Piotr Tompalski

Remote Sensing Technologies for Enhancing Forest Inventories: A Review

Abstract Forest inventory and management requirements are changing rapidly in the context of an increasingly complex set of economic, environmental, and social policy objectives. Advanced remote sensing technologies provide data to assist in addressing these escalating information needs and to support the subsequent development and parameterization of models for an even broader range of information needs. This special issue contains papers that use a variety of remote sensing technologies to derive forest inventory or inventory-related information. Herein, we review the potential of 4 advanced remote sensing technologies, which we posit as having the greatest potential to influence forest inventories designed to characterize forest resource information for strategic, tactical, and operational planning: airborne laser scanning (ALS), terrestrial laser scanning (TLS), digital aerial photogrammetry (DAP), and high spatial resolution (HSR)/very high spatial resolution (VHSR) satellite optical imagery. ALS, in particular, has proven to be a transformative technology, offering forest inventories the required spatial detail and accuracy across large areas and a diverse range of forest types. The coupling of DAP with ALS technologies will likely have the greatest impact on forest inventory practices in the next decade, providing capacity for a broader suite of attributes, as well as for monitoring growth over time.

Updating residual stem volume estimates using ALS-and UAV-acquired stereo-photogrammetric point clouds

ABSTRACT To improve precision management and the cost effectiveness of forest practices, we investigate a pre-harvest airborne laser scanning (ALS) forest inventory with an unmanned aerial vehicle (UAV) acquired post-harvest digital aerial photogrammetry (DAP) inventory to identify the location and residual volume of stands following selection harvesting. ALS data and field measurements collected pre-harvest in 2013 (T1) and UAV imagery collected post-harvest in 2015 (T2) were processed to produce analogous point clouds of the study area near Williams Lake, British Columbia, Canada. Tree height, diameter at breast height (DBH), and species were recorded from systematically located variable radius plots subsequent to ALS and DAP collection. Point cloud metrics and field measurements from each data set were used to create T1 ALS and T2 DAP predictive volume models. Direct and indirect volume change estimates were created from the difference between T1 ALS and T2 DAP model results. The estimated root mean square error (RMSE) for volume was 17.34% and 18.50% for the 2013 ALS and 2015 DAP models, respectively. The indirect and direct models predicting volume change produced errors of 16.65% and 86.56%, respectively. Results achieved from ALS and DAP models indicate strong potential for inventories generated using UAV-acquired DAP to estimate the quantity and location of residual volume after harvest operations, and could be applied in tandem to act as a semi-automated inventory cycling method to improve operational efficiency and cost effectiveness in Canadian forest management.

Assessing the status of forest regeneration using digital aerial photogrammetry and unmanned aerial systems

ABSTRACT Accurate, reliable, and cost-effective methods of evaluating forest regeneration success are needed to improve forest inventories and silvicultural operations. While traditional surveys are relatively inexpensive and meet current data requirements, their annual coverage of over 1 million hectares in British Columbia alone are operationally and logistically intensive. To improve the efficiency and utility of forest regeneration inventories, the incorporation of multi-temporal monitoring linked to years since planting (YSP) could help improve understanding of rates and characteristics of vegetative succession while providing a means to evaluate the economic and operational success of management actions on public land. In this study, we evaluate the potential of utilizing Unmanned Aerial System (UAS)-acquired very high spatial resolution imagery to provide spatial, spectral, and structural information on forest regeneration in previously clear-cut stands near Nakusp and Quesnel, British Columbia, Canada. Three stands approximately 5, 10, and 15 YSP were chosen at both sites. Using wall-to-wall UAS-acquired red–green–blue (RGB) imagery, dense Digital Aerial Photogrammetric (DAP) point clouds were produced providing forest structure information. Spectral data in the form of Visible Vegetation Indices (VVI) including the Normalized Green Red Difference Index (NGRDI), visible atmospherically resistant index (VARIg), and Green Leaf Indices (GLIx) were computed. Spectral and structural information from the VVI and DAP were combined to perform Object-Based Image Analyses (OBIA) facilitating supervised classifications of forest cover into conifer, deciduous, and ground classes. Independent classifications were performed on each stand, yielding high overall accuracies (86–95% for Nakusp; 93–95% for Quesnel). Spectral and structural differences amongst classes and YSP were analysed. Height and area coverage of conifers were found to increase with YSP in both sites (0.7–2.7 m for Nakusp; 0.3–2.2 m for Quesnel), while VVI metrics were shown to be more successful than standard RGB at differentiating forest cover through time. The results of this study indicate that UAS-acquired imagery has a potential niche for quickly, accurately, and reliably providing highly detailed spatial, spectral, and structural information on forest regeneration. Methodology and data products from this study show promise for benefiting silvicultural monitoring and operations while improving multi-temporal forest inventory knowledge.

Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling

The increasing availability of highly detailed three-dimensional remotely-sensed data depicting forests, including airborne laser scanning (ALS) and digital aerial photogrammetric (DAP) approaches, provides a means for improving stand dynamics information. The availability of data from ALS and DAP has stimulated attempts to link these datasets with conventional forestry growth and yield models. In this study, we demonstrated an approach whereby two three-dimensional point cloud datasets (one from ALS and one from DAP), acquired over the same forest stands, at two points in time (circa 2008 and 2015), were used to derive forest inventory information. The area-based approach (ABA) was used to predict top height (H), basal area (BA), total volume (V), and stem density (N) for Time 1 and Time 2 (T1, T2). We assigned individual yield curves to 20 × 20 m grid cells for two scenarios. The first scenario used T1 estimates only (approach 1, single date), while the second scenario combined T1 and T2 estimates (approach 2, multi-date). Yield curves were matched by comparing the predicted cell-level attributes with a yield curve template database generated using an existing growth simulator. Results indicated that the yield curves using the multi-date data of approach 2 were matched with slightly higher accuracy; however, projections derived using approach 1 and 2 were not significantly different. The accuracy of curve matching was dependent on the ABA prediction error. The relative root mean squared error of curve matching in approach 2 for H, BA, V, and N, was 18.4, 11.5, 25.6, and 27.53% for observed (plot) data, and 13.2, 44.6, 50.4 and 112.3% for predicted data, respectively. The approach presented in this study provides additional detail on sub-stand level growth projections that enhances the information available to inform long-term, sustainable forest planning and management.

Estimating Forest Site Productivity Using Airborne Laser Scanning Data and Landsat Time Series

Abstract. Site productivity, an important measure of the capacity of land to produce wood biomass, is traditionally estimated by applying species-specific, locally designed models that describe the relation between stand age and dominant height. In this article, we present an approach to derive chronosequences of stand age and height estimates from remotely sensed data to develop site productivity estimates. We first utilized an annual Landsat time series to identify areas of stand replacing disturbances and to estimate the time-since-disturbance, a proxy for stand age. Airborne laser scanning data were used to provide estimates of dominant height for these stands. Nonlinear regression was used to fit a site productivity guide curve for stands aged 7 to 32 years. Existing and developed productivity models, together with remote sensing and inventory data as inputs, were used to validate the site productivity model in three different comparisons. Site productivity was overestimated by 0.70 m (RMSE = 5.55 m) relative to existing forest inventory estimates; further, 89% of remote sensing estimates were within ±1 derived site class of the forest inventory estimates. We conclude that the presented approach is suitable for estimating site productivity for young stands in areas that lack wall-to-wall forest inventory data. Résumé. Le potentiel du site, une mesure importante de la capacité des terres à produire de la biomasse de bois, est traditionnellement estimé en appliquant des modèles spécifiques d’espèces, conçus localement, qui décrivent la relation entre l’âge du peuplement et la hauteur dominante. Dans cet article, nous présentons une approche pour dériver des séquences chronologiques d’estimations de l’âge du peuplement et de la hauteur à partir de données de télédétection pour établir des estimations du potentiel du site. Nous avons d’abord utilisé une série temporelle annuelle Landsat pour identifier les zones de perturbations menant au remplacement des peuplements et pour estimer le temps écoulé depuis la perturbation, un estimateur pour l’âge du peuplement. Des données laser aéroportées ont été utilisées pour fournir des estimations de la hauteur dominante de ces peuplements. Une régression non linéaire a été utilisée pour obtenir une courbe de potentiel du site pour les peuplements âgés de 7 à 32 ans. Les modèles de productivité existants ainsi que des données de télédétection et d’inventaire ont été utilisés comme entrées pour valider le modèle du potentiel du site à partir de trois comparaisons différentes. Le potentiel du site a été surestimé de 0,70 m (RMSE = 5,55 m) par rapport aux estimations existantes d’inventaires forestiers. De plus, 89% des estimations de télédétection étaient à ±1 classe dérivée du site des estimations de l’inventaire forestier. Nous concluons que l’approche présentée est appropriée pour estimer le potentiel du site pour les jeunes peuplements dans les zones avec des données incomplètes d’inventaire forestier.

