内蒙古地区草原聚落公共设施空间可适性研究--可装配轻体系统的应用

公共设施的适宜性布局是城乡居民享受基本的公共服务权利的基础,随着人民生活水平的不断提高,与公众生活质量息息相关的基本公共服务设施也越来越受到各界关注,合理规划基本公共服务设施建设的相关研究成为焦点。同时,由于经济发展水平与生产生活方式的不同,公共服务均等化推进差异较大,尤其是作为欠发达地区的内蒙古草原聚落,其离散型地域特征加剧了公共服务设施供给的难度。研究选择典型区域（内蒙古正镶白旗）草原聚落,以点带面对空间形态及住民生活状况进行调研分析,探讨草原聚落公共设施布局体系结构与公共服务设施适宜性布局方法,对可装配轻体系统的应用做相应的研究和讨论,提出适应性较强的公共服务空间建构模式。     

综合物探方法在内蒙古草原覆盖区寻找隐伏矿床的应用

内蒙古草原覆盖区是近年来隐伏矿床找矿工作的重点区域。为了寻找一种快速、有效的适合草原覆盖区的找矿方法,在阿鲁科尔沁旗某铁多金属矿区进行了大功率激电和EH4 相结合的地球物理方法实验性研究。结果表明,大功率激电法测量识别出3 条相对高阻带和 1 条低阻带,前者同时显示出中高极化率异常,可能属于矿化蚀变带引起的矿致异常;EH4 连续电导率测深结果表明,该矿床深部存在明显的地球物理异常,异常强度大且清晰,与已知的矿化蚀变带和激电测量结果对应良好,显示矿床深部具有良好的成矿前景。实践证明,结合针对性的地质研究,大功率激电和 EH4 技术在草原覆盖区寻找隐伏矿体的应用效果较好。     

中国与欧亚经济联盟主要国家重要贸易农食产品重金属限量标准对比分析

本文介绍了欧亚经济联盟主要国家从中国进口的重要贸易农食产品类别、中国与欧亚经济联盟农食产品的重金属限量标准与法规情况,并且从食品分类方式、农食产品限量指标等方面将中国和EAEU重要贸易农食产品重金属限量进行对比分析,以期为监管部门和企业进行相关研究和促进中国-欧亚经济联盟的农食产品贸易提供参考。通过比较,中国和欧亚经济联盟在食品的分类方式上有各自的特点和不同,我国食品分类较为全面但食品种类相对比较笼统细分度仍然不够,EAEU食品大类虽然不多但具体食品种类规定得比较详细和具体;我国和EAEU在重金属限量标准方面有较大差异,我国对于重要贸易农食产品制定了更为严格的铅限量指标,可以比较铅限量的22种农食产品中有11种农食产品我国规定了更低的铅限量标准;EAEU制定了更为严格的镉限量指标,可以比较镉限量的17种农食产品中有10种产品EAEU规定了更低的镉限量;此外,EAEU规定了部分重要贸易农食产品的镉、砷和汞的限量,而我国GB 2762中未有相关规定;造成这些差异的原因主要与中国和EAEU各国环境中重金属含量差异较大,而且也与各自的饮食习惯、社会文化因素、人群暴露风险和农食产品管理方式不同有关。要推动中国与欧亚经济联盟主要国家重要贸易农食产品出口贸易,需要政府、企业等多方合作共同促进。     

Influence of climate parameters and management of permanent grassland on biogas yield and GHG emission substitution potential

In many regions of Europe, grassland is no longer needed for fodder production as it is not economically viable. However, due to the important role it plays in soil carbon storage, it is imperative that grassland should be maintained. The energetic use of its biomass could be an alternative means of generating income from grassland.The aim of this study is to identify the best permanent grasslands management systems for CHP production with regard to maximizing biogas yields, energy use efficiency and greenhouse gas mitigation potential.A long-term field trial was established in 1994 and managed under various nitrogen fertilizer level regimes and cutting frequencies until 2007. Annual dry matter yields ranged between 9.1 t ha⁻¹ and 10.8 t ha⁻¹.Based on these data the methane yields for the different cutting regimes were calculated. The highest methane yield of 288.4 L kg⁻¹ oDM was calculated for a yearly cutting regime of four cuts.Energy and CO₂ balances were calculated to assess the energy efficiency and the global-warming potential of power generation in a CHP plant using biogas produced from the different grassland management systems. The highest net energy yield (48.52 GJ per hectare per year) was calculated for a two-cut regime. Furthermore, the highest CO₂ equivalent reduction potential was also documented for a cutting frequency of two cuts per year. In this case a CO_2eq mass reduction of 5.1 t per hectare per year could be achieved compared to fossil fuel (consisting of a German power mix and natural gas components) reference systems.     

赖特有机建筑与"天人合一"思想

世界著名建筑大师赖特的有机建筑始终坚持"与自然和谐共生"的设计理念,创造了无数经典之作,在世界范围内引起了很大反响,至今仍为人们所迷恋.赖特的有机建筑分成草原式住宅和美国风住宅两个阶段,这两种风格的住宅创作均体现出中国哲学的"天人合一"思想.因此,挖掘中国传统哲学的内在精神,以此来诠释赖特的有机建筑,可以更加深入地体会建筑的内在涵义,并从中吸取一些对当代建筑创作有益的精髓.     

