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Delineating crop management zones in small fields using multi-temporal Landsat data

机译:使用多时间LANDSAT数据划定在小型字段中的作物管理区域

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Remotely sensed imagery data are widely used for monitoring crop growth and prescribing management practices. However, acquiring multiple images throughout the growing season for several years could be cost prohibitive. Moderate spatial (30m) resolution Landsat data could be a potential source for accomplishing these objectives. While delineating within-field management zones in large fields using Landsat data is well documented, fewer attempts have been made in smaller fields because of the restrictions imposed by the spatial resolution. On the other hand, Landsat data are acquired once every 16 days which increases the possibility of obtaining several images in a growing season. Landsat spectral bands are rigorously calibrated enabling multi-year comparison. This paper reports on the utility of multi-year Landsat images for monitoring crop growth and delineating management zones in small fields in Wyoming (USA). Spectral reflectance values derived from Landsat images acquired in each growing season were converted to vegetation indices. Based on these values the pixels within the field were grouped into low, medium and high growth classes. Using multi-year growth patterns, crop management zones were delineated for each field. Results from this study could provide valuable insights for farmers to identify problem areas within their fields and better manage them.
机译:远程感测的图像数据广泛用于监测作物生长和规定管理实践。然而,在整个生长季节获得多年的多个图像可能是成本令人愉快的。适度空间(30M)分辨率LANDSAT数据可能是实现这些目标的潜在来源。在使用Landsat数据的大字段中划定现场管理区域的划定内部管理区,因此由于空间分辨率施加的限制,较小的领域在较小的领域中取得了更少的尝试。另一方面,每16天获得一次Landsat数据,这增加了在不断增长的季节获得多种图像的可能性。 Landsat光谱频带严格校准,实现多年比较。本文报告了多年岩土图像监测Wyoming(USA)的小型田野中的作物生长和描绘管理区的效用。从每个生长季节获取的Landsat图像衍生的光谱反射率值被转换为植被指数。基于这些值,该字段内的像素被分组为低,中和高生长类。使用多年增长模式,为每个领域划算作物管理区。本研究的结果可以为农民提供有价值的见解,以确定其领域内的问题区域并更好地管理它们。

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