2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models

One of the challenges of remote sensing and computer vision lies in the three-dimensional (3-D) reconstruction of individual trees by using automated methods through very high-resolution (VHR) data sets. However, a successful and complete 3-D reconstruction relies on precise delineation of the trees in two dimensions. In this paper, we present an original approach to detect and delineate citrus trees using unmanned aerial vehicles based on photogrammetric digital surface models (DSMs). The symmetry of the citrus trees in a DSM is handled by an orientation-based radial symmetry transform which is computed in a unique way. Next, we propose an efficient strategy to accurately build influence regions of each tree, and then we delineate individual citrus trees through active contours by taking into account the influence region of each canopy. We also present two efficient strategies to filter out erroneously detected canopy regions without having any height thresholds. Experiments are carried out on eight test DSMs composed of different types of citrus orchards with varying densities and canopy sizes. Extensive comparisons to the state-of-the-art approaches reveal that our proposed approach provides superior detection and delineation performances through supporting a nice balance between precision and recall measures.     

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.     

基于DBSCAN算法的孔深测量与地层反演理论研究

论文针对地质勘探取心工况复杂、钻进深度大、事故发生率高、岩性复杂、钻进参数难以获取、无法实时掌握钻进状态的难题,在充分调研现有工况识别技术的采集原理、功能种类、现场实测的基础上,结合钻探智能化、自动化的发展方向,运用硬件与软件结合的思想,设计了实时测量钻探参数的方案。论文首次提出使用DBSCAN（针对噪声空间基于分布密度进行聚类的算法）密度聚类法分析钻进参数,结合光电编码器增量的正负性进行工况判别,以获取钻头位置以及钻孔深度。该方案可以判别钻进状态,获取钻进工艺参数,将测量数据作为所钻地层的可钻参数来反演地层。钻机的自动化、智能化研究能获取大量地层资料,有利于推进钻进工艺学发展,实现从经验钻探到智能钻探进的突破。同时,为智能钻进系统奠定基础。     

气候变化与人类活动对石家庄市藁城区地下水位埋深的影响分析

为了探寻石家庄市藁城区地下水埋深动态变化规律,以藁城区2001—2018年的年降水量、地下水人工开采量等数据为基础,对藁城区地下水位埋深进行研究。首先采用P-Ⅲ型曲线法确定降水序列的丰、平、枯年份,分析不同降水量情况下地下水位埋深变化规律;其次,利用地下水开采潜力系数法和灰色关联度法对人工开采量和地下水位埋深的关系进行研究。结果表明：1）藁城区地下水位埋深在2001—2016年逐渐增大,在2016—2018年趋于减小,2016年为转折点;在空间上藁城区地下水位埋深呈现出北部埋深小、南部埋深大的特征,北部水位埋深较同期南部水位埋深要浅5~10 m。2）降水是驱动藁城区地下水位埋深变化的重要因素,枯水年水位埋深变幅在0.8~1.5 m之间,平水年水位埋深变幅在0.3~1.2 m之间,丰水年水位埋深变幅在0.3~1.1 m之间。主灌期（3—6月）的地下水位埋深增加速率均为cm/d级,非主灌期（7—10月）的地下水位埋深减少速率均为mm/d级。3）人工开采是驱动藁城区地下水位埋深变化的主导因素,其中农业开采量占人工开采量的80%。综上认为,藁城区一直处于严重超采状态,地下水累计超采量每增加1亿m³,地下水位埋深增加0.45 m。     

The relationship between groundwater and natural vegetation in Qaidam Basin

To accurately evaluate ecological risks trigged by groundwater exploitation, it must be clarified the relationship between vegetation and groundwater. Based on remote sensing data sets MOD13Q1, groundwater table depth (WTD) and total dissolved solids (TDS), the relationship between groundwater and natural vegetation was analyzed statistically in the main plain areas of Qaidam Basin. The results indicate that natural vegetation is groundwater-dependent in areas where WTD is less than 5.5 m and TDS is less than 7.5 g/L. Aquatic vegetation, hygrophytic vegetation and hygrophytic saline-alkali tolerant vegetation are mainly distributed in areas with WTD <1.1 m. Salt-tolerant and mesophytic vegetation mainly occur in areas with WTD of 1.4-3.5 m, while the xerophytic vegetation isprimarily present in areas where WTD ranges from 1.4 m to 5.5 m. Natural vegetation does not necessarily depend on groundwater in areas with WTD >5.5 m. For natural vegetation, the most suitable water TDS is less than 1.5 g/L, the moderately suitable TDS is 1.5-5.0 g/L, the basically suitable TDS is 5.0-7.5 g/L, and the unsuitable TDS is more than 7.5 g/L.     

干旱区地下水位降幅空间分布特性研究

基于GIS和地理统计学的理论、方法对所取观测井地下水位降幅数据进行空间分布特征分析。结果表明:数据服从正态分布,结构符合球状模型,空间数据存在东西方向和南北方向的二价函数趋势;地下水位降幅由北向南呈环状递减,最深降幅达30m,绿洲群大部分居于20～30m降幅之间,为地下水开采密集区,大于10m降幅的面积约69300hm2。利用Kriging最优内插法生成等值线图,可以更准确和直观地展示整个研究区的地下水资源状况、生态环境可能发生退化的区域及未来发展方向。     

有机质热演化过程中地层压力的作用与影响

压力对有机质演化的影响长期以来争论不断,共有3种不同意见：压力对有机质演化没有影响,压力促进有机质的演化,压力抑制有机质的演化。通过对前人所做实验的实验设备、实验样品及实验结果的分析对比发现：不同实验结果主要是由于不同实验条件引起的,特别是实验系统和加压方式的不同,对实验结果影响最大,所代表的地质意义也不同。综合分析结果表明,当压力的增加表现为沉积有机质受到的有效应力增加时可以促进有机质生烃;当压力的增加表现为孔隙流体压力增加时,有机质生烃过程将受到抑制;另外,这两种情况都可能使干酪根的镜质组反射率降低,易使人得出压力增加抑制有机质演化的结论。进一步对压力影响有机质演化的成因机制进行了分析,发现在有机质演化的不同阶段因异常压力的增压机制不同,压力在有机质演化过程中所表现出来的作用也有差异。     

深基础降水喷射泵的特性方程

为方便工程技术人员优化设计并合理地选用降水同心式喷射泵, 介绍了同心式喷射泵井点降水系统结构和应用特点, 建立了深层降水喷射泵降深与结构、性能参数等之间的优化数学模型.既可通过该数学模型, 按降水深度和排水量的要求, 选择工作泵的压力和流量, 设计喷射泵的结构; 又可根据喷射泵设计的数学模型计算特定降深的排水量, 进行深基础降水设计.      

地下闭式循环地热交换发电系统简介

为解决能源问题而提出了地下闭式循环地热交换发电系统.该系统地下部分通过全井下套管形成一个封闭系统,克服了传统地热发电和干热岩发电受地质条件制约、对环境造成危害等缺点,是一种新型的不依赖位置、环境友好的地热发电系统.采用大位移技术进行钻井,应用悬链线技术对井身剖面结构进行了优化,提出了地下连接技术要求,应用分支井和膨胀套管技术固井,设计了水泥配方并进行了相关试验,优化了载热流体,计算了有机工质朗肯循环(ORC)的发电效率.