Suitability of aerial and satellite data for calculation of site-specific nitrogen fertilisation compared to ground based sensor data

被引:0
|
作者
P. Wagner
K. Hank
机构
[1] Martin-Luther-University Halle-Wittenberg,Agribusiness and Farm Management Group
来源
Precision Agriculture | 2013年 / 14卷
关键词
System comparison; Optical sensing; Red edge inflection point; Precision nitrogen management;
D O I
暂无
中图分类号
学科分类号
摘要
Signals for determining rates for site-specific nitrogen fertilisation can be obtained via different sensors. Optical systems that record the nitrogen supply status of the plant via the reflected sunlight have been widely validated. In particular, ground based systems like the YARA N-Sensor have been put into practice. However, such sensors have disadvantages as they only record a small part of the crop population to the left and right of the tramline. This disadvantage is overcome by data obtained from the air (aircraft) or space (satellite). In the study presented, three systems—ground, aerial and space—were compared; of particular interest were data from the RapidEye-System, which has delivered data since 2009. The comparison showed that if the (well suited) Red Edge Inflection Point (REIP) has to be calculated for the determination of the site-specific amount of N-fertiliser, then the system based on satellite imagery would not be suitable for determining N-rates. In addition, the delivered data were shifted by 35 m and had to be corrected. The aerial system also delivered spatially shifted data, however the REIP can be calculated without a problem. Upon considering the costs and the weather dependant availability of the data, the ground based system was most suitable, despite its disadvantage of providing an incomplete crop recording; the aerial system, however, provides a good alternative if its costs can be reduced. The space system would be a good alternative if it were able to deliver all four wavelength ranges that are necessary for the REIP.
引用
收藏
页码:135 / 150
页数:15
相关论文
共 50 条
  • [21] Forest Cover Mapping Based on a Combination of Aerial Images and Sentinel-2 Satellite Data Compared to National Forest Inventory Data
    Ganz, Selina
    Adler, Petra
    Kaendler, Gerald
    FORESTS, 2020, 11 (12): : 1 - 20
  • [22] A black-box model for generation of site-specific WWTP influent quality data based on plant routine data
    Ahnert, Markus
    Marx, Conrad
    Krebs, Peter
    Kuehn, Volker
    WATER SCIENCE AND TECHNOLOGY, 2016, 74 (12) : 2978 - 2986
  • [23] Analysis of Tropospheric Nitrogen Dioxide Using Satellite and Ground Based Data over Northern Thailand
    Lalitaporn, Pichnaree
    Boonmee, Tharinee
    ENGINEERING JOURNAL-THAILAND, 2019, 23 (06): : 19 - 35
  • [24] Site-specific nitrogen management in winter wheat supported by low-altitude remote sensing and soil data
    Argento, F.
    Anken, T.
    Abt, F.
    Vogelsanger, E.
    Walter, A.
    Liebisch, F.
    PRECISION AGRICULTURE, 2021, 22 (02) : 364 - 386
  • [25] Site-specific nitrogen management in winter wheat supported by low-altitude remote sensing and soil data
    F. Argento
    T. Anken
    F. Abt
    E. Vogelsanger
    A. Walter
    F. Liebisch
    Precision Agriculture, 2021, 22 : 364 - 386
  • [26] Site-Specific Vehicle Load Models Based on WIM Data for Long Span Bridges Assessment
    Zhu, R.
    Shi, X. F.
    Ruan, X.
    LIFE-CYCLE OF STRUCTURAL SYSTEMS: DESIGN, ASSESSMENT, MAINTENANCE AND MANAGEMENT, 2015, : 1035 - 1040
  • [27] Site-specific land clutter modelling based on radar remote sensing images and digital terrain data
    Kurekin, Andriy
    Shark, Lik-Kwan
    Lever, Kenneth
    Radford, Darren
    Marshall, Dave
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XVI, 2010, 7830
  • [28] Reliability-based assessment of roofs in Japan subjected to extreme snows: incorporation of site-specific data
    Takahashi, T
    Ellingwood, BR
    ENGINEERING STRUCTURES, 2005, 27 (01) : 89 - 95
  • [29] Comparison of GOME-2 UVA Satellite Data to Ground-Based Spectroradiometer Measurements at a Subtropical Site
    Parisi, Alfio V.
    Downs, Nathan
    Turner, Joanna
    King, Rachel
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (06): : 3145 - 3149
  • [30] GeoEye-1 satellite versus ground-based multispectral data for estimating nitrogen status of turfgrasses
    Caturegli, Lisa
    Casucci, Marco
    Lulli, Filippo
    Grossi, Nicola
    Gaetani, Monica
    Magni, Simone
    Bonari, Enrico
    Volterrani, Marco
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2015, 36 (08) : 2238 - 2251