基于植被覆盖率的农村居民点整理潜力估算及实证

为合理估算农村居民点整理潜力,该文提出基于植被覆盖率的农村居民点整理潜力测算新思路。借助植被覆盖率对农村居民点斑块进行分类,通过分析抽样农村居民点斑块的植被覆盖与内部用地结构得到整理潜力修正系数,从而建立基于植被覆盖率修正的农村居民点整理潜力估算模型,并以北京市门头沟区为例展开实证研究。研究结果表明,门头沟区无整理潜力的农村居民点占大多数,具有整理潜力的农村居民点主要集中在经济相对落后的乡镇,并且这部分农村居民点多远离主干道;山区具有中、高整理潜力的农村居民点略多于平原、浅山区,而低整理潜力的农村居民点明显多于平原、浅山区;门头沟区规划整理的农村居民点内部包含有大量农用地,其中建设用地比例只占63.19%～71.54%,但是,第二次土地调查将整个农村居民点都作为建设用地调绘;因而,一些不考虑植被覆盖修正的农村居民点整理潜力测算方法夸大了整理潜力,放大了城乡建设用地增减挂钩的效果。该文为进一步合理估算农村居民点整理理论潜力提供参考。     

基于语义驱动的日光温室图纸三维建模方法

为了从日光温室施工图纸中重建出温室结构三维模型,提出基于语义映射的施工图纸三维重建方法。首先解析和分类日光温室施工图纸DXF文件,从中识别和理解主要特征构件,建立日光温室构件语义模型并生成分层控制参数,进而基于参数化驱动日光温室三维建模,最后对日光温室三维模型进行真实感渲染。该方法整合CAD制图与三维建模技术,有利于提高日光温室施工图纸的读图效率,建立的三维温室模型具有保真性、交互性和真实感等特性,可用于工程量和造价计算、温室结构优化以及虚拟展示。     

Fractionation of soil humic acids by preparative polyacrylamide gel electrophoresis in the presence of concentrated urea

To separate soil humic acids (HAs) into their constituents and characterize them, polyacrylamide gel electrophoresis (PAGE) was carried out in the presence of 7 M urea using a preparative electrophoresis system. Two types of soil HAs were fractionated into nine fractions by PAGE. The dark-colored constituents were recovered from the electrophoretic fractions by precipitation on acidification, and the brown-colored constituents dissolved in the acidic solution of fast-moving fractions were recovered by adsorption onto DAX-8 resin. High-performance size-exclusion chromatography (HPSEC) confirmed that the constituents of the HAs were separated based on their molecular size by PAGE. The dark-colored constituents exhibited higher degrees of humification than did the corresponding unfractionated HAs, except for the constituents remaining in the electrophoretic gels at the end of electrophoresis. Diffuse reflectance infrared spectroscopy revealed that the chemical properties of the dark-colored constituents changed regularly: the content of carboxyl groups decreased and the proportions of proteinous, aliphatic and polysaccharide moieties increased with increasing molecular size. The humification degrees of the constituents adsorbed onto DAX-8 resin were considerably lower than those of the corresponding unfractionated HAs. The chemical properties of the DAX-8-adsorbed constituents were different from those of the dark-colored constituents. Observation of electrophoretic fractions under blue light (470 nm) and HPSEC with fluorescence detection at an excitation wavelength of 460 nm and an emission wavelength of 520 nm showed that green fluorescent substances were largely concentrated in the smallest molecular size fractions and were partitioned into both the dark-colored precipitates and DAX-8-adsorbed fractions. The proportion of organic carbon recovered by precipitation and adsorption onto DAX-8 resin was 45–63%, indicating that substantial parts of the HA constituents were missing. The unrecovered constituents were considered to be acid-soluble, nearly colorless substances. The dissociation of the acid-soluble constituents from the acid-insoluble dark-colored constituents during the preparative PAGE of soil HAs was ascribed to disruption of hydrogen bonding and hydrophobic interactions caused by concentrated urea.     

基于不同地表曲面模型预测土壤有机碳含量

Local terrain attributes,which are derived directly from the digital elevation model,have been widely applied in digital soil mapping.This study aimed to evaluate the mapping accuracy of soil organic carbon (SOC) concentration in 2 zones of the Heihe River in China,by combining prediction methods with local terrain attributes derived from different polynomial models.The prediction accuracy was used as a benchmark for those who may be more concerned with how accurately the variability of soil properties is modeled in practice,rather than how morphometric variables and their geomorphologic interpretations are understood and calculated.In this study,2 neighborhood types (square and circular) and 6 representative algorithms (Evans-Young,Horn,Zevenbergen-Thorne,Shary,Shi,and Florinsky algorithms) were applied.In general,35 combinations of first-and second-order derivatives were produced as candidate predictors for soil mapping using two mapping methods (i.e.,kriging with an external drift and geographically weighted regression).The results showed that appropriate local terrain attribute algorithms could better capture the spatial variation of SOC concentration in a region where soil properties are strongly influenced by the topography.Among the different combinations of first-and second-order derivatives used,there was a best combination with a more accurate estimate.For different prediction methods,the relative improvement in the two zones varied between 0.30％ and 9.68％.The SOC maps resulting from the higher-order algorithms (Zevenbergen-Thorne and Florinsky) yielded less interpolation errors.Therefore,it was concluded that the performance of predictive methods,which incorporated auxiliary variables,could be improved by attempting different terrain analysis algorithms.     

