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新时代背景下地质类高校地理信息科学一流专业建设与实践
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作者 邵怀勇 杨武年 +8 位作者 何政伟 刘刚 杨鑫 于欢 刘汉湖 戴晓爱 刘恩勤 伊帆 徐争启 《中国地质教育》 2024年第1期50-54,共5页
地理信息科学是地球系统科学、计算机科学与技术、空间科学与技术交叉形成的综合性高新学科。近年来地理信息科学在国民经济与社会发展中发挥越来越重要的作用,已成为当前最具活力和发展前景的专业之一。本文主要论述了成都理工大学地... 地理信息科学是地球系统科学、计算机科学与技术、空间科学与技术交叉形成的综合性高新学科。近年来地理信息科学在国民经济与社会发展中发挥越来越重要的作用,已成为当前最具活力和发展前景的专业之一。本文主要论述了成都理工大学地理信息科学专业在新时代背景下依托地质学国家一流建设学科,坚持立德树人,系统开展了将地质元素融入地理信息科学专业培养方案、课程体系构建和学生实践创新能力培养等方面的探索与实践,以期对地理信息科学一流专业建设尤其是行业类省属高校地理信息科学专业人才培养提供参考。 展开更多
关键词 地理信息科学 专业建设 地质类高校 新时代
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基于XGBoost的多源降水数据融合方法研究 被引量:5
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作者 张钧民 阮惠华 +3 位作者 许剑辉 戴晓爱 郑艳萍 张金标 《热带地理》 CSCD 北大核心 2021年第4期845-856,共12页
气象站点观测降水难以精确反映降水时空分布与变化,而雷达降水存在复杂地形区域精度不高等问题。为了最大限度发挥两者的优势,文章以广东省北部山区为研究区域,选择2018-08-26—30一次暴雨过程为研究对象,结合地形、与海岸线距离、植被... 气象站点观测降水难以精确反映降水时空分布与变化,而雷达降水存在复杂地形区域精度不高等问题。为了最大限度发挥两者的优势,文章以广东省北部山区为研究区域,选择2018-08-26—30一次暴雨过程为研究对象,结合地形、与海岸线距离、植被指数、经纬度等地表辅助参量,分析地面站点降水与地表辅助参量、雷达降水的相关关系,利用XGBoost算法与克里金插值方法,构建地面-雷达日降水数据融合模型,得到了空间分辨率为1 km的日降水融合数据集。此外,采用多元线性回归(LM)与克里金插值方法,实现了地面-雷达日降水数据的融合,并利用地面降水数据分别对XGBoost与LM日降水融合性能进行精度验证。结果表明:1)地面降水与雷达降水存在显著的正相关,地面降水与地表辅助参量之间的相关性随时间变化;2) XGBoost预测精度整体上高于LM预测结果;经模型残差校正后,XGBoost融合模型的精度整体上优于LM融合模型,这是因为XGBoost方法在捕捉地面降水与地表辅助参量、雷达降水之间关系性能上优于LM方法。 展开更多
关键词 多源降水 数据融合 雷达降水 XGBoost算法 粤北地区
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Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau,China 被引量:12
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作者 HE Qian dai xiao'ai CHEN Shiqi 《Journal of Arid Land》 SCIE CSCD 2020年第5期865-886,共22页
Soil erosion in the Three-River Headwaters Region(TRHR)of the Qinghai-Tibet Plateau in China has a significant impact on local economic development and ecological environment.Vegetation and precipitation are considere... Soil erosion in the Three-River Headwaters Region(TRHR)of the Qinghai-Tibet Plateau in China has a significant impact on local economic development and ecological environment.Vegetation and precipitation are considered to be the main factors for the variation in soil erosion.However,it is a big challenge to analyze the impacts of precipitation and vegetation respectively as well as their combined effects on soil erosion from the pixel scale.To assess the influences of vegetation and precipitation on the variation of soil erosion from 2005 to 2015,we employed the Revised Universal Soil Loss Equation(RUSLE)model to evaluate soil erosion in the TRHR,and then developed a method using the Logarithmic Mean Divisia Index model(LMDI)which can exponentially decompose the influencing factors,to calculate the contribution values of the vegetation cover factor(C factor)and the rainfall erosivity factor(R factor)to the variation of soil erosion from the pixel scale.In general,soil erosion in the TRHR was alleviated from 2005 to 2015,of which about 54.95%of the area where soil erosion decreased was caused by the combined effects of the C factor and the R factor,and 41.31%was caused by the change in the R factor.There were relatively few areas with increased soil erosion modulus,of which 64.10%of the area where soil erosion increased was caused by the change in the C factor,and 23.88%was caused by the combined effects of the C factor and the R factor.Therefore,the combined effects of the C factor and the R factor were regarded as the main driving force for the decrease of soil erosion,while the C factor was the dominant factor for the increase of soil erosion.The area with decreased soil erosion caused by the C factor(12.10×10^3 km^2)was larger than the area with increased soil erosion caused by the C factor(8.30×10^3 km^2),which indicated that vegetation had a positive effect on soil erosion.This study generally put forward a new method for quantitative assessment of the impacts of the influencing factors on soil erosion,and also provided a scientific basis for the regional control of soil erosion. 展开更多
关键词 soil erosion vegetation cover rainfall erosivity Logarithmic Mean Divisia Index quantitative assessment Three-River Headwaters Region
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