scholarly journals Fusion of Hyper-Spectral and Thermal Images for Evaluating Nitrogen and Water Status in Potato Fields for Variable Rate Application

2013 ◽  
Author(s):  
Yafit Cohen ◽  
Carl Rosen ◽  
Victor Alchanatis ◽  
David Mulla ◽  
Bruria Heuer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Precision Agriculture ◽  
Water Status ◽  
Irrigation Management ◽  
Water Levels ◽  
Thermal Imagery ◽  
Thermal Images ◽  
The Us ◽  
N Status

Potato yield and quality are highly dependent on an adequate supply of nitrogen and water. Opportunities exist to use airborne hyperspectral (HS) remote sensing for the detection of spatial variation in N status of the crop to allow more targeted N applications. Thermal remote sensing has the potential to identify spatial variations in crop water status to allow better irrigation management and eventually precision irrigation. The overall objective of this study was to examine the ability of HS imagery in the visible and near infrared spectrum (VIS-NIR) and thermal imagery to distinguish between water and N status in potato fields. To lay the basis for achieving the research objectives, experiments in the US and in Israel were conducted in potato with different irrigation and N-application amounts. Thermal indices based merely on thermal images were found sensitive to water status in both Israel and the US in three potato varieties. Spectral indices based on HS images were found suitable to detect N stress accurately and reliably while partial least squares (PLS) analysis of spectral data was more sensitive to N levels. Initial fusion of HS and thermal images showed the potential of detecting both N stress and water stress and even to differentiate between them. This study is one of the first attempts at fusing HS and thermal imagery to detect N and water stress and to estimate N and water levels. Future research is needed to refine these techniques for use in precision agriculture applications.

scholarly journals Use of Thermal Imaging to Assess Water Status in Citrus Plants in Greenhouses

Horticulturae ◽  
2021 ◽  
Vol 7 (8) ◽  
pp. 249
Author(s):  
Gustavo Haddad Souza Vieira ◽  
Rhuanito Soranz Ferrarezi
Keyword(s):  
Thermal Imaging ◽  
Sweet Orange ◽  
Water Status ◽  
Irrigation Management ◽  
Canopy Temperature ◽  
Irrigation Scheduling ◽  
Water Levels ◽  
Automated System ◽  
Thermal Images ◽  
One Year

The direct examination of plant canopy temperature can assist in optimizing citrus irrigation management in greenhouses. This study aimed to develop a method to measure canopy temperature using thermal imaging in one-year-old citrus plants in a greenhouse to identify plants with water stress and verify its potential to be used as a tool to assess citrus water status. The experiment was conducted for 48 days (27 November 2019 to 13 January 2020). We evaluated the influence of five levels of irrigation on two citrus species (‘Red Ruby’ grapefruit (Citrus paradisi) and ‘Valencia’ sweet orange (Citrus sinensis (L.) Osbeck)). Images were taken using a portable thermal camera and analyzed using open-source software. We determined canopy temperature, leaf photosynthesis and transpiration, and plant biomass. The results indicated a positive relationship between the amount of water applied and the temperature response of plants exposed to different water levels. Grapefruit and sweet orange plants that received less water and were submitted to water restrictions showed higher canopy temperatures than the air (up to 6 °C). The thermal images easily identified water-stressed plants. Our proof-of-concept study allowed quickly obtaining the canopy temperature using readily available equipment and can be used as a tool to assess citrus water status in one-year-old citrus plants in greenhouses and perhaps in commercial operations with mature trees in the field after specific experimentation. This technique, coupled with an automated system, can be used for irrigation scheduling. Thus, setting up a limit temperature is necessary to start the irrigation system and set the irrigation time based on the soil water content. To use this process on a large scale, it is necessary to apply an automation routine to process the thermal images in real time and remove the weeds from the background to determine the canopy temperature.

scholarly journals Crop Water Condition Mapping by Optical Remote Sensing

2021 ◽  
pp. 11-17
Author(s):  
M.V. Wojtaszek ◽  
I. Abdurahmanov
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Soil Water ◽  
Precision Agriculture ◽  
Water Status ◽  
Vegetation Indices ◽  
Irrigation Scheduling ◽  
Crop Water ◽  
Stress Monitoring ◽  
Wide Range

