Citas bibligráficas
Núñez, G., (2022). Estimación de la biomasa vegetal aérea mediante teledetección calibrada con un método destructivo en Cajatambo, Lima [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/5309
Núñez, G., Estimación de la biomasa vegetal aérea mediante teledetección calibrada con un método destructivo en Cajatambo, Lima []. PE: Universidad Nacional Agraria La Molina; 2022. https://hdl.handle.net/20.500.12996/5309
@misc{renati/249544,
title = "Estimación de la biomasa vegetal aérea mediante teledetección calibrada con un método destructivo en Cajatambo, Lima",
author = "Núñez Vilca, Gonzalo Alonso",
publisher = "Universidad Nacional Agraria La Molina",
year = "2022"
}
In recent years it has affected a pressure of natural capital by anthropic activity and may affect the trajectory of ecosystems. Front with this problem, it is necessary to create tools capable of carrying information for decision making. Nature management aims to maintain the properties of a theme ecosystem. The study of plant biomass can reveal part of the dynamics of the ecosystem. The use of the remote sensor and cartography has been extended in the field of ecology, becoming increasingly essential especially for its ability to correlate spectral responses with biophysical parameters. Therefore, the objective of this research work was to propose a model of estimate of aerial plant biomass to a vegetation index. A destructive method was used to calculate the dry weight of aerial plant biomass sampled in the countryside. Use the satellite images of LANDSAT 8, SENITNEL-2 and SPOT 7 to calculate vegetation indices. Later they calculated several linear regression models for the calculated one. The selection criterion was the model that presented a better estimate fit and a lower RMSE. The EVI index was chosen for the elaboration of the estimated biomass map when presenting an R2 of 0,43 and an RMSE of 10,006. The model is valid for the biomass specification for grassland and scrubland not very dense. It presented difficulties in estimating the biomass of certain vegetation cover due to the saturation of the vegetation index. The contribution of the study will help the development of similar tools applied to the national reality. As well as highlighting the use of remote sensing as a tool with various uses in the field of ecology and ecosystem management.
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