Coffee County Alabama Land Cover Map: Northern Forest and Southern Farmland

Coffee County’s 2025 land-cover pattern is defined by contrast rather than a single uniform landscape. Forest occupies 39.62% of the county and is especially prominent across the northern half, while agriculture accounts for 28.47% and becomes much more visible toward the south. Two developed concentrations also stand out: a larger one in the east and a smaller one in the west, set within a broad mix of forest, farms, wetlands, grass, and shrub cover.

The page separates that pattern into four views: current land cover, forest and farmland, impervious surface and developed land, and the 1985–2025 class comparison. Each map appears as a WebP preview in the article, and the four original JPG files are available together in one download. The set works well for county reference, environmental classes, presentations, landscape comparison, and projects that need a consistent county outline across several themes.

Two developed centers stand out inside a mostly rural county

The impervious-surface map is a useful place to begin because it quickly locates the most built-up parts of Coffee County. Most of the county is nearly white, indicating little or no hard surface at the 30-meter cell scale. In contrast, a dense orange-red concentration appears in the eastern part of the county and a smaller concentration appears farther west. Thin lines extend away from both clusters, while scattered dots and short segments occur elsewhere. This creates a clear pattern of localized hard surfaces rather than continuous urban cover.

Coffee County reports a mean impervious value of 1.93%, and only 0.77% of the county falls in cells with at least 50% impervious surface. Developed land, however, represents 9.95% of the 2025 land-cover summary. Those numbers answer different questions. A developed land-cover cell can contain roofs and pavement along with lawns, trees, soil, and other surfaces that still absorb water, so developed cover will normally be larger than the fraction measured as impervious.

The county’s official history provides useful geographic context for the two clusters. Elba remained the county seat, while an eastern branch of county government was established in Enterprise in 1907; Coffee County still maintains courthouses in both places. The large eastern concentration on the map is consistent with the Enterprise area, and the smaller western concentration is consistent with Elba. The map itself does not label streets or buildings, however, so individual red cells should not be assigned to a specific facility or parcel.

Impervious mapping can help with watershed teaching, development comparison, or deciding where more detailed drainage data may be worth examining. It should not be treated as a flood-risk map. Storm intensity, terrain, soils, drainage infrastructure, stream connections, and floodplain position all matter when evaluating runoff or flooding. Here, the map’s strongest contribution is simply showing where hard surfaces are concentrated and how limited those concentrations are compared with the county’s much larger forest and agricultural areas.

Forest is stronger in the north, while farmland expands across the south

The forest-and-farmland view removes much of the complexity of the full legend and makes the north–south contrast easier to see. Dark green forest forms larger and more connected areas across the northern half. Cropland and pasture or hay appear there too, but usually as smaller patches within or beside the forest. Moving south, yellow cropland and light-green pasture become much more common, and forest is divided into narrower blocks and strips in many places.

Agriculture is summarized at 28.47%, but that figure should not be read as the acreage of legally defined farms or taxed agricultural parcels. It is a land-cover classification derived from mapped surface conditions. The simplified map is especially helpful because cropland and pasture/hay can be distinguished visually, while shrub and grass, wetlands, water, and developed/other remain separate. That makes it possible to see where several open-cover classes occur together without pretending that they represent the same category.

Wetlands are another important part of the county pattern. They account for 12.01% of the 2025 summary and appear as branching teal features and irregular patches through both forested and agricultural areas. In the southern half, wetland cells repeatedly break up cropland and pasture. Their shape can be useful for broad landscape or watershed context, but a 30-meter land-cover product cannot replace a detailed wetland delineation, stream survey, or floodplain map.

For habitat or landscape lessons, the size and continuity of forest patches may be more informative than the countywide percentage alone. The north contains broader green areas, while the south shows more frequent edges between forest, crops, pasture, wetlands, and shrub/grass cover. That observation can guide questions about fragmentation or land-cover diversity, but the map does not directly measure habitat quality, ownership, management intensity, crop type, or agricultural productivity.

