Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules

The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions.     

基于逻辑回归的四川青川县区域滑坡灾害预警模型

四川省青川县滑坡灾害群发,点多面广,区域滑坡灾害预警是有效防灾减灾的重要手段,预警模型是成功预警的核心。由于研究区滑坡诱发机理复杂、调查监测大数据及分析方法不足等原因,传统区域地质灾害预警模型存在预警精度有限、精细化不足等问题。文章在青川县地质灾害调查监测和降水监测成果集成整理与数据清洗基础上,构建了青川县区域滑坡灾害训练样本集,样本集包括地质环境、降雨等27个输入特征属性和1个输出特征属性,涵盖了青川县近9年（2010—2018年）全部样本,数量达1 826个（其中,正样本613个,负样本1 213个）。基于逻辑回归算法,对样本集进行5折交叉验证学习训练,采用贝叶斯优化算法进行模型优化,采用精确度、ROC曲线和AUC值等指标校验模型准确度和模型泛化能力。其中,ROC曲线也称为“受试者工作特征”曲线;AUC值表示ROC曲线下的面积。校验结果显示,基于逻辑回归算法的模型训练结果准确率和泛化能力均较好（准确率94.3%,AUC为0.980）。开展区域滑坡实际预警时,按训练样本特征属性格式,输入研究区各预警单元27个特征属性,调用预先学习训练好的模型,输出滑坡灾害发生概率,根据输出概率分段确定滑坡灾害预警等级。当输出概率P≥40%且P<60%时,发布黄色预警;当输出概率P≥60%且P<80%时,发布橙色预警;当输出概率P≥80%时,发布红色预警。     

矿石体重回归分析在新疆乌宗布拉克矿区的应用研究

在资源储量估算的过程中,矿石小体重的准确与否将直接影响到资源储量估算的客观程度。对矿石小体重的准确预测将需要通过大量的统计分析工作,传统的方法是利用矿石小体重的算术平均值进行估算矿床资源储量,并没有考虑到多矿种对矿石小体重的影响程度。本文利用Excel软件"数据分析"的"回归"功能模块,对实验室所测定的矿石小体重值与其对应品位进行二元线性回归分析,快速、准确地构建矿石体重与其品位的数学模型,从而为资源储量估算提供了更客观、更科学的矿石体重模型。     

中国东部夏季降水与气温的联合EOF分析

采用JEOF等方法分析中国东部夏季降水和气温的协同变化时空分布特征,结果表明:当时间系数为正时,第1典型场降水型态从北向南(下同)呈"++-"分布,气温表现为冷异常,500 hPa回归场在中纬度地区呈显著低压异常,SST回归场表现为太平洋海域呈西北-东南的分布;第2典型场降水呈"+-"分布,气温则呈"-+"分布;第3典型场降水分布呈中间型,气温场呈"-+"分布。     

降水现象仪观测应用评估

利用2017年9月至2018年8月北京20个站降水现象仪采集数据与人工平行观测数据,对降水现象仪进行了对比评估。结果表明:降水现象仪的缺测率为0.01%,空报率为0.6%,捕获率为93.5%,漏报率为27.9%,错报率为10.0%。从统计结果可知,降水现象仪的缺测率、空报率较低,捕获率较高,体现出设备性能良好的一面,漏报率和错报率偏高,表明设备漏识别和错误识别的情况较多,漏报主要发生在弱降水过程中,错报主要出现在毛毛雨的识别上。设备测量和人工观测降水开始时间一致性较好,终止时间一致性偏差;降水现象仪现存问题:在大雨强时易出现雨滴叠加误识别,在小雨强时识别率会降低,在无降水错误输出降水现象方面缺少质控。     

基于偏最小二乘回归的区域换式风速预报订正技术研究

利用偏最小二乘回归技术,将预报产品作为自变量,相应的自动气象站观测资料作为因变量,对2013-2016年冬季浙江省中尺度区域模式预报近地面风速进行订正和评估。所选956站中多数站点风速订正后有所改善,通过定量分析可知浙江西部地区整体改善效果最好,其中效果明显站点占91.7%;中部地区改善效果明显站点占86.5%;东部沿海地区改善效果略差,明显改善的站点占67%。各地级市整体表现均不错,除舟山地区为49.9%外,其他地区风速改善比例均超过50%。选取2017年1月20日浙江东北地区沿海大风过程分析发现订正后的风速与观测风速更为接近,在定海大岛站点(靠里)中表现尤为明显,订正后的结果具有显著参考价值。     

