Showing papers by "Jianghua Zheng published in 2016"
10 Jul 2016
TL;DR: This paper validated the availability of UAV technique for dynamic monitoring rodent pests in desert forest, and laid a critical foundation for further study.
Abstract: The severe rodent damage in Gurbantunggut desert forest may result in eco-environment destruction and desertification acceleration. However, little is known concerning the level of rodent hazard, spatial distribution and regularity of outbreak. This paper approached to use high-resolution imagery (TDOM and DEM) provided by Unmanned Aerial Vehicles (UAV) for rodent pests monitoring in desert forest. The distribution of rat-holes was extracted from TDOM images, then rat-hole density were calculated for evaluating the rodent hazard degree in the study area. Lastly, topographic factors of slope gradient, slope aspect, elevation were calculated using DEM. Spatial and statistical analysis methods were used for it. The results demonstrated that Rhombimys opimus mainly distributed in the elevation of 432.5∼437.5m, low slope areas of 0∼15°, low RDLS of 0∼0.25m, and shady slope of fixed and semi-fixed sand with well-growth plants by “island” mousehole groups. This paper validated the availability of UAV technique for dynamic monitoring rodent pests in desert forest, and laid a critical foundation for further study.
3 citations
10 Jul 2016
TL;DR: The results show that the SK method is the best method for the spatial interpolation of temperature in Xinjiang, while the second best is the LPI method, and the third is the CRS method.
Abstract: This paper tried to find the best interpolation method for Xinjiang average annual temperature estimation based on exploratory data analysis and 9 spatial interpolation methods comparison. The research used part of annual data set of Chinese terrestrial climatic data from 1951 to 2013 to evaluate Xinjiang average annual temperature, which contained data from 64 meteorological stations in Xinjiang and 11 ones in Gansu and Qinghai, which are nearby provinces. The results show that: 1) the SK method is the best method for the spatial interpolation of temperature in Xinjiang. The second best is the LPI method, and the third is the CRS method. 2) Compared with other methods, the SK method has obvious advantages. The RMSE of SK method is smaller 0.21°C than LPI, and 0.274°C less than CRS; The MBE of SK is less 0.19 and 0.217 than LPI and CRS respectively. The correlation coefficient is higher 0.032 and 0.059 respectively compared with LPI and CRS.