Assessing Forest Species Diversity in Ghana's Tropical Forest Using PlanetScope Data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F24%3A100551" target="_blank" >RIV/60460709:41320/24:100551 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.3390/rs16030463" target="_blank" >http://dx.doi.org/10.3390/rs16030463</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/rs16030463" target="_blank" >10.3390/rs16030463</a>

Result language

angličtina

Original language name

Assessing Forest Species Diversity in Ghana's Tropical Forest Using PlanetScope Data

Original language description

This study utilized a remotely sensed dataset with a high spatial resolution of 3 m to predict species diversity in the Bobiri Forest Reserve (BFR), a moist semi-deciduous tropical forest in Ghana. We conducted a field campaign of tree species measurements to achieve this objective for species diversity estimation. Thirty-five field plots of 50 m x 20 m were established, and the most dominant tree species within the forest were identified. Other measurements, such as diameter at breast height (DBH >= 5 cm), tree height, and each plot's GPS coordinates, were recorded. The following species diversity indices were estimated from the field measurements: Shannon-Wiener (H '), Simpson diversity index (D2), species richness (S), and species evenness (J '). The PlanetScope surface reflectance data at 3 m spatial resolution was acquired and preprocessed for species diversity prediction. The spectral/pixel information of all bands, except the coastal band, was extracted for further processing. Vegetation indices (VIs) (NDVI-normalized difference vegetation index, EVI-enhanced vegetation index, SRI-simple ratio index, SAVI-soil adjusted vegetation index, and NDRE-normalized difference red edge index) were also calculated from the spectral bands and their pixel value extracted. A correlation analysis was then performed between the spectral bands and VIs with the species diversity index. The results showed that spectral bands 6 (red) and 2 (blue) significantly correlated with the two main species diversity indices (S and H ') due to their influence on vegetation properties, such as canopy biomass and leaf chlorophyll content. Furthermore, we conducted a stepwise regression analysis to investigate the most important spectral bands to consider when estimating species diversity from the PlanetScope satellite data. Like the correlation results, bands 6 (red) and 2 (blue) were the most important bands to be considered for predicting species diversity. The model equations from the stepwise regression were used to predict tree species diversity. Overall, the study's findings emphasize the relevance of remotely sensed data in assessing the ecological condition of protected areas, a tool for decision-making in biodiversity conservation.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10600 - Biological sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Remote Sensing

ISSN

2072-4292

e-ISSN

2072-4292

Volume of the periodical

16

Issue of the periodical within the volume

3.0

Country of publishing house

CH - SWITZERLAND

Number of pages

16

Pages from-to

1-16

UT code for WoS article

001159943700001

EID of the result in the Scopus database

2-s2.0-85184718685