sulagnasaharasha/bci-temporal

BCI Temporal Crown Dataset

A multi-temporal, multi-modal dataset of tropical tree crowns from Barro Colorado Island (BCI), Panama. Each tree is observed across 16 acquisition dates spanning June 2024 – September 2025, paired with a ground-level close-up photograph.

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Dataset Summary

Site	Barro Colorado Island (BCI), Smithsonian Tropical Research Institute, Panama
Tree crowns	1,897 labeled polygons across 84 species
Raster dates	16 (monthly, June 2024 – September 2025)
Total temporal rows	~30,000 (1,897 crowns × 16 dates)
Crown area	7 – 1,212 m² (median ~160 m²)
Image resolution	512 × 512 px, RGBA (alpha = crown mask)

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Configurations

This dataset has two configurations that can be joined on polygon_id at load time.

temporal — Crown-view tiles (one row per crown × date)

Each row is a masked aerial crown tile extracted from a monthly RGB orthomosaic raster.

Column	Type	Description
polygon_id	int	Unique crown identifier (join key)
date	string	Acquisition date YYYYMMDD
split	string	train / val / test
species_label	string	Species name used as the classification label
gbif_accepted_scientific_name	string	GBIF-accepted full scientific name
final_plant_name	string	Field-verified plant name
area	float	Crown polygon area in m²
crownview	Image	512×512 RGBA masked aerial tile

Size: ~30,350 rows (train ~21,380 · val ~4,272 · test ~4,704 — 16 dates each)

closeup — Ground-level close-up photos (one row per crown)

Each row is a zoom photograph taken from a drone at lower altitude, centered on the crown.

Column	Type	Description
polygon_id	int	Unique crown identifier (join key)
split	string	train / val / test
species_label	string	Species name used as the classification label
gbif_accepted_scientific_name	string	GBIF-accepted full scientific name
final_plant_name	string	Field-verified plant name
area	float	Crown polygon area in m²
closeup	Image	512×512 RGBA center-cropped/padded close-up photo

Size: 1,897 rows (train 1,336 · val 267 · test 294)

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Data Splits

Splits are stratified by species using a 70 / 15 / 15 allocation. Species with ≤ 6 crowns use fixed small-sample allocations to ensure representation across splits where possible.

Split	Crowns	Species
train	1,336	84
val	267	65
test	294	81
Total	1,897	84

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Species Distribution (Top 10)

Species	Total crowns
Anacardium excelsum	257
Dipteryx oleifera	190
Luehea seemannii	109
Prioria copaifera	95
Jacaranda copaia	90
Hieronyma alchorneoides	83
Virola surinamensis	63
Hura crepitans	57
Tachigali panamensis	45
Quararibea stenophylla	44

The dataset is long-tailed: 84 species total, many with < 10 crowns.

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Temporal Coverage

16 monthly acquisition dates spanning June 2024 – September 2025. The date column in the temporal config uses YYYYMMDD format.

#	Date (YYYYMMDD)	Calendar date	Season
1	20240611	2024-06-11	Wet
2	20240716	2024-07-16	Wet
3	20240813	2024-08-13	Wet
4	20240918	2024-09-18	Wet
5	20241014	2024-10-14	Wet
6	20241112	2024-11-12	Wet
7	20241216	2024-12-16	Wet
8	20250124	2025-01-24	Dry
9	20250217	2025-02-17	Dry
10	20250317	2025-03-17	Dry
11	20250414	2025-04-14	Dry
12	20250512	2025-05-12	Wet
13	20250616	2025-06-16	Wet
14	20250715	2025-07-15	Wet
15	20250818	2025-08-18	Wet
16	20250915	2025-09-15	Wet

Dates span the dry season (January–April) and wet season (May–December) of the Panamanian tropics, capturing phenological variation across a full annual cycle.

