Automatic apple tree blossom estimation from uav rgb imagery

A. Tubau Comas, J. Valente, L. Kooistra

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Apple trees often produce high amount of fruits, which results in small, low quality fruits. Thinning in apple orchards is used to improve the quality of the apples by reducing the number of flowers or fruits the tree is producing. The current method used to estimate how much thinning is necessary is to measure flowering intensity, currently done by human visual inspection of trees in the orchard. The use of images of apple trees from ground-level to measure flowering intensity and its spatial variation through orchards has been researched with promising results. This research explores the potential of UAV RGB high-resolution imagery to measure flowering intensity. Image segmentation techniques have been used to segment the white pixels, which correspond to the apple flowers, of the orthophoto and the single photos. Single trees have been cropped from the single photos and from the orthophoto, and correlation has been measured between percentage of white pixels per tree and flowering intensity and between percentage of white pixels per tree and flower clusters. The resulting correlation is low, with a maximum of 0.54 for the correlation between white pixels per tree and flower clusters when using the ortophoto. Those results show the complexity of working with drone images, but there are still alternative approaches that have to investigated before discarding the use of UAV RGB imagery for estimation of flowering intensity.

LanguageEnglish
Title of host publicationISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands
PublisherISPRS
Pages631-635
Number of pages5
DOIs
Publication statusPublished - 4 Jun 2019
Event4th ISPRS Geospatial Week 2019 - Enschede, Netherlands
Duration: 10 Jun 201914 Jun 2019

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
VolumeXLII-2/W13
ISSN (Print)1682-1750

Conference

Conference4th ISPRS Geospatial Week 2019
CountryNetherlands
CityEnschede
Period10/06/1914/06/19

Fingerprint

Orchards
imagery
Fruits
Pixels
flowering
Unmanned aerial vehicles (UAV)
flower
pixel
orchard
orthophoto
fruit
Image segmentation
thinning
Inspection
segmentation
spatial variation

Keywords

  • Apple orchard
  • flowering intensity
  • image segmentation
  • Thinning
  • UAV

Cite this

Tubau Comas, A., Valente, J., & Kooistra, L. (2019). Automatic apple tree blossom estimation from uav rgb imagery. In ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands (pp. 631-635). (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives; Vol. XLII-2/W13). ISPRS. https://doi.org/10.5194/isprs-archives-XLII-2-W13-631-2019
Tubau Comas, A. ; Valente, J. ; Kooistra, L. / Automatic apple tree blossom estimation from uav rgb imagery. ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands. ISPRS, 2019. pp. 631-635 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives).
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title = "Automatic apple tree blossom estimation from uav rgb imagery",
abstract = "Apple trees often produce high amount of fruits, which results in small, low quality fruits. Thinning in apple orchards is used to improve the quality of the apples by reducing the number of flowers or fruits the tree is producing. The current method used to estimate how much thinning is necessary is to measure flowering intensity, currently done by human visual inspection of trees in the orchard. The use of images of apple trees from ground-level to measure flowering intensity and its spatial variation through orchards has been researched with promising results. This research explores the potential of UAV RGB high-resolution imagery to measure flowering intensity. Image segmentation techniques have been used to segment the white pixels, which correspond to the apple flowers, of the orthophoto and the single photos. Single trees have been cropped from the single photos and from the orthophoto, and correlation has been measured between percentage of white pixels per tree and flowering intensity and between percentage of white pixels per tree and flower clusters. The resulting correlation is low, with a maximum of 0.54 for the correlation between white pixels per tree and flower clusters when using the ortophoto. Those results show the complexity of working with drone images, but there are still alternative approaches that have to investigated before discarding the use of UAV RGB imagery for estimation of flowering intensity.",
keywords = "Apple orchard, flowering intensity, image segmentation, Thinning, UAV",
author = "{Tubau Comas}, A. and J. Valente and L. Kooistra",
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Tubau Comas, A, Valente, J & Kooistra, L 2019, Automatic apple tree blossom estimation from uav rgb imagery. in ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. XLII-2/W13, ISPRS, pp. 631-635, 4th ISPRS Geospatial Week 2019, Enschede, Netherlands, 10/06/19. https://doi.org/10.5194/isprs-archives-XLII-2-W13-631-2019

Automatic apple tree blossom estimation from uav rgb imagery. / Tubau Comas, A.; Valente, J.; Kooistra, L.

ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands. ISPRS, 2019. p. 631-635 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives; Vol. XLII-2/W13).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Automatic apple tree blossom estimation from uav rgb imagery

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AU - Valente, J.

AU - Kooistra, L.

PY - 2019/6/4

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N2 - Apple trees often produce high amount of fruits, which results in small, low quality fruits. Thinning in apple orchards is used to improve the quality of the apples by reducing the number of flowers or fruits the tree is producing. The current method used to estimate how much thinning is necessary is to measure flowering intensity, currently done by human visual inspection of trees in the orchard. The use of images of apple trees from ground-level to measure flowering intensity and its spatial variation through orchards has been researched with promising results. This research explores the potential of UAV RGB high-resolution imagery to measure flowering intensity. Image segmentation techniques have been used to segment the white pixels, which correspond to the apple flowers, of the orthophoto and the single photos. Single trees have been cropped from the single photos and from the orthophoto, and correlation has been measured between percentage of white pixels per tree and flowering intensity and between percentage of white pixels per tree and flower clusters. The resulting correlation is low, with a maximum of 0.54 for the correlation between white pixels per tree and flower clusters when using the ortophoto. Those results show the complexity of working with drone images, but there are still alternative approaches that have to investigated before discarding the use of UAV RGB imagery for estimation of flowering intensity.

AB - Apple trees often produce high amount of fruits, which results in small, low quality fruits. Thinning in apple orchards is used to improve the quality of the apples by reducing the number of flowers or fruits the tree is producing. The current method used to estimate how much thinning is necessary is to measure flowering intensity, currently done by human visual inspection of trees in the orchard. The use of images of apple trees from ground-level to measure flowering intensity and its spatial variation through orchards has been researched with promising results. This research explores the potential of UAV RGB high-resolution imagery to measure flowering intensity. Image segmentation techniques have been used to segment the white pixels, which correspond to the apple flowers, of the orthophoto and the single photos. Single trees have been cropped from the single photos and from the orthophoto, and correlation has been measured between percentage of white pixels per tree and flowering intensity and between percentage of white pixels per tree and flower clusters. The resulting correlation is low, with a maximum of 0.54 for the correlation between white pixels per tree and flower clusters when using the ortophoto. Those results show the complexity of working with drone images, but there are still alternative approaches that have to investigated before discarding the use of UAV RGB imagery for estimation of flowering intensity.

KW - Apple orchard

KW - flowering intensity

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U2 - 10.5194/isprs-archives-XLII-2-W13-631-2019

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M3 - Conference contribution

T3 - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

SP - 631

EP - 635

BT - ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands

PB - ISPRS

ER -

Tubau Comas A, Valente J, Kooistra L. Automatic apple tree blossom estimation from uav rgb imagery. In ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands. ISPRS. 2019. p. 631-635. (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives). https://doi.org/10.5194/isprs-archives-XLII-2-W13-631-2019