scholarly journals Mapping Forest Biomass Using Remote Sensing and National Forest Inventory in China

Forests ◽  
2014 ◽  
Vol 5 (6) ◽  
pp. 1267-1283 ◽  
Author(s):  
Ling Du ◽  
Tao Zhou ◽  
Zhenhua Zou ◽  
Xiang Zhao ◽  
Kaicheng Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Inventory ◽  
Forest Biomass ◽  
National Forest Inventory ◽  
National Forest

Monitoring Canada's forests: The National Forest Inventory

2005 ◽  
Vol 81 (2) ◽  
pp. 214-221 ◽  
Author(s):  
M D Gillis ◽  
A Y Omule ◽  
T. Brierley
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Forest Inventory ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Remote Sensing Data ◽  
National Forest Inventory ◽  
National Forest ◽  
Inventory Data ◽  
International Reporting

A new national forest inventory is being installed in Canada. For the last 20 years, Canada's forest inventory has been a compilation of inventory data from across the country. Although this method has a number of advantages, it lacks information about the nature and rate of changes to the resource, and does not permit projections or forecasts. To address these limitations a new National Forest Inventory (NFI) was developed to monitor Canada's progress in meeting a commitment towards sustainable forest management, and to satisfy requirements for national and international reporting. The purpose of the new inventory is to "assess and monitor the extent, state and sustainable development of Canada's forests in a timely and accurate manner." The NFI consists of a plot-based system of permanent observational units located on a national grid. A combination of ground plot, photo plot and remote sensing data are used to capture a set of basic attributes that are used to derive indicators of sustainability. To meet the monitoring needs a re-measurement strategy and framework to guide the development of change estimation procedures has been worked out. A plan for implementation has been drafted. The proposed plan is presented and discussed in this paper. Key words: Canada, forest cover, inventory, monitoring, National Forest Inventory, re-measurement, panel

scholarly journals Remote-sensing support for the Estonian National Forest Inventory, facilitating the construction of maps for forest height, standing-wood volume, and tree species composition

2020 ◽  
Vol 73 (1) ◽  
pp. 77-97
Author(s):  
Mait Lang ◽  
Allan Sims ◽  
Kalev Pärna ◽  
Raul Kangro ◽  
Märt Möls ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Species Composition ◽  
Tree Species ◽  
Forest Inventory ◽  
Point Clouds ◽  
National Forest Inventory ◽  
National Forest ◽  
Tree Species Composition ◽  
Wood Volume ◽  
Forest Height

Abstract Since 1999, Estonia has conducted the National Forest Inventory (NFI) on the basis of sample plots. This paper presents a new module, incorporating remote-sensing feature variables from airborne laser scanning (ALS) and from multispectral satellite images, for the construction of maps of forest height, standing-wood volume, and tree species composition for the entire country. The models for sparse ALS point clouds yield coefficients of determination of 89.5–94.8% for stand height and 84.2–91.7% for wood volume. For the tree species prediction, the models yield Cohen's kappa values (taking 95% confidence intervals) of 0.69–0.72 upon comparing model results against a previous map, and values of 0.51–0.54 upon comparing model results against NFI sample plots. This paper additionally examines the influence of foliage phenology on the predictions and discusses options for further enhancement of the system.

Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.

2011 ◽  
Vol 41 (1) ◽  
pp. 83-95 ◽  
Author(s):  
Timothy G. Gregoire ◽  
Göran Ståhl ◽  
Erik Næsset ◽  
Terje Gobakken ◽  
Ross Nelson ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Forest Biomass ◽  
National Forest Inventory ◽  
Sample Survey ◽  
National Forest ◽  
Total Biomass ◽  
Stage Design ◽  
Variance Estimators ◽  
Inventory And Monitoring ◽  
Selection Of

Inasmuch as LiDAR is becoming an increasingly prominent tool for forest inventory, it is timely to develop a framework to understand the statistical properties of LiDAR-based estimates. A model-assisted approach to estimation and inference when using LiDAR as a tool to inventory aboveground forest biomass is presented. An empirical example is also presented, yet the article’s focus is largely methodological. The sampling plan in the example is viewed as a two-stage design, with slightly different primary sampling units between the profiling and scanning laser surveys. A regression estimator is presented that uses biomass data from the Norwegian National Forest Inventory as the response variable and laser-derived variables as covariates. A major thrust of this article is the presentation of the variance of the estimators of total biomass and biomass per hectare as well as variance estimators.

