Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina

Remote sensing tools allow the environmental evaluation of coastal wetlands at a landscape scale, but a deeper understanding is needed of the interactions between biophysical parameters and the electromagnetic signal. The goal of this work was to analyze and quantify the influence of the aboveground biomass and the Leaf Area Index (LAI) on the spectral response of Spartina densiflora marshes in Mar Chiquita coastal lagoon, Argentina. Spectral reflectance at high resolution was measured in S. densiflora canopies under natural conditions, manipulating standing crop by means of successive harvest. Reflectance data were acquired using a spectroradiometer in visible, near infrared (IR) and shortwave IR bands. Spectral Vegetation Indices (VI) were calculated for each standing crop-LAI situation. Several VI significantly correlated with standing crop and LAI, including indices 1) based on the red-IR edge (IR Index (IRI), 695/760 ratio, Simple Ratio (SR), Red Edge Inflection Point (REIP), and different variations of the Normalized Difference VI (NDVI Rouse, NDVI amber, NDVI NOAA, NDVI Landsat, NDVI Modis), 2) indices based on the sharp change green-IR (green NDVI (GNDVI), 800/550 ratio) and 3) indices with a correction for soil noise (OSAVI: Optimized Soil Adjusted VI (OSAVI), and Modified SAVI (MSAVI). The indices with significant regressions with standing crop and LAI were IRI, NDVIAmber and REIP. The total and green standing crop showed better adjustments than LAI, showing R2 values of 0.5. These values were obtained with REIP index. Results indicate that LAI and standing crop of S. densiflora stands could be determined from spectral data but estimations should be taken carefully in high biomass scenarios, because of indexes saturation at higher LAI values.

Instituto de Clima y Agua

Fil: Gonzalez Trilla, Gabriela Liliana. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; Argentina

Fil: Pratolongo, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina

Fil: Kandus, Patricia. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; Argentina

Fil: Beget, Maria Eugenia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina

Fil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina

Fil: Marcovecchio, Jorge Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina