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Forest characterization with light detection and ranging (LiDAR) data has recently garnered much scientific and operational attention. The number of forest inventory attributes that may be directly measured with LiDAR is limited; however, when considered within the context of all the measured and derived attributes required to complete a forest inventory, LiDAR can be a valuable tool in the inventory process. In this paper, we present the status of LiDAR remote sensing of forests, including issues related to instrumentation, data collection, data processing, costs, and attribute estimation. The information needs of sustainable forest management provide the context within which we consider future opportunities for LiDAR and automated data processing.Key words: LiDAR, airborne laser altimetry, forest inventory, height, volume, biomass, update, remote sensing RÉSUMÉ La représentation des forêts à partir de données LiDAR (détection de la lumière et calcul de la distance) a attiré dernière-ment beaucoup d'attention tant scientifique qu' opérationnelle. Le nombre de variables d'inventaire forestier qui peuvent être mesurées directement par LiDAR est limité, mais lorsqu' on considère le contexte de toutes les variables mesurées et dérivées requises pour compléter un inventaire forestier, le LiDAR peut constituer un outil précieux du processus d'inventaire. Nous présentons dans cet article un portrait de la télédétection des forêts par LiDAR, ainsi que les questions portant sur l'appareillage, la collecte des données, les coûts et l' estimation des variables. Les besoins d'information en matière d'aménagement forestier durable constituent le contexte que nous retenons pour les possibilités d'application future du LiDAR et du traitement automatisé des données.

Consumer-grade digital cameras are recognized as a cost-effective method of monitoring plant health and phenology. The capacity to use these cameras to produce time series information contributes to a better understanding of relationships between environmental conditions, vegetation health, and productivity. In this study we evaluate the use of consumer grade digital cameras modified to capture infrared wavelengths for monitoring vegetation. The use of infrared imagery is very common in satellite remote sensing, while most current near sensing studies are limited to visible wavelengths only. The use of infrared-visible observations is theoretically superior over the use of just visible observation due to the strong contrast between infrared and visible reflection of vegetation, the high correlation of the three visible bands and the possibilities to use spectral indices like the Normalized Difference Vegetation Index. This paper presents two experiments: the first study compares infrared modified and true color cameras to detect seasonal development of understory plants species in a forest; the second is aimed at evaluation of spectrometer and camera data collected during a laboratory plant stress experiment. The main goal of the experiments is to evaluate the utility of infrared modified cameras for the monitoring of plant health and phenology.Results show that infrared converted cameras perform less than standard color cameras in a monitoring setting. Comparison of the infrared camera response to spectrometer data points at limits in dynamic range, and poor band separation as the main weaknesses of converted consumer cameras. Our results support the use of standard color cameras as simple and affordable tools for the monitoring of plant stress and phenology.3

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