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.

scholarly journals Crop Water Requirements in Egypt Using Remote Sensing Techniques

2014 ◽  
Vol 03 (02) ◽  
pp. 57-65 ◽  
Author(s):  
Mohammed A. El-Shirbeny ◽  
Abd-Elraouf M. Ali ◽  
Nasser H. Saleh
Keyword(s):  
Remote Sensing ◽  
Crop Water ◽  
Water Requirements ◽  
Crop Water Requirements ◽  
Remote Sensing Techniques

The use of earth observation methods for estimating regional crop evapotranspiration and yield for water footprint accounting

2017 ◽  
Vol 156 (5) ◽  
pp. 599-617 ◽  
Author(s):  
G. Papadavid ◽  
L. Toulios
Keyword(s):  
Remote Sensing ◽  
Crop Yield ◽  
Water Footprint ◽  
Earth Observation ◽  
Soil Parameters ◽  
Yield Prediction ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Water Requirements ◽  
Remote Sensing Techniques

AbstractRemote sensing can efficiently support the quantification of crop water requirements included in the goal of assessing water footprints, which is to analyse how human activities or specific products relate to issues of water scarcity and pollution and identify how activities and products can become more sustainable from a water perspective. Remote sensing techniques have become popular in estimating actual crop evapotranspiration and hence crop water requirements in recent decades due to the advantages they offer to users, e.g. low cost, regional data and use of maps instead of point measurements as well as saving time. The use of earth observation data supports models’ accuracy in the procedure for assessing water footprint, since no average values are used: instead, users have real values for the specific parameters.The present study provides two examples of how remote sensing techniques are used essentially for estimating evapotranspiration along with crop yield, two basic parameters, for assessing water footprint. Two different case studies have been illustrated to define the methodology proposed, which refers to Mediterranean conditions and can be applied after inferring the necessary field data of each crop. The first case study refers to the application of Surface Energy Balance Algorithm for Land (SEBAL) for estimating evapotranspiration, while the second refers to the Crop Yield prediction. Both elements, such as evapotranspiration and crop yield, are vital for water footprint accounting. Firstly, the SEBAL was adopted, under the essential adaptations for local soil and meteorological conditions for estimating groundnut water requirements. Landsat-5 TM, Landsat-7 Enhanced Thematic Mapper+ and Landsat 8 OLI images were used to retrieve the required spectral data. The SEBAL model is enhanced with empirical equations regarding crop canopy factors, in order to increase the accuracy of crop evapotranspiration estimation. Maps were created for evapotranspiration (ET) using the SEBAL modified model for the area of interest. The results were compared with measurements from an evaporation pan, used as a reference. Statistical comparisons showed that the modified SEBAL can predict ETc in a very effective and accurate way and provide water footprint modellers with high-level crop water data. Yield prediction plays a vital role in calculating water footprint. Having real values rather than taking reference (or averaged) values from FAO is an advantage that Earth Observation means can provide. This is very important in econometric or any other prediction models used for estimating water footprint because using average data reduces accuracy. In this context, crop and soil parameters along with remotely sensed data can be used to develop models that can provide users with accurate yield estimations. In a second step, crop and soil parameters along with the normalized difference vegetation index were correlated to examine whether crop yield can be predicted and to define the actual time-window to predict the yield. Statistical and remote sensing techniques were then applied to derive and map a model that can predict crop yield. The algorithm developed for this purpose indicates that remote sensing observations can predict crop yields effectively and accurately. Using the statistical Student's t test, it was found that there was no statistically significant difference between predicted and real values for crop yield.

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 Global Satellite-Based ET Products for the Local Level Irrigation Management: An Application of Irrigation Performance Assessment in the Sugarbelt of Swaziland

2019 ◽  
Vol 11 (6) ◽  
pp. 705 ◽  
Author(s):  
Poolad Karimi ◽  
Bhembe Bongani ◽  
Megan Blatchford ◽  
Charlotte de Fraiture
Keyword(s):  
Remote Sensing ◽  
Performance Assessment ◽  
Management Practices ◽  
Local Level ◽  
Water Productivity ◽  
Irrigation Management ◽  
Irrigation Performance ◽  
Crop Water ◽  
Management Regime ◽  
Crop Water Productivity

Remote sensing techniques have been shown, in several studies, to be an extremely effective tool for assessing the performance of irrigated areas at various scales and diverse climatic regions across the world. Open access, ready-made, global ET products were utilized in this first-ever-countrywide irrigation performance assessment study. The study aimed at identifying ‘bright spots’, the highest performing sugarcane growers, and ‘hot spots’, or low performing sugarcane growers. Four remote sensing-derived irrigation performance indicators were applied to over 302 sugarcane growers; equity, adequacy, reliability and crop water productivity. The growers were segmented according to: (i) land holding size or grower scale (ii) management regime, (iii) location of the irrigation schemes and (iv) irrigation method. Five growing seasons, from June 2005 to October 2009, were investigated. The results show while the equity of water distribution is high across all management regimes and locations, adequacy and reliability of water needs improvement in several locations. Given the fact that, in general, water supply was not constrained during the study period, the observed issues with adequacy and reliability of irrigation in some of the schemes were mostly due to poor scheme and farm level water management practices. Sugarcane crop water productivity showed the highest variation among all the indicators, with Estate managed schemes having the highest CWP at 1.57 kg/m3 and the individual growers recording the lowest CWP at 1.14 kg/m3, nearly 30% less. Similarly center pivot systems showed to have the highest CWP at 1.63 kg/m3, which was 30% higher than the CWP in furrow systems. This study showcases the applicability of publicly available global remote sensing products for assessing performance of the irrigated crops at the local level in several aspects.

