Automatic thresholding for hemispherical canopy-photographs based on edge detection
نویسندگان
چکیده
The analysis of hemispherical photographs is nowadays an established method for assessing light indirectly and describing canopy structures. In this article, we present an automatic threshold algorithm for separating canopy and sky by edge detection. The algorithm was evaluated under different canopy conditions by comparing its results for canopy openness, fractal dimension and diffuse transmittance with those from multiple manual thresholding and direct measurements of the percent photosynthetic photon flux density (PPFD). We show that the automatic threshold algorithm is appropriate to replace the widely used manual interactive processing. It also improves the accuracy of results, especially in comparison with single manual thresholding. Whereas manual threshold setting has often been criticised as subjective and a major source of error the less time-consuming edge detection approach is objective, reproducible and can be applied to a large number of images. # 2004 Elsevier B.V. All rights reserved.
منابع مشابه
Assessment of automatic gap fraction estimation of forests from digital hemispherical photography
Thresholding is a central part of the analysis of hemispherical images in terms of gap fraction and leaf area index (LAI), and the selection of optimal thresholds has remained a challenge over decades. The need for an objective, automatic, operatorindependent thresholding method has long been of interest to scientists using hemispherical photography. This manuscript deals with the comparison of...
متن کاملReducing Light Change Effects in Automatic Road Detection
Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...
متن کاملReducing Light Change Effects in Automatic Road Detection
Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...
متن کاملThe Potential of Discrete Return, Small Footprint Airborne Laser Scanning Data for Vegetation Density Estimation
We evaluate the potential of deriving a vegetation leaf area index (LAI) from small footprint airborne laser scanning data. Based on findings from large area histograms of discrete laser returns for two contrasting plots, LAI is estimated from the fraction of first to last and single returns inside the canopy. The canopy returns are classified using thresholding of LIDAR raw data heights subtra...
متن کاملStandardizing the Protocol for Hemispherical Photographs: Accuracy Assessment of Binarization Algorithms
Hemispherical photography is a well-established method to optically assess ecological parameters related to plant canopies; e.g. ground-level light regimes and the distribution of foliage within the crown space. Interpreting hemispherical photographs involves classifying pixels as either sky or vegetation. A wide range of automatic thresholding or binarization algorithms exists to classify the ...
متن کامل