Crop water stress monitoring represents a fundamental step in agricultural production. In order to increase water savings and enhance agricultural sustainability, implementation of suitable irrigation scheduling methods is essential, and requires early detection of water stress in crops, before it causes irreversible damage and yield loss. There are different methods to measure water stress, some of them are based on soil moisture measurements while others are based on calculations of vegetation indices, evapotranspiration or soil water balance. Currently, the use of remote sensing technologies for the analysis of plant water status comprises a wide range of available methods such as infrared thermometry for canopy temperature measures, microwave radiation for soil water content assessment, and spectral vegetation indices for the study of the reflectance responses of canopies to different environmental conditions. The aim of the presented work is to investigate the applicability of the optical trapezoid model (OPtical TRApezoid Model) in mapping the moisture content within agricultural field. The model ability to provide vegetation characteristics, and crop water status at the canopy scale can improve the site-specific decision-making process in a precision agriculture.

scholarly journals Remote Sensing for Plant Water Content Monitoring: A Review

2021 ◽  
Vol 13 (11) ◽  
pp. 2088
Author(s):  
Carlos Quemada ◽  
José M. Pérez-Escudero ◽  
Ramón Gonzalo ◽  
Iñigo Ederra ◽  
Luis G. Santesteban ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Continuous Wave ◽  
Technological Development ◽  
Water Status ◽  
Irrigation Management ◽  
Coefficient Of Determination ◽  
Plant Water ◽  
Monitoring Methods

This paper reviews the different remote sensing techniques found in the literature to monitor plant water status, allowing farmers to control the irrigation management and to avoid unnecessary periods of water shortage and a needless waste of valuable water. The scope of this paper covers a broad range of 77 references published between the years 1981 and 2021 and collected from different search web sites, especially Scopus. Among them, 74 references are research papers and the remaining three are review papers. The different collected approaches have been categorized according to the part of the plant subjected to measurement, that is, soil (12.2%), canopy (33.8%), leaves (35.1%) or trunk (18.9%). In addition to a brief summary of each study, the main monitoring technologies have been analyzed in this review. Concerning the presentation of the data, different results have been obtained. According to the year of publication, the number of published papers has increased exponentially over time, mainly due to the technological development over the last decades. The most common sensor is the radiometer, which is employed in 15 papers (20.3%), followed by continuous-wave (CW) spectroscopy (12.2%), camera (10.8%) and THz time-domain spectroscopy (TDS) (10.8%). Excluding two studies, the minimum coefficient of determination (R2) obtained in the references of this review is 0.64. This indicates the high degree of correlation between the estimated and measured data for the different technologies and monitoring methods. The five most frequent water indicators of this study are: normalized difference vegetation index (NDVI) (12.2%), backscattering coefficients (10.8%), spectral reflectance (8.1%), reflection coefficient (8.1%) and dielectric constant (8.1%).

scholarly journals Water stress coefficient determined by orbital remote sensing techniques

2020 ◽  
Vol 24 (12) ◽  
pp. 847-853
Author(s):  
Élvis da S. Alves ◽  
Roberto Filgueiras ◽  
Lineu N. Rodrigues ◽  
Fernando F. da Cunha ◽  
Catariny C. Aleman
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Irrigation Management ◽  
Simple Algorithm ◽  
Landsat 8 ◽  
Stress Coefficient ◽  
Use Efficiency ◽  
Remote Sensing Techniques ◽  
Water Stress Coefficient ◽  
The Relationship

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.

scholarly journals Water Management Using Drones and Satellites in Agriculture

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 874 ◽  
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.

scholarly journals A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Agronomy ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 140 ◽  
Author(s):  
Deepak Gautam ◽  
Vinay Pagay
Keyword(s):  
Remote Sensing ◽  
Water Status ◽  
Irrigation Management ◽  
3D Structure ◽  
Crop Water ◽  
Horticultural Crops ◽  
Potential Applications ◽  
Remote Measurements ◽  
The Individual ◽  
Precision Irrigation

With increasingly advanced remote sensing systems, more accurate retrievals of crop water status are being made at the individual crop level to aid in precision irrigation. This paper summarises the use of remote sensing for the estimation of water status in horticultural crops. The remote measurements of the water potential, soil moisture, evapotranspiration, canopy 3D structure, and vigour for water status estimation are presented in this comprehensive review. These parameters directly or indirectly provide estimates of crop water status, which is critically important for irrigation management in farms. The review is organised into four main sections: (i) remote sensing platforms; (ii) the remote sensor suite; (iii) techniques adopted for horticultural applications and indicators of water status; and, (iv) case studies of the use of remote sensing in horticultural crops. Finally, the authors’ view is presented with regard to future prospects and research gaps in the estimation of the crop water status for precision irrigation.

