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Ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca) on the basis of indices of remote sensing of land images

机译:基于陆地图像遥感指数的常见乳草(Asclepias syriaca)生态位的生态地理决定因素

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The patterns of variation in vegetative indices received by means of data of remote land sensing are described as being dependant on geomorphological predictors and the sizes of agricultural fields in an experimental polygon within Poltava region. The possibilities of application of vegetative indices have been explored through ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca L.) and other weeds. On the basis of images of the land surface taken on 23 March and 27 August 2015 by the sensor control Operational Land Imager (OLI), installed on the satellite Landsat 8, vegetative indices have been calculated (AC-Index – aerosol/coastal index, Hydrothermal Composite, NDTI – Normalized Difference Tillage Index, NDVI – Normalized Difference Vegetation Index, VI – Vegetation Index, MNDW – Modified Normalized Difference Water Index, LSWI – Land Surface Water Index, NBR – Normalized Burn Ratio, M15). The data obtained have been subjected to principal component analysis and the revealed principal components have been interpreted with the help of regression analysis, in which geomorphological variables have been applied as predictors. It was possible to explain the trends of variability of the vegetative cover, formalized in the form of the principal component, by means of indices which quantitatively characterise features of relief. The various aspects of variation of vegetative cover have been shown to be characterised by the specificity of the influence of relief factors. A prominent aspect of the variation of the vegetative cover of agroecosystems is variability within a field. The degree of a variation of conditions is proportional to the size of a field. Large fields occupy level plain positions. In turn, within small fields sources of variation are changes in ecological conditions which arise owing to unevenness of relief, which increases in proximity to gullies and ravines. We have identified the aspects of the variation of vegetative cover which by their nature can be considered as contributers to the growth of weeds in agroceonoses. Satellite imaging by Landsat does not allow direct identification of concentrations of weeds, but it can reveal complex changes in the landscape cover, which act as markers of the processes connected with development of weed vegetation. The procedure of further decoding of satellite images for the purpose of identification of weeds requires greater attention in this field of research.
机译:通过遥感土地数据获得的营养指数的变化模式被描述为取决于地貌预测因素和波尔塔瓦地区试验多边形内农田的大小。通过普通乳草(Asclepias syriaca L.)和其他杂草的生态位的生态地理决定因素,探索了应用营养指标的可能性。根据2015年3月23日至8月27日由安装在卫星Landsat 8上的传感器控制系统“ Operational Land Imager”(OLI)拍摄的陆地表面图像,计算出植物生长指数(AC指数–气溶胶/沿海指数水热复合物,NDTI –归一化耕种指数,NDVI –归一化植被指数,VI –植被指数,MNDW –归一化归一化水分指数,LSWI –地表水指数,NBR –归一化燃烧比,M15)。对获得的数据进行了主成分分析,并借助回归分析解释了所揭示的主成分,其中将地貌变量用作预测因子。可以通过定量地描述救济特征的指数来解释以主要成分形式形式化的植被覆盖率变化趋势。已经证明,营养覆盖物变化的各个方面都具有缓解因子影响的特异性。农业生态系统营养覆盖面变化的一个突出方面是田间的可变性。条件的变化程度与字段的大小成正比。大字段占据水平的平原位置。反过来,在小片土地上,变化的源头是生态环境的变化,这种变化是由于起伏不均引起的,而这种变化在靠近沟壑和沟壑的地方增加了。我们已经确定了植物覆盖率变化的各个方面,就其性质而言,可将其视为对农杆菌糖中杂草生长的促进剂。 Landsat的卫星成像技术无法直接识别杂草的浓度,但可以揭示景观覆盖区的复杂变化,这些变化是与杂草植被发展有关的过程的标志。为了识别杂草,进一步解码卫星图像的过程需要在该研究领域中得到更大的关注。

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