Suppr超能文献

近程与遥感技术在精准农业管理中作物状况诊断方面的比较

Comparison of Proximal and Remote Sensing for the Diagnosis of Crop Status in Site-Specific Crop Management.

作者信息

Mezera Jiří, Lukas Vojtěch, Horniaček Igor, Smutný Vladimír, Elbl Jakub

机构信息

Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic.

出版信息

Sensors (Basel). 2021 Dec 22;22(1):19. doi: 10.3390/s22010019.

Abstract

The presented paper deals with the issue of selecting a suitable system for monitoring the winter wheat crop in order to determine its condition as a basis for variable applications of nitrogen fertilizers. In a four-year (2017-2020) field experiment, 1400 ha of winter wheat crop were monitored using the ISARIA on-the-go system and remote sensing using Sentinel-2 multispectral satellite images. The results of spectral measurements of ISARIA vegetation indices (IRMI, IBI) were statistically compared with the values of selected vegetation indices obtained from Sentinel-2 (EVI, GNDVI, NDMI, NDRE, NDVI and NRERI) in order to determine potential hips. Positive correlations were found between the vegetation indices determined by the ISARIA system and indices obtained by multispectral images from Sentinel-2 satellites. The correlations were medium to strong (r = 0.51-0.89). Therefore, it can be stated that both technologies were able to capture a similar trend in the development of vegetation. Furthermore, the influence of climatic conditions on the vegetation indices was analyzed in individual years of the experiment. The values of vegetation indices show significant differences between the individual years. The results of vegetation indices obtained by the analysis of spectral images from Sentinel-2 satellites varied the most. The values of winter wheat yield varied between the individual years. Yield was the highest in 2017 (7.83 t/ha), while the lowest was recorded in 2020 (6.96 t/ha). There was no statistically significant difference between 2018 (7.27 t/ha) and 2019 (7.44 t/ha).

摘要

本文探讨了选择合适系统监测冬小麦作物以确定其状况作为氮肥变量施用依据的问题。在一项为期四年(2017 - 2020年)的田间试验中,使用ISARIA实时系统和哨兵2号多光谱卫星图像遥感技术对1400公顷冬小麦作物进行了监测。为了确定潜在关联,对ISARIA植被指数(IRMI、IBI)的光谱测量结果与从哨兵2号获得的选定植被指数(EVI、GNDVI、NDMI、NDRE、NDVI和NRERI)值进行了统计比较。发现ISARIA系统确定的植被指数与哨兵2号卫星多光谱图像获得的指数之间存在正相关。相关性为中等至强(r = 0.51 - 0.89)。因此,可以说这两种技术都能够捕捉到植被发育的相似趋势。此外,在试验的各个年份分析了气候条件对植被指数的影响。植被指数值在各年份之间存在显著差异。通过分析哨兵2号卫星光谱图像获得的植被指数结果变化最大。冬小麦产量在各年份之间有所不同。2017年产量最高(7.83吨/公顷),而2020年记录的产量最低(6.96吨/公顷)。2018年(7.27吨/公顷)和2019年(7.44吨/公顷)之间没有统计学上的显著差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7070/8747194/a46a3a56aa8c/sensors-22-00019-g0A1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验