MA. (2023). Cambios en la producción primaria bruta (GPP) de la vegetación natural en la Comunidad Valenciana (2001-2018). Revista de Teledetección. (61):15-27. https://doi.org/10.4995/raet.2023.18659 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/raet.2023.18659 es_ES
dc.description.upvformatpinicio 15 es_ES
dc.description.upvformatpfin 27 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.issue 61 es_ES
dc.identifier.eissn 1988-8740
dc.relation.pasarela OJS\18659 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.description.references Alcaraz-Segura, D., Liras, E., Tabik, S., Paruelo, J., Cabello, J. 2010. Evaluating the Consistency of the 1982-1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II. Sensors, 10, 1291-1314. https://doi.org/10.3390/s100201291 es_ES
dc.description.references Alsamamra, H., Ruiz-Arias, J.A., Pozo-Vázquez, D., Tovar-Pescador, J. 2009._A comparative study of ordinary and residual kriging techniques for mapping global solar radiation over southern Spain, Agricultural and Forest Meteorology, 149(8), 1343-1357. https://doi.org/10.1016/j.agrformet.2009.03.005 es_ES
dc.description.references Azzali, A., Menenti, M. 2000. Mapping vegetation-soil complexes in southern Africa using temporal Fourier analysis of NOAA AVHRR NDVI data. International Journal of Remote Sensing, 21, 973−996. https://doi.org/10.1080/014311600210380 es_ES
dc.description.references Ben Abbes, A., Bounouh, O., Farah, I.R., de Jong, R., Martínez, B. 2018. Comparative study of three satellite image time-series decomposition methods for vegetation change detection. European Journal of Remote Sensing, 51(1), 607-615. https://doi.org/10.1080/22797254.2018.1465360 es_ES
dc.description.references Berdugo, M., Delgado-Baquerizo, M., Soliveres, S., Hernández-Clemente, R., Zhao, Y., Gaitán, J.J., Gross, N., Saiz, H., Maire, V., Lehman, A., Rillig, M.C., Solé, R.V., Maestre, F.T. 2020. Global ecosystem thresholds driven by aridity. Science. 367, 787-790. https://doi.org/10.1126/science.aay5958 es_ES
dc.description.references CGLOPS1, 2018. Copernicus Global Land Operations "Vegetation and Energy" Product User Manual for Dry Matter Productivity (DMP) and Gross Dry Matter Productivity (GDMP). Collection 1 km, version 2- CGLOPS1_PUM_DMP1km-V2, February 2018, 47 pp. es_ES
dc.description.references Chapin III, F.S., Matson, P.A., Mooney, H.A. 2002. Principles of Terrestrial Ecosystem Ecology. Springer-Verlag, New York. https://doi.org/10.1007/b97397 es_ES
dc.description.references de Beurs, K.M., Henebry, G.M. 2005. A statistical framework for the analysis of long image time series. International Journal of Remote Sensing, 26, 1551−1573. https://doi.org/10.1080/01431160512331326657 es_ES
dc.description.references de Jong, R. de Bruin, S. de Wit, A. Schaepman, M.E.Dent, D.L. 2011. Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sensing of Environment, 115(2), 692-702. https://doi.org/10.1016/j.rse.2010.10.011 es_ES
dc.description.references Furon, A. C., Wagner-Riddle, C., Smith, C. R., Warland, J. S. 2008. Wavelet analysis of wintertime and spring thaw CO2 and N2O fluxes from agricultural fields. Agricultural and Forest Meteorology, 148, 1305−1317. https://doi.org/10.1016/j.agrformet.2008.03.006 es_ES
dc.description.references Gilabert, M.A., Moreno, A., Maselli, F., Martínez, B., Chiesi, M., Sánchez-Ruiz, S., García-Haro, F.J., Pérez-Hoyos, A., Campos-Taberner, M., PérezPriego, O., Serrano-Ortiz, P., Carrara, A. 2015. Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data. ISPRS Journal of Photogrammetry and Remote Sensing, 102, 184-197. https://doi.org/10.1016/j.isprsjprs.2015.01.017 es_ES
