Caveats include: Maps in this series are naturally correlated since all came from one map. No warranty or claim is made of the utility of this map for any particular purpose, this is considered to be a research dataset. The forest area density map portrays relative area density, considering only forest versus non-forest cover types.
Land cover data (MRLC) was obtained from EROS Data Center in binary format.
The image was subdivided into sixteen (16) overlapping rectangles using an in-house software tool named SPLITTER.C. The rectangles overlapped to avoid artifacts near image boundaries during the spatial filtering operations.
Each of the rectangles was then processed via spatial filtering to estimate the index as described below. The spatial filtering program is an in-house software tool named SPATCONV.C (Riitters et al. 1997)
After spatial filtering, a map of index values was constructed by reassembling the 16 rectangles into a single image (via an in-house software tool named LUMPER.C, which removed the overlapping parts of rectangles).
The "header file" information for the derived map is as follows. This information is needed for some image import filters. Ulxmap and Ulymap refer to the center of the upper-left pixel. nrows 13240 ncols 13265 nbands 1 nbits 8 layout bsq skipbytes 0 ulxmap 1154670.000000 ulymap 2064600.000000 xdim 30.000000 ydim 30.000000
Spatial filtering proceeded as follows.
Pixels were re-classified into forest and non-forest classes by using the following scheme:
Original MRLC class Forest/non-forest class 11: open water missing 12: perennial ice/snow missing 21: low intensity developed non-forest 22: high intensity residential non-forest 23: high intensity commercial/industrial non-forest 31: bare rock/sand/clay non-forest 32: quarries/strip mines/gravel pits non-forest 33: transitional barren non-forest 41: deciduous forest forest 42: evergreen forest forest 43: mixed forest forest 51: deciduous shrubland forest 52: evergreen shrubland forest 53: mixed shrubland forest 61: planted/cultivated (orchards, vineyards, groves) non-forest 71: grassland/herbaceous non-forest 81: hay/pasture non-forest 82: row crops non-forest 83: small grains non-forest 84: bare soil non-forest 85: other grass (lawns, city parks, golf courses) non-forest 91: woody wetland forest 92: emergent herbaceous wetland non-forest
A 590.49 ha (81x81 pixel) quadrat was centered on each pixel of the original land cover map. The numbers of forest and non-forest pixels were tabulated for the non-missing pixels in the window. The index was then computed as the number of forest pixels, divided by the sum of numbers of forest and non-forest pixels. This yields a value of 0 when no forest pixels are present, and a value of 1 when all non-missing pixels in a window are forest.
If the center pixel was "missing" in the land cover map, then the index was assigned a "missing" value. Note that the index is defined for all other land cover types.
The calculated values were discretized to the range [1,255] and stored at 30-meter spatial resolution. Thus, a pixel value in the new map represents the index for the surrounding 590.49 ha in the original land cover map.
The transformation used to discretize the values was: D = ( C * 254 ) + 1 where D = discretized value in range [1,255] C = calculated value in range [0,1] If needed, the original calculated values can be approximated by applying the backtransformation: C = ( D - 1 ) / 254 The backtransformed values will be in steps of size approximately 0.00394 as a result of the discretization process.