The Union County Florida Land Cover Map is led by forest, but the county is not uniformly wooded. Forest accounts for 38.35% of the supplied 2025 summary, wetlands 25.78%, agriculture 17.38%, developed land 7.60%, grassland 4.97%, shrubland 4.45%, and water 1.28%. Broad forest dominates much of the north and center, while agricultural colors become more common toward the south and southwest. Wetlands repeatedly break up both areas, creating a varied inland landscape rather than a simple north-south split.
This page includes four connected views: the 2025 land-cover overview, forest and farmland, impervious surface and developed land, and a 1985–2025 class-difference map. The WebP versions are placed in the article for quick comparison, while the four original JPG maps are available together in the download below. The set is useful for explaining where forest, wetlands, farmland, and concentrated development occur and how the two-date comparison differs from a current land-cover map.
Table of Contents
Forest is the largest 2025 class and forms the county’s broad northern interior
Dark green forest covers large areas across the northern half and continues through the center and west. It does not disappear in the agricultural south; smaller wooded pieces remain between fields and open vegetation there as well. The 38.35% forest share matches a map where tree-dominated cover is the most widespread single class, yet it is constantly interrupted by wetlands, farms, roads, and developed pockets.
Wetlands are the second-largest class at 25.78%. Teal areas occur between forest blocks in the north, around the central developed area, across the east and northeast, and within the southern agricultural landscape. Their distribution matters because the county is not divided into a “forest zone” and a separate “wetland zone.” Wet and wooded surfaces are interwoven through much of the map.
Agriculture accounts for 17.38% and is most visually prominent in the south and southwest. Yellow farm blocks become more frequent toward the lower part of the county, with additional agricultural patches in the center and east. In the north, forest and wetland colors are more dominant. The shift is gradual rather than a hard boundary, making the county useful for showing how land-cover classes mix across a relatively small area.
Developed land covers 7.60%. The central red concentration is easy to spot because it is compact, and a second distinct cluster appears near the northeastern edge. Thin developed traces connect through other parts of the county. These red areas do not represent city limits, ownership, or zoning. They are land-cover cells where developed surfaces are the representative mapped class.
Farmland becomes more visible when the developed colors are removed
The forest-and-farmland view makes the county’s southern contrast much clearer. Cropland and pasture or hay occupy many blocks in the lower third of the map, while large forest areas remain dominant farther north. Wetlands continue to interrupt both. Instead of one uninterrupted farm district, the south contains a mixture of working land, forest fragments, wet areas, and smaller developed or other surfaces.
The verified agriculture total is 17.38%. The map separates cropland from pasture or hay with different colors, but the package does not provide individual percentages for those two agricultural subtypes. Their locations can be compared visually, yet creating exact cropland or pasture shares by counting pixels would go beyond the supplied evidence.
Grassland contributes 4.97% and shrubland 4.45%. Those lighter green and brown classes occur around farm blocks, wetlands, and forest edges, with noticeable areas in the south and scattered patches elsewhere. They help explain why the county is not simply forest plus agriculture. Open vegetation occupies a smaller but still visible part of the transition between those larger classes.
UF/IFAS Extension Union County provides local education in agriculture, horticulture, and natural-resource management. That official county-specific context fits a map where working land, forest, and wetlands all have substantial roles. The Extension program does not identify the crop grown in any particular map cell, and the land-cover layer does not show farm ownership or management practice. Those require more detailed local records.
Hard surface remains sparse outside a few compact developed areas
Mean impervious cover is only 1.52%, and 0.32% of the county is mapped at 50% or greater impervious surface. Those values are much lower than the 7.60% developed-land share because developed land is a broader classification. A developed cell may contain lawns, trees, yards, or other permeable ground together with buildings and pavement, while impervious cover isolates the hard fraction.
The strongest red and orange concentrations sit near the central developed area and at the northeastern edge. Smaller hard-surface clusters appear in the south and southwest, and narrow lines cross parts of the county. Most forest, wetland, and agricultural areas remain very pale. The result is a county where developed places are visible but highly concentrated rather than spread evenly across the landscape.
Narrow colored lines may look like roads, but this is not a transportation map. It does not provide route names, traffic counts, lane numbers, or road condition. Impervious percentage only measures the share of hard surface within the mapped cells. A low value also does not imply low flood risk because rainfall, soils, topography, wetlands, rivers, and drainage are separate factors.
Putting the 7.60% developed share beside the 1.52% mean impervious value is one of the most useful comparisons in this map set. It prevents a low-density developed cell from being described as fully urbanized. The map shows that Union County has compact built-up locations, but roofs and pavement still occupy only a small share of the countywide surface.
The 1985–2025 comparison highlights widespread forest and other class differences
The total class difference between 1985 and 2025 is 27.52%. That figure is not the same as saying 27.52% of Union County was physically transformed. The map compares the class assigned to each raster cell at two endpoints. Real land-cover change can contribute, but classification rules, season, imagery, and mixed cells may also influence whether a location receives the same label in both years.
Forest loss is listed at 11.11%. Orange cells appear across the west, center, south, and northeast, rather than forming one single area. The map can identify where forest classification differs between the two dates, but it cannot state why. Timber activity, land conversion, regrowth, storm effects, or classification variation would need intermediate imagery or local records to distinguish.
