轨道交通沿线土地溢价归公的政策与实践——以东莞市为例

轨道交通周边土地开发和溢价归公有助于缓解城市财政压力,推动公交都市建设。结合国外实施溢价归公的政策和实践模式,以东莞市为例,在资料收集、政策分析、文本和案例解读的基础上,探讨了中国城市政府在规划和建设轨道交通中,以土地溢价归公反哺轨道交通融资的政策安排和实施效果。结果表明：1）溢价归公的本质是以特定方式实现正外部效应的内部化,由于土地制度和税收体系的差异,欧美地区溢价归公主要依赖多样化的土地税收体系,而中国城市的实践主要借鉴了“轨道+物业”的联合开发模式;2）东莞市溢价归公策略的形成是综合开发规划编制和审批、沿线土地控制和储备、土地发展权转移、土地增值分配等核心环节有效协调的结果;3）东莞轨道交通沿线土地开发能形成可观的财政收益,潜在土地收益占轨道资金总需求的比例超过20%,但在实施过程中仍面临较大困难。东莞市案例能为其他城市轨道交通融资、土地开发和溢价归公的政策体系编制和有效实施提供一定的参考。     

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.     

山东省地面沉降监测与防治工作进展

近年来,山东省地面沉降监测与防治工作取得了重要进展,初步建立了以二等水准路线、全球定位系统(GPS)、基岩标分层标和地下水监测为基础的"四网合一"地面沉降监测体系,INSAR监测实现了山东全省覆盖。监测成果显示,山东省地面沉降主要位于东营市广饶县、滨州市博兴县、聊城市茌平县,沉降速率呈加快趋势,造成建筑物地基下沉、房屋开裂、地下管道破损等一系列地质环境问题。     

波段选择协同表达高光谱异常探测算法

高光谱遥感影像具有光谱分辨率极高的特点,承载了大量可区分不同类型地物的诊断性光谱信息以及区分亚类相似地物之间细微差别的光谱信息,在目标探测领域具有独特的优势。与此同时,高光谱遥感影像也带来了数据维数高、邻近波段之间存在大量冗余信息的问题,高维度的数据结构往往使得高光谱影像异常目标类和背景类之间的可分性降低。为了缓解上述问题,本文提出了一种基于波段选择的协同表达高光谱异常探测算法。首先,使用最优聚类框架对高光谱波段进行选择,获得一组波段子集来表示原有的全部波段,使得高光谱影像异常目标类与背景类之间的可分性增强。然后使用协同表达对影像上的像元进行重建,由于异常目标类和背景类之间的可分性增强,对异常目标像元进行协同表达时将会得到更大的残差,异常目标像元的输出值增大,可以更好地实现异常目标和背景类的分离。本文使用了3组高光谱影像数据进行异常目标探测实验,实验结果表明,该方法与其他现有高光谱异常目标探测算法对比,曲线下面积AUC(Area Under Curve)值更高,可以更好地实现异常目标与背景分离,能够更有效地对高光谱影像进行异常目标探测。     

Method for evaluating the degrees of land use sustainability of mountainous county and its application in Yunnan Province,China

The evaluation of sustainable land use is the key issue in the field of studying the sustainable land utilization. In general analysis, the sustainable land use is evaluated respectively from its ecological sustainability, economic sustainability and social sustainability in China and other countries in recent years. Although this evaluation is an important work, it seems insufficient and hard to comprehensively reflect the whole degree of land use sustainability. Thus, to make up this deficiency, this paper brings forward the evaluation indexes, which make it possible to quantitatively reflect the whole degree of land use sustainability, namely, the concept of ＂degrees of overall land use sustainability＂ （Dos）, and research and measurement development of the method of and calculation in Dos. Taking the evaluation of the degree of land use sustainability in county regions of Yunnan Province as the actual example for analysis, results are basically as follows：
1） The degree of land use sustainability （Dos） is the ration index to organically and systematically integrate the degree of ecological friendliness （DeF）, the degree of economic viability （Dev） and the degree of social acceptability （Dsa）, able to comprehensively reflect the whole sustainability degree of regional land use
2） Based on the value of Dos, the grading system and standard for the sustainability of land use may be established and totally divided into five grades, namely, the high-degree sustainability, middle-degree sustainability, low-degree sustainability, conditional sustainability and non-sustainability. Meanwhile, the standard for distinguishing sustainability grades has also been confirmed so as to determine the nature of sustainability degrees in different grades. This makes the possibility for the combination of nature determination with ration in research result and provides with the scientific guideline and decision-making gist for better implementation of sustainable land use strategy.
3） The pract     

TEMPORAL TRENDS IN SOIL PRODUCTIVITY EVALUATIONS*

Studies of soil productivity must compensate for the effects of temporal trends in order to examine the pattern of crop yields along spatial gradients. An analysis of the published yield estimates for 30 soils in 233 counties, however, did not find consistent yield increases over the past three decades. On the contrary, the yield estimates for many soils were markedly uniform since 1972. The uniformity appears to have two causes: the acknowledged difficulty of making yield estimates in a time of increasing variability in soil and crop management, both within and between regions, and surveyors' awareness of data stored in a national soils data base. The effect is to cast doubt on soil productivity data reported in county soil surveys published between 1973 and 1988.     

A unique Galactic planetary nebula with a [WN] central star

We report the discovery of the first probable Galactic [WN] central star of a planetary nebula (CSPN). The planetary nebula candidate was found during our systematic scans of the AAO/UKST Hα Survey of the Milky Way. Subsequent confirmatory spectroscopy of the nebula and central star reveals the remarkable nature of this object. The nebular spectrum shows emission lines with large expansion velocities exceeding 150 km s⁻¹, suggesting that perhaps the object is not a conventional planetary nebula. The central star itself is very red and is identified as being of the [WN] class, which makes it unique in the Galaxy. A large body of supplementary observational data supports the hypothesis that this object is indeed a planetary nebula and not a Population I Wolf–Rayet star with a ring nebula.