Mapping from Surveys

The surveys are based on informed opinion, on the analysis of the loss of the original profile, and on maps in which the soil erosion features found in the landscape are plotted.

Surveys involving informed opinion have been developed by using published research on the area of interest. For example, informed opinion was used in the Global Assessment of Soil Degradation (GLASOD) for producing a 1:1,000,000 world map showing the extent and severity of various types of soil degradation including erosion by water, wind, and mass movement [76].

According to Morgan [76], one of the best examples of surveys involving informed opinion is the soil erosion map of western Europe developed by De Ploey [77], using the published research of many European scientists. In particular, the water soil erosion map shows the areas with arable land use having a mean annual soil loss greater than 10 t/ha.

Surveys of soil profiles are used for classifying areas using the percentage of eroded soil profile. For example, in the soil erosion map of Hungary, which is used for soil conservation policies, the following three categories of erosion are used: weakly eroded soils (less than 30% of the original profile has been lost), moderately eroded soils (30%-70%), and strongly eroded soils (>70%) [76].

Soil erosion mapping involves plotting the location of the areas of sheet, rill, and gully erosion; different types of mass movement using data from field surveys; and aerial photograph interpretation. If the available information is extremely detailed and difficult to interpret, the map can be simplified by categorizing the information in erosion severity classes. The main limit of a survey-based map is that it shows the situation for only one time period and gives no information about the rate of erosion [76]. The erosion survey maps become dynamic if the mapping work is repeated at regular time intervals using aerial photography or field survey data corresponding to different dates.

Soil erosion modeling is used for assessing the erosion risk of a given area. The potential risk can be evaluated by climate, soils, and morphological information. Land cover, land use, and management information also are needed for establishing the actual risk. To this aim, two main approaches can be used, one based on factorial scoring, which gives a qualitative assessment, and the other based on modeling, which gives a quantitative result.

Factorial scoring, applicable at different scales, allows the studied area to be divided into subareas for which the different factors affecting soil erosion have a numerical scale, for example, from 1 (low risk) to 5 (high risk). The factorial scoring system is simple and allows the consideration of all erosion processes and of qualitative influencing parameters like human activity [76]. Factorial scoring is based on both numerical and descriptive information. The numerical information is based on either at site measurement (soil erodibility and rainfall erosivity) or areal information (slope steepness and length, land use, and vegetation cover). The areal information can be obtained by topographic maps or digital terrain models (slope and length) and by analyzing remote-sensing images (land use and vegetation cover) [78, 79].

The descriptive information involves evaluating areas affected by different evolving phases of the erosion phenomenon. This last information is achieved by direct surveys or aerial photogrammetry.

All of the described data, having different sources, can be organized into different in-formatic layers of a geographical information system (GIS). The GIS database allows for the management of information and for the production of thematic maps, by overlaying the different layers.

Preliminarly, the studied area has to be divided into homogeneous areas of a given character (land use, slope, or aspect). Using a GIS, the subdivision of the area can be carried out automatically by a square mesh (grid format), which is useful for employing matrix calculus. In each square cell, a score is attributed to each factor that is considered. Overlaying allows for the automatic calculation of the total score of each cell and for its classification according to preestablished soil erosion classes (very low, low, moderate, or high). A map based on factorial scoring is not useful for evaluating the rate of soil erosion.

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