基于地理探测器的区域植被覆盖度的定量影响——以京津风沙源区为例

植被覆盖度（FVC）是衡量生态环境优秀的重要指标.本文基于MODIS NDVI数据,运用像元二分法模型,估算了2000~2018年京津风沙源区FVC,分析了其时空变化特征.在此基础上,基于地理探测器模型,定量分析了自然因素和人类活动因素等12个因子对京津风沙源区FVC空间分布的影响.结果表明,近20a来京津风沙源区FVC整体上呈增加趋势,增加率为8.2%.空间上,研究区73.7%的区域FVC在增加,其中显著增加的区域主要集中在晋北山地丘陵亚区、燕山丘陵山地水源保护亚区、大兴安岭南部亚区和科尔沁沙地亚区的南部.2000~2018年,降水是影响京津风沙源区FVC空间分布的主要自然因子,解释力为63.3%;年末大牲畜头数是影响FVC空间分布的主要人为因子,解释力为34.8%.自然因素和人类活动之间的双因子交互作用以双协同作用和非线性协同作用为主,表明相对于单因子,自然因素和人类活动间的交互作用对FVC的解释力更强.其中,降水与其他11个因子的交互作用对研究区FVC起主导作用,解释力超过60%.     

矿化垃圾作回灌型准好氧填埋场日覆盖材料的适宜性研究

本文在对矿化垃圾的基本性质进行测定的基础上,将其作为填埋场覆盖材料进行室内模拟实验.结果显示:经过筛分后的矿化垃圾细料可作为回灌型准好氧填埋场的日覆盖材料,除了具有日覆盖材料的常规功能外,还有净化渗滤液的能力;矿化垃圾对渗滤液中污染物的净化能力优于普通砂土;矿化垃圾作日覆盖材料的最佳粒度为d≤3mm,最优厚度为13cm,双层结构对污染物的净化能力优于单层结构.所以矿化垃圾是一种性能良好的日覆盖替代材料.     

Flooding in Texas: Examination of Temporal Changes and Impacts of Tropical Cyclones

Annual maximum peak discharge measurements from 62 stations with a record of at least 70 years are used to assess extreme flooding in Texas at the regional scale. This work focuses on examination of the validity of the stationarity assumption and on the impact of tropical cyclones (TCs) on the upper tail of the flood peak distribution. We assess the validity of the stationarity assumption by testing the records for abrupt and gradual changes. The presence of abrupt changes in the first two moments of the flood peak distribution is assessed using the Lombard test. We use the Mann‐Kendall test to examine the presence of monotonic trends. Results indicate that violations of the stationarity assumption are most commonly caused by abrupt changes, which are often associated with river regulation. We fit the time series of stationary flood records with the generalized extreme value distribution to investigate whether TCs control the upper tail of the flood peak distribution. Our results indicate that TCs play a diminished role in shaping the upper tail of the flood peak distribution compared with areas of the eastern United States subject to frequent TCs.     

Winter bird use of seed-rich habitats in agri-environment schemes

To assess the effectiveness of over-winter seed provision by agri-environment schemes, bird use of patches of seed-bearing crops was compared with that of other seed-rich habitats on 53 farms in eastern Scotland over three winters. Seed-bearing crops were the most frequently selected habitat, and held 28% of birds of the 10 species recorded. Outside schemes, cereal stubble was the most selected habitat and held 44% of birds. For nine species, seed-bearing crops were used by more birds than expected from the area of crop available in at least one winter, and five species were more likely to occur in first-winter patches, reflecting a greater abundance of cereal grain than in second-winter patches. For cereal grain specialists such as buntings, sowing cereal-based crops annually would ensure that grain is available in each winter, whilst either a 1-year or a 2-year crop would be appropriate for finches that favour oilseeds, and species with a more generalist diet.     

