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Remote Sensing Applications in Precision Agriculture
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Authors
Aasen, H
Alchanatis, V
Bajwa, S
Balboa, G
Balboa, G
Bareth, G
Bareth, G
Bolten, A
Brand, H
Bruce, A.E
Brungardt, J.J
Canata, T.F
Cao, Q
Chavan, H
Chen, Y
Chen, Y
Ciampitti, I
Ciampitti, I
Cisneros, M
Colaço, A.F
Connor, J
Cushnahan, T
Denton, A.M
Dornbusch, T
EMİNOĞLU, B.M
Ferguson, A
Ferguson, A
Fiorio, P.R
Franzen, D.W
Franzen, J
Frotscher, K.J
Gan, H
Gerighausen, H
Gnyp, M.L
Gnyp, M.L
Gonzalez, J
Goorahoo, D
Grafton, M.C
Griffin, T
Griffin, T
Gérard, B
Han, Y.J
Howatt, K
Huang, S
Huang, Y
Hunt, E
Irwin, M.E
Isakeit, T
Jansen, M
Jasper, J
Kaiser, D
Kereszturi, G
Khalilian, A
Khosla, R
Khosla, R
Kyveryga, P.M
Laacouri, A
Le Roux, M
Lee, W
Lenz-Wiedemann, V
Lilienthal, H
Liu, J
Longchamps, L
Longchamps, L
Maharlooei, M
Maja, J.M
Mangus, D.L
Martello, M
Martinsson, J
McVeagh, P.J
McVeagh, P.J
Miao, Y
Molin, J.P
Moulton, H
Mulla, D
Nichols, R.L
Nowatzki, J
Nowatzki, J.F
Odvody, G.N
Ortiz-Monasterio, I
Panitzki, M
Patto Pacheco, E
Paulus, S
Payero, J.O
Pearson, R
Pennington, D
Piikki, K
Pimstein, A
Prasad, V
Prasad, V
Pritsolas, J
Privette, C.V
Pullanagari, R.R
Qiao, X
Reddy, K
Reusch, S
Rodrigues Jr., F.A
Rondon, S.I
SEYHAN, G.T
Sampson, T
Schacht, R
Scharf, P
Schnug, E
Schulthess, U
Seepersad, G
Seepersad, S
Sharda, A
Shirzadi, A
Siegfried, J
Sivarajan, S
Smith, L
Stadig, H
Stenberg, M
Söderström, M
TALEBPOUR, B
Thomasson, J.A
Thomson, S.J
Tilly, N
Toledo, F.H
Trevisan, R.G
Turner, R.W
TÜRKER, U
Varela, S
Varela, S
White, M
Williams, E
Willis, L.A
Yang, C
Yang, Q
Yang, Q
Yao, Y
Yegul, U
Yuan, F
Yule, I.J
Yule, I.J
Zamzow, M
Zamzow, M
Zarco-Tejada, P.J
Zhang, Y
Zhao, T
Zhao, T
Zillmann, E
Zur, Y
hassanijalilian, O
ÇOLAK, A
Topics
Remote Sensing Applications in Precision Agriculture
Type
Oral
Poster
Year
2016
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Topics

Filter results35 paper(s) found.

1. Selection and Utility of Uncooled Thermal Cameras for Spatial Crop Temperature Measurement Within Precision Agriculture

Since previous research used local, single-point measurements to indicate crop water stress, thermography is presented as a technique capable of measuring spatial temperatures supporting its use for monitoring crop water stress. This study investigated measurement accuracy of uncooled thermal cameras under strict environmental conditions, developed hardware and software to implement uncooled thermal cameras and quantified intrinsic properties that impact measurement accuracy and repeatability... D.L. Mangus, A. Sharda

2. Spectral Vegetation Indices to Quantify In-field Soil Moisture Variability

Agriculture is the largest consumer of water globally. As pressure on available water resources increases, the need to exploit technology in order to produce more food with less water becomes crucial. The technological hardware requisite for precise water delivery methods such as variable rate irrigation is commercially available. Despite that, techniques to formulate a timely, accurate prescription for those systems are inadequate. Spectral vegetation indices, especially Normalized Differenc... J. Siegfried, R. Khosla, L. Longchamps