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Image Details

Crown-view tiles (crownview)

• Source: RGB COG rasters acquired over BCI (~4 cm/px GSD)
• Processing: Each labeled crown polygon is tilerized using geodataset. Pixels outside the crown polygon are zeroed out (alpha = 0 in RGBA). Images are center-cropped or zero-padded to 512 × 512.
• Format: PNG-encoded RGBA, stored as HuggingFace Image feature

Close-up photos (closeup)

• Source: Drone zoom photos collected via the CanopyRS platform (zoom_url field)
• Processing: Downloaded from CanopyRS, center-cropped / zero-padded to 512 × 512 RGBA
• Format: PNG-encoded RGBA, stored as HuggingFace Image feature
• Temporal note: One close-up per crown (date-invariant) — join to temporal on polygon_id

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Usage

Load a single config

from datasets import load_dataset

# Multi-temporal crown views
temporal = load_dataset("sulagnasaharasha/bci-temporal", "temporal")
print(temporal["train"][0])
# {'polygon_id': 12345, 'date': '20250915', 'species_label': 'Anacardium excelsum',
#  'crownview': <PIL.Image ...>, ...}

# Close-up photos
closeup = load_dataset("sulagnasaharasha/bci-temporal", "closeup")
print(closeup["train"][0])
# {'polygon_id': 12345, 'species_label': 'Anacardium excelsum',
#  'closeup': <PIL.Image ...>, ...}

Join temporal + closeup for multi-modal training

from datasets import load_dataset
import pandas as pd

temporal = load_dataset("sulagnasaharasha/bci-temporal", "temporal")
closeup  = load_dataset("sulagnasaharasha/bci-temporal", "closeup")

# Convert to pandas and join
t = temporal["train"].to_pandas()
c = closeup["train"].to_pandas()[["polygon_id", "closeup"]]
paired = t.merge(c, on="polygon_id")
# Each row now has both crownview (date-specific) and closeup (date-invariant)

PyTorch Dataset example

import torch
from torch.utils.data import Dataset
from datasets import load_dataset
from torchvision import transforms

class BCITemporalDataset(Dataset):
    def __init__(self, split: str = "train", transform=None):
        temporal = load_dataset("sulagnasaharasha/bci-temporal", "temporal", split=split)
        closeup  = load_dataset("sulagnasaharasha/bci-temporal", "closeup",  split=split)

        t_df = temporal.to_pandas()
        c_df = closeup.to_pandas()[["polygon_id", "closeup"]]
        self.df = t_df.merge(c_df, on="polygon_id").reset_index(drop=True)

        self.species = sorted(self.df["species_label"].unique())
        self.label_map = {s: i for i, s in enumerate(self.species)}
        self.transform = transform or transforms.ToTensor()

    def __len__(self) -> int:
        return len(self.df)

    def __getitem__(self, idx: int) -> dict:
        row = self.df.iloc[idx]
        crown   = self.transform(row["crownview"].convert("RGB"))   # [3, H, W]
        closeup = self.transform(row["closeup"].convert("RGB"))     # [3, H, W]
        label   = self.label_map[row["species_label"]]
        return {"crownview": crown, "closeup": closeup,
                "label": torch.tensor(label), "date": row["date"],
                "polygon_id": row["polygon_id"]}

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Source Data

• Site: Barro Colorado Island (BCI)
• Crown polygons: Produced by CanopyRS using automated segmentation + expert annotation
• Aerial rasters: Monthly RGB orthomosaics acquired over BCI (COG format), hosted by the CanopyRS platform
• Taxonomy: Species names resolved against GBIF Backbone Taxonomy and WCVP

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License

Creative Commons Attribution 4.0 International (CC BY 4.0)

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Citation

If you use this dataset, please cite:

@misc{sulagna_saha_2026,
    author       = { Sulagna Saha and Arthur Ouaknine and Etienne Laliberté and Carol Altimas and Evan M. Gora and Adriane Esquivel Muelbert and Ian R. McGregor and Cesar Gutierrez and Vanessa E. Rubio and David Rolnick },
    title        = { bci-temporal (Revision d222b07) },
    year         = 2026,
    url          = { https://huggingface.co/datasets/sulagnasaharasha/bci-temporal },
    doi          = { 10.57967/hf/8132 },
    publisher    = { Hugging Face }
}