TABLE 26 - Rating system for land degradation assessment (after FAO,1979) - soil erosion by water

TABLE 27 - Rating system for land degradation assessment (after FAO,1979) - degradation by wind erosion

TABLE 28 - Rating system for land degradation assessment (after FAO,1979) - based on indicator variables of biological degradation

TABLE 29 - Ratings for evaluating physical land degradation - based on values of indicator variables for compaction and crusting

TABLE 30 - Calculated current risk for each type of degradation

TABLE 31 - Calculated state of present land degradation (e.g.Texcoco River Watershed,Mexico)

TABLE 32 - Degradation classes for Texcoco watershed by sampling quadrats

Using the ratings provided by FAO (1979), it was possible to classify the values into classes that reflect the degree of affectation by a given factor causing degradation of the land. The classes were given categorical names for communication purposes. The classes and their meaning are:

• 1 = none to slight,

• 2 = moderate,

• 3 = high/severe,

• 4 = very high/severe.

As an example of such a classification, Table 32 shows degradation classes by land degradation type in one of the case study areas.

Mapping land degradation

Upscaling quadrat sampling assessments

Once the status of land degradation at each quadrat sampling site has been assessed and the classification for each quadrat completed upscaling the assessment in terms of degradation class, applicable to the entire land cover polygon, becomes a spatial interpolation/extrapolation exercise again. The starting point is point samples within a framework of polygons (vector format) or classes of pixels (raster format) mapping.

In addition to the problem of assigning to a polygon a single rating from a possible number of ratings from more than one site in the polygon, there is the problem of dealing with assessments for several individual indicators of processes and types of degradation at a given site. Therefore, the problem is a multivariate problem in the sense that it requires consideration of the multiple types of degradation indicators to be combined into one single rating. This rating should convey, in a synthesized fashion, the complete status of land degradation for a given location.

Wherever possible optimal spatial interpolation techniques (i.e. the various forms of kriging, splines, etc.) should be attempted. However, their major constraint is the large number of sampling sites (data points) required for reliable interpolation. A conservative approach can solve both the multivariate and the upscaling problems.

In order to combine the various degradation assessments for a given mapping unit (land cover classes or LUT) into one rating or symbol, it could be decided that, for land cover classes or LUTs polygons containing more than one sampling quadrat, the rating of the quadrat site with the highest classification for each land degradation process be assigned. That is to say, it is preferable to portray in map form for a given polygon the class of the quadrat site with the highest degree of degradation and assign it to the entire polygon. This is also a form of spatial interpolation. The approach is precautionary and conservative in the sense of preferring to reflect the “worse case” scenario in terms of intensity and type of land degradation. By way of example, Table 33 shows the level of degradation affecting each land cover polygon modelled in the case study of the Texcoco watershed, Mexico.

A table of classes as shown in Table 33 can be useful for attributing the values of the class (i.e. degradation intensity) by type of degradation process (i.e. the columns in the Table 33, which are attributes of polygons in a map) to polygons in a map where the spatial representation of each type of land degradation can be made by means of the GIS. Figure 27 shows an example with the mapping of soil erosion by wind, as a process of physical degradation type.

Mapping land degradation by types of degradation

In order to obtain a map of land degradation by type, which integrates all ratings of degradation by indicators and processes within a given land degradation type into a single map, the “maximum limitation” method is adopted. This method consists of combining ratings of land degradation processes into a single rating by land degradation type, by selecting the rating that is the most severe among the degradation indicators and processes to achieve measures of total physical, chemical and biological degradation. To illustrate, Table 34 shows the results for total physical, chemical and biological degradation across the studied area (e.g. the Texcoco watershed). The spatial representation of such a table can be seen in terms of three land degradation maps (by type) and their corresponding compound symbology in Figure 28. Maps of this kind constitute one of the main outputs of the assessment.

TABLE 33 - Land degradation process classification by land cover polygon

TABLE 34 - Results of applying the maximum limitation method on land degradation for the Texcoco watershed by land cover class polygon

FIGURE 27 - Physical degradation - soil erosion by wind

FIGURE 28 - Maximum limitation classification of land degradation by land cover class for physical,chemical and biological degradation