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The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices

机译:空间和光谱分辨率对基于卫星植被指数的有效性的作用

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Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop needs or health problems and provide solutions for a better crop management. Vegetation indices (Vis) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation.In the present study, the experimental area is located near the village Eleftherion of Larissa Prefecture in the Thessaly Plain, and consisted of two adjacent agricultural fields of cotton and corn.Imagery from WorldView-2 (WV2) satellite platform was obtained from European Space Imaging and Landsat-8 (L8) free of charge data were downloaded from the United States Geological Survey (USGS) archive. The images were selected for a four month span to evaluate continuity with respect to vegetation growth variation.Vis for each satellite platform data such as the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Fraction Photosynthetically Radiation (FPAR) were calculated. The comparison of these Vis produced from thetwo satellite systems with different spatial and spectral resolution was mad,e for each growth stage of the crops and their results were analyzed in order to examine their correlation.Utilizing the WV2 new spectral data, several innovative chlorophyll and vegetation indices were created and evaluated so as to reveal their effectiveness in the detection of problematic plant growth areas. The Green Chlorophyll index appeared to be the most efficient index for the delineation of these areas.
机译:遥感应用旨在为农民提供及时的作物监控和生产信息。这些信息可用于识别作物需求或健康问题,并为更好的作物管理提供解决方案。衍生自卫星数据的植被指数(VI)已被广泛用于评估植被的生理状态和生物物理性质的变化。在本研究中,实验区位于萨利亚县的村庄村庄的村庄普通,并组成两个邻近的棉花和玉米农业领域来自WorldView-2(WV2)卫星平台从欧洲空间成像获得,并从美国地质调查(USGS)存档下载了Landsat-8(L8)。选择图像四个月的时间,以评估关于植被生长变化的连续性。对于诸如归一化差异植被指数(NDVI)的每个卫星平台数据,土壤调整后植被指数(SAVI)和分数光合作用辐射(FPAR)计算出来。从具有不同空间和光谱分辨率的ThetWo卫星系统产生的这些VI的比较是致法的,对于作物的每个生长阶段,分析它们的结果,以检查它们的相关性。ilizeWV2新的光谱数据,几种创新叶绿素和叶绿素创建和评估植被指数,以揭示其在检测问题植物生长区域的有效性。绿色叶绿素指数似乎是划定这些区域的最有效的指标。

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