Combining national forest inventory field plots and remote sensing data for forest databases

2008 ◽  
Vol 112 (5) ◽  
pp. 1982-1999 ◽  
Author(s):  
Erkki Tomppo ◽  
Håkan Olsson ◽  
Göran Ståhl ◽  
Mats Nilsson ◽  
Olle Hagner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Inventory ◽  
Remote Sensing Data ◽  
National Forest Inventory ◽  
National Forest ◽  
Sensing Data ◽  
Field Plots

New estimate of growing stock volume and carbon sequestration of Russian forests based on national forest inventory and remote sensing data

2021 ◽  
Author(s):  
Dmitry Schepaschenko ◽  
Elena Moltchanova ◽  
Stanislav Fedorov ◽  
Victor Karminov ◽  
Petr Ontikov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soviet Union ◽  
Forest Inventory ◽  
Remote Sensing Data ◽  
National Forest Inventory ◽  
The State ◽  
National Forest ◽  
Sensing Data ◽  
Growing Stock ◽  
Russian Forests

<p>Since the collapse of the Soviet Union and transition to a new forest inventory system, Russia has reported (FAO, 2014) almost no changes in growing stock (+1.8%) and biomass (+0.6%). Yet remote sensing products indicate increased vegetation productivity (Guay et al., 2014), tree cover (Song et al., 2018) and above-ground biomass (Liu et al., 2015). Here, we challenge the official national statistics with a combination of recent National Forest Inventory and remote sensing data products to provide an alternative estimate of the growing stock of Russian forests and assess the relative changes in the post-Soviet era. Our estimate for the year 2014 is 118.29±1.3 10<sup>9</sup> m<sup>3</sup>, which is 48% higher than the official value reported for the same year in the State Forest Register. The difference is explained by increased biomass density in forested areas (+39%) and larger forest area estimates (+9%). Using the last Soviet Union report (1988) as a reference, Russian forests have accumulated 1163×10<sup>6</sup> m<sup>3</sup> yr<sup>-1</sup> of growing stock between 1988–2014, which compensates for forest growing stock losses in tropical countries (FAO FRA, 2015). Our estimate of the growing stock of managed forests is 94.2 10<sup>9</sup> m<sup>3</sup>, which corresponds to sequestration of 354 Tg C yr<sup>-1</sup> in live biomass over 1988–2014, or 47% higher than reported in the National Greenhouse Gases Inventory (National Inventory Report, 2020).</p><p>Acknowledgement: The research plots data collection was performed within the framework of the state assignment of the Center for Forest Ecology and Productivity of the Russian Academy of Sciences (no. АААА-А18-118052590019-7), and the ground data pre-processing were financially supported by the Russian Science Foundation (project no. 19-77-30015).</p>

Steigende Bestandszahlen bei Spechten und anderen Vogelarten dank Zunahme von Totholz? | An increase in the population of woodpeckers and other bird species thanks to an increase in the quantities of deadwood?

2009 ◽  
Vol 160 (11) ◽  
pp. 334-340 ◽  
Author(s):  
Pierre Mollet ◽  
Niklaus Zbinden ◽  
Hans Schmid
Keyword(s):  
Forest Inventory ◽  
Bird Species ◽  
National Forest Inventory ◽  
Population Increase ◽  
National Forest ◽  
Forest Species ◽  
Breeding Populations ◽  
Willow Tit ◽  
Middle Spotted Woodpecker ◽  
Important Habitat

Results from the monitoring programs of the Swiss Ornithological Institute show that the breeding populations of several forest species for which deadwood is an important habitat element (black woodpecker, great spotted woodpecker, middle spotted woodpecker, lesser spotted woodpecker, green woodpecker, three-toed woodpecker as well as crested tit, willow tit and Eurasian tree creeper) have increased in the period 1990 to 2008, although not to the same extent in all species. At the same time the white-backed woodpecker extended its range in eastern Switzerland. The Swiss National Forest Inventory shows an increase in the amount of deadwood in forests for the same period. For all the mentioned species, with the exception of green and middle spotted woodpecker, the growing availability of deadwood is likely to be the most important factor explaining this population increase.

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