VITAL - Teledetection of vitality in perennial plants

Context and objectives

Vitality assessment of trees is used in pomology and forestry to estimate harvests or to focus treatments, but it often means a time-consuming and tedious procedure of questionable reliability. This project aimed to improve conventional methods of vitality assessment of trees through the use of air-and satellite borne spectroscopic images, in order to facilitate the detection of unhealthy trees, their degree of vitality and specific stress factors. The spectral reflectance of five different kinds of naturally occurring stress factors (aphids, viruses, bacterial infections, etc.) was investigated from test-plots in the orchards of Velm and the pine stands of Pijnven in the same region.  The increasing degree of complexity in the reflection signal on different spatial levels is a major challenge for the identification of specific stress signals on coarser resolutions and was followed up with measurements on different scales. The whole orchard and forest stands were investigated with airborne imaging spectroscopy, and the position of stressed and unstressed trees; their LAI and structural properties were measured.

The general objective of the flight measurements above Pijnven and Gorsem was the improvement of the use of imaging spectroscopy data for vegetation oriented data needs in forest inventories, calamity prevention in fruit-growing, and vegetation modeling. This was achieved in co-operation with three parallel projects at the Group of Geomatics and Forest Engineering, using leaf fluorescence as a main vitality indicator.

Project outcome

Expected scientific results

Pijnven
1. Texture analysis: 8 Haralick texture parameters were calculated from the grey-level co-occurrence matrices (GLCMs) and a statistical regression analysis between the parameters from the field measurements and the texture parameters from the digital images was performed, see Products [7].
2. LAI, fractal dimension and gap fraction determination: comparison of different in situ techniques for LAI determination, see [1,2]
3. Architectural description of Pinus sylvestris L.: complete architectural description of 10 young Pinus sylvestris L. trees, random branch data collection in two different stands from the platform of a high-lift, reflectance measurements with the spectro-radiometer for validation on the level of branches, measurements of tree position, tree height and crown extension, see [5, 6].

Gorsem
4. Vitality study and stress detection in apple orchards: reflectance data from apple leafs were tested upon their sensitivity for stress or diseases. It was demonstrated that the reflectance pattern between stressed and unstressed leaves was clearly different. Further statistical analysis confirmed those assumptions. The same generic methodology was used for testing combinations of wavelengths. So we found that there is a probability for a vegetation index such as SDVI to detect stress in two particular cased (scab infection and nitrogen stress). For  both stress and disease, we found regions with very high significance in different spectral regions. By choosing the appropriate wavelengths for the SDVI it is possible not only to detect stress but also to distinguish between different stresses and diseases, see [3, 4, 8].