Crop water stress index derived from multi-year ground and aerial thermal images as an indicator of potato water status

2014 ◽  
Vol 15 (3) ◽  
pp. 273-289 ◽  
Author(s):  
Ronit Rud ◽  
Y. Cohen ◽  
V. Alchanatis ◽  
A. Levi ◽  
R. Brikman ◽  
...  
Keyword(s):  
Water Stress ◽  
Water Status ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Thermal Images ◽  
Water Stress Index ◽  
Crop Water Stress

scholarly journals ↵​Impact of A Selected Mycorrhizal Complex and A Rhizobacterial Species on Tomato Plants’ Growth under Water Stress Conditions

2021 ◽  
Author(s):  
Slimani Afafe ◽  
Harkousse Oumaima ◽  
Mazri Mouaad Amine ◽  
Zouahri Abdelmajid ◽  
Ouahmane Lahcen ◽  
...  
Keyword(s):  
Water Stress ◽  
Mycorrhizal Fungi ◽  
Growth Parameters ◽  
Water Status ◽  
Field Capacity ◽  
Water Levels ◽  
Stress Conditions ◽  
Bacillus Sp ◽  
Tomato Plants ◽  
The Impact

Background: Plant strategies for adapting to drought could be improved by associations between plant roots and soil microorganisms, including arbuscular mycorrhizal fungi (AMF) and plant growth promoting rhizobacteria (PGPR). In this study, the impact of a selected AMF complex and a selected PGPR species on the growth of tomato (Lycopersicum esculentum Mill.) under induced water stress was evaluated. Methods: Three different inoculation treatments were applied to tomato seedlings (a complex of AMF composed mainly of Glomus genus a Bacillus sp. PGPR treatment and a combination of both) and three different water levels (75%, 50% and 25% of field capacity). Result: A significant damaging impact of drought on tomato growth parameters and root mycorrhizal colonization, although the presence of microbes stimulated tomato plants growth and decreased the impact ofdrought stress. Indeed inoculated plants presented greater heights, fresh and dry weights, leaves number and area; greater water status; and greater proteins, sugars and chlorophylls contents either with the AMF complex or the Bacillus sp. in normal and drought stress conditions compared to the non-inoculated plants. However dual inoculation recorded the highest values under all water levels treatments.

scholarly journals The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat

2015 ◽  
Vol 19 (11) ◽  
pp. 4653-4672 ◽  
Author(s):  
G. Boulet ◽  
B. Mougenot ◽  
J.-P. Lhomme ◽  
P. Fanise ◽  
Z. Lili-Chabaane ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Energy Balance ◽  
Surface Temperature ◽  
Series Resistance ◽  
Water Status ◽  
Soil Evaporation ◽  
Stress Levels ◽  
Dual Source ◽  
Rainfed Wheat

Abstract. Evapotranspiration is an important component of the water cycle, especially in semi-arid lands. A way to quantify the spatial distribution of evapotranspiration and water stress from remote-sensing data is to exploit the available surface temperature as a signature of the surface energy balance. Remotely sensed energy balance models enable one to estimate stress levels and, in turn, the water status of continental surfaces. Dual-source models are particularly useful since they allow derivation of a rough estimate of the water stress of the vegetation instead of that of a soil–vegetation composite. They either assume that the soil and the vegetation interact almost independently with the atmosphere (patch approach corresponding to a parallel resistance scheme) or are tightly coupled (layer approach corresponding to a series resistance scheme). The water status of both sources is solved simultaneously from a single surface temperature observation based on a realistic underlying assumption which states that, in most cases, the vegetation is unstressed, and that if the vegetation is stressed, evaporation is negligible. In the latter case, if the vegetation stress is not properly accounted for, the resulting evaporation will decrease to unrealistic levels (negative fluxes) in order to maintain the same total surface temperature. This work assesses the retrieval performances of total and component evapotranspiration as well as surface and plant water stress levels by (1) proposing a new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) in two versions (parallel and series resistance networks) based on the TSEB (Two-Source Energy Balance model, Norman et al., 1995) model rationale as well as state-of-the-art formulations of turbulent and radiative exchange, (2) challenging the limits of the underlying hypothesis for those two versions through a synthetic retrieval test and (3) testing the water stress retrievals (vegetation water stress and moisture-limited soil evaporation) against in situ data over contrasted test sites (irrigated and rainfed wheat). We demonstrated with those two data sets that the SPARSE series model is more robust to component stress retrieval for this cover type, that its performance increases by using bounding relationships based on potential conditions (root mean square error lowered by up to 11 W m−2 from values of the order of 50–80 W m−2), and that soil evaporation retrieval is generally consistent with an independent estimate from observed soil moisture evolution.

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