台湾西南部泥岩土地利用型态与环境劣化趋势之分析

台湾泥岩恶地因其特殊之土壤理化性质及区域微气候的相互恶性循环，衍生生态环境等问题。在以往之35年，裸化面积从1967年的2532hm^2，至2001年11月已扩大为15539hm^2。其表土大量流失、崩塌、河川含砂量激增、植被退化与微气候变异等破坏，更显示泥岩之环境劣化问题。以SPOT卫星影像判识泥岩裸露面积，探讨不同时期之地景变异，并应用地景生态理论量化泥岩地表不同土地利用之空间结构变化，分析地景结构变迁之生态内涵与生态指标意义。因子分析结果其主要变异为多样性因子与形状破碎型因子所影响，而应用马可夫链模式计算出不同时期之土地利用变迁内涵，此结果搭配指标分析可解释泥岩裸露面积与竹林面积皆持续扩大，乃由人为土地利用之活动及植被变迁所引起。     

Disjunctive Kriging with Hard and Imprecise Data

This paper presents a methodology for assessing local probability distributions by disjunctive kriging when the available data set contains some imprecise measurements, like noisy or soft information or interval constraints. The basic idea consists in replacing the set of imprecise data by a set of pseudohard data simulated from their posterior distribution; an iterative algorithm based on the Gibbs sampler is proposed to achieve such a simulation step. The whole procedure is repeated many times and the final result is the average of the disjunctive kriging estimates computed from each simulated data set. Being data-independent, the kriging weights need to be calculated only once, which enables fast computing. The simulation procedure requires encoding each datum as a pre-posterior distribution and assuming a Markov property to allow the updating of pre-posterior distributions into posterior ones. Although it suffers some imperfections, disjunctive kriging turns out to be a much more flexible approach than conditional expectation, because of the vast class of models that allows its computation, namely isofactorial models.     

Surface sediment Chironomidae (Insecta: Diptera) distributions along an ecotonal transect in subarctic Fennoscandia: developing a tool for palaeotemperature reconstructions

We used multivariate statistical techniques to analyse the distributions of surface sediment chironomid assemblages with respect to surface-water temperature, and an additional set of 27 environmental variables, in 30 freshwater lakes of northern Fennoscandia. Our study transect spans boreal coniferous forest to subarctic tundra and includes a steep temperature gradient. Canonical correspondence analysis (CCA) with forward selection and associated Monte Carlo permutation tests revealed that there were statistically significant (P<0.05) relationships between chironomid distributions and two environmental variables, namely lakewater temperature and maximum lake depth. A constrained CCA with temperature as the only predictor variable suggested that the relationship between lakewater temperature and chironomid composition was sufficiently robust for developing a weighted-averaging (WA) based quantitative inference model that will allow palaeotemperature reconstructions using subfossil chironomid remains preserved in lake sediments.     

含粗粒金矿样品采集加工与分析研究进展

含粗粒金矿,由于粗粒金的存在使其样品的采集、加工和分析极具挑战性,如何获得具有代表性和均匀性的化学分析样品,并提供准确的分析结果,长期以来一直是该类金矿资源勘查评价急待解决的技术难题。本文对近年来国内外含粗粒金矿样品的采集、加工和分析方法等3方面开展的研究工作及主要成果进行归纳分析,认为:1含粗粒金矿样品的采集是确保样品代表性的首要环节,含粗粒金矿样品分析结果的潜在误差有80%来源于样品采集,因此研究经济、有效的样品采集方法至关重要。2含粗粒金矿样品的加工主要从提高自然金的粉碎度,改进加工流程,选择样品加工设备等方面进行,但查明金的粒度分布及伴生矿物是拟定样品加工流程的关键。3含粗粒金矿样品的分析方法有常规的化学分析方法、批量浸金法和人工重砂加权平均法,相对于复杂的加工流程研究,后者有望成为此类样品经济有效的分析方法。本文指出,含粗粒金矿资源评价质量的误差来源于地质、采样、加工、分析等诸多方面,总体而言应最小化所有阶段误差,应特别重视样品采集方法的研究,确保采集样品的代表性是提高该类金矿资源评价质量的前提。     

