Roland Goossens

Extraction of forest stand parameters from panchromatic and multispectral SPOT-1 data

Abstract The main objective of this paper is to determine the extent to which forest structural variables can be estimated from SPOT-1 panchromatic and multispectral radiance. The test site is the state-owned Pynven forest, featuring a large amount of evenly-aged pine stands from which those with Corsican pine (Pinus nigra Am. var. Calabrica Loud.) are selected. Investigated image parameters include waveband, first-order statistics estimators and sample window size. The forest stand parameters are stand density, stand age, average tree diameter, stand basal area, average canopy height and stand volume. Empirical linear models are constructed based on Bartletts three-group method, followed by inversion and validation using an independent test data set. The green and red SPOT-1 waveband are useless for forest stand parameter estimation, and the arithmetic mean of sample window radiance is the only usable estimator from the set of tested statistical measures. Stand density and average canopy height can sati...

Remote sensing for wildlife management: Giant panda habitat mapping from LANDSAT MSS images

Abstract Remote sensing is a powerful and accurate means of collecting data for wildlife management, particularly for large areas which are difficult of access and feature delicate ecosystems. Giant panda habitat in the Peoples Republic of China was evaluated by visual interpretation of multitemporal LANDSAT MSS images. The resulting map, combined with ground survey data, provides important information upon which management decisions can be planned. This case study illustrates that remote sensing techniques can make a significant contribution to the management programme for the conservation of a threatened animal species.

Evaluation of SPOT and TM data for forest stratification: a case study for small-size poplar stands

The value of SPOT and TM data for stratification of poplar stands prior to volume inventory is assessed. The stratification is based upon the poplar development stage, which is determined by canopy closure and tree height. The effect of development stage and type of understorey vegetation on the spectral radiance of poplar stands is analyzed throughout the vegetation period. The optimal acquisition date(s) and spectral range(s) and the most suited classification approach for discrimination of poplar development stages are determined. Satellite images recorded during the full growing season are preferred for poplar stand stratification according to development stage. In this period the interfering effect of the understory vegetation is minimal in proportion to the effect of the poplar stand development stage. Young poplar stands can accurately be classified as long as the appropriate spectral range of an image registered during the full growing period is selected. The discrimination between young and other popular development stages is accurate enough for use in a stratification prior to volume inventory. >