Abstract
This paper presents a remote sensing model for crop monitoring that was developed by the authors in a multi-year study. It also presents two experiments conducted for testing a newly developed application. The model combines remote sensing models using mapping of the spatial distribution of vegetation in an agricultural field, with precision agricultural models that maximize the output (yield) while minimizing the input (cost). This combination enables one to operate a monitoring and management process that includes every sub-unit of the field using remote sensing mapping. The model consists of five steps: (1) Preparing information layers that map the crop-affecting elements, e.g. irrigation and topography; (2) Collecting spectral and plant data simultaneously; (3) Processing and analyzing the data in order to prepare vegetation maps; (4) Decision-making in accordance with the above-mentioned maps or with predicted-yield maps; and (5) Quality control. The experiments showed that although the results were not statistically significant, the application of the proposed model enables one to draw recommendations within 45 h, and that remote sensing monitoring results in more benefits than do traditional control methods. The quality control was not ideal, due to the narrow range of the spectrum used in the remote sensing monitoring.
Original language | English |
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Pages (from-to) | 47-54 |
Number of pages | 8 |
Journal | ISPRS Journal of Photogrammetry and Remote Sensing |
Volume | 64 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2009 |
Bibliographical note
Funding Information:The authors hereby acknowledge the use of the mapping and computing facilities offered by the Remote Sensing and GIS Laboratory of the University of Haifa, Israel. Also, the authors would like to acknowledge the following individuals who helped in conducting the experiments: Dodi Shemesh, Shai Citain and Uzi Naftaliahu from the Israel Ministry of Agriculture; Gabi Gera from the experimental farm near Acre; Israel. Yehuda Neer from Kibbutz Saad. The following Funds financed extensive parts of this research: The University of Haifa Fund for Research, and The Negev Farmers’ Committee.
Keywords
- Agricultural monitoring
- Quality control
- Real-time
- Remote sensing
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Engineering (miscellaneous)
- Computer Science Applications
- Computers in Earth Sciences