dc.description.references Giner, C., Martínez, B., Gilabert, M.A., Alcaraz-Segura, D. 2012. Tendencias en el verdor de la vegetación y en la producción primaria bruta de las áreas forestales en la España peninsular (2000-2009). Revista de Teledetección, 38, 51-64. Disponible en: http://www.aet.org.es/?q=revista38-7 es_ES
dc.description.references Heinsch, F.A., Maosheng, Z., Running, S.W., Kimball, J.S., Nemani, R.R., Davis, K.J., et al., 2006. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Transaction on Geoscience and Remote Sensing, 44(7), 1908-1925. https://doi.org/10.1109/TGRS.2005.853936 es_ES
dc.description.references Huang, S., Tang, L., Hupy, J., Wang, Y., Shao, G. 2020. A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Journal of Forest Research, 32, 1-6. https://doi.org/10.1007/s11676-020-01155-1 es_ES
dc.description.references Jamali, S., Jönsson, P., Eklundh, L., Ardö, J., Seaquist, J. 2015. Detecting changes in vegetation trends using time series segmentation. Remote Sensing of Environment, 156, 182-195. https://doi.org/10.1016/j.rse.2014.09.010 es_ES
dc.description.references Jones, L.A., Kimball, J.S., Reichle, R.H., Madani, N., Glassy, J., Ardizzone, J.V., et al. 2017. The SMAP level 4 carbon product for monitoring ecosystem land-atmosphere CO2 exchange. IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6517- 6532. https://doi.org/10.1109/TGRS.2017.2729343 es_ES
dc.description.references Kimball, J.S., Jones, L.A., Zhang, K., Heinsch, F.A., McDonald, K.C., Oechel, W.C. 2009. A satellite approach to estimate land-atmosphere CO2 exchange for boreal and arctic biomes using MODIS and AMSR-E. IEEE Transactions on Geoscience and Remote Sensing, 47(2), 569-587. https://doi.org/10.1109/TGRS.2008.2003248 es_ES
dc.description.references Li, X.B., Chen, Y.H., Fan, Y. Da, Zhang, Y.X. 2003. Detecting inter-annual variations of vegetation growth based on satellite-sensed vegetation index data from 1983 to 1999. International Geoscience and Remote Sensing Symposium (IGARSS), 5(C), 3263-3265. es_ES
dc.description.references McKee, T.B., Doesken, N.J., Kliest, J. 1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference of Applied Climatology, 17-22 January, Anaheim, CA. American Meteorological Society, Boston, MA. 179-184. es_ES
dc.description.references Martínez, B., Gilabert, M.A. 2009. Vegetation dynamics from NDVI time series analysis using the wavelet transform. Remote Sensing of Environment, 113(9), 1823-1842. https://doi.org/10.1016/j.rse.2009.04.016 es_ES
dc.description.references Martínez, B. Gilabert, M.A. García-Haro, F.J. Faye, A. Meliá, J. 2011. Characterizing land condition variability in Ferlo, Senegal (2001-2009) using multi-temporal 1-km Apparent Green Cover (AGC) SPOT Vegetation data. Global and Planetary Change, 76, 152-165. https://doi.org/10.1016/j.gloplacha.2011.01.001 es_ES
dc.description.references Monteith, J.L. 1972. Solar radiation and productivity in tropical ecosystems. Journal of Applied Ecology, 9, 747-766. https://doi.org/10.2307/2401901 es_ES
dc.description.references Moreno, A., Gilabert, M.A., Martínez, B. 2011. Mapping daily global solar irradiation over Spain: a comparative study of selected approaches. Solar Energy, 85, 2072-2084. https://doi.org/10.1016/j.solener.2011.05.017 es_ES
dc.description.references Percival, D.B., Walden, A.T. (2000). Wavelet methods for time series analysis. Cambridge University Press 594 pp. https://doi.org/10.1017/CBO9780511841040 es_ES
