scholarly journals Using Remote Sensing Methods in Precision Agriculture

2020 ◽  
Author(s):  
Gulnara Bikbulatova ◽  
Elena Kupreyeva ◽  
Lilia Pronina ◽  
Marat Shayakhmetov
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Remote Sensing Methods

Application of Remote Sensing in Agriculture

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Crop Production ◽  
Satellite Images ◽  
Crop Yields ◽  
Spatial Scales ◽  
Strong Relationship ◽  
Physical Parameters ◽  
Agricultural Crop ◽  
Remote Sensing Methods

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.

scholarly journals UAS-Remote Sensing Methods for Mapping, Monitoring and Modeling Crops

2020 ◽  
Vol 12 (23) ◽  
pp. 3873
Author(s):  
Francisco Javier Mesas-Carrascosa
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Crop Management ◽  
Small Sample ◽  
Special Issue ◽  
Sensor Applications ◽  
Aerial Vehicle ◽  
Continue Research ◽  
Remote Sensing Techniques ◽  
Remote Sensing Methods

The advances in Unmanned Aerial Vehicle (UAV) platforms and on-board sensors in the past few years have greatly increased our ability to monitor and map crops. The ability to register images at ultra-high spatial resolution at any moment has made remote sensing techniques increasingly useful in crop management. These technologies have revolutionized the way in which remote sensing is applied in precision agriculture, allowing for decision-making in a matter of days instead of weeks. However, it is still necessary to continue research to improve and maximize the potential of UAV remote sensing in agriculture. This Special Issue of Remote Sensing includes different applications of UAV remote sensing for crop management, covering RGB, multispectral, hyperspectral and LIght Detection and Ranging (LiDAR) sensor applications on-board (UAVs). The papers reveal innovative techniques involving image analysis and cloud points. It should, however, be emphasized that this Special Issue is a small sample of UAV applications in agriculture and that there is much more to investigate.

scholarly journals Remote Sensing Vegetation Indices in Viticulture: A Critical Review

Agriculture ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 457
Author(s):  
Rigas Giovos ◽  
Dimitrios Tassopoulos ◽  
Dionissios Kalivas ◽  
Nestor Lougkos ◽  
Anastasia Priovolou
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Regional Scale ◽  
Vegetation Indices ◽  
Proximal Sensing ◽  
Spectral Bands ◽  
Sensing Platforms ◽  
Precision Viticulture ◽  
Remote Sensing Methods

One factor of precision agriculture is remote sensing, through which we can monitor vegetation health and condition. Much research has been conducted in the field of remote sensing and agriculture analyzing the applications, while the reviews gather the research on this field and examine different scientific methodologies. This work aims to gather the existing vegetation indices used in viticulture, which were calculated from imagery acquired by remote sensing platforms such as satellites, airplanes and UAVs. In this review we present the vegetation indices, the applications of these and the spatial distribution of the research on viticulture from the early 2000s. A total of 143 publications on viticulture were reviewed; 113 of them had used remote sensing methods to calculate vegetation indices, while the rejected ones have used proximal sensing methods. The findings show that the most used vegetation index is NDVI, while the most frequently appearing applications are monitoring and estimating vines water stress and delineation of management zones. More than half of the publications use multitemporal analysis and UAVs as the most used among remote sensing platforms. Spain and Italy are the countries with the most publications on viticulture with one-third of the publications referring to regional scale whereas the others to site-specific/vineyard scale. This paper reviews more than 90 vegetation indices that are used in viticulture in various applications and research topics, and categorized them depending on their application and the spectral bands that they are using. To summarize, this review is a guide for the applications of remote sensing and vegetation indices in precision viticulture and vineyard assessment.

scholarly journals NON-DESTRUCTIVE MONITORING OF RICE BY HYPERSPECTRAL IN-FIELD SPECTROMETRY AND UAV-BASED REMOTE SENSING: CASE STUDY OF FIELD-GROWN RICE IN NORTH RHINE-WESTPHALIA, GERMANY

