TY - JOUR
T1 - NDVI Performance for Monitoring Agricultural Energy Inputs Using Landsat Imagery
T2 - A Study in the Ecuadorian Andes (2012–2023)
AU - Zea, Pedro
AU - Pascual, Cristina
AU - García-Montero, Luis G.
AU - Cedillo, Hugo
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/1
Y1 - 2025/1
N2 - The NDVI is typically associated with medium-resolution images, e.g., Landsat imagery, and has often been linked to various agricultural parameters, except agricultural energy inputs. Thus, our objective was to analyze the performance of the NDVI associated with Landsat images to monitor both the evolution and impact of energy inputs on the spectral activity in some rural mountain crops. To do so, we studied energy inputs in three scenarios in the Ecuadorian Andes: high-mountain agroforestry systems (HAFSs), short-cycle production systems (SHCs), and low-mountain agroforestry systems (LAFSs). In 2022, information on energy inputs was collected for 415 systems (through field surveys). Using Google Earth Engine, we analyzed NDVI data associated with Landsat images between 2012 and 2023. Statistical analysis demonstrated significant positive correlations between energy inputs and the NDVI. As a novelty, this result means that energy inputs influence crops’ spectral activity. Furthermore, we demonstrated a historical enhancement of energy inputs across the inputs at the Landsat image scale. Therefore, further studies are needed to improve the resolution of this approach, for example, by integrating higher-resolution images to assess a more accurate NDVI response.
AB - The NDVI is typically associated with medium-resolution images, e.g., Landsat imagery, and has often been linked to various agricultural parameters, except agricultural energy inputs. Thus, our objective was to analyze the performance of the NDVI associated with Landsat images to monitor both the evolution and impact of energy inputs on the spectral activity in some rural mountain crops. To do so, we studied energy inputs in three scenarios in the Ecuadorian Andes: high-mountain agroforestry systems (HAFSs), short-cycle production systems (SHCs), and low-mountain agroforestry systems (LAFSs). In 2022, information on energy inputs was collected for 415 systems (through field surveys). Using Google Earth Engine, we analyzed NDVI data associated with Landsat images between 2012 and 2023. Statistical analysis demonstrated significant positive correlations between energy inputs and the NDVI. As a novelty, this result means that energy inputs influence crops’ spectral activity. Furthermore, we demonstrated a historical enhancement of energy inputs across the inputs at the Landsat image scale. Therefore, further studies are needed to improve the resolution of this approach, for example, by integrating higher-resolution images to assess a more accurate NDVI response.
KW - agro-productive systems
KW - cocoa
KW - crop temporal analysis
KW - deciduous fruit trees
KW - Ecuadorian Andes
KW - energy inputs
KW - Google Earth Engine
KW - Landsat imagery
KW - normalized difference vegetation index
KW - short-cycle crops
UR - https://www.scopus.com/pages/publications/105003824423
U2 - 10.3390/su17083480
DO - 10.3390/su17083480
M3 - Artículo
AN - SCOPUS:105003824423
SN - 2071-1050
VL - 17
JO - Sustainability (Switzerland)
JF - Sustainability (Switzerland)
IS - 8
M1 - 3480
ER -