dc.description.references Pérez-Hoyos, A., García-Haro, F.J., San Miguel-Ayanz, J. 2012a. A methodology to generate a synergetic land-cover map by fusion of different land-cover products. International Journal of Applied Earth Observation and Geoinformation, 19, 72-87. https://doi.org/10.1016/j.jag.2012.04.011 es_ES
dc.description.references Pérez-Hoyos, A., García-Haro, F.J., San-MiguelAyanz, J. 2012b. Conventional and fuzzy comparisons of large-scale land cover products: Application to CORINE, GLC2000, MODIS and GlobCover in Europe. ISPRS Journal of Photogrammetry and Remote Sensing, 74, 185-201. https://doi.org/10.1016/j.isprsjprs.2012.09.006 es_ES
dc.description.references Poyatos, R., Latron, J. Llorens, P. 2003. Land Use and Land Cover Change After Agricultural Abandonment. The Case of a Mediterranean Mountain Area (Catalan Pre-Pyrenees). Mountain Research and Development, 23(4), 362-368. https://doi.org/10.1659/0276-4741(2003)023[0362:LUALCC]2.0.CO;2 es_ES
dc.description.references Rhif, M., Ben Abbes, A., Farah, I.R., Martínez, B., Sang, Y. 2019. Wavelet transform application for/in nonstationary time-series analysis: A review. Applyed Sciences, 9(7), 1345. https://doi.org/10.3390/app9071345 es_ES
dc.description.references Rigina, O., Rasmussen, M.S. 2003. Using trend line and principal component analysis to study vegetation changes in Senegal 1986-1999 from AVHRR NDVI 8 km data. Geografisk Tidsskrift, Danish Journal of Geography, 103(1), 31−42. https://doi.org/10.1080/00167223.2003.10649477 es_ES
dc.description.references Roujean, J.L., Breon, F.M. 1995. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements, Remote Sensing of Environment, 51(3), 375-384. https://doi.org/10.1016/0034-4257(94)00114-3 es_ES
dc.description.references Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W., Harlan, J.C. 1974. Monitoring the vernal advancement of retrogradation of natural vegetation, Final Report, Type III, NASA/GSFC, Greenbelt, MD, 371 pp. es_ES
dc.description.references Running, S.W., Nemani, R.R., Heinsch, F.A., Zhao, M., Reeves, M., Hashimoto, H. 2004. Continuous Satellite-Derived Measure of Global Terrestrial Primary Production, BioScience, 54(6), 547-560. https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2 es_ES
dc.description.references Schimel, D. 2010. Drylands in the earth system. Science, 22, 418-419. https://doi.org/10.1126/science.1184946 es_ES
dc.description.references Stöckli, R., Vidale, P.L. 2004. European plant phenology and climate as seen in a 20-year AVHRR landsurface parameter dataset. International Journal of Remote Sensing, 25, 3303−3330. https://doi.org/10.1080/01431160310001618149 es_ES
dc.description.references Tramontana, G., Jung, M., Schwalm, C.R., Ichii, K., Camps-Valls, G., Radulu, B., et al., 2016. Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression. Biogeosciences 13, 4291-4313. https://doi.org/10.5194/bg-13-4291-2016 es_ES
dc.description.references Verbesselt, J., Hyndman, R., Newnham, G., Culvenor, D. 2010. Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment, 114(1), 106-115. https://doi.org/10.1016/j.rse.2009.08.014 es_ES
dc.description.references Xiao, J. Chevallier, F. Gomez, C. Guanter, L. Hicke, J.A. Huete, A.R. Ichii, K. Ni, W. Pang, Y. Rahman, A.F. et al., 2019. Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years. Remote Sensing of Environment, 233, 111383. https://doi.org/10.1016/j.rse.2019.111383 es_ES
dc.description.references Zhao, X., Hu, H., Shen, H., Zhou, D., Zhou, L., Myneni, R.B., Fang, J. 2015 Satellite-indicated longterm vegetation changes and their drivers on the Mongolian Plateau. Landscape Ecology, 30, 1599-611. https://doi.org/10.1007/s10980-014-0095-y es_ES


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