Mapping multiple tree species classes using a hierarchical procedure with optimized node variables and thresholds based on high spatial resolution satellite data

ABSTRACT

Tree species distribution mapping using remotely sensed data has long been an important research area. However, previous studies have rarely established a comprehensive and efficient classification procedure to obtain an accurate result. This study proposes a hierarchical classification procedure with optimized node variables and thresholds to classify tree species based on high spatial resolution satellite imagery. A classification tree structure consisting of parent and leaf nodes was designed based on user experience and visual interpretation. Spectral, textural, and topographic variables were extracted based on pre-segmented images. The random forest algorithm was used to select variables by ranking the impact of all variables. An iterating approach was used to optimize variables and thresholds in each loop by comprehensively considering the test accuracy and selected variables. The threshold range for each selected variable was determined by a statistical method considering the mean and standard deviation for two subnode types at each parent node. Classification of tree species was implemented using the optimized variables and thresholds. The results show that (1) the proposed procedure can accurately map the tree species distribution, with an overall accuracy of over 86% for both training and test stages; (2) critical variables for each class can be identified using this proposed procedure, and optimal variables of most tree plantation nodes are spectra related; (3) the overall forest classification accuracy using the proposed method is more accurate than that using the random forest (RF) and classification and regression tree (CART). The proposed approach provides results with 3.21% and 7.56% higher overall land cover classification accuracy and 4.68% and 10.28% higher overall forest classification accuracy than RF and CART, respectively.     

地理国情监测地表覆盖分类数据的质量控制

自2016年开始,地理国情工作的重心由普查转移到监测上来。地理国情监测地表覆盖分类数据成果的各项质量指标均比普查时更严格,如何更好地做好地表覆盖分类数据质量控制工作,直接影响监测数据成果的质量水平。本文结合山东省2019年度国情监测数据成果验收工作,对地表覆盖分类数据成果质量问题进行分析探讨,并对提高地表覆盖分类数据的质量水平提出建议。     

Automatic soil-boundary location from transect data

Spatially distributed soil data possess a short-range erratic variation, an irregular longer range pattern, and maybe multivariate. In order to reveal a pattern or meaning in them, they are usually classified by drawing boundaries. A method is described for determining boundaries automatically on transects. A small portion of a sampled transect is taken and divided about its midpoint, and Mahalanobis' generalized distance, Dor D²,between the two halves calculated from the sample data. The procedure is repeated for portions of the same length at positions one-sampling interval apart along the transect. High peaks on the resultant series of D² identify the boundaries. The length of portions is set equal to, or somewhat less than, the expected average distance between boundaries, and is determined by constructing correlograms of principal components. The lag distance over which fairly steady decay occurs is related closely to the distance between boundaries. The procedure is illustrated with data from a 6-km transect in Oxfordshire and shows good agreement with boundaries drawn by combined air-photo interpretation and field judgment. A means of extending the procedure to two dimensions is suggested.     

前馈神经网络在矿物识别方面的应用

本文首先介绍人工神经网络的发展现状，然后着重阐述BP人工网络的基本原理和算法，并以蓝宝石的产地识别和石榴子石分类识别作为具体实例，用此说明人工神经网络方法在矿物学中的应用，最后对识别结果及BP算法本身进行了讨论。     

论酸性－中酸性火成岩中包体的分类与命名

本文针对在酸性－中酸性火成岩中包体分类与命名方面存在的一些问题，阐释和厘定了有关包体名称和概念的基本含义．在此基础上，对现有包体名称和概念进行了归类．根据包体的特征及其研究工作的特点，提出了包体的分类命名原则．同时，通过分析寄主岩及其包体形成的地质作用过程，系统提出了包体的成因分类．     

应用遗传算法建立地震预报的分类体系初探

本文对模拟自然界生物进化过程的遗传算法和用它所建立的分类体系进行了简要介绍，并将它们应用于地震预报探索研究，建立了初步的地震预报分类体系，结果表明：采用具有自动学习和自相适应的方法，结合现有的研究成果，可以将地震活动性的时空参数结合起来综合考虑，获得较为优化的地震预报规则集。     

西安医疗热矿水分类及其利用

西安地热资源较丰富，目前开凿的热水井多用于洗浴医疗。区内不同类型的地下热水其水质各具特点。按医疗效矿水分类，基岩热矿水属氟水、硅水和氡水，第三系热矿水属氟水、硅水、碘水、棚木及锶水；第四系热矿水属氟水。本文初步分析了西安医疗热矿水的分类及其利用，并提出了进一步开发利用时注意的问题。     

地质过程动力学体系、研究层次及认识论

本文根据作者个人的观点讨论了地质过程动力学的本质特征,根据地质过程动力学广泛的研究对象和研究内容归纳了地质过程动力学的分支体系,并依据地质过程动力学的不同研究水平和研究方法把地质过程动力学划分成3个不同的层次,分别讨论了各层次动力学的研究方法。最后,作者讨论了有关地质过程动力学研究中经常遇到的几个认识问题,期望对地质过程动力学研究起到推动作用。     

应用Fuzzy集理论对地下水位动态分类

本文应用Fuzzy集理论,给出一个对地下水位动态进行分类的数学模型,并借助计算机对西安市部分地区地下水位进行了分类。     

桂东超单元花岗岩各单元特征及其归属探讨

通过对桂东超单元各单元特征的对比,我们认为桂东超单元包括了两类不同地质、岩石、矿物学及地球化学特征的花岗岩,进而探讨了这两类花岗岩的成因及其形成构造环境,得出牛塘、三洞两单元为1型花岗岩,形成于板块碰撞的环境,大塘、寨前、子公坑、五峰仙单元为S型花岗岩,形成于陆一陆同碰环境。建议将牛塘、三洞两单元建立桂东序列,其余四单元归属江西汤湖超单元。