Anouk Verheyden

HIGH-RESOLUTION VEGETATION DATA FOR MANGROVE RESEARCH AS OBTAINED FROM AERIAL PHOTOGRAPHY

In this methodological study, the applicability of aerial photographs for monitoring mangrove vegetation dynamics at high resolution was investigated. Vegetation maps of three mangrove forests in Sri Lanka (Galle, Rekawa and Pambala) were produced based on visual analysis of aerial photographs. The visual analysis was aided by applying an interpretation key constructed during a first fieldwork mission. Image attributes used for the identification of individual trees included: gray values, texture, form and size of the crowns and the presence or absence of a shaded side. For the identification of species assemblages, the vegetation structure (i.e. the distribution of individual trees) appeared to be an important attribute. The accuracy and reliability of the vegetation maps were investigated during a second fieldwork mission. The aerial photographs proved to be very useful for the production of genus-based vegetation maps. The error analysis showed that density estimations (quantitative identification) based on aerial photography was not sufficiently accurate for the objectives of the study, but that the overall identification of vegetation assemblages (qualitative identification) coincided most satisfactory with the ground-truth data. In addition to the applicability of aerial photography in monitoring mangroves, the importance of aerial photography in the management of the mangrove ecosystem is clearly highlighted.

Reduction of the Gibbs phenomenon applied on nonharmonic time base distortions

A sine wave fitting procedure for characterizing measurements of a periodic signal in the presence of additive noise and an unknown time base distortion is presented. If the time base distortion is modeled by a Fourier series, it suffers from the Gibbs phenomenon (ringing) at the borders of the data record. Usually, this is solved by ignoring data samples at the borders. The latter is unacceptable for very short data records where measuring a sample is (very) expensive and/or (very) time consuming. This paper presents a solution that suppresses the ringing in the estimated time base distortion without ignoring data samples at the borders. The theory is illustrated on simulations and on real vessel density in the wood of a mangrove tree from Kenya (Rhizophora mucronata).

Reduction of the Gibbs phenomenon in the special case of non-harmonic time base distortions

This paper presents a sine wave fitting procedure for characterizing measurements of a harmonic signal in the presence of additive noise and an unknown time base distortion. In general the reconstructed time base distortion of the existing solutions (Verspecht, 1994; Schoukens et al., 1997) suffers from the Gibbs phenomenon (ringing) at the borders of the data record. Ignoring data samples at the borders is unacceptable for very short data records where measuring a sample is (very) expensive and/or (very) time consuming. This paper presents a solution that suppresses the Gibbs phenomenon in the estimated time base distortion without ignoring data samples at the borders. The theory is illustrated on simulations and on real measurements of the vessel density of a mangrove tree from Kenya (Rhizophora mucronata).