Very high resolution crop surface models (CSMs) from UAV-based stereo images for rice growth monitoring In Northeast China
Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed geodata in the last years (Hardin & Jensen 2011). Various applications in numerous fields of research like archaeology (Hendrickx et al., 2011), forestry or geomorphology evolved (Martinsanz, 2012)....
Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2013-08-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W2/45/2013/isprsarchives-XL-1-W2-45-2013.pdf |
Summary: | Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed geodata in the last years (Hardin
& Jensen 2011). Various applications in numerous fields of research like archaeology (Hendrickx et al., 2011), forestry or
geomorphology evolved (Martinsanz, 2012). This contribution deals with the generation of multi-temporal crop surface models
(CSMs) with very high resolution by means of low-cost equipment. The concept of the generation of multi-temporal CSMs using
Terrestrial Laserscanning (TLS) has already been introduced by Hoffmeister et al. (2010). For this study, data acquisition was
performed with a low-cost and low-weight Mini-UAV (< 5 kg). UAVs in general and especially smaller ones, like the system
presented here, close a gap in small scale remote sensing (Berni et al., 2009; Watts et al., 2012). In precision agriculture frequent
remote sensing on such scales during the vegetation period provides important spatial information on the crop status. Crop growth
variability can be detected by comparison of the CSMs in different phenological stages. Here, the focus is on the detection of this
variability and its dependency on cultivar and plant treatment. The method has been tested for data acquired on a barley experiment
field in Germany. In this contribution, it is applied to a different crop in a different environment. The study area is an experiment
field for rice in Northeast China (Sanjiang Plain). Three replications of the cultivars Kongyu131 and Longjing21 were planted in
plots that were treated with different amounts of N-fertilizer. In July 2012 three UAV-campaigns were carried out. Establishment of
ground control points (GCPs) allowed for ground truth. Additionally, further destructive and non-destructive field data were
collected. The UAV-system is an MK-Okto by Hisystems (<a href="http://www.mikrokopter.de"_target="blank">http://www.mikrokopter.de</a>) which was equipped with the high resolution
Panasonic Lumix GF3 12 megapixel consumer camera. The self-built and self-maintained system has a payload of up to 1 kg and an
average flight time of 15 minutes. The maximum speed is around 30 km/h and the system can be operated up to a wind speed of less
than 19 km/h (Beaufort scale number 3 for wind speed). Using a suitable flight plan stereo images can be captured. For this study, a
flying height of 50 m and a 44% side and 90% forward overlap was chosen. The images are processed into CSMs under the use of
the Structure from Motion (SfM)-based software Agisoft Photoscan 0.9.0. The resulting models have a resolution of 0.02 m and an
average number of about 12 million points. Further data processing in Esri ArcGIS allows for quantitative comparison of the plant
heights. The multi-temporal datasets are analysed on a plot size basis. The results can be compared to and combined with the
additional field data. Detecting plant height with non-invasive measurement techniques enables analysis of its correlation to biomass
and other crop parameters (Hansen & Schjoerring, 2003; Thenkabail et al., 2000) measured in the field. The method presented here
can therefore be a valuable addition for the recognition of such correlations. |
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ISSN: | 1682-1750 2194-9034 |