Remote sensing of boreal forest biophysical and inventory parameters: a review

2008 ◽  
Vol 34 (sup2) ◽  
pp. S286-S313 ◽  
Author(s):  
David A Lutz ◽  
Robert A Washington-Allen ◽  
Herman H Shugart
Keyword(s):  
Remote Sensing ◽  
Boreal Forest

scholarly journals Estimation of Boreal Forest Growing Stock Volume in Russia from Sentinel-2 MSI and Land Cover Classification

2021 ◽  
Vol 13 (21) ◽  
pp. 4483
Author(s):  
W. Gareth Rees ◽  
Jack Tomaney ◽  
Olga Tutubalina ◽  
Vasily Zharko ◽  
Sergey Bartalev
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Boreal Forest ◽  
Remote Sensing Data ◽  
Land Cover Classification ◽  
Fundamental Parameter ◽  
Sensing Data ◽  
Growing Stock ◽  
Stock Volume ◽  
Sentinel 2

Growing stock volume (GSV) is a fundamental parameter of forests, closely related to the above-ground biomass and hence to carbon storage. Estimation of GSV at regional to global scales depends on the use of satellite remote sensing data, although accuracies are generally lower over the sparse boreal forest. This is especially true of boreal forest in Russia, for which knowledge of GSV is currently poor despite its global importance. Here we develop a new empirical method in which the primary remote sensing data source is a single summer Sentinel-2 MSI image, augmented by land-cover classification based on the same MSI image trained using MODIS-derived data. In our work the method is calibrated and validated using an extensive set of field measurements from two contrasting regions of the Russian arctic. Results show that GSV can be estimated with an RMS uncertainty of approximately 35–55%, comparable to other spaceborne estimates of low-GSV forest areas, with 70% spatial correspondence between our GSV maps and existing products derived from MODIS data. Our empirical approach requires somewhat laborious data collection when used for upscaling from field data, but could also be used to downscale global data.

scholarly journals No growth stimulation of Canada’s boreal forest under half-century of combined warming and CO2 fertilization

2016 ◽  
Vol 113 (52) ◽  
pp. E8406-E8414 ◽  
Author(s):  
Martin P. Girardin ◽  
Olivier Bouriaud ◽  
Edward H. Hogg ◽  
Werner Kurz ◽  
Niklaus E. Zimmermann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boreal Forest ◽  
Spatial Patterns ◽  
Tree Growth ◽  
Hydrological Cycle ◽  
Forest Growth ◽  
Spatiotemporal Variability ◽  
Late 20Th Century ◽  
Growth Trends ◽  
Growth Variability

Considerable evidence exists that current global temperatures are higher than at any time during the past millennium. However, the long-term impacts of rising temperatures and associated shifts in the hydrological cycle on the productivity of ecosystems remain poorly understood for mid to high northern latitudes. Here, we quantify species-specific spatiotemporal variability in terrestrial aboveground biomass stem growth across Canada’s boreal forests from 1950 to the present. We use 873 newly developed tree-ring chronologies from Canada’s National Forest Inventory, representing an unprecedented degree of sampling standardization for a large-scale dendrochronological study. We find significant regional- and species-related trends in growth, but the positive and negative trends compensate each other to yield no strong overall trend in forest growth when averaged across the Canadian boreal forest. The spatial patterns of growth trends identified in our analysis were to some extent coherent with trends estimated by remote sensing, but there are wide areas where remote-sensing information did not match the forest growth trends. Quantifications of tree growth variability as a function of climate factors and atmospheric CO2 concentration reveal strong negative temperature and positive moisture controls on spatial patterns of tree growth rates, emphasizing the ecological sensitivity to regime shifts in the hydrological cycle. An enhanced dependence of forest growth on soil moisture during the late-20th century coincides with a rapid rise in summer temperatures and occurs despite potential compensating effects from increased atmospheric CO2 concentration.

