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 LPT map considers one scale, three general cover types, and arbitrary rules for classifying LPTs.
Wickham and Norton (1994) define landscape pattern types and illustrate a vector-based method that was modified here for raster maps.
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, agriculture, and urban classes by using the following scheme:
Original MRLC class Forest/Agriculture/Urban 11: open water missing 12: perennial ice/snow missing 21: low intensity developed urban 22: high intensity residential urban 23: high intensity commercial/industrial urban 31: bare rock/sand/clay forest 32: quarries/strip mines/gravel pits urban 33: transitional barren missing 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) agriculture 71: grassland/herbaceous forest 81: hay/pasture agriculture 82: row crops agriculture 83: small grains agriculture 84: bare soil agriculture 85: other grass (lawns, city parks, golf courses) urban 91: woody wetland forest 92: emergent herbaceous wetland forest
A 590.49 ha (81x81 pixel) quadrat was centered on each pixel of the original land cover map. The numbers of forest (F), urban (D), and agriculture (A) pixels were tabulated for the non-missing pixels in the window. The index was then computed by the following rules:
Let F, D, and A be the proportions of forest, developed, and agriculture respectively, in a given window (excluding "missing" pixels). Assign "missing" value if the total area of A, D, and F is less than 1/4 of the quadrat. Otherwise, define LPT by the following algorithm: if F >= 0.6 if D > A if A >= 0.1 then LPT = 15 break else if D >= 0.1 then LPT = 9 break else if D >= 0.1 then LPT = 14 break else if A >= 0.1 then LPT = 8 break else LPT = 3 break else if A >= 0.6 if D > F if F >= 0.1 then LPT = 10 break else if D >= 0.1 then LPT = 4 break else if D >= 0.1 then LPT = 11 break else if F >= 0.1 then LPT = 5 break else LPT = 1 break else if D >= 0.6 if F > A if A >= 0.1 then LPT = 13 break else if F >= 0.1 then LPT = 6 break else if F >= 0.1 then LPT = 12 break else if A >= 0.1 then LPT = 7 break else LPT = 2 break else if A >= 0.1 if D >= 0.1 if F >= 0.1 then LPT = 19 break else LPT = 16 break else if F >= 0.1 then LPT = 17 break else LPT = 18 break /* fall-through, set to missing*/ LPT = 0 break
Note the algorithm assigns LPT's by looking at the proportions of A, F, and D in relation to the breakpoints of 60% and 10%.
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 are in the range [0,19] 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.