Natural Resources Research - Focusing on vertical multi-layer superimposition of unconventional natural gas reservoirs in coal-bearing strata, research on the co-production of tight gas and coalbed... 相似文献
The Pingluo area, as an experimental study area in Yinchuan, has been subjected to major environmental degradation due to soil salinization problems. Soil salinization is one of the main problems of land degradation in arid and semiarid regions. In the present study, remote sensing was integrated with mathematical modeling to evaluate soil salinization adequately. To detect soil salinization, soil water content and electrical conductivity of soil samples were analyzed. The reflectance of soil samples was measured using a spectrometer (SR-3500) with 1024 bands. Indices of soil salinity, vegetation and drought were analyzed using Landsat images over the study area. Based on Landsat images, physicochemical analysis, reflectance of sensitive bands for soil salinization and environmental indices, canopy response salinity index (CRSI), perpendicular drought index (PDI) and enhanced normalized difference vegetation index (ENDVI), a new model was established for simulation and prediction of soil salinization in the study area. Correlation analyses and multiple regression methods were used to construct an accurate model. The results showed that green, blue and near-infrared light was significantly correlated with soil salinity and that the spectral parameters improved this correlation significantly. Therefore, the model was more effective when combining spectral parameters with sensitive bands with modeling. After mathematical transformation of soil reflectance, the correlations of bands sensitive to soil salinization were 0.739 and 0.7 for electrical conductivity and water content, respectively. After transformation of vegetation reflectance, the correlation coefficient of soil salinity became 0.577. After inversion of the model based on soil hyperspectral and water content, the significance became 0.871 and 0.726, respectively, which can be used to predict soil salinity and water content. The spectral soil salinity model had a coefficient of 0.739 for soil salinity prediction. Among the salinity indices, the CRSI was selected as the most significant, with R2 of 0.571, whereas the R2 for PDI reached only 0.484. Among the vegetation indices, the ENDVI had the highest response to soil salinity, with R2 of 0.577. After scale conversion, the correlation percentages between CRSI and measured soil salinity and between ENDVI and measured soil salinity increased to 16.2% and 8.5%, respectively. Following the correlation between PDI and soil water content, the percentage of correlation increased to 11.6%. The integration of hyperspectral remote sensing, ground methods and an inversion method for salinity is a very important and effective technique for rapid and nondestructive monitoring of soil salinization.
GPS Solutions - A cable crane collision accident usually causes serious damage to workers, equipment and materials. Owing to the emergence of global position system (GPS), some new collision... 相似文献
GPS Solutions - We derive orbit and clock errors for BeiDou satellites from March 1, 2013, to September 30, 2016 by comparing broadcast ephemerides with the precise ephemerides produced by Wuhan... 相似文献
Assistive tools are important for improving teaching and learning quality in courses that involve practical work. This article presents an overview of GEN_MAT, the first MATLAB‐based map generalization algorithm toolbox. The toolbox provides 42 map generalization algorithms for aggregation, selective omission, simplification, smoothing, collapse, agglomeration, merging, dissolving, displacement, and typification. A beta test of the application of GEN_MAT in teaching and learning was conducted. Evaluations showed that GEN_MAT has positive effects on teaching and learning. Comparing tool‐based and non‐tool‐based courses indicated that the experimental group performed better than the control group, and the two groups exhibited significant discrepancy (p < 0.05) in confidence, awareness, skills and attitudes or behaviors. 相似文献
This study proposes a knowledge-based, computerized method to develop an initial sinkhole database as a basis for subsequent field investigation to improve on the established database. The knowledge-based data analysis represents sinks (i.e., topographic depressions) as isolines and associates them with contextual land use, land cover, and hydrologic information relevant to potential sinkhole hazard. Sinks of high priority for subsequent field investigation are identified based on combinations of contextual attributes. The proposed methodology for knowledge-based development of a preliminary sinkhole database is valuable for hazard planning and management. 相似文献