Assessment of the MODIS LAI product for Australian ecosystems

The leaf area index (LAI) product from the Moderate Resolution Imaging Spectroradiometer (MODIS) is important for monitoring and modelling global change and terrestrial dynamics at many scales. The algorithm relies on spectral reflectances and a six biome land cover classification. Evaluation of the specific behaviour and performance of the product for regions of the globe such as Australia are needed to assist with product refinement and validation. We made an assessment of Collection 4 of the MODIS LAI product using four approaches: (a) assessment against a continental scale Structural Classification of Australian Vegetation (SCAV); (b) assessment against a continental scale land use classification (LUC); (c) assessment against historical field-based measurement of LAI collected prior to the Terra Mission; and (d) direct comparison of MODIS LAI with coincident field measurements of LAI, mostly from hemispherical photography. The MODIS LAI product produced a wide variety of geographically and structurally specific temporal response profiles between different classes and even for sub-groups within classes of the SCAV. Historical and concurrent field measurements indicated that MODIS LAI was giving reasonable estimates for LAI for most cover types and land use types, but that major overestimation of LAI occurs in some eastern Australian open forests and woodlands. The six biome structural land cover classification showed some significant deviations in class allocation compared to the SCAV particularly where grasslands are allocated to shrubland, savanna woodlands are allocated to shrubland, savanna and broadleaf forest, and open forests are allocated to savanna and broadleaf forest. The land cover and LAI products could benefit from some additional examination of Australian data addressing the structural representation of Eucalypt canopies in the “space of canopy realisation” for savanna and broadleaf forest classes.     

新疆阜康县草地资源产量动态监测模型的研究

利用ＮＯＡＡ／ＡＶＨＨＲ数据和地面实测产量值，分析、模拟了鲜草重量和植被指数之间的数理关系，并对草地产量进行了模拟预报。结果表明，采用两种植被指数和七种经验公式所选出的最优预报模型，在地势比较平坦，草地类型变化不大的地区，可以较准确地反映草地产量的变化；但在地形复杂、草地类型变化较大的地区，模型稳定性变差，不适合于草地产量的预报。     

The Study on Snow Depth Retrieval in Xinjiang Region based on FY3B-MWRI Data

The snow depth is one of the necessary parameters of weather and hydrological model,which is not only used to study the balance of surface radiation,but also to study the hydrological effects of snow.Meanwhile,the snow depth monitoring plays an important role in snow-melt runoff forecasting,water resources management and flood control.the sites to measure snow depth data to constructe existing snow depth retrieval models based on FY3B-MWRI data mainly distribute in middle,east and south of China,and the sites in Xinjiang region are relative less.Thus,it causes the poor precision of the snow depth retrieval algorithm in the Xinjiang region.In this paper,we select Xinjiang region as the study area and select FY3B-MWRI as the data source.According to the topography characteristics and surface land cover characteristics of the region,we use regression analysis method to study the different snow depth retrieval algorithms of the three land covertypes (forestland,farmland and grassland).Then we verify the accuracy of the algorithms comparing to the field measured data.The results show that the R² and RMSE of the three land covertypes are 0.758,2.58,0.729,3.21,0.854,5.70 respectively,so the algorithms of this paper have a high accuracy of the snow depth retrieval in Xinjiang region.     

利用实测资料评估被动微波遥感雪深算法

利用SSM/I微波亮温数据,结合地面站点实测资料,比较Chang算法和Che算法在前苏联、中国及蒙古境内6种不同积雪类型的反演精度,结果表明:被广泛应用于全球雪深反演的Chang算法低估了前苏联境内雪深7.6cm,相对误差为-24.3%,而分别高估中国及蒙古境内雪深9.2cm与11.4cm,相对误差分别为108.8%和180.9%,区域反演效果很差;针对中国境内积雪的Che算法严重低估前苏联境内雪深,整体低估21.3cm,相对误差为-68.6%,RMSE为31.4cm;在中国及蒙古境内反演效果有所改善。6个积雪类型中,植被较单一,地形较平坦的苔原型积雪和草原型积雪雪深的反演效果较好。随着纬度和积雪深度的增加被动微波雪深反演有由高估变为低估的趋势。Che算法反演的雪深大体以40°N为界,以北表现为低估,以南表现为高估,另一方面,整体上该算法在雪深低于6.7cm时表现为低高估,高于6.7cm表现为低估;因此,全球算法应用到局部地区需要进行修正,不同下垫面性质以和气候条件下形成的积雪的被动微波反演应区别对待。     

Estimation of Grassland Aboveground Biomass Using Landsat 8 OLI Satellite Image in the Northern Hillside of Tianshan Mountain

The Landsat 8 OLI remote sensing data was used to obtain six kinds of commonly vegetation indices including NDVI,RVI,DVI,EVI,GNDVI and SAVI.Meanwhile,combining with the measured data of grassland in the research area,the research area was divided into two kinds of shady and sunny slope according to the slope.Then the biomass remote sensing estimation models of shady and sunny slope in Ziniquan Ranch were created by Statistical analysis method and biomass space inversion and verification was implemented.The results of correlation analysis showed that the selected vegetation indices were significantly correlated with pasture biomass and there was a significant difference between the correlation of the classified data and the non classified data by slope,in which NDVI was the highest and EVI was the lowest.The optimal inversion model of Ziniquan Ranch biomass was based on the two order polynomial model of SAVI with the accuracy 80%.By using this model reversion,the grassland average yield of Ziniquan Ranch in 2015 was 113 g/m²,which equaled to dry grass yield 41.85 g/m².The research shows that the slope direction is an important factor affecting the distribution of biomass.Using remote sensing data and ground measured biomass data and combining with the characteristics of the topography of shady and sunny slope of the research area,the biomass estimation model has higher accuracy,which could provide scientific basis for the reasonable estimation of grassland biomass and management of grassland grazing in the pastoral area.