3. High Resolution Hyperspectral Imagery to Assess Wheat Grain Protein in a Farmer's Field

The agricultural research sector is working to develop new technologies and management knowledge to sustainably increase food productivity, to ensure global food security and decrease poverty. Wheat is one of the most important crops into this scenario, being among the three most important cereal commodities produced worldwide. Precision Agriculture (PA) and specially Remote Sensing (RS) technologies have become in the recent years more affordable which has improved the availability and flexi... F.A. Rodrigues jr., I. Ortiz-monasterio, P.J. Zarco-tejada, F.H. Toledo, U. Schulthess, B. Gérard

4. Spatial-temporal Evaluation of Plant Phenotypic Traits Via Imagery Collected by Unmanned Aerial Systems (UAS)

Unmanned aerial systems (UAS) and a stereovision approach were implemented to generate a 3D reconstruction of the top of the canopy. The 3D reconstruction or CSM (crop surface model) was utilized to evaluate biophysical parameters for both spatial- and temporal-scales. The main goal of the project was to evaluate sUAVs technology to assist plant height and biomass estimation. The main outcome of this process was to utilize CSMs to gain insights in the spatial-temporal dynamic of plants within... S. Varela, G. Balboa, V. Prasad, T. Griffin, I. Ciampitti, A. Ferguson

5. High Resolution 3D Hyperspectral Digital Surface Models from Lightweight UAV Snapshot Cameras – Potentials for Precision Agriculture Applications

Precision agriculture applications need timely information about the plant status to apply the right management at the right place and the right time. Additionally, high-resolution field phenotyping can support crop breeding by providing reliable information for crop rating. Flexible remote sensing systems like unmanned aerial vehicles (UAVs) can gather high-resolution information when and where needed. When combined with specialized sensors they become powerful sensing systems. Hyp... H. Aasen

6. Detecting Nitrogen Variability at Early Growth Stages of Wheat by Active Fluorescence and NDVI

Low efficiency in the use of nitrogen fertilizer, has been reported around the world which often times result in high production costs and environmental damage. Today, unmanned aerial vehicles (UAV) cameras are being used to obtain conditions of crops, and can cover large areas in a short time. The objectives of this study were (i) to investigate N-variability in wheat at early growth stages using induced fluorescence indices, NDVI measured by active sensor and NDVI obtained by digital i... E. Patto pacheco, J. Liu, L. Longchamps, R. Khosla

7. Comparison Between Tractor-based and UAV-based Spectrometer Measurements in Winter Wheat

In-season variable rate nitrogen fertilizer application needs a fast and efficient determination of nitrogen status in crops. Common sensor-based monitoring of nitrogen status mainly relies on tractor mounted active or passive sensors. Over the last few years, researchers tested different sensors and indicated the potential of in-season monitoring of nitrogen status by unmanned aerial vehicles (UAVs) in various crops. However, the UAV-platforms and the available sensors are not yet accepted t... M. Gnyp, M. Panitzki, S. Reusch, J. Jasper, A. Bolten, G. Bareth

8. Measuring Pasture Mass and Quality Indices Over Time Using Proximal and Remote Sensors

Traditionally pasture has been measured or evaluated in terms of a dry matter yield estimate, which has no reference to other important quality factors. The work in this paper measures pasture growth rates on different slopes and aspects and pasture quality through nitrogen N% and metabolizable energy and ME concentration. It is known that permanent pasture species vary greatly in terms of quality and nutritional value through different stages of maturity. Pasture quality decreases as grass t... I.J. Yule, M.C. Grafton, L.A. Willis, P.J. Mcveagh

9. First Experiences with the European Remote Sensing Satellites Sentinel-1A/ -2A for Agricultural Research

The Copernicus program headed by the European Commission (EC) in partnership with the European Space Agency (ESA) will launch up to twelve satellites, the so called “Sentinels” for earth and environmental observations until 2020. Within this satellite fleet, the Sentinel-1 (microwave) and Sentinal-2 (optical) satellites deliver valuable information on agricultural crops. Due to their high temporal (5 to 6 days repeating time) and spatial (10 to 20 m) resolutions a continuous monit... H. Lilienthal, H. Gerighausen, E. Schnug

10. 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

11. Comparison Between High Resolution Spectral Indices and SPAD Meter Estimates of Nitrogen Deficiency in Corn

Low altitude remote sensing provides an ideal platform for monitoring time sensitive nitrogen status in crops. Research is needed however to understand the interaction between crop growth stage, spatial resolution and spectral indices derived from low altitude remote sensing. A TetraCam camera equipped with six bands including the red edge and near infrared (NIR) was used to investigate corn nitrogen dynamics. Remote sensing data were collected during the 2013 and 2014 growing seasons at four... D. Mulla, A. Laacouri, D. Kaiser

