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Al-Busaidi, A
Tarshish, R
Tsipris, J
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Authors
Meron, M
Tsipris, J
Orlov, V
Alchnatis, V
Cohen, Y
Jayasuriya, H
Al-Busaidi, A
Ahmed, M
Pelta, R
Beeri, O
Shilo, T
Tarshish, R
Sahoo, M
Tarshish, R
Alchanatis , V
Herrmann, I
Topics
Remote Sensing Application / Sensor Technology
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Oral
Year
2008
2018
2022
2024
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Filter results4 paper(s) found.

1. Crop Water Stress Mapping for Site Specific Irrigation by Thermal Imagery and Artificial Reference Surfaces

Variable rate irrigation machines or solid set systems have become technically feasible; however, crop water status mapping is necessary as a blueprint to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide these maps in sufficient detail and at a timely delivery. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high- resolution thermal imagery and artificial reference... M. Meron, J. Tsipris, V. Orlov, V. Alchnatis, Y. Cohen

2. Precision Irrigation Management Through Conjunctive Use of Treated Wastewater and Groundwater in Oman

Agriculture under arid environment is always become a challenge due to water scarcity and salinity problems.  With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstraction... H. Jayasuriya, A. Al-busaidi, M. Ahmed

3. A Hyperlocal Machine Learning Approach to Estimate NDVI from SAR Images for Agricultural Fields

The normalized difference vegetation index (NDVI) is a key parameter in precision agriculture used globally since the 1970s. The NDVI is sensitive to the biochemical and physiological properties of the crop and is based on the Red (~650 nm) and NIR (~850 nm) spectral bands. It is used as a proxy to monitor crop growth, correlates to the crop coefficient (Kc), leaf area index (LAI), crop cover, and more. Yet, it is susceptible to clouds and other atmospheric conditions which might alter... R. Pelta, O. Beeri, T. Shilo, R. Tarshish

4. Comparing Hyperspectral and Thermal UAV-borne Imagery for Relative Water Content Estimation in Field-grown Sesame

Sesame (Sesamum indicum) is an irrigated oilseed crop, and studies on its water content estimation are sparred. Unmanned aerial vehicle (UAV)-borne imageries using spectral reflectance as well as thermal emittance for crops are an ample source of high throughput information about their physiological and chemical traits. Though several studies have dealt with thermal emittance to assess the crop water content, evaluating its relation to the plant’s solar reflectance is limitedly... M. Sahoo, R. Tarshish, V. Alchanatis , I. Herrmann