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Zillmann, E
Li, B
Zhoa, L
Tucker, M.A
Trindall, J
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Authors
Zhao, C
Li, B
Frotscher, K.J
Schacht, R
Smith, L
Zillmann, E
Vellidis, G
Liakos, V
Porter, W
Liang, X
Tucker, M.A
Trindall, J
Rainbow, R
Palla, S
Bhandari, M
Zhoa, L
Topics
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Oral
Poster
Year
2014
2016
2018
2024
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1. Heavy Metal PB2+ Pollution Detection In Soil Using Terahertz Time-domain Spectroscopy For Precision Agriculture

Soil is an important natural resource for human beings. With the rapid development of modern industry, heavy metals pollution in soil has made prominent influences on farmland environment. It was reported that, one fifth of China's cultivated lands and more than 217,000 farms in the US have been polluted at different levels by heavy metals. The crop grows in the polluted soil and the heavy metal ions transfer from soil to the plant and agro-products. As a result, the crop yield... C. Zhao, B. Li

2. Planet Labs' Monitoring Solution in Support of Precision Agriculture Practices

Satellite imagery is particularly useful for efficiently monitoring very large areas and providing regular feedback on the status and productivity of agricultural fields. These data are now widely used in precision farming; however, many challenges to making optimal use of this technology remain, such as easy access to data, management and exploitation of large datasets with deep time series, and sharing of the data and derived analytics with users. Providing satellite imagery through a cloud... K.J. Frotscher, R. Schacht, L. Smith, E. Zillmann

3. A Dynamic Variable Rate Irrigation Control System

Currently variable rate irrigation (VRI) prescription maps used to apply water differentially to irrigation management zones (IMZs) are static.  They are developed once and used thereafter and thus do not respond to environmental variables which affect soil moisture conditions.  Our approach for creating dynamic prescription maps is to use soil moisture sensors to estimate the amount of irrigation water needed to return each IMZ to an ideal soil moisture condition.  The UGA Smart... G. Vellidis, V. Liakos, W. Porter, X. Liang, M.A. Tucker

4. Accelerating Precision Agriculture to Decision Agriculture: Enabling Digital Agriculture in Australia

For more than two decades, the success of Australia’s agricultural and rural sectors has been supported by the work of the Rural Research and Development Corporations (RDCs). The RDCs are funded by industry and government. For the first time, all fifteen of Australia’s RDC’s have joined forces with the Australian government to design a solution for the use of big data in Australian agriculture. This is the first known example of a nationwide approach for the digital transformation... J. Trindall, R. Rainbow

5. Growth Analysis on Cotton Using Unoccupied Aerial Systems (UAS) Based Multi-temporal Canopy Features

The use of Unoccupied Aerial Systems (UAS) is rapidly evolving to generate imagery to determine crop growth patterns. A field experiment was conducted with thirty cotton varieties in 2016 and forty-two cotton varieties in 2021. The main objectives were (i) to perform growth analysis by using Canopy Cover (CC) and Canopy Height (CH) measurements obtained from UAS, (ii) to extract growth parameters from CC and CH data, (iii) to assess the relationship between the yield of cotton... S. Palla, M. Bhandari