2016 ◽  
Vol XLI-B1 ◽  
pp. 1071-1077 ◽  
Author(s):  
M. Willkomm ◽  
A. Bolten ◽  
G. Bareth
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Nitrogen Availability ◽  
Growth Parameters ◽  
Paddy Rice ◽  
Growth Monitoring ◽  
World Population ◽  
Area Index ◽  
Nitrogen Treatments ◽  
Remote Sensing Methods

In the context of an increasing world population, the demand for agricultural crops is continuously rising. Especially rice plays a key role in food security, not only in Asia. To increase crop production of rice, either productivity of plants has to be improved or new cultivation areas have to be found. In this context, our study investigated crop growth of paddy rice (Oryza Sativa J.) in Germany. An experimental field in the vegetation period of 2014 with two nitrogen treatments was conducted using remote sensing methods. The research project focussed on two main aspects: (1) the potential of UAV-based and hyperspectral remote sensing methods to monitor selected growth parameters at different phenological stages; (2) the potential of paddy rice cultivation under the present climate condition in western Germany. We applied a low-cost UAV-system (Unmanned Aerial Vehicle) to generate high resolution Crop Surface Models (CSM). These were compared with hyperspectral in-field measurements and directly measured agronomic parameters (fresh and dry aboveground biomass (AGB), leaf-area-index (LAI) and plant nitrogen concentration (PNC)). For all acquisition dates we could determine single in-field structures in the CSM (e.g. distribution of hills) and different growth characteristics between the nitrogen treatments. Especially in the second half of the growing season, the plants with higher nitrogen availability were about 25 – 30 % larger. The plant height in the CSM correlates particularly with fresh AGB and the LAI (R<sup>2</sup> > 0.8). Thus, the conducted methods for plant growth monitoring can be a contribution for precision agriculture approaches.

scholarly journals HYPER SPECTRAL REMOTE SENSING FOR DAMAGE DETECTION AND CLASSIFICATION MODELS IN AGRICULTURE - A REVIEW

2021 ◽  
Vol 9 (1) ◽  
pp. 380-386
Author(s):  
Akshay Dhande, Rahul Malik
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Geographical Information Systems ◽  
Agricultural Sector ◽  
Multiple Scales ◽  
Agricultural Practices ◽  
Geographical Information ◽  
Positioning Systems ◽  
Remote Sensing Techniques ◽  
Remote Sensing Methods

Agriculture is the pillar of the financial system of any country and it's far enormously crucial for financial improvement and social stability. Remote sensing has numerous benefits within the discipline of agronomical studies purpose.  Remote sensing has the capacity to face this big obstacle in the evolutionary changes in agricultural practices, by delivering recurrent information on crop condition at multiple scales and for different actors during the season. Because of the rapid changes in farming started from mid to past 1980, remote sensing has become an indispensable a part of precision agriculture. Agricultural systems need to be monitored in regular interval. Remote sensing act as vital method in well timed tracking and provides a correct snapshot of the agricultural with good accuracy. The tracking of agricultural strongly follows seasonal patterns on the subject of the organic life of crops. Because of this background we studied various remote sensing methods like crop classification, crop tracking and yield assessment. We discovered that almost all of the remote sensing methods have been exploratory investigations, examined on a nearby scale with direct dependence on ground data. In tandem with other specialized methods such as geographical information systems and global positioning systems, remote sensing plays an important role in the measurement and monitoring of agricultural activities. We begin this review by presenting an outline of the existing methods of remote sensing relevant to the agricultural sector. This paper analyses remote sensing methods progress, problems and future in agricultural context. This article will offer an outline of commercially remote sensors having high resolution which have been used or have ability for accuracy in collecting agriculture information. Further, overview illustrates current research trends in remote sensing methods that allow reinforcing applicative skills with precise necessities for specific forms of stakeholders. We offer a synthesis of the rising possibilities in remote sensing techniques that have to reinforce the role in imparting long time and efficient services for agricultural purpose. SAR remote sensing techniques have extremely good capability and could play an important role in diverse fields of agricultural remote sensing. Finally, the paper outlines challenges, limitation and future trends of remote sensing methods in crop evaluation. This paper concludes that current utilization of remote sensing methods in crop evaluation still remains in an experimental stage.

