Multisensor Fusion of Ground-based and Airborne Remote Sensing Data for Crop Condition Assessment

In this study, the performances of the optical sensors and instruments carried on both ground-based and airborne platforms were evaluated for monitoring crop growing status, detecting the vegetation response to aerial applied herbicides, and identifying crop nitrogen status. Geostatistical analysis on remotely sensed data was conducted to investigate spatial structure of crop canopy normalized difference vegetation index and multispectral imagery. A computerized crop monitoring system was developed that combined sensors and instruments that measured crop structure and spectral data with a global positioning system. The integrated crop monitoring system was able to collect real-time, multi-source, multi-form, and crop related data simultaneously as the tractor-mounted system moved through the field. This study firstly used remotely sensed data to evaluate glyphosate efficacy on weeds applied with conventional and emerging aerial spray nozzles. A weedy field was In this study, the performances of the optical sensors and instruments carried on both ground-based and airborne platforms were evaluated for monitoring crop growing status, detecting the vegetation response to aerial applied herbicides, and identifying crop nitrogen status. Geostatistical analysis on remotely sensed data was conducted to investigate spatial structure of crop canopy normalized difference vegetation index and multispectral imagery. A computerized crop monitoring system was developed that combined sensors and instruments that measured crop structure and spectral data with a global positioning system. The integrated crop monitoring system was able to collect real-time, multi-source, multi-form, and crop related data simultaneously as the tractor-mounted system moved through the field. This study firstly used remotely sensed data to evaluate glyphosate efficacy on weeds applied with conventional and emerging aerial spray nozzles. A weedy field was set up in three blocks and four aerial spray technology treatments were tested. Spectral reflectance measurements were taken using ground-based sensors from all the plots at 1, 8, and 17 days after treatment. The results indicated that the differences among the treatments could be detected with spectral data. This study could provide applicators with guidance equipment configurations that can result in herbicide savings and optimized applications in other crops. The main focus of this research was to apply sensor fusion technology to ground-based and airborne imagery data. Experimental plots cropped with cotton and soybean plants were set up with different nitrogen application rates. The multispectral imagery was acquired by an airborne imaging system over crop field; at the same period, leaf chlorophyll content and spectral reflectance measurements were gathered with chlorophyll meter and spectroradiometer at canopy level on the ground, respectively. Statistical analyses were applied on the data from individual sensor for discrimination with respect to the nitrogen treatment levels. Multisensor data fusion was performed at data level. The results showed that the data fusion of airborne imagery with ground-based data were capable of improving the performance of remote sensing data on detection of crop nitrogen status. The method may be extended to other types of data, and data fusion can be performed at feature or decision level

Variogram investigation of covariance shape within longitudinal data with possible use of a krigeage technique as an interpolation tool: Sheep growth data as an example

peer-reviewedMost quantitative traits considered in livestock evolve over time and several continuous functions have been proposed to model this change. For individual records (longitudinal data), it is evident that measures taken at close dates are generally more related than these further apart in time. Since milk production involves several parities, the covariance structure within this trait has been analysed by time series methodology. However, the covariance structure within traits that are not repeated during life, such as those linked to growth, has not yet been formally modelled by considering time lags as is done in time series analysis. We propose an adaptation of the variogram concept to shape this structure; which gives the possibility of kriging missing data at any particular time. A new parameter, the halftime variogram, has been proposed to characterise the growing potential of a given population. The weight records of a Barbarine male lamb population were used to illustrate the methodology. The variogram covering the whole growth process in this population could be modelled by a logistic equation. To estimate the missing data from birth to 105 days of age, a simple linear interpolation was sufficient since kriging on a linear model basis gives a relatively more accurate estimation than kriging on a logistic model basis. Nevertheless, when both known records around the missing data are distant, a krigeage on the basis of the logistic model provides a more accurate estimation

Drones: Innovative Technology for Use in Precision Pest Management.

Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well-established and crop losses accrue. Pest monitoring is time-consuming and may be hampered by lack of reliable or cost-effective sampling techniques. Thus, we argue that an important research challenge associated with enhanced sustainability of pest management in modern agriculture is developing and promoting improved crop monitoring procedures. Biotic stress, such as herbivory by arthropod pests, elicits physiological defense responses in plants, leading to changes in leaf reflectance. Advanced imaging technologies can detect such changes, and can, therefore, be used as noninvasive crop monitoring methods. Furthermore, novel methods of treatment precision application are required. Both sensing and actuation technologies can be mounted on equipment moving through fields (e.g., irrigation equipment), on (un)manned driving vehicles, and on small drones. In this review, we focus specifically on use of small unmanned aerial robots, or small drones, in agricultural systems. Acquired and processed canopy reflectance data obtained with sensing drones could potentially be transmitted as a digital map to guide a second type of drone, actuation drones, to deliver solutions to the identified pest hotspots, such as precision releases of natural enemies and/or precision-sprays of pesticides. We emphasize how sustainable pest management in 21st-century agriculture will depend heavily on novel technologies, and how this trend will lead to a growing need for multi-disciplinary research collaborations between agronomists, ecologists, software programmers, and engineers

Differences in optical properties of males and females pupae of Anastrepha fraterculus (Diptera: Tephritidae)

One alternative to pesticide-based control of important fruit fly (Tephritidae) species is the sterile insect technique (SIT). SIT is based on mass releases of sterile males (subjected to radiation) to control a given pest population. For several important species such as Rhagoletis pomonella, Bractocera oleae and Anastrepha fraterculus, a technical challenge is to differentiate males from females in the pupal stage. Although for some species sterile females are released in the field, it is not desirable to release females from Anastrepha spp. as puncture damage may occur. Therefore, we investigated hyperspectral and RGB imaging to classify the sex in A. fraterculus pupae. We aimed to discriminate, through the description of RGB spectra and hyperespectral profiles, males and females in different stages of pupal development. Images of pupae of different degree-day (DD) development times were obtained. The hyperspectral profiles pupae of 288, 345 and 403 DD showed differences, indicating that pupal hue is altered throughout the development. In the NIR spectrum (800 to 1,700 nm), a higher reflectance between 1,100 and 1,400 nm was observed. In these bands differences in the spatial standard deviation of reflectance between males and females occur. As for the RGB images we observed differences in radiometric variation angle from the top to the basal part of the pupae. For females the radiometric variation angle was greater (26°) than for the males (15°). Thus, it is possible to determine discriminatory characteristics using the spectral profiles, imaging techniques and data analysis to discriminate the sexes

Summaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 1: AVIRIS Workshop

This publication is the first of three containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in this volume; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in Volume 3; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production