Multispectral drone imagery dataset for plus and non-plus trees in northern Peru.

Data Brief

Departamento de Ciencias Computacionales e Ingenierías, Universidad de Guadalajara, Ameca, 46600, Jalisco, Mexico.

Published: June 2025


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

("Algarrobo") is an endangered species native to seasonally dry forests. Preserving this species necessitates creating spatially explicit records of specimens with superior phenological traits, commonly referred to as "plus" trees, which serve as a foundation for reforestation programs. This dataset article describes a collection of multispectral images of Algarrobo trees classified as plus and non-plus, captured between January and September 2023 across the Lambayeque, Piura, and Tumbes departments in northern Peru. Sampling was conducted within forest management zones supervised by the Servicio Nacional Forestal y de Fauna Silvestre. Fieldwork included in-situ evaluation, classification, and georeferencing of specimens, followed by image acquisition using a multispectral drone at a flight altitude of 70 m. Subsequent processing isolated regions of interest corresponding to tree crowns, from which morpho-geometric parameters were extracted, summarized, and compared between tree classes. The dataset contains 500 images per class, geographically distributed across the study area, with plus trees predominantly located in Piura (70 %), Tumbes (20 %), and Lambayeque (10 %). Plus trees exhibit larger mean values for area, perimeter, and major and minor axes. The distributions of major and minor axes and equivalent diameter approximate normal distributions, differing in central tendency and dispersion between classes. However, no significant differences in roundness were observed. This database provides a foundational resource for developing classification models to distinguish between plus and non-plus trees, supporting conservation and reforestation efforts.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12149542PMC
http://dx.doi.org/10.1016/j.dib.2025.111645DOI Listing

Publication Analysis

Top Keywords

multispectral drone
8
non-plus trees
8
northern peru
8
piura tumbes
8
major minor
8
minor axes
8
trees
6
drone imagery
4
imagery dataset
4
dataset non-plus
4

Similar Publications

Above-ground biomass contributes a large proportion of mangrove carbon stock; however, spatio-temporal dynamics of biomass are poorly understood in carbonate settings of the Southern Hemisphere. This influences the capacity to accurately project the effects of accelerating sea-level rise on this important carbon store. Here, above-ground biomass and productivity dynamics were quantified across mangrove age zones dominated by , spanning a tidal gradient atop a reef platform at Low Isles, Great Barrier Reef, Australia.

View Article and Find Full Text PDF

The extent to which phenological synchrony between trophic levels may be disrupted by environmental change has been a topic of increased focus in recent years. Phenological associations between deciduous trees, phytophagous insects, and their consumers (e.g.

View Article and Find Full Text PDF

Effective water pollution assessment is essential for promoting sustainable development, especially in mining regions, where water resources are frequently degraded. Unmanned Aerial Vehicles (UAVs) and satellite imagery offer valuable tools for monitoring and evaluating surface water quality. This study aimed to compare the results of on-site water sampling with data obtained from multispectral images captured by UAVs and Sentinel-2 satellites, while also identifying the limitations of these methods.

View Article and Find Full Text PDF

The red imported fire ant (RIFA; ) is an invasive species that severely threatens ecology, agriculture, and public health in Taiwan. In this study, the feasibility of applying multispectral imagery captured by unmanned aerial vehicles (UAVs) to detect red fire ant mounds was evaluated in Fenlin Township, Hualien, Taiwan. A DJI Phantom 4 multispectral drone collected reflectance in five bands (blue, green, red, red-edge, and near-infrared), derived indices (normalized difference vegetation index, NDVI, soil-adjusted vegetation index, SAVI, and photochemical pigment reflectance index, PPR), and textural features.

View Article and Find Full Text PDF

Technological advances have made drones (UAVs) increasingly important tools for the collection of trait data in plant science. Many costs for the analysis of plant populations have dropped precipitously in recent decades, particularly for genetic sequencing. Similarly, hardware advances have made it increasingly simple and practical to capture drone imagery of plant populations.

View Article and Find Full Text PDF