12. A Photogrammetry-based Image Registration Method for Multi-camera Systems

In precision agriculture, yield maps are important for farmers to make plans. Farmers will have a better management of the farm if early yield map can be created. In Florida, citrus is a very important agricultural product. To predict citrus production, fruit detection method has to be developed. Ideally, the earlier the prediction can be done the better management plan can be made. Thus, fruit detection before their mature stage is expected. This study aims to develop a thermal-visible camer... H. Gan, W. Lee, V. Alchanatis

13. Potential Improvement in Rice Nitrogen Status Monitoring Using Rapideye and Worldview-2 Satellite Remote Sensing

For in-season site-specific nitrogen (N) management of rice to be successful, it is crucially important to diagnose rice N status efficiently across large area in a timely fashion. Satellite remote sensing provides a promising technology for crop growth monitoring and precision management over large areas. The FORMOSAT-2 satellite remote sensing imageries with 4 wavebands have been used to estimate rice N status. The objective of this study was to evaluate the potential of using high spatial ... S. Huang, Y. Miao, F. Yuan, M.L. Gnyp, Y. Yao, Q. Cao, V. Lenz-wiedemann, G. Bareth

14. CropSAT - a Public Satellite-based Decision Support System for Variable-rate Nitrogen Fertilization in Scandinavia

CropSAT is a free-to-use web application for satellite-based production of variable-rate application (VRA) files of e.g. nitrogen (N) and fungicides currently available in Sweden and Denmark. Even in areas frequently covered by clouds, vegetation index maps from data derived from low-cost or freely available optical satellites can be used in practice as a cost-efficient tool in time-critical applications such as optimized nitrogen use. During the very cloudy year 2015, or more useable ima... M. Söderström, H. Stadig, J. Martinsson, M. Stenberg, K. Piikki

15. Measuring Height of Sugarcane Plants Through LiDAR Technology

Sugarcane (Saccharum spp.) has an important economic role in Brazilian agriculture, especially in São Paulo State. Variation in the volume of plants can be an indicative of biomass which, for sugarcane, strongly relates to the yield. Laser sensors, like LiDAR (Light Detection and Ranging), has been employed to estimate yield for corn, wheat and monitoring forests. The main advantage of using this type of sensor is the capability of real-time data acquisition in a non-destructive way, p... T.F. Canata, J.P. Molin, A.F. Colaço, R.G. Trevisan, P.R. Fiorio, M. Martello

16. Window-based Regression Analysis of Field Data

High-resolution satellite and areal imagery enables multi-scale analysis that has previously been impossible.  We consider the task of localized linear regression and show that window-based techniques can return results at different length scales with very high efficiency.  The ability of inspecting multiple length scales is important for distinguishing factors that vary over different length scales.  For example, variations in fertilization are expected to occur on shorter len... A.M. Denton, H. Chavan, D.W. Franzen, J.F. Nowatzki

17. Hyperspectral Imaging to Measure Pasture Nutrient Concentration and Other Quality Parameters

Managing pasture nutrient requirements on large hill country sheep and beef properties based on information from soil sampling is expensive because of the time and labor involved. High levels of error are also expected as these properties are often greatly variable and it is therefore extremely difficult to sample intensively enough to capture this variation. Extensive sampling was also not considered viable as there was no effective means of spreading fertilizer with a variable rate capabili... I.J. Yule, R.R. Pullanagari, G. Kereszturi, M.E. Irwin, P.J. Mcveagh, T. Cushnahan, M. White

18. Creating Prescription Maps from Historical Imagery for Site-specific Management of Cotton Root Rot

Cotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivore, is a severe plant disease that has affected cotton production for over a century. Recent research found that a commercial fungicide, Topguard (flutriafol), was able to control this disease. As a result, Topguard Terra Fungicide, a new and more concentrated formulation developed specifically for this market was registered in 2015, so cotton producers can use this product to control the disease. Cotton root rot only inf... C. Yang, G.N. Odvody, J.A. Thomasson, T. Isakeit, R.L. Nichols

19. Retrieving Crops' Quantitative Biophysical Parameters Through a Newly Developed Multispectral Sensor for UAV Platforms

