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soil cover相关的网络例句

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与 soil cover 相关的网络例句 [注:此内容来源于网络,仅供参考]

On the basis of sensitivity analyses using the PROSAIL model, the present study demonstrates an approach that uses a neural network based on image classification incorporated in PROSAIL for accurate retrieval of LAI. By including the soil reflectance index in the original PROSAIL model to take the place of soil background reflectance parameters that are difficult to determine, specific neural networks are constructed corresponding to individual types of vegetation cover.

在PROSAIL模型敏感性分析的基础上提出了一种基于影像分类的神经网络反演方法,引进了土壤反射指数用于替代原模型中难以确定的土壤背景反射参数,分别针对不同植被类型建立各自的神经网络,对经过大气纠正后的Landsat ETM+影像进行了模拟实验并同野外实测LAI数据进行比较。

At one time, we emphasized the solar radiation transfer mechanics. To advance the estimation precision, in this paper, we classed land cover into four layer, canopy of Robinia pseudoacacia L ,top of Melilotus albus Desr,bottome of Melilotus albus Desr and layer of soil, separately estimated their fluxes of moisture, heat and CO2 ,actualized the separated simulation for each composement in soil-vegetation-atmosphere contimuum.

同时,本次研究强调了太阳辐射在冠层间的辐射传输机制,为了提高估算精度,本文把地表覆盖分为刺槐冠层,草木樨上层、草木樨下层及土壤层四个层面来分别估算其水热及CO2通量,做到了土壤-植被-大气连续体能量及物质通量的分离模拟。

As a part of "Outstanding Young Researcher project- Water Erosion Predicting model", the purpose of this study is to do research on the method for estimating Cover and Management Factor in China, to evaluate the effects of crop cover in different stages by estimating soil loss ratio of individual crop stage period, and to compare the effects of different land use patterns by their average annual value of C factor.

本研究作为杰出青年基金项目《土壤水蚀预报模型研究》的一部分,目的在于探讨我国覆盖与管理因子的计算方法,估计不同耕作制度下农地多年平均C值;通过估计不同农作期土壤流失率评价作物发育不同时期对土壤侵蚀的作用;通过估计多年平均覆盖与田间管理因子分析不同土地利用方式的水土保持效益。

The process of ecological degradation in the vicinity of Shaoguan Pb/Zn smelter may be summed as: heavy metals and acidic deposits from the waste gas from smelter resulted in the vanishment of the sensitive plant species, increasing accumulation of heavy metals in soils and acidification of topsoil worsened the chemical properties and then shallow-rooted plant, mainly the herbaceous, vanished. With the demolishment of the vegetation cover, increasing water-soil erosion worsened physico-chemical properties of soil and, subsequently, some woody plants disappeared and barren land was finally appeared.

该生态系统的退化过程可以归纳为:来自于冶炼废气的重金属和酸沉降导致了敏感植物的消亡,丧失了对土壤的缓冲保护作用;重金属在土壤表层的积累,酸性物质在土壤表层的增加导致的土壤酸化以及由此引发的有机质与养分的淋溶和重金属及Al的活性增加,加剧植被的快速退化,特别是浅根植物的衰亡;地被层的破坏,导致水土流失和土壤侵蚀加深,进一步恶化表层土壤的理化性质,一些木本植物随之消失,最终形成光板地。

The following results are made from this research: Assessing data quality and band combination of different bands in line with geo-target features in desertification areas, and determining basic bands for desertification monitoring. And understanding and studying the spectral features and variation rules of geo-targets in the experimental area, raising that it is the basis of geo-targets information collection with imaging spectrometer data to understand spectral features and variation rules of geo-targets, realizing that in a great extent spectral-integrated-form-based classification method can remove the phenomenon of "different spectrum with same objects" resulted from reflection ratio curve translation because of the angle change among sensor, targets and observation direction, and the average and variance images can be introduced to solve the problem of two kinds of geo-target with similar spectral forms and much different values of whole reflectionratio. It is suggested that "red edge" range bands of vegetation, which has close relationship with vegetation cover and biomass, is the main characteristic bands and important basis for careful vegetation classification and quantitative retrieval, and pixel-based derivative spectral analysis is very useful for removing the effects of soil background values and quantitatively retrieving vegetation biomass and cover. The remote sense quantitative retrieval model is developed for main appraisable factors of desertification monitoring assessment with imaging spectrometer data and then the applicability of model is analyzed.

