Agricultural Systems Studies Using Remote Sensing

Remote Sensing Handbook - Three Volume Set ◽

10.1201/b19355-66 ◽

2018 ◽

pp. 847-864

Keyword(s):

Remote Sensing ◽

Agricultural Systems ◽

Systems Studies

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Water Management Using Drones and Satellites in Agriculture

Water ◽

10.3390/w11050874 ◽

2019 ◽

Vol 11 (5) ◽

pp. 874 ◽

Cited By ~ 3

Author(s):

Javier J. Cancela ◽

Xesús P. González ◽

Mar Vilanova ◽

José M. Mirás-Avalos

Keyword(s):

Water Management ◽

Remote Sensing ◽

Water Status ◽

Irrigation Management ◽

Irrigation Efficiency ◽

Agricultural Systems ◽

Special Issue ◽

Crop Water ◽

Water Requirements ◽

Remote Sensing Techniques

This document intends to be a presentation of the Special Issue “Water Management Using Drones and Satellites in Agriculture”. The objective of this Special Issue is to provide an overview of recent advances in the methodology of using remote sensing techniques for managing water in agricultural systems. Its eight peer-reviewed articles focus on three topics: new equipment for characterizing water bodies, development of satellite-based technologies for determining crop water requirements in order to enhance irrigation efficiency, and monitoring crop water status through proximal and remote sensing. Overall, these contributions explore new solutions for improving irrigation management and an efficient assessment of crop water needs, being of great value for both researchers and advisors.

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On the use of remote sensing techniques for monitoring spatio-temporal soil organic carbon dynamics in agricultural systems

CATENA ◽

10.1016/j.catena.2012.01.001 ◽

2012 ◽

Vol 94 ◽

pp. 64-74 ◽

Cited By ~ 47

Author(s):

H. Croft ◽

N.J. Kuhn ◽

K. Anderson

Keyword(s):

Remote Sensing ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Carbon Dynamics ◽

Agricultural Systems ◽

Spatio Temporal ◽

Remote Sensing Techniques ◽

Soil Organic Carbon Dynamics

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Applications of Artificial Intelligence for Precision Agriculture

EDIS ◽

10.32473/edis-ae529-2018 ◽

2018 ◽

Vol 2018 (6) ◽

Author(s):

Yiannis Ampatzidis

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Remote Sensing ◽

Computer Vision ◽

Precision Agriculture ◽

Agricultural Systems ◽

Disease Identification ◽

Technological Advances

Technological advances in computer vision, mechatronics, artificial intelligence and machine learning have enabled the development and implementation of remote sensing technologies for plant/weed/pest/disease identification and management. They provide a unique opportunity for developing intelligent agricultural systems for precision applications. Herein, the Artificial Intelligence (AI) and Machine Learning concepts are described, and several examples are presented to demonstrate the application of the AI in agriculture. Available on EDIS at: https://edis.ifas.ufl.edu/ae529

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