Soil erosion (SE) processes are closely related to natural conditions and human activities, posing a threat to environment and society. Identifying the human impact on regional SE changes is increasingly essential for pertinent SE management. Jiangxi province is studied here as a representative area of hilly-red-soil regions within southern China. The main objectives of this study were to investigate the changing trend of SE within Jiangxi and identify human impacts on regional SE change from the perspective of spatial differences, through a new approach based on a gravity-center model. Our results showed that SE status presented an overall amelioration from 1990 to 2015, while the average soil erosion modulus (SEM) declined from 864 to 281 Mg/(km²·a). Compared to the situation under human and natural impacts, human-induced spatial differences of SE change demonstrated that the western and northwest regions showed stronger negative effects; the southern region shifted towards negative effects; the northeast region presented a much weaker negative effect. Our results indicated that 4 cities with strong negative effects need more attention in further SE management suited to their local conditions and development, and also suggested that the approach based on a gravity-center has potential for identifying the human impact on regional SE change from the perspective of spatial patterns.

Accurate grid size suitability evaluations are necessary to enhance the spatialization quality of gridded population distributions. This paper proposes an improved average local variance (ALV) method to express discrepancies in population density and was validated in Anhui Province, China. A dataset consisting of 14 spatial scales, from 100 m to 900 m, and 1000 m to 5000 m, was processed by both the proposed and traditional ALV methods. Line graphs of two sets of ALV values and grid sizes were comparatively analyzed to evaluate the grid size suitability. The ALV trends calculated by the proposed method encompassed more accurate and useful features compared to the traditional method. The case study results showed that the 200 m grid size accurately expresses the population distribution characteristics of Anhui Province. The standard deviation (SD) index was adopted to validate these results; the proposed ALV method was proven valuable both in theory and practice for assessing grid size suitability. The method may be further improved by determining the essential laws of ALV values based on grid characteristics, and by enhancing the adaptability to various locations.