研究结果如下:首先针对荒漠化地区的地物特征,对高光谱数据不同波段的数据质量、波段组合进行了评价,提出了适用于荒漠化监测的基本波段选择集;初步了解和掌握了研究地区的地物光谱特性及变异规律,进一步明确了掌握地物光谱特征和变异规律是用成像光谱仪数据提取地物信息的基础;发现了基于光谱整体形状的分类方法在很大程度上能够消除由于传感器、地物目标观测方向之间的角度变化引起的反射率曲线整体平移的"同物异谱"现象,对于谱形相似而整体反射率的值相差较大的两类地物,通过引入均值和方差图像参与分类得到解决;研究还表明在植被"红边"范围内的波段是进行荒漠化监测的主要特征波段,这些波段与植被生物量和盖度都有密切的关系,是开展精细植被分类研究和植被定量反演的重要基础;像元的导数光谱分析可以消除土壤背景的影响,是进行植被生物量和盖度定量反演的有力工具;建立了荒漠化监测主要评价因子的定量反演模型,并分析了模型的适用性。

The following results are made from this research: Assessing data quality and band combination of different bands in line with geo-target features in desertification areas, and determining basic bands for desertification monitoring. And understanding and studying the spectral features and variation rules of geo-targets in the experimental area, raising that it is the basis of geo-targets information collection with imaging spectrometer data to understand spectral features and variation rules of geo-targets, realizing that in a great extent spectral-integrated-form-based classification method can remove the phenomenon of "different spectrum with same objects" resulted from reflection ratio curve translation because of the angle change among sensor, targets and observation direction, and the average and variance images can be introduced to solve the problem of two kinds of geo-target with similar spectral forms and much different values of whole reflectionratio. It is suggested that "red edge" range bands of vegetation, which has close relationship with vegetation cover and biomass, is the main characteristic bands and important basis for careful vegetation classification and quantitative retrieval, and pixel-based derivative spectral analysis is very useful for removing the effects of soil background values and quantitatively retrieving vegetation biomass and cover. The remote sense quantitative retrieval model is developed for main appraisable factors of desertification monitoring assessment with imaging spectrometer data and then the applicability of model is analyzed.

研究结果如下:首先针对荒漠化地区的地物特征,对高光谱数据不同波段的数据质量、波段组合进行了评价,提出了适用于荒漠化监测的基本波段选择集;初步了解和掌握了研究地区的地物光谱特性及变异规律,进一步明确了掌握地物光谱特征和变异规律是用成像光谱仪数据提取地物信息的基础;发现了基于光谱整体形状的分类方法在很大程度上能够消除由于传感器、地物目标观测方向之间的角度变化引起的反射率曲线整体平移的&同物异谱&现象,对于谱形相似而整体反射率的值相差较大的两类地物,通过引入均值和方差图像参与分类得到解决;研究还表明在植被&红边&范围内的波段是进行荒漠化监测的主要特征波段,这些波段与植被生物量和盖度都有密切的关系,是开展精细植被分类研究和植被定量反演的重要基础;像元的导数光谱分析可以消除土壤背景的影响,是进行植被生物量和盖度定量反演的有力工具;建立了荒漠化监测主要评价因子的定量反演模型,并分析了模型的适用性。

In this paper, the cosmogenic 7Be content of different cover materials on the soil surface was analyzed, the results showed that the withered plant cover contained the highest 7Be activity among the incomplete decomposed and the living plant cover in the end of springtime.

本文对不同地被物中的7Be含量进行了分析,结果表明:春季末地表不同地被覆盖物中干枯植物的7Be含量最大,半分解物次之,活植物中含量最少。

Statistical analysis shows that bulk density, saturated hydraulic conductivity, and dust on road surface have significant effects on runoff and soil loss. Stone cover may increase surface runoff, but vegetation cover is very effective in erosion control and runoff reduction.

土质道路的容重和路面浮土与径流系数和土壤流失量呈显著正相关,饱和导水率则呈显著负相关;路面杂草能显著减少径流,防治路面侵蚀。

In each of the three effect factors, the main items are: crown cover—crown density and thickness of the crown; litter layer——dry weight of the litter on each unit area, thickness of the litter and the biggest amount of holding water in the litter; soil——soil porosity, soil capillary space and soil moisture content.

三层次中的主要影响因子有:林冠层——郁闭度和林冠厚度;枯落物层——单位面积枯落物干重、枯落物厚度及枯落物最大持水量;土壤层——土壤总孔隙度、毛管孔隙度及土壤含水量。

The results showed:(1)Nitrogen addition changed the soil physical and chemical properties, enhancing the content of NO3—- N available resources in the soil, increasing the plants height and cover, reducing the vegetation light penetration. With increasing of N addition, both the species richness and the diversity decrease sharply (P 0.001).(2)N addition increased the aboveground biomass significantly (P 0.05). With increasing of N addition, the aboveground biomass increased first then decreased, and the grasses biomass increased while the forbs and legumes biomass decreased.(3)There was a significant linear positive relationship between species richness and vegetation light penetration (P 0.05), and also between aboveground biomass and soil NO3—- N content (P 0.05). The relationship between aboveground biomass and species richness was negative upon enhanced N supply.

结果表明:(1)氮素添加提高了土壤中NO3—- N等可利用资源的含量,增加了植物群落植被的盖度,减小了植被的透光率,随着施氮量的增加群落中物种丰富度显著降低(P 0.001);(2)氮素添加显著改变了植物群落地上生产力(P 0.05),随着施氮量的增加地上生产力呈现先增加后降低的变化趋势,各功能群中禾草生物量显著增加,而杂草和豆科生物量随施氮量增加逐渐减少;(3)物种多样性与植被透光率呈线性正相关(P 0.05);地上生产力与土壤NO3—- N含量呈线性正相关(P 0.05);随着施氮量的增加物种丰富度与生产力之间呈负相关关系。

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