水库流域体积降水量预报方法研究

根据广东飞来峡水库流域汇流特征,将全流域划分为5个支流,并采用求积仪分别计算各支流面积;然后用加权平均法计算各支流的面雨量,并将各支流面雨量对相应的支流面积进行积分,计算各支流体积降雨量;利用洪水过程飞来峡水库入库流量、出库流量和水库流域蒸发量对体积降水量预报结果进行验证,求出误差订正系数.结果表明:利用加权平均法计算的水库流域体积降水量,经过误差订正后,预报准确率可控制在90%左右,基本满足预报业务服务要求.     

基于约束Markov决策过程的初至自动识别技术

随着地震数据采集技术的进步,地震数据量日益增加,全自动、高精度的地震初至走时拾取技术受到了更加广泛的关注.本文将初至拾取看作特征空间内带约束的Markov决策过程,在奖励函数空间,按一定准则全局寻优获得积累奖励值最大的路径,从而达到在高维空间自动拾取初至信息的目的.同时,状态值函数中包含与距离相关的折扣因子γ,使Markov决策过程拾取初至能够考虑地震数据的横向连续性,并且回避地震数据中的坏道信息.在此基础上,本文方法进一步引入受空间几何信息约束的动作（Actions）和转移概率（Transitions Probability）,从而降低了对起始状态和折扣因子选取的难度,让地震数据初至走时拾取更加准确和自动化.实际数据测试结果表明,在初至能量较弱（信噪比较低）情况或浅层存在相邻较近复杂波形时,本文提出的约束Markov算法仍能准确地进行初至走时的自动拾取,并且具有一定的质量监控能力,让拾取结果更有物理意义.

     

历史数据和强化学习相结合的低频轨迹数据匹配算法

针对低频(采样间隔大于1min)轨迹数据匹配算法精度不高的问题,提出了一种基于强化学习和历史轨迹的匹配算法HMDP-Q,首先通过增量匹配算法提取历史路径作为历史参考经验库;根据历史参考经验库、最短路径和可达性筛选候选路径集;再将地图匹配过程建模成马尔科夫决策过程,利用轨迹点偏离道路距离和历史轨迹构建回报函数;然后借助强化学习算法求解马尔科夫决策过程的最大回报值,即轨迹与道路的最优匹配结果;最后应用某市浮动车轨迹数据进行试验。结果表明:本文算法能有效提高轨迹数据与道路匹配精度;本算法在1min低频采样间隔下轨迹匹配准确率达到了89.2%;采样频率为16min时,该算法匹配精度也能达到61.4%;与IVVM算法相比,HMDP-Q算法匹配精度和求解效率均优于IVVM算法,16min采样频率时本文算法轨迹匹配精度提高了26%。     

Swelter in the city: Urban greenery and its effects on temperature in Guwahati,India

Changing urban landscape with multistoried high rises, roads and pavements is continuously reducing urban green space. These structures result in high surface temperature variation within cities. To explore the relationship between surface temperature and normalized difference vegetation index (NDVI), this study estimates two models—geographically weighted regression (GWR) and a fixed effect panel data model in relation to the Guwahati Metropolitan Area (GMA), a secondary city in north east India. The results indicate the superiority of GWR regression in presence of spatial dependence. Panel data analysis shows that the densely populated urban areas in the GMA with less than 10 per cent greenery are 1°C warmer than the sub-urban areas with 50 per cent greenery.     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

Texture Segmentation Based on Image Model and Neural Network

INTRODUCTIoNImagetextureanalysisisanimportantpartofresearchin-tocomputervision.Forobjectidentificationandunderstand-ing,textureanalysisisthebasisoftheresearchwork.Ingeneral,texturecanberegardedasakindofstructurethatconsistsofmanytextureelementsorpatternswhicharemoreorlesssimilar,i.e.,primitivesthatformtexturesandspatialdependenceorinteractionbetweentheprimitives.Ex-tensiveresearchhasbeendoneintextureanalysis,andrefer-ence(Haralick,l979)hasmadeathoroughsurvey.Amongthesetextureanalysismetho…