This paper reviews the historical development of base maps used for soil mapping, and evaluates the dependence of soil mapping on base maps. Formerly, as a reference for spatial position, paper base maps controlled the cartographic scale of soil maps. However, this relationship is no longer true in geographic information systems. Today, as parameters for digital soil maps, base maps constitute the library of predictive variables and constrain the supported resolution of the soil map.
Tag: soil maps
This raster contains the natural, inherent, soil wetness of the lower 48 states, as determined by the ordinally based Natural Soil Drainage Index (DI). The DI is intended to reflect the amount of water that a soil can supply to growing plants under natural conditions. It ranges from 0 for the very driest soils and exposed bedrock, to … Continue reading Drainage Index Grid (conterminous U.S.)
This raster describes the inherent, soil productivity of the lower 48 states, as determined by the ordinally based Natural Soil Productivity Index (PI). The PI uses family-level Soil Taxonomy information, i.e., interpretations of taxonomic features or properties that tend to be associated with naturally low or high soil productivity, to rank soils from 0 (least productive) to 19 (most … Continue reading Productivity Index Grid (conterminous U.S.)
Soil Survey maps are the preeminent data set collected about our environment. Although there are other impressive data sets that are regularly used for studying and utilizing the environment, none match the wide utility and potential of soil maps. Recent innovations create opportunities to increase both the resolution and the efficiency at which Soil Survey maps are made.
We introduce, evaluate, and apply a new ordinally based soil Productivity Index (PI). The index has a wide application generally at landscape scales. Unlike competing indexes, it does not require copious amounts of soil data, for example, pH, organic matter, or cation exchange capacity, in its derivation. Geographic information system applications of the PI, in particular, have great potential. For regionally extensive applications, the PI may be as useful and robust as other indexes that have much more exacting data requirements.
The integration of soil survey maps with Geographic Information Systems (GIS) allows for an almost infinite level of collaboration across disciplines that use information related to soil databases. This study created a Quaternary geologic map by categorizing soil descriptions into a geologic context and joining the attributes with the Soil Survey Geographic (SSURGO) database in ArcGIS®. The resulting map communicates many of the spatial intricacies of the Des Moines Lobe landform with 15 map units based on geologic units.