放牧对浑善达克沙地丘间低地植被群落及土壤的影响

为探究放牧对丘间低地植被群落及土壤的影响,分析了浑善达克沙地丘间低地在重度和轻度放牧下植被的地上生物量、物种重要值、物种丰富度、Shannon-Wiener多样性指数、Pielou均匀度指数、Simpson生态优势度指数及0~10 cm土壤中黏粒、粉粒、砂粒、有机碳和全氮含量。结果表明：（1）植被地上生物量、土壤黏粒、粉粒、砂粒、土壤有机碳和全氮含量在不同放牧程度下存在极显著差异（P<0.01）,物种丰富度、Shannon-Wiener多样性指数和Pielou均匀度指数在不同放牧程度下差异不显著（P>0.05）,Simpson生态优势度指数在不同放牧程度下差异显著（P<0.05）。（2）放牧区植被以禾本科为主,禾本科植被地上生物量占整个植被群落的54.88%~57.76%;重度放牧区植被地上生物量为63.59 g·m^-2,比轻度放牧区低26.61%。（3）羊草（Leymus chinensis）和狗尾草（Setaria viridis）是放牧区的优势种,其重要值依次为14.16%（重度放牧区）和19.10%（轻度放牧区）、13.40%（重度放牧区）和15.42%（轻度放牧区）,重度放牧下雾滨藜（Bassia dasyphylla）、克氏针茅（Stipa krylovii）和猪毛蒿（Artemisia scoparia）的重要值较显著高于轻度放牧区,而羊草则低于轻度放牧区。（4）重度放牧加剧了土壤沙漠化,使砂粒含量增加,草地生产力下降,土壤有机碳和全氮含量降低。     

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。     

土地资源体多级变粒度空间数据管理方法

结合资源体的概念和土地要素功能提出了土地资源体概念,将土地资源数据对象组织成土地利用资源体、土地权属资源体等不同类型的土地资源体.在土地资源体对象基础上,结合具体的土地资源管理业务需要,提出了土地资源体多级变粒度数据组织管理模式,对土地资源体横向按资源体、图库、图层集合、图层和地物等不同资源授权粒度,纵向按多级区域层次管理的方式进行管理.国家、省、市级别的土地资源管理以县为基本单位,以区域特征管理国家、省、市、县等逻辑关系,县级的土地资源时空数据按资源体、图库、图层集合、图层和地物等不同资源授权粒度来对数据进行管理.在具体的土地资源管理和业务实施时,可以根据实际的需要对位于不同位置、不同层次、不同资源体类型的土地资源体进行动态组合.     

德州市临盘采油区地面沉降监测

济南市的鹊山上设立了3块岩层水准标石的原点组。使用美国Tri mble Di Ni 12电子水准仪和条码式铟钢水准标尺施测一等精密水准82.2 km,二等精密水准30.8 km,联测各类水准点35个。对观测结果进行统计与分析表明,在临盘采油区(以后仓西北采油四队LY18为中心)形成了一个较明显的沉降区域,年沉降量为54.3 mm。建议在其周边增埋地面观测标石,进行加密观测,以掌握其变化规律。     

Estimation of the Land Surface Emissivity in the Hinterland of Taklimakan Desert

An accurate accounting of land surface emissivity(ε) is important both for the retrieval of surface temperatures and the calculation of the longwave surface energy budgets.Since ε is one of the important parameterizations in land surface models(LSMs),accurate accounting also improves the accuracy of surface temperatures and sensible heat fluxes simulated by LSMs.In order to obtain an accurate emissivity,this paper focuses on estimating ε from data collected in the hinterland of Taklimakan Desert by two different methods.In the first method,ε was derived from the surface broadband emissivity in the 8–14 μm thermal infrared atmospheric window,which was determined from spectral radiances observed by field measurements using a portable Fourier transform infrared spectrometer,the mean ε being 0.9051.The second method compared the observed and calculated heat fluxes under nearneutral atmospheric stability and estimated ε indirectly by minimizing the root-mean-square difference between them.The result of the second method found a mean value of 0.9042,which is consistent with the result by the first method.Although the two methods recover ε from different field experiments and data,the difference of meanvalues is 0.0009.The first method is superior to the indirect method,and is also more convenient.     