我国华南江南春季雷暴气候特征分析

基于我国华南江南地区274个基本地面气象观测站数据、全国闪电定位数据以及欧洲中心的全球大气再分析数据(ERA-Interim),对1981—2017年华南江南地区的春季雷暴日采用经验正交函数分解方法(EOF),并与气象要素场做回归分析。得出以下主要结论:(1)我国华南江南地区春季雷暴活动高发区主要在广西东部至广东西部;其高峰期在下午18:00和凌晨4:00左右,且大多数雷暴活动持续时间不超过3 h;山区雷暴活动主要在傍晚至夜间;平原雷暴活动主要在白天,高峰在17:00及06:00前后;(2)华南江南地区的雷暴活动存在着3~5年的短周期和16年左右的长周期变化;(3)雷暴日距平EOF分析的前3个主成分累计方差贡献达到72.3%。按其向量场的方差贡献分型,Ⅰ型表现为华南江南雷暴活跃特征呈现较统一的变化规律。深厚西南低涡槽前、上干下湿的水汽层结、上冷下暖的温度层结为华南江南地区发生大范围雷暴天气提供良好的动力、水汽和位势不稳定条件,是华南江南雷暴活跃异常的主要模态;Ⅱ型表现为从华南南部到江西与浙江南部有一条西南-东北向、下宽上窄的雷暴活跃正距平异常区,而两侧为负距平异常区。其环流特征表现为温度整层偏冷,水汽整层偏湿,而西南槽前动力抬升有利于水汽抬升凝结触发对流形成雷暴;Ⅲ型表现为华南和江南地区雷暴活跃特征呈南北反位相异常,其分界线在26 °N附近。其环流特征表现为较强的干冷空气南下与南方暖湿空气在南岭山区对峙形成异常的垂直环流圈。在其上升支,低层干冷空气被卷入中高层使得中高层暖湿空气凝结释放潜热形成对流,造成华南地区多雷暴发生,而江南地区处于垂直环流的下沉支,整层湿度偏干,造成江南地区雷暴相对偏少。      

基于多元线性回归分析的页岩气有利区评价新方法 ——以上扬子地区五峰组—龙马溪组海相页岩为例

本文以四川盆地及其周缘五峰组—龙马溪组页岩气评价为例,总结了页岩气有利区优选的储层参数、保存参数和压力系数等参数,量化了各关键参数平面分布,运用多元线性回归分析方法计算了参数权重,通过多参数加权叠加公式建立了多元线性回归模型:有利区=-0.317+0.75×埋深+0.285×TOC+0.148×RO+0.093×孔隙度...     

Use of SPOT 5 and IKONOS imagery for mapping biocenoses in a Tunisian Coastal Lagoon (Mediterranean Sea)

Mapping marine biocenoses is an efficient method for providing useful data for the management and conservation of Mediterranean lagoons. Fused images from two satellites, SPOT 5 and IKONOS, were tested as management tools for identifying specific ecosystems in the El Bibane lagoon, situated in southern Tunisia near the Libyan border. The objectives of this study were to provide a precise map of the entire El Bibane lagoon using fused images from SPOT 5 and to compare fused images from SPOT 5 and IKONOS over a test-area. After applying a supervised classification, pixels are automatically classified in four classes: low seagrass cover, high seagrass cover, superficial mobile sediments and deep mobile sediments. The maps of the lagoon revealed and confirmed an extremely wide distribution of seagrass meadows within the lagoon (essentially Cymodocea nodosa; 19 546 ha) and a large area of mobile sediments more or less parallel to the shore (3 697 ha). A direct comparison of overall accuracy between SPOT 5 over the entire area, SPOT 5 over the test-area and IKONOS over the test-area revealed that these tools provided accurate mapping of the lagoon environment (83.25%, 85.91% and 73.41% accuracy, respectively). The SPOT 5 images provided greater overall accuracy than the IKONOS image, but did not take into account the heterogeneous spatial structure of the seagrasses and sediments present in the lagoon environment. Although IKONOS imagery provided lower overall accuracy than SPOT 5, it proved a very useful tool for the mapping of heterogeneous structures as it enabled the patchiness of formations to be better taken into account. The use of SPOT 5 and IKONOS fused images appears to be very promising for completing the mapping of lagoons in other regions and countries of the Mediterranean Sea.     

Dissolved organic carbon in the southern Baltic Sea: Quantification of factors affecting its distribution

During a cruise of r/v ‘Oceania’ in May 2006, seven vertical dissolved organic carbon (DOC) concentration profiles were produced against a background of CTD, chlorophyll a (chl a) and phaeopigment concentration profiles. The results indicate distinct vertical and spatial DOC fluctuations, ranging from 248 ± 7 μmol C dm⁻³ at 70 m depth at the westernmost station G/06 to 398 ± 5 μmol C dm⁻³ at 5 m depth at station A/06 in the western Gulf of Gdańsk. DOC concentrations were the highest at 10 m depth, where phytoplankton activity was relatively intensive, as reflected by the active chl a concentration distribution. DOC concentrations decreased towards the sea bottom.