基于地统计与遥感反演相结合的有机质预测制图研究

土壤水分对土壤光谱反射率有显著影响,而以往有机质遥感反演制图中却很少将水分作为预测建模的变量。为了使遥感制图更加符合野外实际环境,提高有机质预测制图精度,在充分考虑土壤样点空间自相关、异相关与野外复杂环境特点的基础上,通过地统计获得研究区水分的空间分布数据,结合遥感反射率,建立多因子预测模型,得到了吉林省黑土区土壤有机质空间分布图。结果表明,有机质遥感制图中,水分因素的加入,使模型的建立更加符合野外实际情况,显著提高了有机质预测制图的精度。     

运用模糊隶属度进行土壤属性制图的研究——以黑龙江鹤山农场研究区为例

通过传统土壤类型图所得的土壤属性图已不能满足精准农业和生态环境模型所需土壤属性的精度,而目前应用较多的统计方法和地统计方法均存在一定的局限性。鉴于此,本文探索了一种采用模糊聚类获取模糊隶属度进行土壤属性制图的方法。首先,采用模糊c均值聚类(Fuzzyc-means clustering,FCM)方法对环境因子进行聚类,通过野外采样(称为建模点)建立土壤-环境关系知识;然后,计算区域内各像元点对土壤类型的模糊隶属度;最后,对模糊隶属度采用加权平均的方法获取土壤属性值。将该方法应用于黑龙江鹤山农场老莱河流域的研究小区,以土体厚度和表层有机质为例进行土壤属性制图。为了评价该方法的有效性,将其与采用环境因子所建立的多元线性回归模型进行比较,通过野外验证点集评价两种模型所得的土壤属性,评价指标为观测值和预测值的相关系数、平均绝对误差(MAE)、均方根误差(RMSE)和准确度(AC)。结果表明,尽管通过建模点建立的多元线性回归方程R2较大,但该方程并不适用于研究区内的其他样本点,这表明多元线性回归方法在该区具有一定的局限性。与之相比,模糊隶属度加权平均的方法则可以通过较少的建模点得到更好的预测效果。     

低分子有机酸对土壤中重金属的解吸及影响因素

研究了柠檬酸、草酸、酒石酸和苹果酸对矿区土壤中重金属Pb、Cd、Cu和Zn的解吸行为,并探讨了介质pH值对其解吸土中重金属的影响。振荡解吸试验结果表明四种低分子有机酸对供试污染土壤中Pb、Cd、Cu和Zn都具有一定的解吸能力。由于土壤中重金属有效态含量较低,各重金属的解吸率都不高。在对Pb和Cd的解吸中,各低分子有机酸能力大小顺序为柠檬酸>酒石酸≈苹果酸>草酸;Cu的解吸顺序为柠檬酸>草酸>酒石酸≈苹果酸;Zn的解吸顺序为酒石酸>柠檬酸≈苹果酸>草酸。低分子有机酸随浓度的增加,其解吸能力提高。低分子有机酸对重金属的解吸量随pH值的降低而增加。     

DEM栅格分辨率对多元线性土壤—景观模型及其制图应用的影响

以亚热带丘陵地区为对象,以该区4 km×3 km的5 m、10 m、15 m、20 m、25 m、30 m数字高程模型(DEM)为基础,建立多元线性土壤景观模型,并应用该模型预测研究区内土壤表层有机质含量分布,进而比较不同分辨率DEM中土壤景观模型及其预测制图的精度。结果表明:在本研究区11 km2范围内,随着DEM栅格分辨率降低,坡度、曲率、比汇水面积(对数)频度均表现出了向其中值区集中的趋势;地形因子的这一变化规律对土壤景观模型的影响较小,例如模型的变量、变量系数及R2在不同分辨率DEM中的差异很小;但地形因子的这一变化规律对模型预测制图的精度具有较大影响,各项指标均说明,模型在10~25 m DEM中的制图精度较高,而在更高分辨率(5 m)或更低分辨率(30 m)DEM中较低。本研究结果对其他亚热带丘陵地区具有一定的指示意义。     

中尺度土壤预测制图中地形变量提取的适宜分辨率探讨

地形变量是土壤预测制图中重要的预测变量之一,为了满足中尺度土壤预测制图的精度要求,又能够减少数据的冗余,需要选择合适分辨率范围的地形变量。基于ASTER GDEM数据,对不同地形起伏状况的3个样区,通过重采样得到30 m、60 m、90 m、120 m、150 m共5组不同分辨率的DEM数据,分别选取土壤预测制图中常用的高程、坡度、平面曲率和剖面曲率4组地形变量,通过地形信息熵、局部方差均值以及比例尺和空间分辨率的关系,选取巢湖流域用于土壤预测制图的地形变量提取的适宜分辨率范围。研究表明:对于特定比例尺的土壤预测制图,地形变量的提取需要综合考虑两个因素:一是土壤预测制图的比例尺,二是地形变量提取的分辨率。中尺度土壤预测制图地形变量提取的适宜分辨率为30m,既能保留有实际意义的地形信息,又能满足土壤预测制图的精度要求。     

Bibliometric Profile of an Agbioscience Research Enhancement Grant Program

This study is a bibliometric analysis of journal articles generated from an intramural grant program in the agbiosciences. Using citation analysis and bibliometric mapping, the study analyzes 515 journal articles published from 1999 to 2017. Results show the growth of journal article output, identify the major research fields and topics, describe national and international authorial and institutional collaborations, and quantify the performance and impact of the article output. The grant program’s journal article output presents a multi-disciplinary range of scholarly publications that reflect the disciplines of The Ohio State University’s College of Food, Agricultural, and Environmental Sciences, which houses the grant program.