2.5. Land Cover and Land Use Changes (LCLUC) and annual rate of soil erosion changes (2005 - 2015)
For LCLUC mapping (2005 - 2015), we utilized MODIS 1 km LCLU datasets which were reclassified at six IPCC LCLU classes. At the national scale, 2005 and 2015 LCLU maps were compared in terms of area. Like soil erosion change assessment, for LCLUC assessment we used a cross tabular or change matrix method between 2005 and 2015 in which, diagonal values show the stability of LCLU classes while LCLU loss (omission) and gain (commission) statistically and spatially. In the change matrices of soil erosion and LCLUC, the loss and gain values are vice versa.
The estimated annual soil erosion rates against six LCLU categories at seven administrative units of Pakistan were also reported for the identification of soil erosion prone areas where soil conservation practices and ground innervations can be implemented and monitored.
Bivariate analysis is one of the simplest forms of the quantitative analysis. It involves the analysis of two variables, for the purpose of determining the empirical relationship between them. In order to see if the variables are related to one another, it is common to measure how those two variables simultaneously change together (Nandi & Shakoor, 2010). In this study, at 5 km spatial resolution for bivariate analysis mapping, gain, loss and no change in annual soil erosion and LCLU between 2005 and 2015 were spatially plotted using three by three bivariate choropleth map legend.
The overall methodological flow is given in Figure 2.
3. Results
The results of annual soil erosion dynamics in Pakistan consist of two sections: (1) Soil erosion - RUSLE factors, (2) Soil erosion change assessment (2005 - 2015) and (3) Land Cover and Land Use Changes (LCLUC) and soil erosion changes (2005 - 2015).