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 Remote Sensing Applications for Planning Irrigation Management. The Use of SEBAL Methodology for Estimating Crop Evapotranspiration in Cyprus

2012 ◽  
Vol 9 (1) ◽  
pp. 17-21
Author(s):  
George Papadavid ◽  
Skevi Perdikou ◽  
Michalakis Hadjimitsis ◽  
Diofantos Hadjimitsis
Keyword(s):  
Remote Sensing ◽  
Water Allocation ◽  
Surface Energy Balance ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Severe Drought ◽  
Remotely Sensed Data ◽  
Sensing Applications ◽  
Remote Sensing Applications ◽  
Remote Sensing Techniques

Abstract Water allocation to crops has always been of great importance in the agricultural process. In this context, and under the current conditions, where Cyprus is facing a severe drought the last five years, the purpose of this study is basically to estimate the needed crop water requirements for supporting irrigation management and monitoring irrigation on a systematic basis for Cyprus using remote sensing techniques. The use of satellite images supported by ground measurements has provided quite accurate results. Intended purpose of this paper is to estimate the Evapotranspiration (ET) of specific crops which is the basis for irrigation scheduling and establish a procedure for monitoring and managing irrigation water over Cyprus, using remotely sensed data from Landsat TM/ ETM+ and a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL).

Estimating rice water requirements in the Lis Valley (Portugal) using remote sensing platforms: preliminary results for the 2020 cultivation season

2021 ◽  
Author(s):  
Romeu G. Jorge ◽  
Isabel P. de Lima ◽  
João L.M.P. de Lima
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Irrigation Water ◽  
Crop Yields ◽  
Irrigation District ◽  
Water Requirements ◽  
Local Conditions ◽  
Preliminary Results ◽  
Sentinel 2A ◽  
Rice Water

<p>In irrigated agricultural areas, where the availability of water for irrigation does not rely on any water storage, water management requires special attention, in particular under large annual and inter-annual variability in the hydrological regime and the uncertainty of climate change. The inherent increased vulnerability of the agro-ecosystem, makes the monitoring of crop conditions and water requirements a valuable tool for improving water use efficiency and, therefore, crop yields.</p><p>This presentation focus on one such agricultural area, located in the Lis Valley (Centre of Portugal), which is a rather vulnerable area also facing drainage and salinity problems. The study aims at contributing to better characterizing the temporal and spatial distribution of rice water requirements during the growing season. Irrigation water sources are the Lis River and its tributaries, which discharges depend directly from precipitation. The most important problems of water distribution in the Lis Valley irrigation district are water shortage and poor water quality in the dry summer period, aggravated by limitations of the irrigation and drainage systems that date back to the end of the 1950’s.</p><p>We report preliminary results on using remote sensing data to better understand rice cropping local conditions, obtained within project GO Lis (PDR2020-101-030913) and project MEDWATERICE (PRIMA/0006/2018). Rice irrigation is traditionally conducted applying continuous flooding, which requires much more irrigation water than non-ponded crops, and therefore needs special attention. In particular, data obtained from satellite Sentinel-2A land surface imagery are compared with data obtained using an unmanned aerial vehicle (UAV). Data for rice cultivated areas during the 2020 cultivation season, together with weather and crop parameters, are used to calculate biophysical indicators and indices of water stress in the vegetation. Actual crop evapotranspiration was appraised with remote sensing based estimates of the crop coefficient (Kc) and used to assess rice water requirements. Procedures and methodologies to estimate Kc were tested, namely those based on vegetation indices such as the Normalized Difference Vegetation Index (NDVI). Results are discussed bearing in mind the usefulness of the diverse tools, based on different resolution data (Sentinel-2A and UAV), for improving the understanding of the impacts of irrigation practices on crop yield and main challenges of rice production and water management in the Lis Valley irrigation district.</p>

Remote Sensing Techniques and Its Application in Arid Zones of India

2017 ◽  
pp. 193-211
Author(s):  
Lokesh Kumar Jain
Keyword(s):  
Remote Sensing ◽  
Water Status ◽  
Leaf Age ◽  
Nutrient Status ◽  
Arid Zones ◽  
Large Area ◽  
Leaf Reflectance ◽  
Agronomic Management ◽  
Crop Type ◽  
Remote Sensing Techniques

Remote sensing technologies offer the potential for contributing the security to human existence on arid zones in the country in variety of ways. Remote Sensing in agriculture particularly for natural resource management. It provides important coverage, mapping and classification of land cover features. The remote view of the sensor and the ability to store, analyze, and display the sensed data on field maps are make remote sensing a potentially important tool for agriculture. The aerial photography gives two main advantages viz., speedy survey in very large area or remote area and precise description and recording of resources status. Remotely sensed images provide a means to assess field conditions and gave valuable insights into agronomic management. It led to understanding of leaf reflectance and leaf emittance changes in response to leaf thickness, species, canopy shape, leaf age, nutrient status, and water status. Understanding of leaf reflectance has led to quantify various agronomic parameters, e.g., leaf area, crop cover, biomass, crop type, nutrient status, and yield.

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