Annex 3A4 Overview of potential methods for developing Approach 3 datasets

Figure 3A.4.1 Overview of Approach 3: Direct and repeated assessments of land use from full spatial coverage

Description

Under Approach 3 the country is sub-divided into spatial units such as grid cells or small polygons. In this example grid cells are used for sub-division of the area. The grid cells may be sampled by remote sensing and/or ground survey, in order to establish the areas of the land use whose estimated extent is shown by the grey lines below the grid. Remote sensing can also enable complete coverage of all grid cells (Figure 3A.4.1A) in the interpretation of land use. Ground surveys can be carried out in a sample of grid cells and can be used to establish land use directly, as well as to help interpret remotely sensed data. The sample of grid cells can be distributed regularly (Figure 3A.4.1B) or irregularly (Figure 3A.4.1C), for example, to give greater coverage where land-use conversion is more likely. Generalised maps can be prepared using the grid cells, which can also be aggregated into polygons (Figure 3A.4.1D). The final result of the Approach can result in either a tabular or spatially-explicit land-use conversion matrix.

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Figure 3A.4.1A Remote sensing can also enable complete coverage of all grid cells.

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Figure 3A.4.1C The sample of grid cells can be distributed irregularly

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Figure 3A.4.1D Generalised maps can be prepared using the grid cells, which can also be aggregated into polygons

Figure 3A.4.1D Generalised maps can be prepared using the grid cells, which can also be aggregated into polygons

Note: F = Forest Land, G = Grassland, C = Cropland, W = Wetlands, S = Settlements, O = Other Land

When using Approach 3, inventory compilers should:

• Use a sampling strategy consistent with the advice provided in this chapter. This strategy should ensure that the data are unbiased and can be scaled up where necessary. The number and location of the sampling units may need to change over time in order to remain representative.

• Where remote sensing data are used, develop a method for its interpretation into land categories using ground reference data as set out in this chapter (Remote sensing techniques). Care should be taken to correctly assign land cover information obtained through imagery, into land-use category. Conventional forest inventories or other survey data can be used for this. It is necessary to avoid possible misclassification of land types and map accuracy established by means of ground reference or very high resolution remotely sensed data. The conventional technique is to establish a matrix5 showing, for any given classification of land, the proportion of misclassification as one of the other candidate classifications.

• Construct confidence intervals for those land category areas and changes in area that will be used in the estimation of carbon stock changes, emissions and removals.

• Derive summary tables of the national areas under different land-use conversion.

5 Sometimes called the confusion matrix.

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