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The use of geotechnologies for the identification of the urban flora in the city of Teresina, Brazil

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Abstract

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.

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Availability of data and material

The data obtained in this Research, can be made available as a scientific article in this journal of scientific importance—Urban ecosystems.

Code availability

The software used in this Research was obtained due to a partnership with the Ashoka Trust for Research in Ecology and the Environment, Bangalore, India.

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Acknowledgements

The author thanks the Federal Institute of Piauí, Federal University of Piauí and Capes and for the support granted to research

Funding

This research was funded by the Ministry of Health of Brazil, with protocol nº 293/2013. This research was the starting point of a study between urban plants x phlebotominios association, where the main point was to know if leishmaniasis disease is associated with vegetation. For this purpose, high resolution satellite images were also used to identify urban plants.

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Authors and Affiliations

  1. Instituto Federal Do Piauí, Campus Parnaíba, Parnaíba, Brazil

    Marcelo Ribeiro Mesquita

  2. Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura, Jakkur, Bangalore, India

    Shivani Agarwal

  3. Universidade Federal Do Piauí, Campus Helvídio Nunes de Barros, Picos, Brazil

    Leonardo Henrique Guedes de Morais Lima

  4. Universidade Federal Do Piauí, Campus Amílcar Ferreira Sobral, Floriano, Brazil

    Maria Regiane Araujo Soares & Diogo Brunno e Silva Barbosa

  5. Universidade Federal Do Piauí, Campus Amílcar Ferreira Sobral, Teresina, Brazil

    Vladimir Costa Silva

  6. Instituto de Medicina Social, Universidade Do Estado Do Rio de Janeiro, Rio de Janeiro, Brazil

    Guilherme Loureiro Werneck

  7. Fundação Oswaldo Cruz / Fiocruz-Piaui, Teresina, Brazil

    Guilherme Loureiro Werneck

  8. Departamento de Medicina Comunitária, Universidade Federal Do Piauí, Campus Petrônio Portella, Teresina, Brazil

    Carlos Henrique Nery Costa

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  1. Marcelo Ribeiro Mesquita
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  2. Shivani Agarwal
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  4. Maria Regiane Araujo Soares
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Contributions

MRM: Acquisition of data, Analysis and interpretation of data, Drafting the manuscript or revising it critically for important intellectual content; SA: Analysis and interpretation of data, Drafting the manuscript or revising it critically for important intellectual content; LHGML: Acquisition of data, Drafting the manuscript or revising it critically for important intellectual content; MRAS: Acquisition of data, Drafting the manuscript or revising it critically for important intellectual content; DBSB: Acquisition of data, Drafting the manuscript or revising it critically for important intellectual content; VCS: Acquisition of data, Drafting the manuscript or revising it critically for important intellectual content; GLW: Analysis and interpretation of data, Drafting the manuscript or revising it critically for important intellectual content; CHNC: Conception and design of the study, Analysis and interpretation of data, Drafting the manuscript or revising it critically for important intellectual content.

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Correspondence to Marcelo Ribeiro Mesquita or Carlos Henrique Nery Costa.

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Mesquita, M.R., Agarwal, S., de Morais Lima, L.H.G. et al. The use of geotechnologies for the identification of the urban flora in the city of Teresina, Brazil. Urban Ecosyst 25, 523–534 (2022). https://doi.org/10.1007/s11252-021-01153-z

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