Agricultural loss is 2.87%, and cells classified as developed account for 1.80% of the comparison. Purple other-class difference is 11.42% and is also widespread. The current developed share of 7.60% should not be combined mathematically with the 1.80% change category. One describes the 2025 surface; the other identifies a set of cells whose two-date classification falls into a particular difference category.
Wetland difference appears in the legend but does not have a separate verified county percentage in the supplied summary. Its visible locations can be discussed, but estimating a new rate from colored pixels would be inappropriate. Because wetlands already cover 25.78% of the current county summary and often meet forest or farmland, classification differences near their edges can appear in many places.
Frequently Asked Questions
Where are the strongest differences between forest and agriculture in Union County?
Forest is most extensive across the north and center, while agricultural blocks become much more common toward the south and southwest. The pattern is not a hard boundary because forest, wetlands, and farmland overlap in many places. Countywide, forest is 38.35% and agriculture is 17.38%.
Why is developed land 7.60% while mean impervious cover is only 1.52%?
Developed land can contain lawns, trees, yards, and other permeable surfaces along with buildings and roads. Impervious cover isolates hard surfaces such as rooftops, pavement, and parking areas. Only 0.32% of the county is mapped at 50% or greater impervious surface, so the hardest surfaces are highly concentrated.
Does the 27.52% class difference equal the area that physically changed?
No. The 27.52% value is the share of cells classified differently in the 1985 and 2025 comparison. Listed components include 1.80% to developed, 11.11% forest loss, 2.87% agricultural loss, and 11.42% other difference. Classification variation may be included, so specific causes require additional evidence.
Wetlands matter locally, but land cover is not the same as regulation
Union County’s comprehensive plan includes policies requiring new development and mining activity to maintain the natural functions of wetlands and 100-year floodplains. It also gives special attention to parts of the Santa Fe River floodplain. That official planning context shows that wet areas are an important local concern, which is consistent with wetlands occupying 25.78% of the supplied land-cover summary.
The planning policy does not turn every teal raster cell in this article into a legal wetland boundary. Land cover describes what physically covers the ground as classified from remote sensing. Regulatory wetlands, floodplain boundaries, zoning, ownership, and development rights are separate questions that require official planning, survey, and site-specific information.
Union County Planning & Development separately maintains the Comprehensive Plan, land-development regulations, and a zoning atlas. The existence of those resources is a useful reminder that a land-cover map should not be used as a substitute for legal land-use information. This map set is strongest for county-scale environmental and landscape comparison.
Choose the map according to the question rather than treating all four as interchangeable
The 2025 overview is the best starting point for a county profile. It shows forest, wetlands, agriculture, developed land, grassland, shrubland, and water together and makes the north-center forest pattern and southern agricultural concentration easy to compare. For a lesson, one useful exercise is to ask where agricultural colors become more common and where wetlands interrupt the forest.
The forest-and-farmland view works better when the focus is working land and vegetation. The impervious map is the stronger choice for development intensity because it isolates hard surface. The change map should usually come after the current views, because its colors represent differences between 1985 and 2025 rather than the present-day surface.
For comparisons with other Florida counties, use the same observation year and classification system whenever possible. Mixing a 2025 Union County value with an older value from another county can blur the difference between geography and time. The two-date change map is also not an annual history; a location could change more than once between 1985 and 2025 without those intermediate steps appearing.
Raster cells and the 2480×1754 JPG size limit parcel-level interpretation
Annual NLCD is raster data. The landscape is divided into grid cells, and each cell receives a representative land-cover class. A real cell can contain trees, crops, grass, pavement, buildings, standing water, and bare soil at the same time. The map simplifies that mixture to reveal broad patterns. Small forest edges, wetland boundaries, field margins, and narrow roads therefore should not be read as survey-accurate lines.
The original JPG maps in this package are 2480×1754 pixels each. Enlarging them can make small patterns easier to see, but it cannot create new source detail. The asset manifest does not mark the files as meeting the package’s A3 high-resolution reference. They remain useful for screens, presentations, ordinary handouts, and county-scale comparisons, while very large printing should be checked at the intended output size.
Map File Information
This ZIP contains the four original JPG maps used to compare 2025 land cover and related themes across Union County.
- Included Files: Use only the versions confirmed in the article and supplied images
- File Type: Use the confirmed download contents
- Intended Use: Printing, education, presentations, and map-based projects
Related Maps
- Alachua County Florida Land Cover Map
- Baker County Florida Land Cover Map
- Bay County Florida Land Cover Map
Sources and Reference Data
- MRLC Annual NLCD Data – annual land-cover data used for the 2025 and two-date comparison views.
- USGS Annual NLCD Land Cover Classification – definitions for forest, wetland, agricultural, developed, and other mapped classes.
- U.S. Census Bureau TIGER/Line Shapefiles – official county-boundary reference for Union County.
- UF/IFAS Extension Union County – official local agriculture, horticulture, and natural-resource education.
- Union County Planning & Development – official comprehensive planning, development regulation, and zoning resources.
Green Map creates custom-edited map images using open geographic data sources such as geoBoundaries, Natural Earth, OpenStreetMap, and government open data.
These maps are edited visual materials, not raw data files, and are provided for education, documents, presentations, and graphic reference.
