Tesis
Cálculo de la severidad en zonas incendiadas en la subcuenca del río Chambo en el período 2017 a 2020 mediante teledetección.
Fecha
2021-11-08Registro en:
Vasco Lucio, Martha Marisol. (2021). Cálculo de la severidad en zonas incendiadas en la subcuenca del río Chambo en el período 2017 a 2020 mediante teledetección. Escuela Superior Politécnica de Chimborazo. Riobamba.
Autor
Vasco Lucio, Martha Marisol
Resumen
The present study aims to calculate the severity of burned areas using spectral index in the
ecosystems of the Chambo River sub-basin in the period 2017 to 2020. In the research, Landsat 8
satellite images obtained from the Google Earth Engine platform were used to calculate the
Normalized Difference Vegetation Index (NDVI), Burned Area Index (BAI) and Normalized
Burning Rate (NBR), subsequently using ArcGIS software, the spectral indices were combined:
Burned Area Index (BAI) and Normalized Burned Area Index (NBR) to correct the detection of
burned area polygons calculating the Normalized Burned Area Index (NBA) which establishes
the severity of the fires, whose values were classified into high, medium and low severity. In
addition, the TerrSet software was used to evaluate the transition intensity, which allows
determining the gains and losses between categories. The results indicate that the largest number
of polygons detected as fires were located in the Herbazal del Páramo ecosystem with a total of
3313.51 hectares, with high severity values ranging from 200 to 509.68. On the other hand, the
transition intensity determined that the period from 2019 to 2020 has the highest rate of change
corresponding to 0.80 hectares. With the detection of the indexes, it is concluded that the area
that experienced high fire severity corresponds to the Chimborazo Reserve, an area altered
mainly by the agricultural work carried out by the 42 communities located around the area. The
use of spectral indices is recommended because of the variety of information it provides in the
forest area, which provides a more complete view of it, of vital importance in decision making.