Longleaf Pine (Pinus palustris Mill.) Morphology and Climate/Growth Responses Along a Physiographic Gradient in North Carolina     

Thomas W. Patterson  Lindsay W. Cummings  Paul A. Knapp 《The Professional geographer》2016,68(2):238-248

Geographic differences in tree morphology and climate and growth responses of longleaf pine have been documented, yet how these differences vary at a larger scale has not. In this study, we documented changes in tree morphology and climate and radial growth responses of six longleaf pine (Pinus palustris Mill.) stands in three physiographic regions in North Carolina. We sampled from more than fifteen trees per stand and compared site- and regional-level total and latewood ring width values to temperature, precipitation, and drought. All morphological characteristics expressed a strong west–east gradient. Climate and radial growth response was strongest for the Sandhills region and then Piedmont and Coastal Plain regions. The distinct morphological characteristic gradient did not covary with climate and radial growth response, suggesting that additional environmental influences affect needle length, trunk diameter, and height.  相似文献   

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5' Machine Learning Approach     

Alireza Sadat Hosseini  Mehdi Shafieefar 《海洋工程》2016,(1):19-32

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.  相似文献   

Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges     

Trylee Nyasha Matongera  Onisimo Mutanga  Timothy Dube  Romano Trent Lottering 《国际地球制图》2018,33(3):209-224

Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space.  相似文献   

四川稻城海子山方枝柏树轮宽度与气候因子的响应关系研究     

邹莉丽  徐姗姗  郑超刚  李生芮  连婉婧  商志远  张志刚  孔兴功  赵志军 《冰川冻土》2021,43(3):917-927

对四川稻城县海子山高原上的方枝柏进行树芯采集,经交叉定年后建立林线上限位置的方枝柏树轮宽度年表。标准化年表与气象资料的响应分析结果揭示了该地区树木生长主要受当年生长季前期温度条件的控制。轮宽指数与前一年9月到当年2月的平均气温呈显著正相关（R=0.56,P<0.01）。由此重建了该地区1850—2019年这170 a的前一年9月到当年2月平均气温的变化,转换函数方差解释量31.7%。重建结果与邻近地区树轮记录的温度变化具有较好的一致性。重建序列显示工业革命以来,研究区经历较冷的时期有：1870—1890年和1960—1980年;较暖的时期有：1884—1892年、1919—1925年、1940—1960年以及1980—2019年。1940—1960年是20世纪最暖的时期,20世纪60年代后温度呈现下降趋势,1980年开始气温保持持续升高,2010年之后气温有小幅下降。重建气温序列与太阳黑子数变化和北大西洋多年代际涛动AMO有较强的响应,揭示了太阳活动、海温等因子可能对该区温度变化产生重要影响。  相似文献   

基于梯度提升算法的岩性识别方法     

王恒  姜亚楠  张欣  仲鸿儒  陈庆轩  高世臣 《吉林大学学报(地球科学版)》2021,51(3):940-950

传统的岩性识别方法如岩屑录井、钻井取心及测井资料解释等技术,对录井质量的依赖程度较高,识别精度与效率低,泛化能力差。随着计算机技术的迅速发展,将测井资料与计算机技术相结合开展岩性研究已成为岩性识别的有效手段。本文提出了一种基于梯度提升算法XGBoost和LightGBM的岩性识别方法。以苏里格气田苏东41-33区块下碳酸盐岩储层为例进行测试验证,采用该方法结合测井资料中的声波时差、自然伽马、光电吸收截面指数、密度、深侧向电阻率和补偿中子等6种参数进行岩性识别,并与KNN （K近邻分类器）、朴素贝叶斯和支持向量机等传统算法进行对比,结果表明,3种传统算法的岩性识别准确率分别为78.45%、74.43%和78.72%,基于梯度提升算法XGBoost和LightGBM的识别准确率分别达到了98.90%和98.72%,远高于传统算法。  相似文献   

一种基于机器学习算法的岩性填图方法     

冀全伟  王文磊  刘治博  祝茂强  袁长江 《地质力学学报》2021,27(3):339-349

通过野外地质调查与机器学习方法的有机融合,提出了一种基于梯度提升决策树算法的岩性单元填图方法。研究以多龙矿集区为模型试验区,选择1∶5万勘查地球化学数据为基础预测数据,以1∶5万区域地质图为参考,进行基于梯度提升决策树算法的岩性预测填图模型试验。首先选择研究区内小范围空白区开展野外填图,建立原始数据集并初步构建岩性单元与预测数据对应关系;其次利用机器学习方法对预测数据进行多分类任务,进而开展目标填图区预测填图工作;最后通过概率选区选定概率较低目标区,开展进一步的小范围野外地质调查填图,对原始数据和知识库进行补充,迭代循环以上流程,直至预测填图达到要求。试验显示,随着迭代次数的增加,模型精度不断提高,并在7次迭代后模型准确率达到87%。该方法强调在实际应用中野外地质调查与基于机器学习预测填图的深度融合,以及野外实地工作在整个流程中的重要性和不可或缺性;同时能够充分挖掘已有数据资料的有用信息,用于辅助修正已有岩性填图内容,或根据已勘探区资料对邻近的未勘探区进行岩性分类,有效减少野外填图工作量,是对岩性填图方法、地质单元定量预测识别的有益探索,为区域地质填图工作提供了新的参考思路和辅助手段。   相似文献   

