Optimizing model for land use/land cover retrieval from remote sensing imagery based on variable precision rough sets

The suitable spectral mode in remote sensing is often desirable to facilitate the inversion of ecological environment and landscape. This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory. In the case study of Lake Baiyangdian which has important ecological functions to the northern China, this model is established successfully according to the domain-experts knowledge. The procedure is as follows. First step is data collection, including remote-sensing data (e.g., Landsat-5 TM bands), the digitized relief maps, and statistical yearbooks. Second, the remote sensing imagery (RSI) and relief maps are co-registered into the same resolution. Third, a condition set, including various attributes is derived from spectral bands, band math or ratio indices based on previous studies, at the same time, the decision set is derived from true land types after investigation and validation. Then, the remote sensing decision table (RSDT) is constructed by linking condition set with decision set according to the sequential pixels in RSI. Fourth, we create one forward greedy searching algorithm based on VPRS to handle this RSDT. After adjusting parameters such as β and knowledge granularity diameter (KGD), we obtain the stable optimized results. Comparative experiments and evaluation show that the discrimination or retrieval accuracy of VPRS model is satisfying (overall accuracy: 87.32% and KHAT: 0.84) and better than original data. Moreover, data dimension has been decreased dramatically (from 12 to 3) and key attributes found by the model may be useful for specific retrieval in wetland inventories.     

Heat of absorption of CO2 in aqueous ammonia and ammonium carbonate/carbamate solutions

A reaction calorimeter was used to determine the enthalpies of absorption of CO₂ in aqueous ammonia and in aqueous solutions of ammonium carbonate at temperatures of 35–80 °C. The heat of absorption of CO₂ with 2.5 wt% aqueous ammonia solution was found to be about 70 kJ/mol CO₂, which is lower than that with MEA (around 85 kJ/mol) at 35 and 40 °C. The value decreases with increased loading, but not to as low a value as expected by the carbonate–bicarbonate reaction (26.88 kJ/mol). The enthalpy of absorption of CO₂ in aqueous ammonia at 60 and 80 °C decreases with loadings at first, then increases between 0.2 mol CO₂/mol NH₃ and 0.6 mol CO₂/mol NH₃, and then decreases again. The behavior of the heat of absorption of CO₂ in 10 wt% ammonium carbonate solution was found to be the same as that of aqueous ammonia at loadings above 0.6 mol CO₂/mol NH₃. The heat of absorption increases with increasing temperature. The heats of absorption are directly related to the extent of the various reactions with CO₂ and can be assessed from the species variation in the liquid phase.     

Assessment of elemental distribution and trace element contamination in surficial wetland sediments, Southern Tibetan Plateau

In order to analyze and evaluate different trace metals on surface water of the Changjiang River, concentrations of dissolved trace metals (Cu, Ni, Fe, Co, Sc, Al, Zn, Pb, Cd, Se, As, Cr, and Hg), major elements(Ca and Mg), and nutrient(NO $_{3}^{-})$ were measured. Samples were taken at 76 positions along Changjiang River in flood and dry seasons during 2007?C2008. Spatial distributions identified two main large zones mainly influenced by mineral erosion (sites 1?C22) and anthropogenic action (sites 23?C76), respectively. Principal component analysis (PCA) and hierarchical cluster analysis were used to identify the variance distinguishing the origin of water. Four significant components were extracted by PCA, explaining 74.91% of total variable. Cu, Ni, Fe, Co, Sc, Al, Ca, and Mg were mainly associated with the weathering and erosion of various rocks and minerals, while an anthropogenic source was identified for Cd and As. Although erosion was one source of Pb and Zn, they were also input by atmospheric deposition and industrial pollutions. NO $_{3}^{-}$ and Se were mainly associated with agriculture activities. However, Hg and Cr showed different sources. CA confirmed and completed the results obtained by PCA, classifying the data into two large groups representing different areas. Group 1 referred to the upper reaches which represented samples mainly corresponding to natural background areas. Group 2 referred to the middle and lower reaches including samples under anthropogenic influence. Meanwhile, group 2 was subdivided into three new groups, representing agricultural, industrial, and various artificial pollution sources, respectively.     

Chemical composition of precipitation and its sources in Hangzhou, China

To understand the origin and chemical characteristics of precipitation in Hangzhou, rainwater samples were collected from June 2006 to May 2008. All samples were analyzed for pH, electrical conductivity, and major ions (NH??, Ca2?, Mg2?, Na?, K?, SO?2?, NO??, F?, and Cl?). Acidification of precipitation in Hangzhou was serious with volume-weighted mean pH value of 4.5, while frequency of acid rain was 95%. The calculated SO?2?/NO?? ratio in Hangzhou precipitation was 2.87, which indicated that the precipitation of Hangzhou belonged to sulfate-based acid rain. The results of acid neutralization analysis showed that not all the acidity in the precipitation of Hangzhou was neutralized by alkaline constituents. The results of sea salt contribution analysis showed that nearly all SO?2?, Ca2?, and Mg2? and 33.7% of K? were of non-sea origins, while all Na? and Cl? and 66.3% of K? originated from sea sources. The principal component analysis which was used to analyze the sources of various ions indicated that chemical compositions of precipitation in Hangzhou mainly came from terrestrial sources, factory emissions, fuel wood burning, and marine sources.     

