Gully erosion is one of the most severe forms of land degradation and poses a serious threat to regional food security, biodiversity, and human survival. However, there are few methods for the quantitative evaluation of gully activity, and the relationships between gully activity and influencing factors require further in-depth study. This study takes the Sunshui River Basin, as a case study. Based on field investigation, unmanned aerial vehicle (UAV) photography and remote sensing images, 71 typical gullies were identified. The vegetation coverage (VC), slope and main-branch gully ratio (MBGR) were used as evaluation indicators, and the gully activity was calculated using the fuzzy mathematics membership degree and then evaluated quantitatively. The factors influencing different active gullies were also analyzed. The results showed that (1) the fuzzy comprehensive evaluation method can be used to identify gully activity. Different levels of gully activity were defined based on the gully activity index. The active indices of stable gullies ranged from 0-0.25, those of semiactive gullies ranged from 0.25-0.75, and those of active gullies ranged from 0.75-1. (2) The activity indices of the 71 gullies ranged from 0.054 to 0.999, with an average value of 0.656. There are 31 active gullies, and 31 semiactive gullies. A total of 87.32% of the gullies in the study area were in the early or middle stage of gully development. Gully erosion was intense, which is consistent with the serious reality of soil erosion. (3) Gully activity was affected by multiple factors. It was significantly positively correlated with topographic relief (TR) (r = 0.64, P<0.01) and surface curvature (SC) (r = 0.51, P<0.01), while it was significantly negatively correlated with land use type (LUT) (r = -0.5, P<0.01). Surface roughness (SR) (r = 0.2, P<0.01) was positively correlated with gully activity; but not significantly. There was no significant correlation between aspect (As) and gully activity. The results of this study are helpful for quantitatively determining the level of gully activity and understanding the development process and mechanism controlling gullies, providing a reference for research on related regions and geomorphologic information.

选取供水、供肥、供氧和抗侵蚀力等4个因素作为玉米种植适宜性评价对象,选取水源、土层厚度、有机质含量、土壤孔隙度、土壤质地和地形坡度等多个对玉米种植适宜性评价对象有一定影响的因子,对浙江省浦江县各地的玉米种植适宜性进行分级和评价.结果表明,浦江县耕地高度适宜玉米种植的地区像元个数为38个,共计0.87 km2,占旱地总面积的7％;一般适宜地区像元个数为360个,共计6.50 km2,占旱地总面积的51％;适宜地区主要集中在东南部渭南街道和黄宅镇,像元个数为293个,共计5.29 km2,占旱地总面积的41％;不适宜地区像元个数为9个,共计0.16 km2,占旱地总面积的1％.

利用四川省1980、1990、2000、2010年和2020年共5期土地利用基本数据,采用GIS技术及地学信息图谱方法合成1980—2020年4个时段的土地利用格局变化图谱,从而得到近40 a内的土地利用变化数据,并由此分析四川省土地利用格局的时空变化.结果表明:近40 a来,四川省土地利用方式大多维持不变,为全期稳定型模式,变化主要发生在2010—2020年;1990—2010年成都平原城市化进程加快,2010—2020年四川省城市化进程加快,这与四川省经济发展模式相呼应;四川省耕地面积一直在减小,2000年后尤为明显;林地面积在1980—2000年减小,2000年后增加,推断这与我国退耕还林及"绿水青山就是金山银山"等政策和理论的实施相关.

Rill erosion is one of the most common types of erosion, and the development conditions of the asymmetric characteristics of rill cross-sections are still relatively poorly understood. To explore the relationship between rill topography and rill cross-sectional asymmetry, we used the microtopographic profiler method to measure 712 groups of rill cross-sections in the Yuanmou dry-hot valley area. The results of correlation analysis and principal component analysis to investigate the topographical conditions of rill development show that: (1) asymmetry is the main feature in rill cross-sections; 53% of rill cross-sections are right-biased and 47% are left-biased. (2) There is an extremely significant positive correlation between the slope difference and the rill cross-section asymmetry ratio ( p < 0.01); the asymmetry ratio increases as the slope difference on both sides ( B ) increases, and the directionality of the asymmetry ratio is affected by B . The difference between the catchment areas on both sides has a significant linear correlation with the asymmetry ratio of the width (r = 0.07, p < 0.05). (3) Seven topographic factors were divided into two types of principal components: the first represents the rill slope surface shape and the rill shape, and the second represents the difference between the two sides of the rill.