## 2 Materials and Methods
### Materials  
Three significant years were selected for examining the changes in land transportation's _accessibility_ and _potential_. In 1964, water transportation in Anxin County began to decline. In 1996, the modern road network construction began and was essentially completed in 2008.  
Figure 1: Study area: (**a**) Map of the study area; (**b**) Administrative divisions and main highways in Anxin County; 1: Xushui-Anxin County Highway; 2: Baojing Provincial Highway; 3: Rongcheng-Lixian National Highway; 4: Baoding-Anxin Provincial Highway; 5: Gaoyang-Baoding Provincial Highway.  
Data for 1964 are from decllassified CORONA satellite images from September 21, 1964. Data for 1996 and 2008 are derived from Landsat satellite image acquisitions from 13 May 1996 and 21 June 2008. Because of the long time interval between 1964 and 1996, we also checked remote sensing (RS) images acquired on 29 May 1972 as a reference for this interval but do not include them in the subsequent centrality indices' calculation because of the insignificant differences from 1964. To calibrate RS images and scanned maps, Landsat OLI images from 9 May 2020 were selected as the standard base map. All RS images and historical maps were projected in the WGS84 coordinate system UTM50N projection. These image data and their parameters are shown in Table 1.  
The spatial data in this study can be divided into two categories. The first is point data representing villages (Figure 2). After interpreting settlement patches from historical RS images and performing collation and segmentation according to the village directory in the county annals [22], we used ArcGIS to convert these vector polygon features into point data. To calculate the weight of each village, quantitative data included population and per capita income derived from statistics in the county annals [22; 23] were assigned as attributes of the village point. The coverage areas of the villages' patches in the study years were automatically generated as attributes of the village points. In terms of geographical characteristics, the villages can be roughly divided into three types: water villages entirely surrounded by water, land villages located entirely on land, and semi-waterside villages located in water-land border areas. We only selected the latter two to build the village dataset, because they would be more affected by land transportation than those entirely on the water. The study also incorporates villages outside the county boundary into the original dataset to overcome the edge effect in spatial analysis. In total, 264 villages were included. The second category is the road network, which is represented as line data. Dikes were also digitalized and added to this dataset because they also serve as transportation routes. The road network is mainly derived from the vectorization of administrative maps in county annals of the studied year and supplemented by manual interpretation from remote sensing images.  
Figure 2: Point data of villages.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Year** & **Map Materials** & **Source** & **Scale/Resolution** & **Coordinate System** \\ \hline
1964 & & Declassified Corona Satellite Imagery & 3 m \(\times\) 3 m & None \\ \hline
1972 & & Declassified Corona Satellite Imagery & 3 m \(\times\) 3 m & None \\ \hline
1996 & & Anxin County Chronicle & 1:50,000 & None \\ \hline