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management   总被引：1，自引：0，他引：1  

Zizheng Guo  Yu Shi  Faming Huang  Xuanmei Fan  Jinsong Huang 《地学前缘(英文版)》2021,12(6):243-261

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.  相似文献   

我国中东部平原地区临界气温条件下降水相态判别分析   总被引：1，自引：0，他引：1  

陈双  谌芸  何立富  郭云谦 《气象》2019,45(8):1037-1051

基于2001—2013年地面观测和探空资料,对地面气温位于0～2℃(以下称临界气温)我国降雪的时空分布及其与降雨的垂直热力特征进行了研究,引入了决策树判别方法对上述条件下雪和雨进行了判别分析,结果表明:临界气温下降雪出现频率总体高于降雨、雨夹雪出现频率,且在我国华北南部至江南北部的中东部地区分布较多,年均可达7.69～15.38站次;临界气温下,降水相态为雨或雪对应的平均温度廓线最大差异位于650 hPa附近,且地面气温较低时,平均温度差异更明显,平均湿度廓线差异则主要位于低层,且在地面气温较高时,平均湿度差异更明显;临界气温下,降水相态为雨时,地面上空存在暖层样本占比,较降水相态为雪时更高,且降雨时暖层主要位于中层,降雪时暖层则主要位于低层,降雨时其暖层强度显著大于降雪时暖层强度;在临界气温下雨雪判别分析中,地面气温能显著提升判别准确率,湿球温度能在一定程度上提升判别准确率,基于云顶温度、中层融化参数、低层湿球温度构建的决策树判别模型,判别准确率达到91.86%,能较好地解决临界气温下雨和雪的判别问题。  相似文献   

Modelling and observation of hedgerow transpiration effect on water balance components at the hillslope scale in Brittany     

Z. Thomas  R. Ghazavi  P. Merot  A. Granier 《水文研究》2012,26(26):4001-4014

Vegetation has a major influence on the water and energy balance of the earth's surface. In the last century, human activities have modified land use, inducing a consequent change in albedo and potential evapotranspiration. Linear vegetation structures (hedgerows, shelterbelts, open woodland, etc) were particularly abundant but have declined considerably over the past several decades. In this context, it is important to quantify their effect on water and energy balance both on a global scale (climate change and weather prediction) and on a local scale (soil column, hillslope and watershed). The main objective of this study was to quantify the effect of hedgerows on the water cycle by evaluating spatial and temporal variations of water balance components of a hillslope crossed by a hedgerow. Water flow simulation was performed using Hydrus‐2D to emphasize the importance of transpiration in the water balance and to evaluate water extraction from groundwater. Model validation was performed by comparing simulated and observed soil matrix potentials and groundwater levels. Hedgerow transpiration was calculated from sap flow measurements of four trees. Water balance components calculated with a one‐dimensional water balance equation were compared with simulations. Simulation runs with and without tree root uptake underlined the effect of hedgerow transpiration, increasing capillary rise and decreasing drainage. Results demonstrated that the spatial and temporal variability of water balance components was related to the hedgerow presence as well as to the meteorological context. The relations between transpiration, groundwater proximity and soil‐water availability determined the way in which water balance components were affected. Increased capillary rise and decreased drainage near hedges were related to the high transpiration of trees identified in this study. Transpiration reached twice the potential evapotranspiration when groundwater level and precipitation amounts were high. Water balance analysis showed that transpiration was a substantial component, representing 40% of total water output. These results may offer support for improving hydrological models by including the effect of land use and land cover on hydrological processes. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

地图数据库中的结构化河网及其自动建立   总被引：3，自引：0，他引：3  

杜清运 《武汉大学学报(信息科学版)》1988,(2)

本文提出了一种基于河段的结构化河网,讨论了这种结构化河网的自动建立过程,主要包括两个结构索引即线索树结构索引及层次结构索引的自动产生;根据包含以上两个索引的结构化河网,提供了若干检索函数,作为地图数据库中结构处理时结构信息的提取手段。  相似文献