MIEX树脂特性及其在饮用水处理中的应用

阐述了MIEX阴离子交换树脂的特性及其在饮用水处理中对消毒副产物前质、色度、浊度、藻类等的去除效果.对近年来MIEX树脂与超滤、活性炭、臭氧等工艺组合的应用情况进行了介绍,初步分析了MIEX树脂用于净水处理的经济性.     

砷矿区植物对重金属的吸收和富集特征

通过野外调查研究了云南楚雄雨露砷矿区采矿、冶炼废弃地生长的16种优势植物的生长状态及其对应根区土壤的基本理化性质.结果表明,该矿区植物长势良好,未出现受害症状.土壤磷氮含量充足,As含量远远超过《土壤环境质量标准》3级标准中的旱地As含量标准值,高达133倍.16种植物的地上部重金属含量As最高,并且在总As平均质量比高达5 318 mg/kg的土壤环境条件下,蜈蚣草(Pteris vittata L.)体内As质量比可达2 327 mg/kg,小酸模(Rumex acetosella L.)、辣子草(Galinsoga parviflora Cav.)、鬼针草(Bidens pilosa L.)等7种植物对Cd,以及牛口刺(Cirsium shansiense Petrak.)对Zn的富集系数和转移系数均大于1.0,其中地石榴对Cd的富集系数高达7.99.上述植物对重金属污染均表现出了较强的耐性,具有进一步的研究潜力.     

物联网技术在地震救灾中的应用

研究了物联网技术在地震救灾中的应用。在体系结构设计中主要针对无线传感器网络节点、自组网技术、数据采集与灾情分析软件、多源信息融合等几个方面开展研究,构造出基于物联网技术的信息处理平台,在此基础上组建一个地震监测、预警及救灾部署控制中心,并实现信息处理平台与城市基础设施的互连接口。最终,在地震救灾中能够利用多源信息融合技术为控制中心实现决策和指挥提供科学、高效的服务。     

雨凇环境影响因子研究与应用——以湖南省为例

运用概率论和数理统计方法,基于湖南气象观测资料、NCEP资料及地理信息资料,分析了气象因子、地理因子对雨凇天气形成的影响,揭示了各影响因子的临界影响点。进而分析了主要影响因子位于不同影响点时其它因子对雨淞天气形成的作用,在此基础上,研制了基于气象要素因子、地理因子的雨凇日数学模型。选取平均连续雨凇日数、年平均雨凇日数、雨凇最长持续时间等3项与雨凇日数有关的气候指标对模型模拟结果进行了检验,结果表明模型模拟结果与实际观测结果相关性高,均值差异小。雨凇日模型已被用于精细化的雨凇气候区划。     

南北差异视角下个体食物浪费行为——基于大学生高校食堂就餐情境的分析

饮食习惯一直被认为是造成食物浪费的重要因素。基于对29省29所高校9192份大学生食堂就餐的实地调查问卷,从南北差异视角探讨了个体食物浪费行为的差异特征。研究表明：相对北方籍大学生,南方籍大学生浪费食物的概率更高,南方籍大学生在高校食堂就餐时食物浪费量和浪费率也高于北方籍大学生。通过中介效应模型,证实南北方主流饮食模式是引发浪费差异的关键所在。进一步匹配大学生南北方籍贯和所就读高校的南北区位,并以“南方大学生在南方高校求学”模式为基准,发现“南方大学生到北方高校求学”模式下,个体有更低的食物浪费概率、浪费量和浪费率。但“北方大学生到南方高校求学”模式下,个体没有显示出较低的食物浪费概率、食物浪费量和食物浪费率,从而稳健地证实南北方主流饮食模式是引发浪费差异的关键所在这一结论。     

食物转化视角下我国家庭食物浪费程度与影响因素——基于CHNS数据的实证分析

长期以来,我国食物供应充足稳定,但是人口、环境等因素不断对此提出挑战,并且我国每年的食物损失和浪费数量十分惊人。从食物转化视角将食物浪费率定义为家庭食物消费中未能正常转化为家庭成员身体质量指数的比例,采用随机前沿模型并基于CHNS数据估算我国家庭食物浪费率,并探讨家庭异质性特征的影响。结果显示：家庭平均浪费率为11.28%;家庭规模越小、孩子或老年人的数量越多、收入水平越高、南方地区、户主的受教育程度越低、主要女性成员的受教育程度越高或者有工作、对膳食知识掌握程度越低的家庭浪费率越高。因此,要鼓励生产小包装食物和小型厨具,指导家庭根据实际需求购买食物,加强推广食育运动,开展节粮活动并教授减损措施。