Dataset: Satellite imagery classification, Port Fourchon, 2022
View Data: Data not available yet
Data Citation:
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 2025-01-03 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/947958 [access date]
Terms of Use
This dataset is licensed under Creative Commons Attribution 4.0.
If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.
Spatial Extent: N:29.164671 E:-90.149744 S:29.092646 W:-90.269831
Marshes surrounding Port Fourchon, Louisiana.
Temporal Extent: 2022-09-23 - 2022-09-29
Principal Investigator:
James Nelson (University of Louisiana at Lafayette)
Student:
Herbert Leavitt (University of Louisiana at Lafayette)
Alexander Thomas (University of Louisiana at Lafayette)
Contact:
Herbert Leavitt (University of Louisiana at Lafayette)
BCO-DMO Data Manager:
Karen Soenen (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Version:
1
Version Date:
2025-01-03
Restricted:
No
Validated:
No
Current State:
Data not available
Habitat classification (mangrove, marsh, water) based on satellite imagery taken in fall 2022 in Port Fourchon, LA
Abstract:
This dataset contains habitat classifications based on satellite imagery downloaded from Google Earth, representing the locations of sites sampled during the Fall 2022 drop sampling season. The imagery includes geospatial coverage of estuarine and adjacent terrestrial habitats, providing detailed landscape features such as vegetation type, water bodies, and land use around each sampling site. The spatial resolution of the satellite imagery allows for precise analysis of habitat variables at multiple scales.
The satellite imagery used to classify the habitats in this dataset was taken in 2022 within 1 year of our sampling timeframe. The imagery was analyzed to extract environmental variables, such as land-water ratios, vegetation coverage, and proximity to habitat edges. These variables are crucial for defining habitat characteristics and exploring their relationship to species abundance.
The primary purpose of this dataset is to investigate how habitat scale influences models linking species abundance to landscape metrics. This information is particularly useful for researchers studying estuarine ecosystems, landscape ecology, and habitat management. Data collection and interpretation were conducted by Herbert Leavitt, Dr. James Nelson, and Alex Thomas, with affiliations at the time of sampling being with the University of Louisiana at Lafayette.