A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species
Urbanization poses significant challenges to ecosystems, resources, and human well-being, necessitating sustainable planning. Urban vegetation, particularly trees, provides critical ecosystem services such as carbon sequestration, air quality improvement, and biodiversity conservation. Traditional t...
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Land |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-445X/14/1/106 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832588140967100416 |
|---|---|
| author | Fabio Recanatesi Antonietta De Santis Lorenzo Gatti Alessio Patriarca Eros Caputi Giulia Mancini Chiara Iavarone Carlo Maria Rossi Gabriele Delogu Miriam Perretta Lorenzo Boccia Maria Nicolina Ripa |
| author_facet | Fabio Recanatesi Antonietta De Santis Lorenzo Gatti Alessio Patriarca Eros Caputi Giulia Mancini Chiara Iavarone Carlo Maria Rossi Gabriele Delogu Miriam Perretta Lorenzo Boccia Maria Nicolina Ripa |
| author_sort | Fabio Recanatesi |
| collection | DOAJ |
| description | Urbanization poses significant challenges to ecosystems, resources, and human well-being, necessitating sustainable planning. Urban vegetation, particularly trees, provides critical ecosystem services such as carbon sequestration, air quality improvement, and biodiversity conservation. Traditional tree assessments are resource-intensive and time-consuming. Recent advances in remote sensing, especially high-resolution multispectral imagery and object-based image analysis (OBIA), offer efficient alternatives for mapping urban vegetation. This study evaluates and compares the efficacy of Sentinel-2 and Pléiades satellite imagery in classifying tree species within historic urban parks in Rome—Villa Borghese, Villa Ada Savoia, and Villa Doria Pamphilj. Pléiades imagery demonstrated superior classification accuracy, achieving an overall accuracy (OA) of 89% and a Kappa index of 0.84 in Villa Ada Savoia, compared to Sentinel-2’s OA of 66% and Kappa index of 0.47. Specific tree species, such as Pinus pinea (Stone Pine), reached a user accuracy (UA) of 84% with Pléiades versus 53% with Sentinel-2. These insights underscore the potential of integrating high-resolution remote sensing data into urban forestry practices to support sustainable urban management and planning. |
| format | Article |
| id | doaj-art-7df4a471695a4d1195ab62a25ffc8c8f |
| institution | Kabale University |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj-art-7df4a471695a4d1195ab62a25ffc8c8f2025-01-24T13:37:55ZengMDPI AGLand2073-445X2025-01-0114110610.3390/land14010106A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree SpeciesFabio Recanatesi0Antonietta De Santis1Lorenzo Gatti2Alessio Patriarca3Eros Caputi4Giulia Mancini5Chiara Iavarone6Carlo Maria Rossi7Gabriele Delogu8Miriam Perretta9Lorenzo Boccia10Maria Nicolina Ripa11Department of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyDepartment of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyDepartment of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyDepartment of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyDepartment of Economics, Engineering, Society and Business Organization (DEIM), University of Tuscia, Via 6 del Paradiso, 47, 01100 Viterbo, ItalyDepartment of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyDepartment of Economics, Engineering, Society and Business Organization (DEIM), University of Tuscia, Via 6 del Paradiso, 47, 01100 Viterbo, ItalyDepartment of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyDepartment of Economics, Engineering, Society and Business Organization (DEIM), University of Tuscia, Via 6 del Paradiso, 47, 01100 Viterbo, ItalyDepartment of Architecture, University of Naples Federico II, Via Forno Vecchio, 36, 80134 Naples, ItalyDepartment of Architecture, University of Naples Federico II, Via Forno Vecchio, 36, 80134 Naples, ItalyDepartment of Agricultural and Forestry Sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, 8, 01100 Viterbo, ItalyUrbanization poses significant challenges to ecosystems, resources, and human well-being, necessitating sustainable planning. Urban vegetation, particularly trees, provides critical ecosystem services such as carbon sequestration, air quality improvement, and biodiversity conservation. Traditional tree assessments are resource-intensive and time-consuming. Recent advances in remote sensing, especially high-resolution multispectral imagery and object-based image analysis (OBIA), offer efficient alternatives for mapping urban vegetation. This study evaluates and compares the efficacy of Sentinel-2 and Pléiades satellite imagery in classifying tree species within historic urban parks in Rome—Villa Borghese, Villa Ada Savoia, and Villa Doria Pamphilj. Pléiades imagery demonstrated superior classification accuracy, achieving an overall accuracy (OA) of 89% and a Kappa index of 0.84 in Villa Ada Savoia, compared to Sentinel-2’s OA of 66% and Kappa index of 0.47. Specific tree species, such as Pinus pinea (Stone Pine), reached a user accuracy (UA) of 84% with Pléiades versus 53% with Sentinel-2. These insights underscore the potential of integrating high-resolution remote sensing data into urban forestry practices to support sustainable urban management and planning.https://www.mdpi.com/2073-445X/14/1/106urban forestSentinel-2Pleiadesobject-based image analysis |
| spellingShingle | Fabio Recanatesi Antonietta De Santis Lorenzo Gatti Alessio Patriarca Eros Caputi Giulia Mancini Chiara Iavarone Carlo Maria Rossi Gabriele Delogu Miriam Perretta Lorenzo Boccia Maria Nicolina Ripa A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species Land urban forest Sentinel-2 Pleiades object-based image analysis |
| title | A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species |
| title_full | A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species |
| title_fullStr | A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species |
| title_full_unstemmed | A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species |
| title_short | A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species |
| title_sort | comparative analysis of spatial resolution sentinel 2 and pleiades imagery for mapping urban tree species |
| topic | urban forest Sentinel-2 Pleiades object-based image analysis |
| url | https://www.mdpi.com/2073-445X/14/1/106 |
| work_keys_str_mv | AT fabiorecanatesi acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT antoniettadesantis acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT lorenzogatti acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT alessiopatriarca acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT eroscaputi acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT giuliamancini acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT chiaraiavarone acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT carlomariarossi acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT gabrieledelogu acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT miriamperretta acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT lorenzoboccia acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT marianicolinaripa acomparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT fabiorecanatesi comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT antoniettadesantis comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT lorenzogatti comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT alessiopatriarca comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT eroscaputi comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT giuliamancini comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT chiaraiavarone comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT carlomariarossi comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT gabrieledelogu comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT miriamperretta comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT lorenzoboccia comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies AT marianicolinaripa comparativeanalysisofspatialresolutionsentinel2andpleiadesimageryformappingurbantreespecies |