Phenological dataset for ecological forecasting - PheDEF - Landsat image subsets and derived vegetation indices

DOI:10.4121/9e6b4bca-f3d3-40f3-a8f5-4f71f7790c2f.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/9e6b4bca-f3d3-40f3-a8f5-4f71f7790c2f

Datacite citation style

Aguilar Bolivar, Rosa; Ofosu-Bamfo, Bismark; Mensah, Caleb; Yawson, Daniel; Zurita-Milla, Raul (2025): Phenological dataset for ecological forecasting - PheDEF - Landsat image subsets and derived vegetation indices . Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/9e6b4bca-f3d3-40f3-a8f5-4f71f7790c2f.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

University of Twente logo

Geolocation

The study area is defined by two polygons in the forest close to Sunyani, Ghana. Coordinates of centroids of the polygons are given below (WGS84).
lat (N): [7.775973, 6.690227]
lon (E): [-1.717484, -1.301089]

Time coverage

2020-01-01 until 2025-05-31

Licence

CC BY 4.0

Interoperability

This dataset is part of a data collection that combines phenology and climate data from multiple sources in two tropical forest ecosystems, a moist semi-deciduous and a dry semi-deciduous forest, that can be used for machine learning applications in climate, forests, and biodiversity conservation at community and landscape scales. The dataset includes Landsat satellite image subsets and derived indices.

Images were downloaded using the Earth Explorer Python API. Individual bands were stacked and cropped to the study area.

To calculate the vegetation indices, bands were scaled using the scaling Factor SR = (DN * 0.0000275) - 0.2 as described in the Landsat8-9, Collection2 Level2 Science Product Guide. Indices were then multiplied by 10000, and the datatype was set to int16.

We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).

History

  • 2025-08-13 first online, published, posted

Publisher

4TU.ResearchData

Format

.tif - int16

Funding

  • Lacuna Fund (grant code 19497.62 Grantee 90) [more info...] Lacuna Fund

Organizations

University of Twente, Faculty of Geo-Information Science and Earth Observation, Department of Geo-information Processing
University of Energy and Natural Resources, School of Sciences, Department of Biological Sciences, Sunyani, Ghana

DATA

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