From the Capital to the Interior
Urban Planning's Impact on Forests and Landscape Metrics in South Brazil
Bibliographic Data
| ID | 21648487 |
|---|---|
| Authors | Tarik Cuchi (0000-0002-8930-2341, Agricultural Research and Rural Extension Company of Santa Catarina (EPAGRI)/Center for Socioeconomics and Agricultural Planning Florianópolis Santa Catarina Brazil), Rorai Pereira Martins‐Neto (0000-0001-5318-2627, Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague Prague Czech Republic), Rogério Bobrowski (0000-0003-4868-3376, Department of Forest Engineering Midwestern State University (UNICENTRO) Irati Paraná Brazil, corresponding author) |
| Year | 2026 |
| Volume | 37 |
| Issue | 1 |
| Pages | 104-119 |
| Publication date | 2026-01-15 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Land Degradation and Development (JOURNAL) |
| Journal identifiers | ISSN: 1085-3278 • E-ISSN: 1099-145X |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/ldr.70098 |
| OpenAlex | W4413004447 |
| Language | EN |
| References cited | 59 |
Urban planning can show deficiencies in implementing infrastructure, especially green infrastructure, resulting in disparities between urban development, environmental quality, and quality of life. However, effective management of green infrastructure and consequently urban forests is crucial for enhancing essential ecosystem services. This study focused on analyzing the composition and configuration of the urban landscape in two scenarios: (1) the overall landscape and (2) tree vegetation landscape, based on land use and land cover (LULC) maps in southeastern Paraná cities, including Irati (IRT), Prudentópolis (PRD), Rebouças (RBC), and São Mateus do Sul (SMS), comparing them with the state capital, Curitiba (CWB). We used LULC maps generated through classifying PlanetScope Dove imagery by machine learning techniques, using six LULC classes: water, built‐up area, bare soil, tree vegetation, non‐tree vegetation, and shadow. Landscape metrics described area, fragments, edges, aggregation, and shape. The metrics CA, TE, and NP were the most important to analyze city landscapes. CWB stood out with greater tree vegetation coverage and aggregation, reflecting effective public policies. RBC, SMS, and PRD displayed disaggregated fragments, highlighting a lack of adequate management. IRT showed positive results, approaching CWB. The lack of effective public policies in southeastern Paraná cities resulted in less qualified urban forest characteristics compared to CWB. Our findings offer insights into regions experiencing rapid urbanization in developing countries and highlight the importance of promoting management strategies that prioritize preserving and expanding green infrastructure to ensure greater environmental sustainability and improved quality of life
Agroforestry · Archaeology · Civil engineering · Environmental planning · Environmental resource management · Geography · Landscape planning · Urban Forestry · Urban planning · Engineering · Environmental Science · Land Use and Ecosystem Services · Urban Green Space and Health · Urban Heat Island Mitigation · Forestry
Textural Features for Image Classification
Ecosystem services classification
Landscape metrics in the analysis of urban land use patterns
Air pollution and urban structure linkages
Landscapemetrics
Efficiency of parks in mitigating urban heat island effect
Evidence-based guidelines for greener, healthier, more resilient neighbourhoods
Controlling the False Discovery Rate
Random Forests
Urban tree cover provides consistent mitigation of extreme heat in arid but not humid cities
Urban ecology and sustainability
| Highly cited | No |
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