The full 2025 map puts all major cover classes back together

In the full land-cover summary, forest leads at 39.62% and agriculture follows at 28.47%. Wetlands make up 12.01%, developed land 9.95%, shrubland 4.59%, grassland 4.55%, and open water 0.72%. Barren land is present in the legend but is visually limited. Taken together, the numbers confirm what the map shows: Coffee County is neither overwhelmingly forested nor overwhelmingly agricultural, and developed land remains concentrated within a broader rural landscape.

The northern half contains more continuous green forest, especially along the upper boundary and northwest portion. Agricultural yellow becomes more frequent through the center and expands across much of the southern half. Teal wetlands weave through both. The eastern developed area is large enough to remain visually obvious even on a countywide map, while the western developed area is smaller but still distinct. Smaller red traces extend along transportation-shaped corridors between and around these concentrations, though the map does not identify the roads by name.

This map is best used for orientation. A reader can first identify the largest cover classes, then compare their location with the more specialized maps. Red developed cells can be checked against the impervious view; green forest and agricultural yellow can be simplified in the forest-and-farmland view; areas of current cover can then be compared with the class-difference map. Because every image uses the same county boundary, the user can move from one question to another without having to relocate the same area each time.

Land cover is not zoning, ownership, or legal land use. A green cell indicates a surface classified as forest, not that the land is public forest or protected. An agricultural cell does not establish a farm boundary, tax classification, or development right. A developed cell does not define a municipality or building-permit jurisdiction. Coffee County’s Mapping & Appraisal office maintains separate parcel-oriented GIS information, which is the more appropriate source when property location or administrative boundaries matter.

The 1985–2025 comparison records class differences, not a single change rate

The change map reports that 39.42% of Coffee County has a different mapped class in 2025 than in 1985. Within that total, 2.70% is shown as classified to developed, 8.46% as forest loss, 5.65% as agricultural loss, and 21.59% as other class difference; wetland difference is also represented as its own legend category. The total therefore cannot be described as 39.42% development, forest loss, or agricultural conversion. It is a combined class-comparison measure.

Orange forest-loss cells and purple other differences are widely scattered across the county, while yellow agricultural-loss areas also appear in many locations. Red cells classified to developed are more noticeable around the current eastern and western developed centers and along some linear patterns, but they do not dominate the map. This is a useful reminder that a place can have substantial class differences over four decades while still having a relatively low countywide impervious average today.

A cell labeled forest loss should not automatically be interpreted as permanent deforestation. The class in 2025 differs from the 1985 forest class, but the map does not explain the process that produced the difference. Timber harvest and regrowth, vegetation stage, agricultural change, development, image conditions, and classification behavior can all require further investigation. Annual NLCD’s year-by-year products, aerial imagery, field records, or management data are better tools for examining the history of a specific location.

The map also warns that differences may include classification variation. At 30-meter resolution, edges between crops, forest, wetlands, grass, and developed surfaces can shift between classes even when the real-world boundary is narrow or mixed. For that reason, this map works best as a screening layer that highlights where to look more closely. It does not provide an exact date of change, a legal record of land conversion, or a parcel-level history.

A practical way to compare the four maps

One simple workflow is to use the two developed centers as anchors. Find the eastern and western red concentrations on the full land-cover map, then move to the impervious map to see which parts of those developed areas contain the strongest hard-surface values. Next, switch to the forest-and-farmland view to understand the rural cover around the same locations. Finally, use the class-difference map to see whether those cells were recorded in the same or a different class at the two comparison endpoints.

A second workflow is to compare north and south. Northern Coffee County has larger forest blocks in 2025, while the south contains more agricultural cover and more frequent boundaries among farms, forest, wetlands, and open classes. The change map adds a different question: not what dominates now, but where 1985 and 2025 classifications differ. Keeping those questions separate prevents a current land-cover pattern from being mistaken for a historical trend.