西南典型“退耕还林”区土地利用/覆被变化对土壤中硒及重金属含量的影响

人类活动（土地利用）和环境变化（土地覆被变化）对土壤中硒和重金属含量分布具有重要影响.“退耕还林”生态工程的实施改变了土地利用/覆被,为研究土地利用/覆被变化对土壤中硒和重金属影响提供了理想的实验场所.在西南典型“退耕还林”区,采集了旱地、水田和林地（天然林地和次生林地）的91件表层土壤样品.测定和分析了土壤中硒、重金属、 pH和有机质等参数.结果表明：（1）研究区表土中ω（Se）(0.42×10^-6)、ω（As）(13.0×10^-6)和ω（Sb）(1.03×10^-6)均值显著高于渝西地区的土壤背景值;（2）人工次生林地表土中Se、 Cd、 Cr、 Ni、 Pb和Zn含量都显著高于旱地,表明“退耕还林”工程的实施可能会显著影响表土中硒和重金属富集;（3）土壤有机质（SOM）含量水平是控制表土中硒和重金属含量差异的重要因子.结果发现土地利用/覆被变化通过影响土壤pH和SOM间接深刻地影响土壤中硒和重金属迁移和富集.     

利用Landsat7反演的亮温与土地覆盖类型相关性分析

随着城市人口的急剧增加,城市建筑规模迅速膨胀,大量热源集中排放,产生了城市内部温度明显高于郊区的特殊城市气候现象,即“热岛效应”.以安徽省芜湖市为研究区域,采用GIS叠加分析方法、缓冲区分析方法进行地表辐射亮温与土地覆盖类型的相关性研究.研究结果表明,辐射亮温与地表类型有明显的相关关系,建筑与辐射亮温的相关系数为0.87,植被、水体与辐射亮温的相关系数分别为0.59、0.78.人工建筑因素是产生热岛效应的主要原因之一,加大植被、水体在城市土地用地中的比重,是控制城市热岛效应行之有效的方法,而且利用辐射亮温图可很好地指示城市土地覆盖类型在时间上和空间上的变化.     

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.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.     

Pressure cookers or pressure valves: Do roads lead to deforestation in China?

The effect of roads on forests is ambiguous. Many studies conclude that building and upgrading roads increases pressure on forests but some find that new and better roads may reduce the rate of deforestation. In this paper we use satellite remote sensing images of forest cover in Jiangxi Province, China, to test whether the existence and the size of roads (ranging from expressways to tertiary roads) in 1995 affected the level of forest cover in 2000 or the rate of change between 1995 and 2000. To account for road access for each of our 1 km² (“pixel”) units of forest cover we measure whether or not and what type of roads penetrate the “watershed” in which the pixel lies. These watersheds allow more plausible measures of accessibility than do traditional “crowfly” distance measures that ignore topography. To account for possible confounding we also use 12 additional covariates: geographic and climatic variables (e.g., elevation, slope, rainfall, temperature, soil properties); demographic and economic variables (e.g., local population and GDP per square kilometer); and distance variables (e.g., distance to the nearest provincial capital). Although simple univariate OLS regressions show that forest levels are lower and deforestation rates higher either when there is a road, or when there is a higher quality road, these results are not robust. Controlling for all of the covariates and also using recently developed covariate matching techniques to estimate treatment effects, we find that roads in China’s Jiangxi Province can most safely be described as having no impact on the level of forests and no impact on the rate of deforestation.     

季节性雪被对青藏高原东缘高寒草甸土壤氮矿化的影响

依据自然雪被分布的差异,在青藏高原东缘高寒草甸中设置3条样带(即深雪、中等厚度雪被和浅雪),于2008年的秋冬过渡期,连续监测各样带中的雪被厚度和土壤温度,并采用原位培养法测定每月的土壤氮素氨化、硝化和矿化速率,以研究不同厚度雪被对高寒草甸土壤氮矿化的影响.结果表明,月均土温、每月日最高土温均值分别与雪被厚度极显著相关,二次函数关系拟合较好(R2=0.576,0.685),且根据每月日最高土温均值与雪被厚度的二次函数关系方程可知,25 cm厚的雪被可以起到较好的隔绝效果;土壤含水量受雪被厚度和土壤温差两个因素的显著影响.在秋冬过渡期末,浅雪梯度下土壤硝态氮含量显著降低,且雪被下的净氮矿化速率与月均土温、每月日最高土温均值、每月日最低土温均值都分别呈极显著相关,二次函数关系拟合较好(R2=0.589,0.541,0.601).研究表明,不同厚度的雪被对土壤温度和含水量影响显著,从而显著地影响着土壤氮的矿化,深雪更有利于氨化、硝化和氮矿化.图7表2参36