Today’s intensive agricultural production needs to increase its efficiency in order to keep its profitability in the current market of decreasing prices on one hand, and to reduce the environmental impact on the other. Crop growers are starting to adopt side dressing nitrogen fertilization as part of their fertilization programs, for which they need accurate information about biomass development and nitrogen condition in the crop. This information is usually acquired through ground samp... A. Pimstein, Y. Zur, M. Le roux

20. Development of Sensor Reflection Indices To Predict Yield And Protein Content Based On In-Season N Status

Environmental and economic demands make it necessary for farmers to adopt   management systems that improve Nitrogen Use Efficiency. The premium paid to producers has made farmers striving for maximum grain protein levels because protein is a very important quality component of grains and an important attribute in the market place. The protein content of wheat grains approximately ranges from 8 to 20%. The optimization of nitrogen (N) fertilization is the object of intense research ... U. Yegul, B. Talebpour, U. TÜrker, B.M. EmİnoĞlu, G.T. Seyhan, A. Çolak

21. Intuitive Image Analysing on Plant Data - High Throughput Plant Analysis with Lemnatec Image Processing

For digital plant phenotyping huge amounts of 2D images are acquired. This is known as one part of the phenotyping bottleneck. This bottleneck can be addressed by well-educated plant analysts, huge experience and an adapted analysis software. Automated tools that only cover specific parts of this analysis pipeline are provided. During the last years this could be changed by the image processing toolbox of LemnaTec GmbH. An automated and intuitive tool for the automated analysis of huge amount... S. Paulus, T. Dornbusch, M. Jansen

22. In Season Estimation of Barley Biomass with Plant Height Derived by Terrestrial Laser Scanning

The monitoring of plant development during the growing season is a fundamental base for site-specific crop management. In this regard, the amount of plant biomass at a specific phenological stage is an important parameter to evaluate the actual crop status. Since biomass is directly only determinable with destructive sampling, methods of recording other plant parameters, such as crop height or density, which are suitable for reliable estimations are increasingly researched. Over the past two ... N. Tilly

23. Spatial-temporal Evaluation of Plant Phenotypic Traits Via Imagery Collected by Unmanned Aerial Systems (UAS)

Unmanned aerial systems (UAS) and a stereovision approach were implemented to generate a 3D reconstruction of the top of the canopy. The 3D reconstruction or CSM (crop surface model) was utilized to evaluate biophysical parameters for both spatial- and temporal-scales. The main goal of the project was to evaluate sUAVs technology to assist plant height and biomass estimation. The main outcome of this process was to utilize CSMs to gain insights in the spatial-temporal dynamic of plants within... S. Varela, G. Balboa, V. Prasad, T. Griffin, I. Ciampitti, A. Ferguson

24. Assessing Soybean Injury from Dicamba Using RGB and CIR Images Acquired on Small UAVs

Dicamba is an herbicide used for postemegence control of several broadleaf weeds in corn, grain sorghum, small grains, and non-cropland. Currently, dicamba-tolerant (DT) soybean and cotton are under development, which provide new options to combat weeds resistant to glyphosate, the most widely used herbicide.  With the use of DT-trait cotton and soybean, off-target dicamba drift onto susceptible crops will become a concern. To relate soybean injury to different rates of dicamba applicati... Y. Huang, H. Brand, D. Pennington, K. Reddy, S.J. Thomson

25. Utilizing Space-based Technology for Cotton Irrigation Scheduling

Accurate soil moisture content measurements are vital to precision irrigation management. Electromagnetic sensors such as capacitance and time domain reflectometry have been widely used for measuring soil moisture content for decades. However, to estimate average soil moisture content over a large area, a number of ground-based in-situ sensors would need to be installed, which would be expensive and labor intensive. Remote sensing using the microwave spectrum (such as GPS signals) has been us... A. Khalilian, X. Qiao, J.O. Payero, J.M. Maja, C.V. Privette, Y.J. Han

26. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy Temperature

Development of herbicide-resistant crops has resulted in significant positive changes to agronomic practices, while repeated and intensive use of herbicides with the same mechanisms of action has caused the development of herbicide-resistant weeds. As of 2015, 35 weed species are reported to be resistant to glyphosate worldwide. A greenhouse study was conducted to identify characteristics which can be helpful in field mapping of glyphosate resistant weeds by using UAV imagery. The experiment ... A. Shirzadi, M. Maharlooei, O. Hassanijalilian, S. Bajwa, K. Howatt, S. Sivarajan, J. Nowatzki

