**4. Discussion**

*4.1. Mapping Landscape with Small Biotopes*

The heterogeneous character of the landscape (mosaic) and the influence of the spatial arrangement of the composing patches of many ecological processes have been recognized [7,9,58]. As shown in Figure 5, this reflects that the ecotones shapes formed a more complicated landscape. However, ecotones are essential components of heterogeneity, which are usually ignored in traditional landscapes. The agricultural ecosystem of the Baijixun sample plot has been abandoned for more than ten years and has been transformed into grassland, with the surrounding forests showing the trend of expansion. Ecotones are growing around the boundary between the abandoned land and forests. It has created the considerable potential for species exchange and materials flux between the forests and abandoned land [56,59,60]. It also indicates that the interaction between the forests and grassland ecosystems is more robust in the ecotones. This would better reflect the process and progress of ecological restoration after the implementation of RFFP. As mentioned above, the RFFP policy has played a significant role in land cover transitions [16,61,62], as well as the ecological processes that are responsible for the spatial distribution of species [18]. However, the conventional landscape pattern without ecotones derived from remote sensing image data generally ignores the gradual transition zones between different landscape units or patches [63,64]. This is also why we conduct a two-step data validation, because the shrunken-based detection method relies on highly accurate land cover mapping, and our validation clearly meets this need (Table 1). The experience based on field investigation provides reliable verification object for verification work. Note that this result is also imaged by OBIC. It also means that the forest and vegetation transition processes caused by the RFFP policy could also be ignored when the landscape or land cover without ecotones maps are used. In this study, the findings revealed the landscape pattern of all ecotones within the sample plot, which facilitated the concurrent measurement of the spatial patterns of ecotones. With continuous investigation and monitoring, it is believed that it will be possible to gain an improved understanding of the entire ecological process of agricultural abandoned land restoration.

### *4.2. Canopy Height Model*

At the aspect of CHM modeling, the point cloud data derived from photogrammetry is used to extract ground points supported by the result of OBIC from the high-resolution orthoimage. The terrain elevation of the unknown region is predicted by using geostatistics (Figure 4). It should be emphasized that this is still a model for prediction based on geostatistics, although this approach has achieved some results in our study. The success of the experiment depends on the topographic heterogeneity of the predicted area and the spatial configuration of the ground points that may be extracted. Moreover, according to the cross-validation results, we found that regardless of the statistical model, the prediction of variability is generally underestimated (Table S2). It reflects the possibility that the fluctuation of topographic heterogeneity on the fine scale is beyond the prediction ability of geostatistical models. Therefore, it may be more effective to restore the changes of terrain elevation at a large scale, as this increases the probability of obtaining effective ground points. It reflects the feasibility of the technology to monitor the landscape with ecotones under the influence of the policy of RFFP.
