Vegetation change as related to terrain factors at two glacier forefronts, Glacier National Park, Montana, U.S.A.

Glacier recession is a globally occurring trend. Although a rich body of work has documented glacial response to climate warming, few studies have assessed vegetation cover change in recently deglaciated areas, especially using geospatial technologies. Here, vegetation change at two glacier forefronts in Glacier National Park, Montana, U.S.A.was quantified through remote sensing analysis,fieldwork validation, and statistical modeling.Specifically, we assessed the spatial and temporal patterns of landcover change at the two glacier forefronts in Glacier National Park and determined the role of selected biophysical terrain factors(elevation, slope, aspect, solar radiation, flow accumulation, topographic wetness index, and surficial geology) on vegetation change(from nonvegetated to vegetated cover) at the deglaciated areas.Landsat imagery of the study locations in 1991, 2003,and 2015 were classified and validated using visual interpretation. Model results revealed geographic differences in biophysical correlates of vegetation change between the study areas, suggesting that terrain variation is a key factor affecting spatialtemporal patterns of vegetation change. At Jackson Glacier forefront, increases in vegetation over some portion or all of the study period were negatively associated with elevation, slope angle, and consolidated bedrock. At Grinnell Glacier forefront,increases in vegetation associated negatively with elevation and positively with solar radiation.Integrated geospatial and field approaches to the study of vegetation change in recently deglaciated terrain are recommended to understand and monitor processes and patterns of ongoing habitat change in rapidly changing mountain environments.

Characteristics and influencing factors of proximity distance index on the northern Shaanxi Loess Plateau in China

Topographic feature points and lines are the framework of topography,and their spatial distance relationship is an breakthrough in the study of topographical geometry,internal structure and development level.Proximity distance(PD)is an indicator to describe the distance between the gully source point(GSP)and the watershed boundary.In the upstream catchment area,PDs can be expressed by the streamline proximity distance(SPD),as well as by the horizontal proximity distance(HPD)and the vertical proximity distance(VPD)in the horizontal and vertical dimensions,respectively.The series of indicators(e.g.,SPD,HPD and VPD)are important for quantifying the geomorphological development process of a loess basin because of the headward erosion of loess gullies.In this study,the digital elevation model data with 5 m resolution and a digital topographic analysis method are used for the statistical analyses of the SPD,VPD and HPD in 50 sample areas of 6 geomorphic types in the Loess Plateau of northern Shaanxi.The spatial characteristics and the influencing factors are also analysed.Results show that:1)Central tendencies for the HPDs and the VPDs for the whole study area and the six typical loess landforms are evident.2)Spatial patterns of the HPDs and the VPDs exhibit evident trends and zonal distributions over the whole study area.3)The HPDs have a strong positive correlation with gully density(GD)and hypsometric integral.The VPDs also correlates with GD to an extent.Vegetation cover,mean annual precipitation and loess thickness have stronger effects on the VPD than on the HPD.

Analysis and Research about the Rainstorm on May 12,2012 in Jiangxi Province Based on GIS

Using the rainfall data at Jiangxi Meteorological Observatory and 1：50 000 DEM data of Jiangxi, spatial distribution characteristics of the rainstorm process on May 12; 2012 were studied. With the help of GIS software, the impact factors for spatial distribution of precipitation and the influence brought by rainstorm were analyzed. The results showed that terrain factors were effective for the estimation model of rainstorm in Jiangxi, especially large reservoir. Moreover, spatial distribution characteristics of the actual precipitation under the multiple linear regression model were estimated.

黄土高原沟蚀区地表蚕食度空间分布特征和影响因素研究

In China’s Loess Plateau severe gully erosion(LPGE)region,the shoulder-line is the most intuitive and unique manifestation of the loess landform,which divides a landform into positive and negative terrains(PNTs).The spatial combination model of PNTs is of great significance for revealing the evolution of the loess landform.This study modeled and proposed the Surface Nibble Degree(SND),which is a new index that reflects the comparison of the areas of PNTs.Based on 5 m DEMs and matched high-resolution remote sensing images,the PNTs of 164 complete watersheds in the LPGE were extracted accurately,and the SND index was calculated.The spatial distribution trend of SND was discussed,and the relationship between SND and the factors that affect the evolution mechanism of regional landform was explored further.Results show that:(1)The SND can be calculated formally.It can quantify the development of the loess landform well.(2)The SND of the LPGE has evident spatial differentiation that increases from southwest to northeast.High values appear in Shenmu of Shaanxi,Shilou of Shanxi,and northern Yanhe River,whereas the low values are mainly distributed in the southern loess tableland and the inclined elongated ridge area of Pingliang in Gansu and Guyuan in Ningxia.(3)In the Wuding River and Yanhe River,the SND decreases with the increase in flow length(FL).In the North-Luohe River and Jinghe River,the SND increases with FL.(4)SND is significantly correlated with gully density and sediment modulus and moderately correlated with hypsometric integral.As for the mechanism factors analysis,the relationship between loess thickness and SND is not obvious,but SND increased first and then decreased with the increase of precipitation and vegetation in each geographical division,and we found that the land use type of low coverage grassland has greater erosion potential.