APG:A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies     

Seyed Amir Naghibi  Hossein Hashemi  Biswajeet Pradhan 《地学前缘(英文版)》2021,12(6):90-104

One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7％from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4％from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.  相似文献   

A novel index to evaluate discretization methods:A case study of flood susceptibility assessment based on random forest     

Xianzhe Tang  Takashi Machimura  Wei Liu  Jiufeng Li  Haoyuan Hong 《地学前缘(英文版)》2021,12(6):313-325

The selection of a suitable discretization method(DM)to discretize spatially continuous variables(SCVs)is critical in ML-based natural hazard susceptibility assessment.However,few studies start to consider the influence due to the selected DMs and how to efficiently select a suitable DM for each SCV.These issues were well addressed in this study.The information loss rate(ILR),an index based on the informa-tion entropy,seems can be used to select optimal DM for each SCV.However,the ILR fails to show the actual influence of discretization because such index only considers the total amount of information of the discretized variables departing from the original SCV.Facing this issue,we propose an index,infor-mation change rate(ICR),that focuses on the changed amount of information due to the discretization based on each cell,enabling the identification of the optimal DM.We develop a case study with Random Forest(training/testing ratio of 7:3)to assess flood susceptibility in Wanan County,China.The area under the curve-based and susceptibility maps-based approaches were presented to compare the ILR and ICR.The results show the ICR-based optimal DMs are more rational than the ILR-based ones in both cases.Moreover,we observed the ILR values are unnaturally small(＜1％),whereas the ICR values are obviously more in line with general recognition(usually 10％-30％).The above results all demonstrate the superiority of the ICR.We consider this study fills up the existing research gaps,improving the ML-based natural hazard susceptibility assessments.  相似文献   

面向自然资源信息提取的多源异构数据融合技术——以汉江流域NDVI数据为例     

汤宇磊  吴杨杨  蒋兴征  冯亮  高阳 《中国地质调查》2021,8(2):74-82

高时空分辨率的自然资源指标数据对大尺度自然资源动态观测与趋势评估至关重要。大数据时代下的海量多源数据为数据高效融合利用提供了可能。以重构汉江流域归一化植被指数(Normalized Difference Vegetation Index,NDVI)数据为例,搭建了PostgreSQL自然资源时空大数据处理底层架构,集成了数据级融合法、特征级融合法和决策级融合法,基于机器学习算法构建了一套面向自然资源信息提取的多源异构数据智能融合技术,实现了多源数据的高效利用与特征空间优选。同时,重构了2000—2019年汉江流域NDVI 1 km逐年数据集,全面反映了汉江流域植被动态变化。研究结果可为地球科学时空大数据的高效提取与模拟分析提供科学参考,为定量核算林草资源禀赋规模、探究生态系统时空演变规律提供一种更精准、更便捷的技术手段。  相似文献   

人工智能在冰雹识别及临近预报中的初步应用   总被引：1，自引：0，他引：1  

张文海  李磊 《气象学报》2019,77(2):282-291

基于广东10部S波段多普勒天气雷达的三维拼图资料,利用机器学习技术开发了一种冰雹识别和临近预报的人工智能算法。算法设计时以雷达回波反射率的垂直和水平扫描数据为基础训练集,将冰雹云的雷达反射率扫描数据作为正样本,将其他雷达反射率扫描数据作为负样本,通过贝叶斯分类法对正、负样本数据集进行机器学习,训练人工智能识别冰雹云内在规律的能力。训练时以广东省2008-2013和2015-2016年的数据作为训练集,使用了2014年广东省12次冰雹过程的数据做检验。对比检验的结果表明,人工智能法比传统的概念模型法击中率高9个百分点。研究结果表明了人工智能对冰雹这类非线性强天气过程具有较强的识别能力。   相似文献   

Integrating farmers’ adaptive knowledge into flood management and adaptation policies in the Vietnamese Mekong Delta: A social learning perspective     

《Global Environmental Change》2019

Flood management and adaptation are important elements in sustaining farming production in the Vietnamese Mekong Delta (VMD). While over the past decades hydraulic development introduced by the central government has substantially benefited the rural economy, it has simultaneously caused multiple barriers to rural adaptation. We investigate the relational practices (i.e., learning interactions) taking place within and across the flood management and adaptation boundaries from the perspective of social learning. We explore whether and how adaptive knowledge (i.e., experimental and experiential knowledge) derived from farmers’ everyday adaptation practices contributes to local flood management and adaptation policies in the selected areas. We collected data through nine focus groups with farmers and thirty-three interviews with government officials, environmental scientists, and farmers. Qualitative analysis suggests that such processes are largely shaped by the institutional context where the boundary is embedded. This study found that while the highly bureaucratic operation of flood management creates constraints for feedback, the more informal arrangements set in place at the local level provide flexible platforms conducive to open communication, collaborative learning, and exchange of knowledge among the different actors. This study highlights the pivotal role of shadow systems that provide space for establishing and maintaining informal interactions and relationships between social actors (e.g., interactions between farmers and extension officials) in stimulating and influencing, from the bottom-up, the emergence of adaptive knowledge about flood management and adaptation in a local context.  相似文献   

