Modeling Gross Primary Production (GPP) of a Mediterranean Grassland in Central Spain Using Sentinel-2 NDVI and Meteorological Field Information

Author:

Cicuéndez Víctor1ORCID,Inclán Rosa2,Sánchez-Cañete Enrique P.3ORCID,Román-Cascón Carlos4,Sáenz César56ORCID,Yagüe Carlos1ORCID

Affiliation:

1. Departamento de Física de la Tierra y Astrofísica, Universidad Complutense de Madrid (UCM), Plaza de Ciencias 1, Ciudad Universitaria, 28040 Madrid, Spain

2. Departamento de Medio Ambiente, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Avda. Complutense 40, 28040 Madrid, Spain

3. Departamento de Física Aplicada, Universidad de Granada (UGR), Avda. de Fuente Nueva, s/n, 18071 Granada, Spain

4. Departamento de Física Aplicada, Facultad de Ciencias del Mar y Ambientales, INMAR, CEIMAR, Universidad de Cádiz, 11510 Puerto Real, Spain

5. Departamento de Ingeniería Agroforestal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid (UPM), Avda. Complutense 3, 28040 Madrid, Spain

6. Quasar Science Resources S.L., Camino de las Ceudas 2, 28232 Las Rozas de Madrid, Spain

Abstract

Mediterranean grasslands provide different ecosystems and social and economic services to the Mediterranean basin. Specifically, in Spain, pastures occupy more than 55% of the Spanish surface. Farmers and policymakers need to estimate the Gross Primary Production (GPP) to make sustainable management of these ecosystems and to study the role of grasslands acting as sinks or sources of Carbon in the context of climate change. High-frequency satellites, such as Sentinel-2, have opened the door to study GPP with a higher spatial and lower revisit time (10 m and 5 days). Therefore, the overall objective of this research is to estimate an ecosystem light use efficiency (eLUE) GPP model for a Mediterranean grassland in central Spain using Sentinel-2 NDVI Normalized Difference Vegetation Index (NDVI), complemented with meteorological information at the field scale for a relatively long period (from January 2018 to July 2020). The GPP models studied in this research were the MODIS GPP product, as well as the four eLUE models built with MODIS or Sentinel-2 NDVI and complemented by the inclusion of minimum temperature (Tmin) and soil water content (SWC). The models were validated through the GPP obtained from an eddy-covariance flux tower located in the study site (GPP_T). Results showed that the MODIS GPP product underestimated the GPP_T of the grassland ecosystem. Besides this, the approach of the eLUE concept was valid for estimating GPP in this Mediterranean grassland ecosystem. In addition, the models showed an improvement using Sentinel-2 NDVI compared to MODIS GPP product and compared to the models that used MODIS NDVI due to its higher spatial and temporal resolution. The inclusion of Tmin and SWC was also a determinant in improving GPP models during winter and summer periods. This work also illustrates how the main wind directions of the study area must be considered to appropriately estimate the footprint of the eddy covariance flux tower. In conclusion, this study is the first step to efficiently estimating the GPP of Mediterranean grasslands using the Sentinel-2 NDVI with complementary meteorological field information to make the management of these ecosystems sustainable.

Funder

I+D+i Spanish National Projects

Ministerio de Ciencia e Innovación of Spain

postdoctoral Juan de la Cierva fellowship

European Union ≪NextGenerationEU≫/≪PRTR≫

Community of Madrid

Publisher

MDPI AG

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