27. Challenges and Successes when Generating In-season Multi-temporal Calibrated Aerial Imagery

Digital aerial imagery (DAI) of the crop canopy collected by aircraft and unmanned aerial vehicles is the yardstick of precision agriculture.  However, the quantitative use of this imagery is often limited by its variable characteristics, low quality, and lack of radiometric calibration.  To increase the quality and utility of using DAI in crop management, it is important to evaluate and address these limitations of DAI.  Even though there have been improvements in spatial reso... P.M. Kyveryga, J. Pritsolas, J. Connor, R. Pearson

28. Detection of Potato Beetle Damage Using Remote Sensing from Small Unmanned Aircraft Systems

Remote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution.  We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center (HAREC) to assess advantages and disadvantages of sUAS for precision farming. In 2014, we conducted an experiment in irrigated potatoes with 4 levels of artificial infestation by Colorado Potato Bee... E. Hunt, S.I. Rondon, A.E. Bruce, R.W. Turner, J.J. Brungardt

29. Time Series Analysis of Vegetation Dynamics and Burn Scar Mapping at Smoky Hill Air National Guard Range, Kansas Using Moderate Resolution Satellite Imagery

Military installments are import assets for the proper training of armed forces. To ensure the continued viability of the training grounds, management practices need to be implemented to sustain the necessary environmental conditions for safe and effective training. This analysis uses satellite imagery over time to gain insight into vegetation conditions over a large military installment. MODIS imagery was collected multiple times a year for 11 years at Smoky Hill Air National Guard Range (Sm... E. Williams

30. Melon Classification and Segementation Using Low Cost Remote Sensing Data Drones

Object recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the f... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang

31. Aerial Photographs to Predict Yield Loss Due to N Deficiency in Corn

Nitrogen fertilizer is a crucial input for corn production, and in the U.S. more nitrogen is applied to corn than to all other crops combined.  In wet weather, nitrogen can be lost from soil by leaching and by denitrification.  Which process predominates depends largely on soil drainage.  Nitrogen deficiency in nearly any plant is expressed by a lighter green color of leaves than in nitrogen-sufficient plants.  Nitrogen deficiency in corn can be easily seen from the air.&n... P. Scharf

32. Almond Canopy Detection and Segmentation Using Remote Sensing Data Drones

The development of Unmanned Aerial System (UAV) makes it possible to take high resolution images of trees easily. These images could help better manage the orchard. However, more research is necessary to extract useful information from these images. For example, irrigation schedule and yield prediction both rely on accurate measurement of canopy size. In this paper, a workflow is proposed to count trees and measure the canopy size of each individual tree. The performances of three different m... T. Zhao, M. Cisneros, Y. Chen, Q. Yang, Y. Zhang

33. AGOC: Agriculture Operations Center

After another long day, the farmer sits down in front of a computer (wishing this time was instead spent on the front porch catching a last glimpse of the sunset), and reflects once again ...     What if   ...  I actually knew the health of 100% of my crops rather than what I know today. a mere 20%. What if   ...  there was an effective, simple way to synchronize crop scouting and crop imagery efforts. ... M. Zamzow, H. Moulton

34. The Agriculture Operations Center: the Answer to “What If...”

Can’t farming be simpler?  Yes…with an Agriculture Operations Center -- we call it the AGOC, and it’s the next big step for precision agriculture.  Leveraging decades of lessons from the US Air Force, the AGOC provides the ability to schedule, execute, collect, consolidate, and distribute all the support a farmer needs from satellites, piloted aircraft, unmanned aircraft, sensing, modeling, and analysis…all packaged into “one stop shopping.”&nbs... M. Zamzow

35. Precision Agriculture Techniques for Crop Management in Trinidad and Tobago: Methodology & Field Layout

Agriculture in Trinidad and Tobago has not advanced at the same rate at which new agricultural technology has been released. This has led to large-scale abandonment of crop lands as challenges posed by labor availability and their agronomic capability could not meet the technological demands for agricultural production, competitiveness and sustainability. There is an urgent need to develop technology-based agriculture models to meet the demands of a modern agricultural sector and to maintain ... G. Seepersad, T. Sampson, S. Seepersad, D. Goorahoo