Measuring visual pollution by outdoor advertisements in an urban street using intervisibilty analysis and public surveys

ABSTRACT Debates on the encroaching commercialization of public space by outdoor advertising highlight its possible negative impact on local quality of life and enjoyment of public spaces. These overstimulating outdoor advertisements are often considered a source of visual pollution, but cities have no standard way of measuring where it exists and its local impact, and thus cannot regulate it effectively. This study illustrates that visual pollution can be measured in a useful way by relating public opinion to the number of visible advertisements (intervisibility analysis). Using a 2.5D outdoor advertisement (OA) dataset (location and height) of a busy urban street in Lublin, Poland, this preliminary experiment translates visibility into visual pollution. It was found that streetscape views with more than seven visible OAs created visual pollution in this case study. The GIS-based methodology proposed could provide Lublin officials with a basic tool to assess and manage visual pollution, by informing permitting decisions on OAs.

Land Cover and Landscape Diversity Analysis in the West Polesie Biosphere Reserve

Abstract The aim of this research was to present the land cover structure and landscape diversity in the West Polesie Biosphere Reserve. The land cover classification was performed using Object Based Image Analysis in Trimble eCognition Developer 8 software. The retrospective land cover changes analysis in 3 lake catchments (Kleszczów, Moszne, Bia³eW³odawskie Lakes)was performed on the basis of archival aerial photos taken in 1952, 1971, 1984, 1992, 2007 and one satellite scene from 2003 (IKONOS).On the basis of land cover map structure, Shannon diversity index was estimated with the moving window approach enabled in Fragstats software. The conducted research has shown that the land cover structure of the West Polesie Biosphere Reserve is diverse and can be simply described by selected landscape metrics. The highest level of land cover diversity, as showed by Shannon Diversity Index, was identified in the western part of the West Polesie Biosphere Reserve, which is closely related to the agricultural character of land cover structure in those regions. The examples of three regional retrospective land cover analyses demonstrated that the character of land cover structure has changed dramatically over the last 40 years.

Environmental landscape determinants of maximum forest canopy height of boreal forests

Aims Canopy height is a key driver of forest biodiversity and carbon cycling. Accurate estimates of canopy height are needed for assessing mechanisms relating to ecological patterns and processes of tree height limitations. At global scales forest canopy height patterns are largely controlled by climate, while local variation at fine scales is due to differences in disturbance history and local patterns in environmental conditions. The relative effect of local environmental drivers on canopy height is poorly understood partly due to gaps in data on canopy height and methods for examining limiting factors. Here, we used airborne laser scanning (ALS) data on vegetation structure of boreal forests to examine the effects of environmental factors on potential maximum forest canopy height. Methods Relationships between maximum canopy height from ALS measures and environmental variables were examined to assess factors limiting tree height. Specifically, we used quantile regression at the 0.90 quantile to relate maximum canopy height with environmental characteristics of climate (i.e. mean annual temperature [MAT] and mean annual precipitation), terrain (i.e. slope) and depth-to-water (DTW) across a 33 000 km2 multiple use boreal forest landscape in northeast Alberta, Canada. Important Findings Maximum canopy height was positively associated with MAT, terrain slope and terrain-derived DTW, collectively explaining 33.2% of the variation in heights. The strongest explanatory variable was DTW explaining 26% of canopy height variation with peatland forests having naturally shorter maximum canopy heights, but also more sites currently at their maximum potential height. In contrast, the most productive forests (i.e. mesic to xeric upland forests) had the fewest sites at their potential maximum height, illustrating the effects of long-term forest management, wildfires and general anthropogenic footprints on reducing the extent and abundance of older, taller forest habitat in Alberta’s boreal forest.

Reply to Vauhkonen: Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347

Piotr Tompalski 1,* , Nicholas C. Coops 1 , Peter L. Marshall 1 , Joanne C. White 2 , Michael A. Wulder 2 and Todd Bailey 3 1 Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada; nicholas.coops@ubc.ca (N.C.C.); peter.marshall@ubc.ca (P.L.M.) 2 Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5, Canada; joanne.white@canada.ca (J.C.W.); mike.wulder@canada.ca (M.A.W.) 3 West Fraser–Slave Lake, P.O. Box 1790, Slave Lake, Alberta, AB T0G 2A0, Canada; todd.bailey@westfraser.com * Correspondence: piotr.tompalski@ubc.ca