Fire activity and its influence on Aerosol Optical Depth and Green-House Gases over PEEX area for the last two decades

2021 ◽  
Author(s):  
Larisa Sogacheva ◽  
Anu-Maija Sundström ◽  
Timo H. Virtanen ◽  
Antti Arola ◽  
Tuukka Petäjä ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Boreal Forest ◽  
Atmospheric Composition ◽  
Future Climate Change ◽  
Individual Species ◽  
Modeling Tools ◽  
Fire Emissions ◽  
Burned Areas ◽  
Fire Activity

<p>The Pan-Eurasian Experiment Program (PEEX) is an interdisciplinary scientific program bringing together ground-based in situ and remote sensing observations, satellite measurements and modeling tools aiming to improve the understanding of land-water-atmosphere interactions, feedback mechanisms and their effects on the ecosystem, climate and society in northern Eurasia, Russia and China. In a view of the large area covering thousands of kilometres, large gaps will remain where no or little ground-based observational information will be available. The gap can partly be filled by satellite remote sensing of relevant parameters as regards atmospheric composition.</p><p>Biomass burning is a violent source of atmospheric pollutants. Fires and corresponding emissions to the atmosphere dramatically change the atmospheric composition in case of long-lasting fire events, which might cover extended areas. In the burned areas, CO2 exchange, as well as emissions of different compounds are getting to higher levels, which might contribute to climate change by changing the radiative budget through the aerosol-cloud interaction and cloud formation. In the boreal forest, after CO2, CO and CH4, the largest emission factors for individual species were formaldehyde, followed by methanol and NO2 (Simpson et al., ACP, 2011). The emitted long-life components, e.g., black carbon, might further be transported to the distant areas and measured at the surface far from the burned areas.</p><p>In the boreal forest region, fires are very common, very large and produce a lot of smoke. Boreal areas  have been burning regularly for thousands of years and is adapted to fires, which happen most often between May and October. In boreal ecosystems, future increases in air temperature may lengthen the fire season and increase the probability of fires, leading some to hypothesize a positive feedback between warming, fire activity, carbon loss, and future climate change (Kasischke et al., 2000). </p><p> During the last few decades, several burning episodes have been observed over PEEX area by satellites (as fire counts), specifically over Siberia and central Russia. The following information available from satellites will be utilized to reveal a connection between Fire activity and atmospheric composition <span>for the period 2002-2020 over the PEEX area:</span></p><ul><li>- Fire count, FRP and burned areas from MODIS</li> <li>- Absorbing Aerosol Index (AAI), multi-instrument (GOME-2, OMI, TOMS) product</li> <li>- CO from MOPPIT</li> <li>- HCHO and NO2 from OMI</li> </ul><p>Monthly temperature and humidity fields from ERA5 re-analysis will be also utilized to reveal if a connection exist between climate variables and occurrence and intensity of the forest fires.</p><p>Kasischke, B. J. Stocks: Fire, Climate Change, and Carbon Cycling in the Boreal Forest. M. M. Cadwellet al.,Eds., Ecological Studies (Springer, New York, 2000)</p><p>Simpson, I. J., Akagi, S. K., Barletta, B., Blake, N. J., Choi, Y., Diskin, G. S., Fried, A., Fuelberg, H. E., Meinardi, S., Rowland, F. S., Vay, S. A., Weinheimer, A. J., Wennberg, P. O., Wiebring, P., Wisthaler, A., Yang, M., Yokelson, R. J., and Blake, D. R.: Boreal forest fire emissions in fresh Canadian smoke plumes: C<sub>1</sub>-C<sub>10</sub> volatile organic compounds (VOCs), CO<sub>2</sub>, CO, NO<sub>2</sub>, NO, HCN and CH<sub>3</sub>CN, Atmos. Chem. Phys., 11, 6445–6463, https://doi.org/10.5194/acp-11-6445-2011, 2011.</p><p> </p>

Remote sensing of biophysical variables in boreal forest stands of Picea mariana

1996 ◽  
Vol 17 (15) ◽  
pp. 3077-3081 ◽  
Author(s):  
F. G. HALL ◽  
D. R. PEDDLE ◽  
E. F. LEDREW
Keyword(s):  
Remote Sensing ◽  
Boreal Forest ◽  
Picea Mariana ◽  
Forest Stands

Clear-cut Detection in Boreal Forest Aided by Remote Sensing

2003 ◽  
Vol 18 (6) ◽  
pp. 537-546 ◽  
Author(s):  
Timo Saksa ◽  
Janne Uuttera ◽  
Taneli Kolström ◽  
Mikko Lehikoinen ◽  
Anssi Pekkarinen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boreal Forest ◽  
Clear Cut ◽  
Cut Detection
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