Dataset: Habitat variables (mangrove, marsh, water) of Port Fourchon, LA dervied from satellite imagery taken in fall 2022

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.947975.1Version 1 (2025-01-06)Dataset Type:model results

Principal Investigator, Contact: James Nelson (University of Louisiana at Lafayette)

Student: Herbert Leavitt (University of Louisiana at Lafayette)

Student: Alexander Thomas (University of Louisiana at Lafayette)

BCO-DMO Data Manager: Karen Soenen (Woods Hole Oceanographic Institution)


Project: CAREER: Integrating Seascapes and Energy Flow: learning and teaching about energy, biodiversity, and ecosystem function on the frontlines of climate change (Louisiana E-scapes)


Abstract

This dataset consists of satellite-derived habitat data tables used to quantify fine-scale landscape metrics in an estuarine environment undergoing rapid climate-driven habitat change. The data were generated as part of a study evaluating the effects of mangrove encroachment and marsh loss on species-landscape relationships in coastal Louisiana. Habitat variables were derived for buffer zones ranging from 150 to 600 meters around 52 field sampling sites and edge zones 1, 3, and 5 meters from ...

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No raw data is included in this dataset. For information pertaining to the collection methods for the data used to generate this dataset, refer to methods sections of linked datasets


Related Datasets

IsDerivedFrom

Dataset: Satellite imagery classification, Port Fourchon, 2022
Relationship Description: The dataset "Classified satellite imagery of Port Fourchon, LA from 2022." contains the shapefiles used to generate the tables in this dataset. Habitat variables were calculated based on these files.
Leavitt, H., Thomas, A., Nelson, J. (2025) Habitat classification (mangrove, marsh, water) based on satellite imagery taken in fall 2022 in Port Fourchon, LA. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-04-07 http://lod.bco-dmo.org/id/dataset/947958
IsDerivedFrom

Dataset: Meteorological observations from NOAA station 8761724
Relationship Description: The dataset "Meteorological observations from NOAA station 8761724, Grande Isle, LA from September 20, 2022, to September 29, 2024" contains the meterological data used to generate the tables in this dataset.
Leavitt, H., Thomas, A., Nelson, J. (2025) Meteorological observations from NOAA station 8761724, Grande Isle, LA from September 20, 2022, to September 29, 2024. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-02-19 doi:10.26008/1912/bco-dmo.953856.1
IsDerivedFrom

Dataset: Drop Sampling Data - Port Fourchon, LA 2022
Relationship Description: The dataset "Drop-sampling site data collected from Fall 2022 in Port Fourchon, Louisiana from September 23, 2022 to September 29, 2022" contains the latitude and longitude of sampling sites in this dataset, which are imported and used to define the habitat characteristics around each site.
Leavitt, H., Thomas, A., Nelson, J. (2025) Species counts, site-level information and environmental context sampled near Port Fourchon, Louisiana from September 23 - 29, 2022. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-04-07 doi:10.26008/1912/bco-dmo.947784.1
IsSourceOf

Dataset: Habitat scale model outputs Port Fourchon, LA during Fall 2022
Relationship Description: The dataset "2022 Satellite-derived habitat scales from Port Fourchon, Louisiana" contains the habitat variable tables for each site included in the analysis at scales where we used satellite-derived data to calculate habitat metrics. Each table corresponds to a habitat scale that was tested in this mode. In the code, this data is imported as the object hab and merged with species data to generate the pf.env table used in the GAM models. The scripts necessary to generate this data from raw shapfiles are also included.
Leavitt, H., Thomas, A., Nelson, J. (2025) Habitat scale model output of Port Fourchon, LA dervied from drone and satellite imagery taken in fall and spring 2023. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-01-08 http://lod.bco-dmo.org/id/dataset/948167

Related Publications

Methods

Broussard, W., Suir, G., & Visser, J. (2018). Unmanned Aircraft Systems (UAS) and satellite imagery collections in a coastal intermediate marsh to determine the land-water interface, vegetation types, and Normalized Difference Vegetation Index (NDVI) values. Engineer Research and Development Center (U.S.). https://doi.org/10.21079/11681/29517
Methods

Zhao, J., Fang, Y., Zhang, M., & Dong, Y. (2020). Identification of Remote Sensing-Based Land Cover Types Combining Nearest-Neighbor Classification and SEaTH Algorithm. Journal of the Indian Society of Remote Sensing, 48(7), 1007–1020. https://doi.org/10.1007/s12524-020-01131-6