To some degree, landforms influence the distribution and evolution of ecology and other environmental factor, which is the core and the basic content of geography [1]. Landform morphological classification is the basic unit of landform, and also the first step in solving geomorphic problems. The landform classifications of large scale were started in 1950 in China. In 1956, the 1:4,000,000 Landform Classifications and Region Planning Map of China, according to the altitude and surface cutting degree (Table 1). In 1979, the Mapping Standard of 1:1,000,000 Landform Classifications in China were completed, and classified the landform types with the altitude, relative altitude and the surface cutting degree, according to the classification schemes of З.A.Cварицевская (1975). Until 1989, only 15 sheets landform maps (1:1,000,000 scale) were completed. This mission was suspended for a long time. Until 2009, the 1:1,000,000 scale landform atlases of whole China is accomplished [2]. The two landform classifications schemes above, is based on manual process.

The 1:40,000,000’s scheme is based on forms and exogenic forces, and many parameters are not quantitative. There were many quantitative factors is introduced into the 1:1,000,000’s scheme, such as altitude, local relief, and slope. The local relief is classified into 4 classless, less than 500 m is low relief hills; 500 - 1000 m is moderate relief hills, 1000 - 2500 m is high relief mountains and more than 2500 m is very high relief mountains [3]. There are also some papers adopted local reliefs but different classes in whole China’s landform scheme. Cai Zongxin (1986) classified grade into 5 classes, less than 20 m is plains; 20 - 200 m is hills, 200 - 500 is low mountains, 500 - 1500 m is middle mountains and more than 1500 m is high mountains (Table 2) [3]. Tu Hanming et al. [4] classified local relief of China into 7 classes based on the statistics of samples from whole China’s DEMs. In 2009, Zhou Chenghu et al., classified the landform of China into 7 types and 25 classes, according to slope, relief and altitude (Table 3).

In 1990’s, there are some scholars contributing to extracting the single landform parameters in China, such as ridge line and valley line [5] [6] [7], summit [8], shoulder line of valleys [9] [10], micro topography [11]. All above are based on the regions of simple landforms evolutions. There are many limits to automatically whole China’s landform classifications. Liu Aili et al. (2006) [12] attempted to automate classify the landforms of whole China based on image classifications methods. But the sampling cell is 1000 m × 1000 m, which is coarse enough to omit many small landform units.

In this paper, we classified the landform of whole China in Hammond’s scheme according of slope, local relief, and profile type [13] [14]. We compare the result with and the scheme by Zhou Chenghu et al. (2009) [2]. The computer-program is based on the approach developed by Dikau et al. [15]. In order to compare with the international landform maps, the parameters of Hammond’s scheme are kept unchanged.

This automated process was tested on almost whole China, which consists of mainland, Hainan and Taiwan islands. The data includes 816 sheets of topological map with a scale of 1:250,000, which were digitalized by National Geometrics Center of China in 1998. The content consists of 14 layers: hydrological system, Residential, Railway, Road, boundary, Terrain, and some auxiliary ones. The terrain data include contours and mark point, and the contours interval is 50 or 100 m.

The maps were constructed respectively with 5 types, 16 classes and 90 subclasses (Table 2, Figure 2, Figure 3). The whole area of China is 9482552.72 km² besides some small island were not calculated. The 5 Landform types of landforms were Plains (PLA), 20.25% of whole areas; Tablelands (TAB) of 3.56%; Plains with Hills or Mountains (PHM) of 32.84%; Open Hills and Mountains (OHM) of 18.72%; Hills and Mountains (HM) of 24.63%. The PLA were located in Songnen Plain, Sanjiang Plain, Huabei Plain, Huaihai Plain, Jianghai Plain, Aletai Basin, Talimu Basin, Loess Plateau, etc. The TAB were scattered in whole China, which each patch is small. The PHMs were located in Xiao-Xing’anling Mountains, Shandong peninsula, Inner-Mongolian, Qinghai-Tibet Plateau, Sichuan Basin, Guangxi and Hunan province. The OHM were located in Da-Xing’anling Mountains, Shaanxi province, Guizhou province and scatted in North of Tibet Plateau. The HMO is located in East of Tibet Plateau, around the Sichuan Basin, Yunnan, Fujian Taiwan province. The result indicates it produced a classification that has good resemblance to the landforms in China.

Some classes were not generated, such as irregular plains and low hill. The PLA is primary flat or smooth without some relief. The altitude in hill or mountain region is high, so there are almost not low hill.

According to Hammond’s scheme, the area of TAB is only 3.56%. The area of tableland in some manual scheme is much more than that [19]. There are several large tablelands, such as Qinghai-Tibet Plateau, Mongolia Plateau, Loess Plateau,

Yun-gui Plateau. In Figure 2, Qinghai-Tibet Plateau is mainly classified into PHM; Mongolia Tableland and Loess Tableland is classified into PLA or PHM and the Yun-gui Tableland is classified into HMO. There are many hills or mountains in tableland in China . The basin is basically classified into PLA, but the Sichuan Basin is mainly classified into PHM or PLA.

Automated landform classification produced a classification that has good resemblance to those of manual approach. However, some classes are different from manual method. There are much more complex landform in China, and the geomorphologic evolution is much more different, so it needs to improve the method to classified more reasonable. Furthermore, the effects of scale and generalization also should be paid special attention.

The author declares no conflicts of interest regarding the publication of this paper.

Ye, B.Y. (2020) Automated Landform Classification of China Based on Hammond’s Method. Journal of Computer and Communications, 8, 23-30. https://doi.org/10.4236/jcc.2020.86003