COMPARISON OF TECHNOLOGICAL TOOLS TO DETERMINE VEGETATION INDICES IN Tectona grandis PLANTATIONS, GUANACASTE, COSTA RICA (#2002)
Read ArticleDate of Conference
July 17-19, 2024
Published In
"Sustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0."
Location of Conference
Costa Rica
Authors
Porras-Granados, Arleth
Soto-Montoya, Cassia
Arias-Aguilar, Dagoberto
Aguilar-Arias, Heileen
Romero-Badilla, David
Abstract
For the proper management of forest resources, it is necessary to have reliable and low-cost information on stand variables; in this sense, the use of new and adequate tools is of special importance. With the development of satellite technologies, spectroradiometers and more recently Remotely Piloted Aircraft Systems (RPAS) with specialized cameras, different parameters can be estimated and used, including vegetation indices, such as NDVI and GNDVI, as useful tools. in the monitoring of the vegetation, especially in areas of difficult access or large extensions. With the purpose of comparing the different technologies to obtain the NDVI and GNDVI indices, which include a UniSpec SC field spectroradiometer, Sentinel-2 satellite images and photogrammetric products of the multispectral RPAS Phantom 4, a study was carried out in a Tectona grandis plantation in the province of Guanacaste, Costa Rica, using a completely randomized experimental design with 20 observation plots and located on the ground using a GNSS total station. The NDVI did not present differences between the values obtained from satellite images and those obtained in the field; however, it did show differences between the field data and the values obtained with the RPAS, the latter being the lowest values. The GNDVI showed significant differences between the different methods studied, being the values obtained with the RPAS the lowest and those obtained with the satellite image the highest. The use of Sentinel-2 images is recommended for the estimation of vegetation indices and recommendations are provided on aspects to improve with the use of RPAS.