Site-specific management of common olive: Remote sensing, geospatial, and advanced image processing applications

2016 ◽  
Vol 127 ◽  
pp. 680-689 ◽  
Author(s):  
Omid Noori ◽  
Sudhanshu Sekhar Panda
2017 ◽  
Vol 19 (4) ◽  
pp. 684-707 ◽  
Author(s):  
Claudia Georgi ◽  
Daniel Spengler ◽  
Sibylle Itzerott ◽  
Birgit Kleinschmit

Agronomy ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 437 ◽  
Author(s):  
Piero Toscano ◽  
Annamaria Castrignanò ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Vittorio Vonella ◽  
Domenico Ventrella ◽  
...  

The availability of big data in agriculture, enhanced by free remote sensing data and on-board sensor-based data, provides an opportunity to understand within-field and year-to-year variability and promote precision farming practices for site-specific management. This paper explores the performance in durum wheat yield estimation using different technologies and data processing methods. A state-of-the-art data cleaning technique has been applied to data from a yield monitoring system, giving a good agreement between yield monitoring data and hand sampled data. The potential use of Sentinel-2 and Landsat-8 images in precision agriculture for within-field production variability is then assessed, and the optimal time for remote sensing to relate to durum wheat yield is also explored. Comparison of the Normalized Difference Vegetation Index(NDVI) with yield monitoring data reveals significant and highly positive linear relationships (r ranging from 0.54 to 0.74) explaining most within-field variability for all the images acquired between March and April. Remote sensing data analyzed with these methods could be used to assess durum wheat yield and above all to depict spatial variability in order to adopt site-specific management and improve productivity, save time and provide a potential alternative to traditional farming practices.


2008 ◽  
Vol 31 (7) ◽  
pp. 1188-1202 ◽  
Author(s):  
Umakant Mishra ◽  
David Clay ◽  
Todd Trooien ◽  
Kevin Dalsted ◽  
Douglas Malo ◽  
...  

2010 ◽  
Vol 2 (8) ◽  
pp. 1973-1997 ◽  
Author(s):  
Sudhanshu Sekhar Panda ◽  
Gerrit Hoogenboom ◽  
Joel O. Paz

HortScience ◽  
1999 ◽  
Vol 34 (3) ◽  
pp. 559D-559
Author(s):  
John LeBoeuf

The initial surge of interest in precision agriculture technologies exhibited by innovators and early adopters involved in crop production appears to have crossed over an important threshold and made a significant development. As valuable field experience increases and learning by doing advances, successful applications of management practices are being identified. Access to accurate information pertaining to practical applications of site-specific management would be expected to motivate more producers to incorporate technology uses with crop production. This next group of producers has been watching technology developments as they preferred to avoid risk and wait for identifiable benefits. Waiting for detailed case studies involving high value fruit and vegetables may be the wrong approach to take. Fierce competition and strict confidentiality are expected, especially in the fresh-market industry that places quality attributes high on the list of desired features. Practical applications of technology that pertain to manageable factors will be the impetus to implementation of site-specific management. High resolution remote sensing imagery from digital aerial and satellite sensors has been used to identify plant stress, direct plant tissue and soil sampling efforts to identifiable soil variability, and provide valuable information for analysis and interpretation of crop growth. Examples of remote sensing imagery that has provided valuable in season progress reports will be identified. Imagery can then be used in a geographic information system along with field maps based on soil properties and physical characteristics determined by on-the-go tractors using various sensors. The focus will be on practice, not theory, as seen from an industry perspective.


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