Search

Soil erosion is a continuous process of detachment, transportation, and deposition of soil particles. Obtaining accurate descriptions of soil surface topography is crucial for quantifying changes to the soil surface during erosion processes. A digital close range photogrammetric observation system based on wireless networking technology was explored and established in this study. Through wireless networking, multi-cameras were concurrently controlled, solving the problems of synchronous acquisition of underlying digital image, big data transmission and storage. Image sensors collected data in parallel based on network command, and noise on the images such as raindrops was eliminated based on the K-means clustering algorithm by serialization technology during data acquisition. After parallel preprocessing, high density 3D point clouds and digital elevation models (DEMs) were reconstructed. The evolution of soil surface topography was dynamically monitored by instantaneous image acquisition at different time intervals during ongoing rainfall. The results showed that the measurement precision of the established system could reach a sub-millimeter level with the minimum single measurement error being 0.0069 mm. In addition, based on the DEM generated from digital point clouds, the amount of soil erosion in different topographic positions within various time periods was calculated. The digital photogrammetric observation methods explored in our study provide a reliable way to monitor soil erosion processes, especially under rainfall conditions. This approach can accurately resolve the evolution of the underlying surface soil erosion, which is of great importance in understanding soil erosion mechanisms.

The importance of microhabitat, a localized environment with a microclimate that is distinct from the regional climate, is increasingly recognized in ecological conservation planning. Although there is a growing body of literature on microhabitats and the thermal buffering effect (the difference between temperatures within and outside of a microhabitat), uncertainties remain in quantifying this effect due to variation among microhabitats and the species that use them. Here, we review studies on thermal buffering in various microhabitats, and outline a framework for the quantification of the thermal buffering effect. Our framework emphasizes the importance of clearly defining ambient temperature and other temperature metrics used in quantifying the thermal buffering effect, as well as the spatial and temporal scales of investigation. We believe a suitable framework can help to reduce the uncertainties in quantifying the thermal buffering of microhabitats and assessing the vulnerability of species to regional climate changes.

Soil erosion is a continuous process of detachment, transportation, and deposition of soil particles. Obtaining accurate descriptions of soil surface topography is crucial for quantifying changes to the soil surface during erosion processes. The objective of this study was to develop an improved close-range photogrammetric technique to assess soil erosion under rainfall conditions. Based on high overlapping image acquisition, digital point cloud matching, digital elevation model (DEM) generation and soil erosion calculation, a digital close-range photogrammetric observation system was explored and established. The results showed that the established digital photogrammetric observation system could accurately calculate the digital point cloud from the underlying surface with a 2 min time interval and a 1.5 mm spatial resolution. In addition, based on the DEM generated from digital point clouds, the amount of soil erosion in different topographic positions within various time periods was calculated. The digital photogrammetric observation methods explored in our study provide a reliable way to monitor soil erosion processes, especially under rainfall conditions. This approach can accurately resolve the evolution of the underlying surface soil erosion, which is of great importance in understanding soil erosion mechanisms.

As the main process of soil erosion in the Loess Plateau of China, rill erosion accounts for a large proportion of the total erosion on the slope. Quantifying the rill shape is crucial for studying the mechanisms and evolution of rill erosion. The objective of this study is to monitor the dynamic process of slope rill erosion using on a digital close range photogrammetry observation system during continuous rainfall. Artificial simulated rainfall experiments were conducted, and images were obtained at different time intervals. We used hydrological analysis and profile analysis tools in geographic information system (GIS) technology to extract rill networks and their main parameters to quantitatively describe the erosion processes of rill morphology. The results showed that (1) compared with the error from the traditional runoff sediment measurement method, the average error of the system for estimating soil loss was -7.06% and 1.05%, respectively, and the highest precision for a single observation was 99.46%; (2) the rill erosion process could be divided into several stages: raindrop splashing - eclipse - drop pit - erosion cave - rill cutting head - rill erosion - rill network; and (3) after rainfall lasted for 80 min, the density and the degree of splitting increased continuously, and the maximum rill width and depth both showed fluctuating trends. The area of 7.5 m to 9.5 m away from the top of the surface was the most active area of rill erosion. The digital close range photogrammetric observation system can accurately obtain evolution information about rill erosion morphology during continuous rainfall, which provides a reference for future studies of soil erosion processes.

In mountain areas, the distribution of plant communities is affected by both regional and microhabitat conditions. The degree to which these different spatial factors contribute to plant communities is not well understood, because few studies have used a uniform sampling methodology to measure trait variation across the range of ecological scales. In this study, a stratified sampling method was used to study community weighted leaf traits and environment factors at different spatial (transect and plot) scales. We measured 6 leaf traits (specific leaf area, leaf tissue density, leaf thickness, leaf carbon, nitrogen and phosphorus content) in 258 communities from 57 sites in 9 transects nested within 3 vegetation zones. These communities are located in the loess hilly and gully area of the Yanhe river watershed. We coupled climatic factors at the transect scale with topographic and edaphic factors at the plot scale using multilevel regression modeling to analyze the trait variation associated with spatial scales. At the transect scale, the mean annual rainfall showed a highly significant positive effect on the leaf nitrogen concentration (LNC) (p < 0.01), while it had a highly significant negative effect on leaf thickness (LT) and leaf tissue density (LTD) (p < 0.001) and a significant negative effect on leaf carbon concentration (LCC) (p < 0.05), explaining 10.91%, 36.08%, 57.25% and 66.01% of LTD, LT, LCC and LNC variation at transect scale respectively. At a plot scale, the slope aspect showed a highly significant positive effect on specific leaf area (SLA) and LNC but a highly significant negative effect on LT and LTD. The soil water content had a significant negative effect on LT (p < 0.05) and LTD (p < 0.001) while soil organic matter showed a positive effect on SLA (p < 0.001) and LNC (p < 0.01). Totally, plot scale variables explained 7.28%, 43.60%, 46.43%, 75.39% and 81.17% of LCC, LT, LNC, LTD and SLA variation. The elevation showed positive effect only on LCC (p < 0.05). The results confirmed the existence of consistent trait–environment relationships at both transect and plot scales. These trait–environment relationships at different spatial scales will provide mechanistic understanding on the vegetation community assembly in the study area. Practically, ignoring trait variation within transects will underestimate roles of microhabitat filters in community assembly, and leads to the homogenization of restoration species. This will be like the past restoration plans and programs, causing serious environmental problems such as dwarf trees and soil desiccation.

Rainfall erosivity factor (R) is one of the most commonly used factors in soil erosion models. While rainfall energy (E) is the most elementary physical parameter to predict R. Based on comparative analysis of previous soil erosion models and rainfall erosivity factor measuring methods, integrated application of modern photogrammetric techniques, image analytic methods and automatic control theories, this paper provided a new method based on image analytic to calculate the rainfall energy and R factor, which obtains raindrop's volume and velocity by means of modern photogrammetric technique. Results show that this method can improve both efficiency and accuracy of rainfall energy calculation and other rainfall physical parameters measurement.