Multitemporal distribution analysis of Dodonaea viscosa (L.) Jacq. by remote sensing in Durango, Mexico

Objective: To determine the distribution of D. viscosa at the Guadalupe Victoria dam for the years 1990, 2010 and 2017. Design/methodology/approach: Landsat satellite images were processed in order to perform a supervised classification using an artificial neural network. The ground cover of pastures, crops, shrubs and oak forest was estimated from images for the years 1990, 2010 and 2017 at sites where the presence of D. viscosa had been recorded. These data were used to calculate the expansion of D. viscosa in the study area. Results: Limitations on study/implications: The supervised classification of the artificial neural network was optimal after 400 iterations, obtaining the best overall precision, 84.5%, for 2017. This contrasted with 1990, where overall precision was low, at 45%, because there were few training sites (fewer than 100) recorded for each of the land cover classes. Findings/conclusions: In 1990, D. viscosa was found on only five hectares, while by 2017 it had increased to 147 hectares. If the disturbance caused by overgrazing continues, the potential distribution projected for D. viscosa shows it invading half the study area, occupying agricultural, forested and scrub areas.Objective: to determine the distribution of D. viscosa in the vicinity of the Guadalupe Victoria Dam in Durango, Mexico, for the years 1990, 2010 and 2017.Design/Methodology/Approach: Landsat satellite images were processed in order to carry out supervised classifications using an artificial neural network. Images from the years 1990, 2010 and 2017 were used to estimate ground cover of D. viscosa, pastures, crops, shrubs, and oak forest. This data was used to calculate the expansion of D. viscosa in the study area.Results/Study Limitations/Implications: the supervised classification with the artificial neural network was optimal after 400 iterations, obtaining the best overall precision of 84.5 % for 2017. This contrasted with the year 1990, when overall accuracy was low at 45 % due to less training sites (fewer than 100) recorded for each of the land cover classes.Findings/Conclusions: in 1990, D. viscosa was found on only five hectares, while by 2017 it had increased to 147 hectares. If the disturbance caused by overgrazing continues, and based on the distribution of D. viscosa, it is likely that in a few years it will have the ability to invade half the study area, occupying agricultural, forested, and shrub area