http://cfs.nrcan.gc.ca/authors/read/14068 Publications by S.J. Titus en-ca 2001-11-01 00:00:00 MST 2001-11-01 00:00:00 MST webmaster@nofc.cfs.nrcan.gc.ca http://cfs.nrcan.gc.ca/publications?id=18697 El área forestal de Whitecourt, Alberta, Canadá, ha servido como zona piloto para el desarrollo de dos modelos de predicción diaria de incendios forestales causados por agentes de ignición humanos: uno es un modelo de regresión logarítmica (el modelo logit) y el otro un modelo de red neuronal artificial. Ambos modelos alcanzaron una precisión similar en sus predicciones (74 vs. 76%). Este artículo describe la metodología seguida para el desarrollo de los modelos, presenta los resultados alcanzados y discute las implicaciones de su posible aplicación práctica en la planificación de la extinción. Thu, 01 Nov 2001 http://cfs.nrcan.gc.ca/publications?id=18697 http://cfs.nrcan.gc.ca/publications?id=18949 Mon, 03 Dec 2001 http://cfs.nrcan.gc.ca/publications?id=18949 http://cfs.nrcan.gc.ca/publications?id=19343 Wed, 13 Feb 2002 http://cfs.nrcan.gc.ca/publications?id=19343 http://cfs.nrcan.gc.ca/publications?id=19029 The logit model was used to predict the number of fire-days in the Whitecourt Forest of Alberta. The database used included fire (1) and no-fire (0) observations for fire season days between April and October for the 1986 through 1990 period. There were 8,009 observations during this period of which 157 were fire observations. Using four variables, we were able to predict 79.0% of the fire-days and 81.5% of the no-fire-days. The model, Zi=-8.5171+7.6590xAREAi+0.7367xDISTRICTi+2.0478xBUIi+3.9563xISIi, failed to predict 37 of the fire-days and produced 29 ''false alarms''. When this model was tested on fire occurrence data from the Whitecourt Forest for 1991 and 1992 fire seasons it was correct 74.1% of the time. The management implications and limitations of this study are also discussed in this paper. Mon, 10 Dec 2001 http://cfs.nrcan.gc.ca/publications?id=19029 http://cfs.nrcan.gc.ca/publications?id=18988 Thu, 06 Dec 2001 http://cfs.nrcan.gc.ca/publications?id=18988 http://cfs.nrcan.gc.ca/publications?id=11190 The estimation of tree top-kill volumes is an important component of quantifying defoliation impact of severe budworm (Choristoneurapinus Freeman) defoliation on jack pine (Pinusbanksiana Lamb.) trees. Field survey is the only method by which this assessment is currently undertaken. This study evaluated an alternative methodology based on large-scale aerial photo (1:900) measurements and a taper model fitted for jack pine. This included generating linear models for the prediction of actual top-kill length from photo-measured top-kill length, the prediction of DBH from photo-measured tree height and crown area, and the estimation of top-kill volumes from a jack pine taper model. The set of three linear equations fitted with ordinary least squares resulted in top-kill volume estimates that showed no bias. The volume of damaged trees not visible on photographs was less than 1% of the volume of all damaged trees, and therefore adjustment for missed trees was not considered necessary. The methodology is convenient to implement, and if combined with forest sampling procedures, the projection of tree top-kill volumes to the stand level can provide an estimate of defoliation impact. The methodology is also potentially suitable for assessing other insect defoliation impacts that cause top kill. Tue, 22 Aug 2000 http://cfs.nrcan.gc.ca/publications?id=11190 http://cfs.nrcan.gc.ca/publications?id=11187 The cutover area and boundary placement mapping accuracies from currently used air photo techniques and LANDSAT TM and MSS imagery were determined for Alberta forestry conditions. Overall area accuracies for the air photo techniques. LANDSAT TM, and MSS images were 86.7%, 89.5%, and 86.9%, respectively. The influence of increasing accuracy with increasing cutover size, however, must be kept in perspective. Although interpreted cutover areas were generally smaller compared with their actual areas, the deviation was systematic and could therefore be corrected by regression techniques. Overall boundary placement errors for air photo techniques. LANDSAT TM, and MSS images were 30.1, 24.9, and 38.3 m, respectively. Most of the LANDSAT TM errors were in the 20-m range and were within 5 m of the target 15-20 m desired by the Alberta Forest Service. Improvements to this may be achieved by using larger scale satellite images. The base map scale of 1:20 000 was a limiting factor to this study, however, as it was too small with both plotting errors and pen line widths contributing to existing map errors. LANDSAT TM images offered a 12:1 cost savings in data acquisition and are more efficient in comparison with conventional air photos. Use of either medium scale air photos or LANDSAT TM images can be recommended depending on the level of timber commitment accuracy requirements and is presented in the paper as an operational cutover update mapping strategy. Tue, 22 Aug 2000 http://cfs.nrcan.gc.ca/publications?id=11187 http://cfs.nrcan.gc.ca/publications?id=4534 Sat, 26 Aug 2000 http://cfs.nrcan.gc.ca/publications?id=4534 http://cfs.nrcan.gc.ca/publications?id=11183 Tue, 22 Aug 2000 http://cfs.nrcan.gc.ca/publications?id=11183