27 The Use of Digital Imaging Systems for Detecting Plant Changes: the APOS – Automated Phenological Observation System

Monday, 12 May 2014
Bellmont BC (Crowne Plaza Portland Downtown Convention Center Hotel)
Carla Cesaraccio, Institute of Biometeorology, Sassari, Italy; and A. Piga, A. Ventura, A. Arca, and P. Duce
Manuscript (163.5 kB)

The importance of phenological research for understanding the consequences of global environmental change on vegetation is highlighted in the most recent IPCC reports. Collecting time series of phenological events, at a variety of scales, appears to be of crucial importance to better understand how vegetation systems respond to climatic regimes fluctuations, and, consequently, to develop effective management and adaptation strategies. Some concerns are related to traditional monitoring of phenology: recording observations dates is labor intensive and costly; quality of data depends heavily upon the observational skills and effort of the observers; data can be affected to a certain degree of subjective inaccuracy; they are typically discontinuous and geographically limited. Moreover, they are typically made on a limited number of individuals, across a limited geographic area or a specific site. Other methods based on satellite remote sensing are used to quantify the seasonal patterns of development and senescence of vegetation (land surface phenology) but they operate at coarse spatial and temporal resolution, and at a regional or larger scale. To overcome the limitation of field observations by individuals, and to scale between ground-based sampling and regional-scale satellite sampling, different approaches for vegetation monitoring based on “near-surface” remote sensing have been proposed in recent researches. These techniques use radiometric instruments or imaging sensors to quantify, at high temporal resolution, the seasonal changes in the optical properties of the vegetation canopy. In this study, a new system to identify vegetation changes, and in particular the phenological behavior of shrubland species, based on digital image sensors, is presented. The Automated Phenological Observation System (APOS) was developed and tested under the INCREASE EU-funded research infrastructure project (an Integrated Network on Climate Change Research), which is based upon large scale field experiments with non-intrusive manipulations of temperature and precipitation. The general architecture of APOS includes several components that perform the following major functions: (1) image acquisition, made using a camera connected to a robot, so as to frame and pan an area in accordance with the visual coverage of the experimental site; (2) image transmission, permitted by a modem-router for broadband access to Internet; (3) image processing (image stitching and elaboration) made by a remote computer. Optimization of the camera-plot focus distance and parameters values for the specific visual coverage of the experimental site were obtained using a specifically developed custom software. Phenology of shrubland was monitored since May 2012. The application of new technologies such as digital imaging systems for detecting vegetation and plant phenology changes appeared to be promising for several reasons: (i) new technologies can make data collection cheaper and easier reducing labor and costs of field observations, (ii) new monitoring tools will exponentially increase rates of data collection, and (iii) long term data collection projects and large, long-term standardized data sets can be easier obtained because data can be systematically recorded and permanently stored.
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