Published June 16, 2025
| Version 1.0.0
Dataset
Open
Mississippi High-Resolution Land Cover Dataset
Authors/Creators
-
1.
Mississippi State University
Description
This dataset contains 1-meter resolution land cover data for the state of Mississippi, USA for the years 2016 and 2023. This dataset is derived from USDA National Agriculture Imagery Program (NAIP) imagery for the corresponding years, and was created using a specialized deep learning model trained on manually annotated imagery. This dataset is provided "as-is" without any warranty of any kind, either expressed or implied. Furthermore, the authors provide no guarantee of suitability or fitness for any particular purpose.
Data Description
The dataset is provided in GeoTIFF format, and includes both state-wide and county-level products for convenience. All data is projected in Mississippi Transverse Mercator coordinate system, and are stored in 8-bit unsigned integer format. The land cover classes in the dataset are described in the following table:
| Pixel Value | Land Cover Class | Description |
| 0 | No Data | N/A |
| 1 | Open Water | Water bodies such as lakes, rivers, ponds, streams, pools, etc. |
| 2 | Impervious Structures | Man-made structures that have elevated surfaces, such as buildings, docks, large vehicles, etc. |
| 3 | Impervious Surfaces | Man-made surfaces that are not elevated, such as roads, parking lots, sidewalks, etc. |
| 4 | Barren Land | Areas absent of vegetation, structures, or water, such as bare soil, sand, gravel, rock, etc. |
| 5 | Tree Canopy/Woody Vegetation | Areas with visible tree canopy or moderate-to-large woody shrubs with substantial density and/or structure. |
| 6 | Herbaceous/Low Vegetation | Low-growing vegetation such as grasses, aquatic plants, pastures, and small shrubs with low density and/or sparse structure. |
| 7 | Cultivated Crops | Agricultural fields with visible crop growth identifiable by high near-infrared reflectance and row crop patterns. |
| 8 | Unclassified | Regions obscured by shadows or other image artifacts that prevent reliable classification. |
The dataset used to train the model can be accessed here. If you have any questions or need assistance with the dataset, please contact Dakota Hester at dh2306@msstate.edu.
Acknowledgements
This dataset was created with support from the Mississippi Agricultural and Forestry Experiment Station under a strategic research initiative in an effort to build machine learning systems that enhance stakeholder understanding of the distribution of natural resources in the state of Mississippi. This dataset is provided under the Creative Commons Attribution 4.0 International License, which allows for free use, distribution, and modification of the dataset with proper attribution to the authors. When using or citing this dataset, please reference the following citation:
@misc{hester2025ms_hires_lc,
author = {Dakota Hester and Vitor Souza Martins},
title = {Mississippi Land Cover Training Dataset},
year = {2025},
publisher = {Mississippi State University},
doi = {10.5281/zenodo.15670824},
}
Files
2016.tif
Files
(13.7 GB)
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md5:e652f64916731f77e29923ee87c592d6
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md5:fe681f50f53aa68fb4c93602ff51186f
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md5:cbbf8226cc67a8e95f6ac49ba45879b5
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3.6 GB | Preview Download |
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md5:910aa190027044c87beaaf57bfde1746
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3.0 GB | Preview Download |
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md5:ad7ab7aaf2293f5c776ae3890e8b885e
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3.6 kB | Preview Download |
Additional details
Dates
- Collected
-
2016
- Collected
-
2023