西安市地面沉降探讨

本文在讨论西安市地面沉降特征的基础上,论述了西安市地下水开采量、承压水位变化与地面沉降三者之间在时间和空间上的对应关系,初步认定大量开采地下水是地面沉降主要原因。典型水准点沉降量与邻近自备井承压水位变化相关分析表明,两者间相关性极强。经综合分析市区地貌、第四系地质、工程地质和水文地质特征并进行工程地质分层后,可确定出市区地面沉降的第一和第二主要压缩层。据地面沉降与承压水位下降值回归方程所预测的地面沉降发展趋势表明,西安地面沉降今后还会继续发展,将对西安城市建设产生严重影响,故应采取相应治理措施。     

“股份+合作”土地流转模式的实践和启示——以宁阳县蒋集镇郑龙村为例

近年来,宁阳县蒋集镇郑龙村对土地流转进行了积极探索,形成了"股份+合作"的土地流转模式,这种模式有一套完整机制,取得了合作多赢的成效,并给国土资源工作一定的启示。这一模式得到国家农业部及省市有关专家充分肯定,认为是全国土地流转成功模式之一。     

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。     

Advances in understanding of the mechanism for generation of earthquake thermal precursors detected by satellites

Stresses building up during an earthquake preparation phase also manifest themselves in the form of a so called increased land surface temperature (LST) leading to a thermal precursor prior to the earthquake event. This phenomenon has now been validated by our observations of short-term thermal anomalies detected by infrared satellite sensors for several recent past earthquakes around the world. The rise in infrared radiance temperature was seen to vary between 5 and 12 °C for different earthquakes. We discuss in this paper different explanations for the generation of such anomalies that have been offered. Emission of gases due to the opening and closure of micropores upon induced stresses and also the participation of ground water have been propounded as a possible cause for generation of thermal anomalies. Seismo-ionosphere coupling, by which gases like radon move to the earth–atmosphere interface and cause air ionization thus bringing about a change in air temperature, relative humidity, etc., has been put forth by some workers. A mechanism of low frequency electromagnetic emission was tested and experimented by scientists with rock masses in stressed conditions as those that exist at tectonic locations. The workers proposed the positive hole pair theory, which received support from several scientific groups. Positive holes (sites of electron deficiency) are activated in stressed rocks from pre-existing yet dormant positive hole pairs (PHPs) and their recombination at rock–air interface leads to a LST rise. A combination of remote sensing detection of rock mechanics behavior with a perception of chemistry and geophysics has been applied to propose the remote sensing rock mechanics theory. Remote sensing detections of such anomalies confirm so far proposed lab theories for such a hotly debated field as earthquake precursor study by providing unbiased observations with consistency in time and space distribution.     

Classifier ensembles for land cover mapping using multitemporal SAR imagery

SAR data are almost independent from weather conditions, and thus are well suited for mapping of seasonally changing variables such as land cover. In regard to recent and upcoming missions, multitemporal and multi-frequency approaches become even more attractive. In the present study, classifier ensembles (i.e., boosted decision tree and random forests) are applied to multi-temporal C-band SAR data, from different study sites and years. A detailed accuracy assessment shows that classifier ensembles, in particularly random forests, outperform standard approaches like a single decision tree and a conventional maximum likelihood classifier by more than 10% independently from the site and year. They reach up to almost 84% of overall accuracy in rural areas with large plots. Visual interpretation confirms the statistical accuracy assessment and reveals that also typical random noise is considerably reduced. In addition the results demonstrate that random forests are less sensitive to the number of training samples and perform well even with only a small number. Random forests are computationally highly efficient and are hence considered very well suited for land cover classifications of future multifrequency and multitemporal stacks of SAR imagery.