A single-type landscape, as an important component of the landscape ecological system, is an abstract for the complicated landscape. The SHDI (Shannon's Diversity Index), typically used to describe the complexity of nonlinear system, consists of various components, measures the diversity and variability on spatial structure, functional mechanism and temporal dynamics. Because the single-type landscape cannot be described by SHDI, based on Shannon Entropy, a spatial distribution index MSHDI (Modified Shannon's Distribution Index) was proposed to address the spatial distribution division and breadth of single-type landscapes. Remote sensing technique can be used effectively to extract information of single landscapes, which directly represent their development. Using three Landsat images (May 4, 1990 by TM sensor, May 10, 2001 by ETM⁺ sensor and May 19, 2007 by TM sensor), this paper presents the quantitative comparison between MSHDI and classic landscape indices (MPS, FI, et al), and discusses the correlative relationship between MSHDI and area index (PLAND, Percentage of Landscape) with multiple mesh grains, choosing the South Central of Henan Province as our study area.The method based on MSHDI in this study is mainly used in six single landscapes (Agriculture land, Transportation landscape, Surface water landscape, Forest and Grassland, Urban construction landscape and Industrial and mining area). Results show that the spatial distribution index on spatial distribution scope and division's description has significant feasibility and adaptability, as it accurately reveals different types of single landscapes' spatial distribution scope and reflects the nuances of edges of different landscape patches. It is relatively stable in the spatial distribution relationships among various single landscapes in this study area (MSHDI: Agriculture land (0.982±0.002) > Transportation (0.822±0.020) > Water (0.789±0.015) > Forest and Grassland (0.778±0.015) > Urban construction (0.643±0.020) > Industrial and mining area (0.626±0.025)). Area index can partially reflect the spatial distribution of single-type landscape; moreover, it does not vary with the size of the mesh. Hence according to the intrinsically closely correlation coefficient (between MSHDI and area index) and its degree of change, MSHDI's characterization and stability can be verified respectively. The correlation between the two indices is significantly positive for matrix and scatter landscape (Agriculture land:r= 0.939, P= 0.000; Urban construction:r= 0.877, P= 0.004; Industrial and mining area:r= 0.870, P= 0.002; Forest and Grassland:r= 0.966, P= 0.001), and little change (Agriculture land: r = 0.921±0.054; Urban construction: r = 0.867±0.107; Industrial and mining area: r = 0.883±0.052; Forest and Grassland: r = 0.964±0.024), while it is more complicated for the webbed landscape (Transportation and Surface water landscape).Consequently, in order to address the single-type landscape appropriately, we proposed the spatial distribution index MSHDI. This study clearly demonstrates that MSHDI is appropriate for single-type landscape on its scope and division's description. We compared MSHDI with conventional landscapes indices comprehensively to prove its characterization. Then, MSHDI's stability was certified by the correlation coefficient between MSHDI and PIAND and its magnitude of change. Thus, it is rigorous and complete for the applicable certification of MSHDI.There are some inadequacies that need to be considered in the future study. First, we only selected the study area in which agriculture is predominated. The regions of other predominant land use types should be considered. Second, for the webbed landscape, the spatial distribution index should be improved to meet its stability. These inadequacies will be resolved in the next step of the study.