Biennial sub-meter tree coverage dataset of Orlando (2013–2021)

Rapid urban development often comes at the cost of significant vegetation loss, and the loss of urban trees is a particularly concerning issue. Many cities have recognized the crucial role of tree canopy cover in addressing a range of pressing environmental challenges, and have set goals in their development plans. However, the lack of resources for monitoring its spatiotemporal changes directly undermines efforts of cities to balance urban growth with environmental sustainability. We developed high-resolution biennial tree canopy maps (2013-2021) for the Orlando metropolitan area using National Agricultural Imagery Program (NAIP) orthoimagery. Our approach addresses challenges such as sensor inconsistencies, shadows, variable observation times, and environmental factors. Extensive ground-truth validation demonstrates 78%-89% accuracy in tree detection, outperforming existing products. This dataset provides the crucial link between planning and action, and supports urban forest management and has broader applications in urban planning, environmental and public health monitoring, and education programs.

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Publication Details

Journal
Scientific Data
Published
2025-04-29
DOI
https://doi.org/10.1038/s41597-025-05059-9
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
0.00

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article

Biennial sub-meter tree coverage dataset of Orlando (2013–2021)

Janak Parajuli, Danlu Cai, Leiqiu Hu
Scientific Data
Urban Green Space and Health
article

Biennial sub-meter tree coverage dataset of Orlando (2013–2021)

Janak Parajuli, Danlu Cai, Leiqiu Hu
article en

Abstract

Rapid urban development often comes at the cost of significant vegetation loss, and the loss of urban trees is a particularly concerning issue. Many cities have recognized the crucial role of tree canopy cover in addressing a range of pressing environmental challenges, and have set goals in their development plans. However, the lack of resources for monitoring its spatiotemporal changes directly undermines efforts of cities to balance urban growth with environmental sustainability. We developed high-resolution biennial tree canopy maps (2013-2021) for the Orlando metropolitan area using National Agricultural Imagery Program (NAIP) orthoimagery. Our approach addresses challenges such as sensor inconsistencies, shadows, variable observation times, and environmental factors. Extensive ground-truth validation demonstrates 78%-89% accuracy in tree detection, outperforming existing products. This dataset provides the crucial link between planning and action, and supports urban forest management and has broader applications in urban planning, environmental and public health monitoring, and education programs.

Scientific DataVol. 12(1)
University of Alabama in Huntsville (US)
National Aeronautics and Space Administration, Nuclear Safety and Security Commission
Life in Land
Openalex Percentile: Top 88%
Urban Green Space and Health
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Biennial sub-meter tree coverage dataset of Orlando (2013–2021) — Janak Parajuli, Danlu Cai, et al. · Scientific Data (2025) | TGRS Research Map | TGRS