Combining Decision Trees with Angle Indices to Identify Mangrove Forest at Shenzhen Bay,China

Mangroves are woody plant communities in the intertidal zone of tropical and subtropical coasts that play an important role in these zones. The infrared wave band is one of the key bands in the remote sensing identification of mangrove forest, and ALI (advanced land imagery) has a large number of infrared bands. Two angle indices were proposed based on liquid water absorption at band 5p and band 5 of EO-1 ALI, denoted as β_1.25 and β_1.65 respectively. A decision tree method was adopted to identify mangrove forest using remote sensing techniques for β_1.25-β_1.65 and NDVI (normalized difference vegetation index) for EO-1 ALI imagery acquired at Shenzhen Bay. The results showed that the reflectance of mangrove forests at band 5p and band 5 was significantly lower than that of terrestrial vegetation due to the characteristics of coastal wetlands of mangrove forests. This resulted in a greater β_1.25-β_1.65 value for mangrove forest than terrestrial vegetation. The decision tree method using β_1.25-β_1.65 and NDVI effectively identifies mangrove forest from other land cover categories. The misclassification and leakage rates were 4.29% and 5.11% respectively. ALI sensors with many infrared bands could play an important role in discriminating mangrove forest.     

基于决策树模型的海岸带分类方法研究

海岸带地物分布复杂,地物混淆常造成海岸带提取困难。该文以江苏省粉砂淤泥质海岸为研究对象,运用图像光谱特征、纹理特征并引入地学知识,构建研究区遥感图像分类决策树模型,并利用ETM 图像进行海岸地物分类研究。结果表明:采用的决策树模型可以较好地结合纹理信息和地学知识,解决遥感图像中复杂地物分类过程中的混淆现象,分类精度达89.26%,比最大似然法分类精度提高了15.19%。     

Gentrifying rural community development: A case study of Bama Panyang River Basin in Guangxi,China

Journal of Geographical Sciences - Rural gentrification is deeply characterized by institutional context and spatiotemporal heterogeneity. Based on a diachronic field investigation, this paper...     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

多维决策圈闭评价方法及其应用

多维决策就是在具有相互冲突、相互影响的多个因素下对评价目标进行的决策,把它应用到圈闭评价时,就是把影响圈闭评价的各个因素看成一个整体,这些影响因素共同反映圈闭的优劣,将多个因素系统合成为一个能从总体上度量圈闭优劣的单因子来进行评价优选。在使用多维决策对研究区进行实际的圈闭评价时,通过多维目标函数,求解各圈闭与所假设的最优和最劣圈闭之间的距离,最后得到综合评价因子序列,此时选出距最优圈闭较近而距最劣圈闭较远的圈闭可作为优先勘探的对象。对四川盆地某区进行了圈闭评价实践,并与地质风险概率法作了对比,证明多维决策圈闭评价方法是有效的。此方法具有简单、实用、易操作、分辨率高等优点,人为因素的干预比较少,预测结果更为客观。     

黑河流域中游水资源管理决策支持系统设计与实现

针对黑河流域水资源管理面临的实际问题以及各决策部门之间的关系,以决策支持系统三库结构为基础,构建了黑河流域中游水资源管理决策支持系统(HD).系统采用了客户端/服务器(C/S)和浏览器/服务器(B/S)两种架构,并根据黑河流域中游水务管理决策部门之间的行政级别,设计了系统功能访问权限控制机制和数据审核机制.基于C/S结...     

基于神经网络的专家系统在温室控制中的应用

为了实现温室控制,针对温室环境的多输入、多输出、非线性和难以建立数学模型等特点,提出一种基于BP神经网络的专家系统并用于温室控制。该方法将传感器采集的温度、湿度等信息输入到神经网络专家系统,在获得决策结果的同时通知控制部分执行相应的决策。这种方法不仅解决了传统专家系统知识获取的瓶颈问题、推理能力差、智能化低的缺点,而且克服了神经网络不具有解释功能的问题。总之,成功实现了神经网络和专家系统功能上的互补,较好的用于温室控制。     

新一轮就矿找矿

本文简要回顾了二十世纪五、六十年代就矿找矿的历史,进而提出新一轮的就矿找矿。相比之下,新一轮就矿找矿具有新的特点。深部找矿实则是一种就矿找矿,地壳连续成矿理论、深部流体(成矿)作用理论、成矿台阶理论都为新一轮就矿找矿提供了理论依据。深部找矿在国内外初显成效,湘中地区亦有很多成功案例。本文从3个方面总结了深部找矿的一些经验标志,即矿种及矿种组合系列标志、花岗岩成矿专属性标志、幔源成因矿床的鉴别标志。此外,辨别成矿流体的深(幔)源标志、加强成矿规律研究、更新观念、引进新技术新方法,都是实际深部找矿工作中需要注意的。     

基于TM影像属性和形态特征的土地覆被制图方法

本文以浙江省中南部地区不同时相30m分辨率的2景TM影像为基本数据,采用面向对象的方法实现了研究区的土地覆被制图。首先,在eCognition软件中采用多尺度分割算法,以光谱信息、纹理特征、几何特征等实现研究区的对象分割,使分割后的对象边界与实际地物边界尽量保持一致,通过建立多层次地物特征规则,进行最优分割尺度下的遥感多层次识别分类;然后,分析可用于分类的属性特征和形态特征,通过对这些特征的统计值对比分析,选取了对象的紧致度、长宽比、MNDWI、LBV等特征构建了决策树模型,实现了研究区1：25万的土地覆被分类;最后,采用目视解译和野外样本2种方式对分类结果进行精度验证,其中,目测随机样点评价得到的总体精度为87.66%,野外样本点评价得到的总体精度为83.38%。研究表明：面向对象的分类方法不仅具有较高的精度,而且图斑与实际地物边界能较好地吻合,很好地避免了混合像元误分的现象,同时能消除像元分类的“椒盐现象”。     

Task-oriented information value measurement based on space-time prisms

Recent years have witnessed a large increase in the amount of information available from the Web and many other sources. Such an information deluge presents a challenge for individuals who have to identify useful information items to complete particular tasks in hand. Information value theory (IVT) from economics and artificial intelligence has provided some guidance on this issue. However, existing IVT studies often focus on monetary values, while ignoring the spatiotemporal properties which can play important roles in everyday tasks. In this paper, we propose a theoretical framework for task-oriented information value measurement. This framework integrates IVT with the space-time prism from time geography and measures the value of information based on its impact on an individual’s space-time prisms and its capability of improving task planning. We develop and formalize this framework by extending the utility function from space-time accessibility studies and elaborate it using a simplified example from time geography. We conduct a simulation on a real-world transportation network using the proposed framework. Our research could be applied to improving information display on small-screen mobile devices (e.g., smartwatches) by assigning priorities to different information items.