For county-to-county comparisons, match the variables as carefully as possible. Coffee County’s 39.62% forest figure should be compared with another county’s 2025 forest value, and its 1.93% mean impervious value should be compared with the same impervious metric for the same year. The 39.42% class-difference figure is most meaningful beside maps using the same 1985–2025 endpoints. Differences in year, spatial resolution, or classification rules can otherwise look like geographic differences when they are really data differences.

Download the four original JPG maps

The downloadable ZIP contains four JPG files: the 2025 land-cover map, forest-and-farmland map, impervious/developed-land map, and 1985–2025 land-cover class comparison. Each JPG is 2480×1754 pixels, while the WebP previews used in the article are 1800 pixels wide. The previews are convenient for quick reading on the page; the original JPGs are better suited to documents, slides, classroom handouts, and side-by-side map layouts.

The asset manifest does not mark these JPGs as meeting an A3 high-resolution reference. They can still be useful for normal screen use and moderate-size printing, but a large poster should be test-printed before final production so the legend and small labels can be checked. Enlarging the image dimensions also does not increase the underlying 30-meter land-cover detail. Image resolution and the spatial resolution of the source data are separate issues.

When presenting the set, label each image by year and purpose. The 39.62% forest value belongs to the 2025 current-cover summary, the 1.93% value is the countywide mean impervious surface, and 39.42% is the 1985–2025 class-difference total. Keeping those labels visible makes it much harder for readers to confuse a present-day percentage with a long-term comparison statistic.

What the 30-meter data can and cannot tell you

Annual NLCD is a raster product, meaning the landscape is represented as a grid of cells rather than parcel polygons. The Annual NLCD product suite uses 30-meter spatial resolution. A single cell can contain trees, grass, a narrow road, a roof, soil, or water at the same time, even though it receives a representative class or fractional impervious value. Zooming in makes the pixels appear larger; it does not reveal smaller features that were never resolved by the source product.

Mixed cells are especially important along the edges of farms, wetlands, forest patches, and developed areas. A narrow stream may be partly represented by wetland or adjacent vegetation, and a small building may not create a distinct developed cell by itself. This generalization is acceptable for countywide mapping, where the goal is to understand broad patterns, but it is not appropriate for surveying a property boundary, measuring a small wetland, locating a single structure, or making a permit decision.

The observation year is another limitation. The current maps describe the 2025 classification, so construction, harvesting, regrowth, or agricultural changes that occurred later may not appear. The change map compares the two endpoints 1985 and 2025 and therefore cannot describe every intermediate transition. A cell might have changed more than once during the period, which is why Annual NLCD time-series data or historical aerial imagery is preferable when the timing of change matters.

Used within those limits, the four-map set gives a compact overview of Coffee County. It shows the stronger northern forest pattern, the more agricultural south, wetlands distributed through both, the Enterprise- and Elba-area hard-surface concentrations, and the locations where the two endpoint classifications differ. Those observations can then guide a more detailed search in parcel maps, stream data, elevation models, planning records, or field information when a project needs greater precision.

Frequently Asked Questions

Related Maps

• Autauga County Alabama Land Cover Map
• Baldwin County Alabama Land Cover Map
• Barbour County Alabama Land Cover Map

Sources and references

• MRLC Annual NLCD Data – Official access to Annual NLCD land-cover and related products.
• USGS Annual NLCD Collection 1.2 Land Cover – USGS documentation for the 30-meter annual land-cover product series, including the 2025 temporal extent.
• U.S. Census Bureau TIGER/Line Shapefiles – Federal boundary data used for county geography and mapping reference.
• Coffee County History – Official county history explaining the Elba county seat, the Enterprise branch of government, and the county’s two courthouses.
• Coffee County Mapping & Appraisal – Official description of Coffee County’s parcel-oriented GIS mapping and appraisal functions, useful for distinguishing land-cover mapping from property mapping.