Flore Devriendt

Propagation of shadow effects on typical remote sensing applications in forestry

Airborne LiDAR and hyperspectral data were acquired over a broadleaved forest area in Belgium. Shadow fractions were calculated, based on Sun angles and a digital surface model derived from the LiDAR data. Pixels in the hyper-spectral image were classified based on the shadow fractions to study the effect of shadow on canopy reflectance and how the effect propagated to typical remote sensing applications in forestry. As a first application, the photosynthetical reflectance index (PRI) was studied, which expresses the relative down-regulation of photosynthesis. A strong correlation (R2 = 0.93) was found between the shadow fraction and the PRI. The second application was a tree species classification problem. A measure for classification uncertainty (CU) was introduced, based on the Shannon entropy. It was shown that the majority of pixels with a low shadow fraction were classified with a lower uncertainty.

Directional Local Filtering for Stand Density Estimation in Closed Forest Canopies Using VHR Optical and LiDAR Data

In this letter, we present a novel object-based approach addressing individual tree crown (ITC) detection to assess stand density from remotely sensed imagery in closed forest canopies: directional local filtering (DLF). DLF is a variant of local maximum filtering (LMF). Within locally homogeneous areas, it uses a 1-D neighborhood and simultaneously searches for local directional maxima and minima. From the extracted local maxima and minima, a proxy for crown dimensions is inferred, which is in turn related to stand density. Developed on artificial imagery, the new object-based ITC method was tested on three different forest types in Belgium, which were all characterized by dense closed canopies: 1) a coniferous forest; 2) a mixed forest; and 3) a deciduous forest. Very high resolution aerial photographs, IKONOS imagery, and Light Detection and Ranging data, in conjunction with manually digitized and field survey data, were used to evaluate the new technique. The directional DLF approach yielded consistently stronger relations (in terms of R2) when compared with the conventional omnidirectional LMF technique. The qualitative evaluation clearly demonstrated that, next to stand density estimation, DLF also offered opportunities for full crown delineation.