Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields.However,due to multi-scale structures and irregular spatial distribution of vortices in complex ...Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields.However,due to multi-scale structures and irregular spatial distribution of vortices in complex geographic flow fields,existing two-dimensional visualization methods are susceptible to the effects of data accuracy and sampling resolution,resulting in incomplete and inaccurate vortex information.To address this,we propose an adaptive Line Integral Convolution(LIC)based geographic flow field visualization method by means of rotation distance.Our novel framework of rotation distance and its quantification allows for the effective identification and extraction of vortex features in flow fields effectively.We then improve the LIC algorithm using rotation distance by constructing high-frequency noise from it as input to the convolution,with the integration step size adjusted.This approach allows us to effectively distinguish between vortex and non-vortex fields and adaptively represent the details of vortex features in complex geographic flow fields.Our experimental results show that the proposed method leads to more accurate and effective visualization of the geographic flow fields.展开更多
Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns(e.g. soilssimple slope classesslope aspectand flo...Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns(e.g. soilssimple slope classesslope aspectand flow accumulation) of flowering around Lake IssaqueenaSouth Carolina(SCUSA) using plant-flowering database collected with GPS- enabled camera(stored in Picasa 3 web albums and project website) on a monthly basis in 2012 and Li DAR-based topography. Pacolet fine sandy loam had the most flowering plantsfollowed by Madison sandy loamboth dominant soil types around the lake. Most flowering plants were on moderately steep(17%–30%) and gently sloping(4%–8%) slopes. Most flowering plants were on west(247.5°–292.5°)southwest(202.5°–247.5°)and northwest(292.5°–337.5°) aspects. Most flowering plants were associated with minimum and maximum flows within the landscape. Chi-square tests indicated differences in the distributions of the proportions of flowering plants were significant by soil typeslopeaspectand flow accumulation for each month(February-November)for all months(overall)and across months. The Chi-square test on area-normalized data indicated significant differences for all months and individual differences by each month with some months not statistically significant. Cluster analysis on flowering counts for nine plant families with the most flowering counts indicated no unique separation by clusterbut implied that the majority of these families were flowering on strongly sloping(9%–16%) slopeson southwest(202.5°–247.5°) aspectsand low flow accumulation(0–200). Presented methodology can serve as a template for future efforts to quantify spatio-temporal patterns of flowering and other phenological events.展开更多
文摘Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields.However,due to multi-scale structures and irregular spatial distribution of vortices in complex geographic flow fields,existing two-dimensional visualization methods are susceptible to the effects of data accuracy and sampling resolution,resulting in incomplete and inaccurate vortex information.To address this,we propose an adaptive Line Integral Convolution(LIC)based geographic flow field visualization method by means of rotation distance.Our novel framework of rotation distance and its quantification allows for the effective identification and extraction of vortex features in flow fields effectively.We then improve the LIC algorithm using rotation distance by constructing high-frequency noise from it as input to the convolution,with the integration step size adjusted.This approach allows us to effectively distinguish between vortex and non-vortex fields and adaptively represent the details of vortex features in complex geographic flow fields.Our experimental results show that the proposed method leads to more accurate and effective visualization of the geographic flow fields.
基金funding from Clemson University.This is technical contribution No.6345 of the Clemson University Experiment Stationsupported by NIFA/USDA,under project number SC-1700452
文摘Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns(e.g. soilssimple slope classesslope aspectand flow accumulation) of flowering around Lake IssaqueenaSouth Carolina(SCUSA) using plant-flowering database collected with GPS- enabled camera(stored in Picasa 3 web albums and project website) on a monthly basis in 2012 and Li DAR-based topography. Pacolet fine sandy loam had the most flowering plantsfollowed by Madison sandy loamboth dominant soil types around the lake. Most flowering plants were on moderately steep(17%–30%) and gently sloping(4%–8%) slopes. Most flowering plants were on west(247.5°–292.5°)southwest(202.5°–247.5°)and northwest(292.5°–337.5°) aspects. Most flowering plants were associated with minimum and maximum flows within the landscape. Chi-square tests indicated differences in the distributions of the proportions of flowering plants were significant by soil typeslopeaspectand flow accumulation for each month(February-November)for all months(overall)and across months. The Chi-square test on area-normalized data indicated significant differences for all months and individual differences by each month with some months not statistically significant. Cluster analysis on flowering counts for nine plant families with the most flowering counts indicated no unique separation by clusterbut implied that the majority of these families were flowering on strongly sloping(9%–16%) slopeson southwest(202.5°–247.5°) aspectsand low flow accumulation(0–200). Presented methodology can serve as a template for future efforts to quantify spatio-temporal patterns of flowering and other phenological events.