## 3 Results
### Transfer Probability Diagram  
Figure 5 is the result of the self- and cross-transiograms of each land cover type. The type is indicated by a code, and the specific meaning is shown in Table 1.  
For the cultivated land, the curve was more tortuous as shown in Figure 5a. The self-transfer (cultivated land with itself) and cross-transfer (with the other four categories of forest, grassland, wetland, and water body) probabilities of the forest were the highest, wetland were lower than forest, water body were lower than wetland, and grassland were basically 0. This finding was due to the scattered distribution of grassland. The transfer probability map results were consistent with the results of expert interpretation. Figure 4: IM0104 Geo-eco zone digital evaluation model (DEM). Figure 3: Demonstration area of (**a**) Globeland30-2015 and (**b**) interpreted sample points distribution map. The forest had the largest proportion, thus its self-transfer probability was higher than those of the four other categories as shown in Figure 5b. The transfer probabilities of the wetland and the water body were lower than the autocorrelation transfer probability of the forest. The conversion relationship from the cultivated land to the grassland and the forest almost did not exist, because the area of these two categories was relatively small. This finding was consistent with the results of expert interpretation. In Figure 5c, the distribution of the grassland was scattered, thus the curve of the transiogram was very tortuous and not as smooth as those of the other categories. Generally, the cross-transfer probability of the grassland and the cultivated land was almost 0, and the short-distance cross-transfer probabilities of the forest land, the water body, and the \begin{table}
\begin{tabular}{c c c} \hline \hline
**Color** & **Code** & **Land Cover Type** \\ \hline  & 10 & Cropland \\  & 20 & Forest \\  & 30 & Grass \\  & 40 & Shrub \\  & 50 & Wetland \\  & 60 & Water \\  & 80 & Artificial \\  & 90 & Bareland \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Land cover types and codes. Figure 5: Transiogram models (**a**) cultivated land-others; (**b**) forest-others; (**c**) grassland-others; (**d**) wetland-others; (**e**) water-others. wetland were similar. The long-distance cross-transfer probability of the forest was higher than that of the other categories because the proportion of the forest was the largest. As shown in Figure 5d, the curve of the wetland was relatively smooth. As the distance increased, the probability of the conversion of the wetland to the forest gradually increased. The probability of the conversion of the wetland to the water body was lower than that of the forest. Almost no conversion relationship was observed in the cultivated land and the grassland. In addition, the wetlands and water bodies always appeared together, and this finding was consistent with our common sense that wetlands always form around water bodies. The shapes of the autocorrelation transfer probability curve and the cross-correlation transfer probability curve of the water body were similar to those of the wetland by comparing Figure 5d,e. As distance increased, the probability of the conversion of the water body to the forest increased gradually. The probability of the conversion of the water body to the wetland was less than that of the forest. Almost no conversion relationship was observed in the cultivated land and the grassland. In addition, wetlands and water bodies always appeared together, wetlands always formed around water bodies, thus their transfer probability curves were very similar. In general, each category had the highest probability of conversion to forest, because the proportion of forest was relatively large. In addition, the forest, wetland, and water sample points were rich, the transfer probability curve was stable, and the credibility was high. Although the curve of cultivated land was not smooth enough, the transiogram model was reliable because of its concentrated distribution.