Urban greenness is an element of vital importance for the population quality of life, and forest inventory is considered the most appropriate method for its assessment. Remote sensing has become an attractive alternative for the accomplishment of forest inventory, facilitating urban flora mapping. The present study aimed to identify the main species of trees in Teresina, Piauí, and evaluate the botanical identification accuracy by using high-resolution satellite images (Worldview-2) as compared to on-site inventory. We used the e-Cognition 8.7 software for the mapping, segmentation, and classification of the vegetal species and ERDAS Imagine 9.2 for accuracy verification. The NDVI (Normalized Difference Vegetation Index) was used to analyze the natural vegetation condition. The outskirts of the city presented higher values of NDVI. An amount of 1,392 individuals from 53 species and 28 families, were identified. Among these, the families Anacardiaceae (20.7%), Fabaceae (19.8%), Meliaceae (9.4%), Myrtaceae (6.9%), Arecaceae (6.1%), and Combretaceae (5.5%) were the most prevalent. Amongst the 53 species identified, the 16 most abundant were chosen for the analysis. The classification had a satisfactory result for the 16 vegetal species with a general classification accuracy of 69.43% and a kappa agreement index of 0,68. The species that obtained the highest accuracy were Ficus benjamin (87,5%), Terminalia cattapa (83,3%), Syzygium malaccense (82,4%), Mangifera indica (76,8%), Caesalpinia ferrea (75,9%), Pachira aquatica (73,9%), and Tabebuia sp (75,9%). The results showed that it is feasible, although challenging, to classify biodiverse vegetation in an urban environment using highresolution satellite images. Our findings support the use of geotechnologies for inventorying urban forest in tropical cities.