EVOLUCIÓN DEL ÍNDICE DE VEGETACIÓN DIFERENCIAL NORMALIZADO (NDVI) PARA EL COMPLEJO FLUVIO LITORAL DEL RÍO PARANÁ (2010-2013) EN BASE A IMÁGENES MODIS (MOD13Q1)

ZAMBONI LISANDRA PAMELA, SIONE WALTER FABIÁN, TENTOR FERNANDO RAÚL Y ACEÑOLAZA PABLO GILBERTO

Jornada; Jornadas Argentinas de Geomática; 2015

Land cover and land use plays a critical role in the interaction between land and the atmosphere, influencing the climate at local, regional and global scale. Their temporal changes affect economic, social and biophysical conditions of each territory. The Parana River Fluvial/Littoral Complex (CFLRP) has developed significant changes in land use, particularly due to the introduction of livestock and modification of flooding patterns, among other processes. This has increased the pressure on ecosystems, shifting vegetation structure, biomass and fuel load. Changes in land cover can be studied using the normalized differentiated vegetation index (NDVI). The product MOD13Q1 (MODIS/Terra Vegetation Indices 16-Day L3 SIN Global Grid 250m V5) provides images for the region since January 2000. These images are pre-processed and corrected, and can be downloaded for free from the site Earth Explorer-USGS (http://earthexplorer.usgs.gov/). The MOD13Q1 product offers the possibility to study historical time series. The "Earth Trends Modeler (ETM)" package has been generated by Clark laboratory for the analysis of the time series images (STI). The ETM allow analyzing, evaluating and modeling trends and patterns within and between STI; identify recurrences, cycles and also completing missing information; decreasing noises and abnormalities. Thus, the objective of this article was to "analyze the evolution of NDVI in different types of land cover classes of the CFLRP for 2010-2013".The methodologies consisted in download, storage and processing MOD13Q1 data, and build a time series of NDVI. For the analysis, land cover class vectors available for the region were used. A number of different types of masks cover (forests, shrublands, grasslands, and aquatic plants) were identified. "Initial" and "rastervector" tools of IDRISI-TerrSet software were used to building masks. Time series, the spectral profiles, trends and relationships between sets for each type of coverage was analyzed. These techniques allowed us to know the behavior of different types of CFLRP plant cover types, and intra or inter-annual trends.