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 high-resolution satellite images. Our findings support the use of geotechnologies for inventorying urban forest in tropical cities.

城市绿化是对人口生活质量至关重要的要素，森林清查被认为是最合适的评估方法。遥感已成为完成森林清查、促进城市植物区系测绘的有吸引力的替代方案。本研究旨在识别皮奥伊特雷西纳的主要树木种类，并通过使用高分辨率卫星图像 (Worldview-2) 与现场库存进行比较来评估植物识别的准确性。我们使用 e-Cognition 8.7 软件进行植物物种的映射、分割和分类，使用 ERDAS Imagine 9.2 进行准确性验证。NDVI（归一化差异植被指数）用于分析自然植被状况。城市郊区的 NDVI 值较高。数量为1，鉴定了来自 53 个物种和 28 个科的 392 个个体。其中，漆树科（20.7%）、豆科（19.8%）、楝科（9.4%）、桃金娘科（6.9%）、槟榔科（6.1%）和梳子科（5.5%）最为普遍。在确定的 53 个物种中，选择了最丰富的 16 个进行分析。16 种植物的分类结果令人满意，总体分类准确率为 69.43%，kappa 一致性指数为 0.68。获得最高准确度的物种是 16 种植物的分类结果令人满意，总体分类准确率为 69.43%，kappa 一致性指数为 0.68。获得最高准确度的物种是 16 种植物的分类结果令人满意，总体分类准确率为 69.43%，kappa 一致性指数为 0.68。获得最高准确度的物种是Ficus benjamin (87,5%), Terminalia cattapa ( 83,3 %), Syzygium malaccense (82,4%), Mangifera indica (76,8%), Caesalpinia ferrea (75,9%), Pachira Aquatica (73, 9%) 和Tabebuia sp (75,9%)。结果表明，使用高分辨率卫星图像对城市环境中的生物多样性植被进行分类是可行的，尽管具有挑战性。我们的研究结果支持使用岩土技术来清查热带城市的城市森林。