Citas bibligráficas
Paredes, M., (2018). Uso de índices de vegetación del sensor Modis-Terra en la estimación de biomasa aérea de pajonales altoandinos [Tesis, Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/3351
Paredes, M., Uso de índices de vegetación del sensor Modis-Terra en la estimación de biomasa aérea de pajonales altoandinos [Tesis]. : Universidad Nacional Agraria La Molina; 2018. https://hdl.handle.net/20.500.12996/3351
@misc{renati/1115202,
title = "Uso de índices de vegetación del sensor Modis-Terra en la estimación de biomasa aérea de pajonales altoandinos",
author = "Paredes Chocce, Miguel Enrique",
publisher = "Universidad Nacional Agraria La Molina",
year = "2018"
}
A study was conducted in high-Andean tussock grasslands of the central highlands of Peru to evaluate the relationship between above ground biomass and vegetation indices (VI): Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) of the MODIS-TERRA sensor. The evaluations were conducted between April and May 2016 in the communities of Canchayllo, San Pedro de Racco and Tomas. A grid of 250 x 250 m (similar to a pixel of a MODIS image) and vegetation coverage maps were used to discriminate pixels of tussock grasslands from other types of coverage. Above ground biomass (Kg DM / ha) was measured using the Comparative Yield Method of Haydock and Shaw (1975) in quadrants of 0.25 m2 along a step transects in each pixel. VIs were extracted of images of the product MOD13Q1 of MODIS. Results show that the relationship between the NDVI - Biomass and EVI - Biomass had coefficients of determination of 0.31 (n = 46, p <0.01) and 0.22 (n = 46, p <0.01) respectively. The variability and low correlation found were attributed to the differences of the tussock grasslands of each of the three evaluation zones; the heterogeneous vegetation contained in a MODIS pixel (6.25 Ha); the number of observations per pixel for the method used to estimate the available biomass; and the cloudiness of the time in which the information was acquired. It is recommended using satellite images of sensors with a higher spatial resolution or other types, such as images taken by DRONES, performing similar experiments with other vegetation indices, and incorporating variables that allow better modeling of vegetation behavior.
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