循环神经网络在雷达临近预报中的应用          下载免费PDF全文

韩丰  龙明盛  李月安  薛峰  王建民 《应用气象学报》2019,30(1):61-69

该文将循环神经网络（recurrent neural network,RNN）应用于雷达临近预报。使用预测循环神经网络（predictive RNN）架构,利用雷达历史组合反射率因子建模,给出雷达组合反射率因子未来1 h的预报结果。预测循环神经网络的核心是在长短时记忆单元（long short-term memory,LSTM）中增加时空记忆模块,能够提取雷达回波不同尺度的空间特征,配合循环神经网络架构,可以有效解决反射率因子预测问题。北京大兴雷达和广州雷达长时间序列的独立检验结果和2个强对流天气个例检验结果表明:该方法和传统的基于交叉相关法的1 h雷达外推临近预报相比,在20 dBZ和30 dBZ检验项目内,临界成功指数（CSI）可以提升0.15~0.30,命中率（POD）提高0.15~0.25,虚警率（FAR）降低0.15~0.20,该方法对反射率因子强度变化有一定预报能力。  相似文献   

基于机器学习的重庆长江航道雾图像特征识别研究     

王远谋  李家启  陈施吉  唐家萍  夏佰成  韩世刚 《气象与环境学报》2021,37(1):106-112

基于重庆市境内长江航道雷达站拍摄的雾天气过程影像资料,利用K最近邻、支持向量机、BP神经网络、随机森林等机器学习算法,对无雾和5类有雾天气个例进行图像识别训练,构建雾图像识别模型,并检验了识别准确率。结果表明：机器学习能够有效识别雾图像,随机森林算法的识别效果优于其余3种算法。对于能见度超过1500 m的无雾天气,模型的识别准确率为100%,对于能见度在1000—1500 m范围内的轻雾、能见度低于50 m的强浓雾,模型的识别准确率在90%以上,对于能见度在50—1000 m范围内的雾、大雾和浓雾,识别准确率超过70%。  相似文献   

全球-地方联结与产业集群的技术学习--以河南许昌发制品产业为例   总被引：27，自引：4，他引：23  

苗长虹 《地理学报》2006,61(4):425-434

以产业区理论、管制理论和全球生产网络理论为基础,以学习创新为核心,构建了一个融生产体系与社会生产体制、制度与协调机制、地方生产网络、全球生产网络“四位一体”的学习型产业区分析框架;运用该框架,以河南许昌发制品产业集群为案例,研究了全球-地方网络联结的方式、动态及其对技术学习的影响。研究发现,通过全球与地方生产网络的建构和有机联结,传统产业集群的技术学习是可以从“低端道路”迈向“高端道路”的,发展学习型产业区应作为我国经济发展与技术创新的一项重大战略和政策。  相似文献   

利用深度学习融合NWP和多源观测数据的闪电落区短时预报方法     

周康辉  郑永光  王婷波 《气象学报》2021,79(1):1-14

强对流短时预报(2—6 h)具有较大难度.一方面,基于观测数据的外推已基本不可用;另一方面,高分辨率数值模式(High-resolution Numerical Weather Prediction,HNWP)的预报性能有待提升.利用深度学习方法,将卫星、雷达、云-地闪电(简称闪电)等观测数据和高分辨率数值模式预测数据...  相似文献   

人工智能在飞机颠簸预报中的应用进展及未来趋势展望          下载免费PDF全文

朱玉祥  刘海文  万文龙  姜晓飞  尕藏程林 《大气科学学报》2023,46(6):825-836

飞机颠簸对飞机运行安全及旅客舒适度具有很大危害,提高飞机颠簸的预报准确率对于减轻人员伤害和财产损失具有重要意义,且一直是航空气象研究的重点领域。随着观测手段的丰富和科学技术的进步,飞机颠簸预报也取得了长足发展。本文首先从定性预报和定量预报的角度对国内外飞机颠簸预报的主要方法,特别是人工智能(AI)方法在其中的最新应用进行了综述。在此基础上,归纳总结出AI用于飞机湍流预报存在的主要问题和未来的重点研究方向：1)飞机实况数据的开放共享以及多源湍流数据的融合构建问题;2)基于人工智能构建飞机颠簸预报模型的可解释性及物理机制问题;3)基于人工智能构建飞机颠簸的集合预报问题。最后,提出了气象领域未来第三代人工智能的发展思路。  相似文献