Applications of georeferenced high-resolution images obtained with unmanned aerial vehicles. Part I: Description of image acquisition and processing

Ballesteros, Rocío; Álvarez, José Fernando Ortega; Hernández, D.; Moreno, M.

doi:10.1007/s11119-014-9355-8

Cited by 74 publications

(65 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The lately widespread UAV-based RGB imaging activities lead to an increased research interest to use this data source for precision agriculture applications (Ballesteros et al, 2014, Lopez-Granados et al, 2016. A well-established crop monitoring approach, which is also based on RGB images from UAVs, is the generation of multitemporal Crop Surface Models (CSMs) for plant height and biomass estimations (Bendig et al, 2013;Hoffmeister et al,.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Uncalibrated Rgbvi With Spectrometer-Based Ndvi Derived From Uav Sensing Systems on Field Scale

Bareth

Bolten

Gnyp

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (< 5 kg) is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs) are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg) for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers' field in Western Germany. (i) A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii) NDVI is computed from a newly modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1) to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2) investigate the UAV-based performance of the modified Yara N-Sensor, and (3) compare the results of the two different UAV-based sensing approaches for winter wheat.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparison of Uncalibrated Rgbvi With Spectrometer-Based Ndvi Derived From Uav Sensing Systems on Field Scale

Bareth

Bolten

Gnyp

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…Con el cálculo de los grados días acumulados (GDA), es posible determinar la duración de las etapas de desarrollo del cultivo, permitiendo así una mejor planificación de la programación de riegos o de cualquier otro aspecto en el manejo de los cultivos. Según Ballesteros et al (2014a), el método del seno doble es el más adecuado para el cálculo de los GDA en el cultivo del maíz. Las temperaturas umbrales para el cálculo de los GDA por esta metodología están presentadas en la Tabla 2, según los mismos autores.…”

Section: Materiales Y Métodosunclassified

Caracterización Del Crecimiento De Un Cultivo De Maíz Regado en Una Zona Semiárida Mediante El Empleo De Imágenes Aéreas De Alta Resolución

Costa

Álvarez

Gomes

et al. 2017

RBAI

View full text Add to dashboard Cite

RESUMENFue realizado el seguimiento fenológico, análisis de crecimiento y desarrollo del cultivo del maíz durante las campañas de riego de los años 2015 y 2016 en parcelas ubicadas en una finca comercial en Tarazona de La Mancha, Albacete, España. Se realizaron vuelos con un vehículo aéreo no tripulado (VANT) equipado con una cámara RGB, durante todo el ciclo del cultivo en ambos años. A partir de las imágenes capturadas en estos vuelos se obtuvieron ortoimágenes de alta resolución espacial, que fueron utilizadas para el cálculo del grado de cobertura verde (GCV) a partir del software de análisis de imágenes LAIC. El GCV presenta una baja cobertura vegetal al inicio de su ciclo, aumentando a medida en que se desarrolla el cultivo, hasta alcanzar su máximo valor, que en el año 2015 se dio al inicio de la etapa media del maíz (91,8%), en cuanto que en el año 2016 los máximos valores de GCV fueron alcanzados al final de esta etapa (81%). Al relacionar los valores de GCV con el índice de área foliar (IAF) en los dos años de estudio, se observa que el crecimiento de la cobertura vegetal está directamente relacionado con la evolución del área foliar del cultivo. Se concluye que el GCV es un parámetro importante en el análisis del desarrollo del cultivo del maíz, puesto que el estudio de las relaciones existentes entre el GCV y el IAF permitió analizar en detalle la arquitectura del cultivo y su evolución a lo largo del tiempo.Palabras-clave: Grado de cobertura verde (GCV), índice de área foliar (IAF), vehículo aéreo no tripulado (VANT), Zea mays L 1 Trabajo parte de la Tesis Doctoral del autor principal.

show abstract

“…Although it is a technology that has been developed for many years, in the agricultural scope passed unnoticed for a long time (Ballesteros et al, 2014); it has been talked about RPA applied to agriculture in the last decade, but it is still a technology with a high initial cost, noticing the large farmers who allocate part of their resource to the implantation of technologies in the property.…”

Section: Introductionmentioning

confidence: 99%

Assembly of a Remotely Piloted Aircraft of Low Cost Applied to Agriculture

Cunha

Neto

2017

Eng. Agríc.

View full text Add to dashboard Cite

ABSTRACT:The remotely piloted aircraft (RPA) have great applicability in agriculture. Although it is a technology that has been developed for many years, in the field of agriculture it passed unnoticed for a long time. The high cost of acquisition is still a limiting factor for small and medium-sized farmers. In this way, this study had as objective to develop a low cost RPA for agriculture application. In the present study, the development and the assembly of an RPA prototype of a quadcopter type is presented, consisting of four engines and of vertical propulsion, capable of moving without human intervention, that is, autonomous flight, applied to agriculture and low cost investment. In it was boarded a data control and processing system collected from sensors and cameras, using hardware and software from a free platform (Open Source). The assembly equipment showed to be robust, with a payload of approximately 1,000 grams, with an acquisition cost (R$ 2,393.16), included the camera module, much lower than those commercially available and suitable for the agricultural application, as acquisition, processing and interpretation of digital images, due to the quality of the images obtained.

show abstract

Applications of georeferenced high-resolution images obtained with unmanned aerial vehicles. Part I: Description of image acquisition and processing

Cited by 74 publications

References 19 publications

Comparison of Uncalibrated Rgbvi With Spectrometer-Based Ndvi Derived From Uav Sensing Systems on Field Scale

Comparison of Uncalibrated Rgbvi With Spectrometer-Based Ndvi Derived From Uav Sensing Systems on Field Scale

Caracterización Del Crecimiento De Un Cultivo De Maíz Regado en Una Zona Semiárida Mediante El Empleo De Imágenes Aéreas De Alta Resolución

Assembly of a Remotely Piloted Aircraft of Low Cost Applied to Agriculture

Contact Info

Product

Resources

About