scholarly journals NON-DESTRUCTIVE MONITORING OF RICE BY HYPERSPECTRAL IN-FIELD SPECTROMETRY AND UAV-BASED REMOTE SENSING: CASE STUDY OF FIELD-GROWN RICE IN NORTH RHINE-WESTPHALIA, GERMANY

2016 ◽  
Vol XLI-B1 ◽  
pp. 1071-1077 ◽  
Author(s):  
M. Willkomm ◽  
A. Bolten ◽  
G. Bareth
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Nitrogen Availability ◽  
Growth Parameters ◽  
Paddy Rice ◽  
Growth Monitoring ◽  
World Population ◽  
Area Index ◽  
Nitrogen Treatments ◽  
Remote Sensing Methods

In the context of an increasing world population, the demand for agricultural crops is continuously rising. Especially rice plays a key role in food security, not only in Asia. To increase crop production of rice, either productivity of plants has to be improved or new cultivation areas have to be found. In this context, our study investigated crop growth of paddy rice (Oryza Sativa J.) in Germany. An experimental field in the vegetation period of 2014 with two nitrogen treatments was conducted using remote sensing methods. The research project focussed on two main aspects: (1) the potential of UAV-based and hyperspectral remote sensing methods to monitor selected growth parameters at different phenological stages; (2) the potential of paddy rice cultivation under the present climate condition in western Germany. We applied a low-cost UAV-system (Unmanned Aerial Vehicle) to generate high resolution Crop Surface Models (CSM). These were compared with hyperspectral in-field measurements and directly measured agronomic parameters (fresh and dry aboveground biomass (AGB), leaf-area-index (LAI) and plant nitrogen concentration (PNC)). For all acquisition dates we could determine single in-field structures in the CSM (e.g. distribution of hills) and different growth characteristics between the nitrogen treatments. Especially in the second half of the growing season, the plants with higher nitrogen availability were about 25 – 30 % larger. The plant height in the CSM correlates particularly with fresh AGB and the LAI (R<sup>2</sup> > 0.8). Thus, the conducted methods for plant growth monitoring can be a contribution for precision agriculture approaches.

Application of remote sensing methods for assessment of anthropogenic transformation of rangelands

2000 ◽  
pp. 16-25
Author(s):  
E. I. Rachkovskaya ◽  
S. S. Temirbekov ◽  
R. E. Sadvokasov
Keyword(s):  
Remote Sensing ◽  
New Technology ◽  
Field Studies ◽  
Digital Data ◽  
Aerial Images ◽  
Expert Assessment ◽  
Automated Classification ◽  
Anthropogenic Transformation ◽  
Initial Processing ◽  
Remote Sensing Methods

Capabilities of the remote sensing methods for making maps of actual and potential vegetation, and assessment of the extent of anthropogenic transformation of rangelands are presented in the paper. Study area is a large intermountain depression, which is under intensive agricultural use. Color photographs have been made by Aircraft camera Wild Heerburg RC-30 and multispectral scanner Daedalus (AMS) digital aerial data (6 bands, 3.5m resolution) have been used for analysis of distribution and assessment of the state of vegetation. Digital data were processed using specialized program ENVI 3.0. Main stages of the development of cartographic models have been described: initial processing of the aerial images and their visualization, preliminary pre-field interpretation (classification) of the images on the basis of unsupervised automated classification, field studies (geobotanical records and GPS measurements at the sites chosen at previous stage). Post-field stage had the following sub-stages: final geometric correction of the digital images, elaboration of the classification system for the main mapping subdivisions, final supervised automated classification on the basis of expert assessment. By systematizing clusters of the obtained classified image the cartographic models of the study area have been made. Application of the new technology of remote sensing allowed making qualitative and quantitative assessment of modern state of rangelands.

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