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 ◽  
...  
2021 ◽  
Author(s):  
Dmitry Schepaschenko ◽  
Elena Moltchanova ◽  
Stanislav Fedorov ◽  
Victor Karminov ◽  
Petr Ontikov ◽  
...  

<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>


2005 ◽  
Vol 81 (2) ◽  
pp. 214-221 ◽  
Author(s):  
M D Gillis ◽  
A Y Omule ◽  
T. Brierley

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


2020 ◽  
Author(s):  
Ana Carolina Moreira Pessôa ◽  
Liana O. Anderson ◽  
Rafael Suertegaray Rossato ◽  
Victor Marchezini ◽  
Bruna Maria Pechini Bento ◽  
...  

<p>Providing scientific subsidies for public policies is a compromise that is beyond the boundaries created by the academic universe, requiring scientists to respond to the challenges posed by increasingly complex societies, both socially and environmentally. Considering this, the objective of this work was to build a pilot project for rapid assessment of Tefé National Forest (TNF) land use zoning and evaluate its relevance as a tool to support actions and influence discussions in protected area management councils.</p><p>The assessment considered remote sensing data on deforestation and fire from 2005 to 2015. Deforestation maps (PRODES-INPE) and active fire (MODIS) information were overlapped with TNF land use zoning. Although National Forest, in general, has its land use rules provided by law, each protected area defines on its Management Plan their own land use zoning, with specific rules.</p><p>The study showed that in 2015, 97% of TNF was covered by forest, and although no deforestation was recorded in the same year, the number of active fires was 1.8 times higher than the average from 2005 to 2014. This demonstrates the vulnerability of this area to the extreme drought which affected the region this year. The Population Zone, where 44% of the TNF population lives, recorded the highest rates of deforestation and fire. The Preservation Zone, on the other hand, showed to be fulfilling its function, presenting no active fires and only one deforestation event during the whole analyzed period.</p><p>These results were presented at the 20th TNF Council Meeting, in 2017. The TNF manager pointed out the great importance of spatial and temporal diagnoses, which can exert in prioritize actions to tackle specific problems in most threatened zones. Community leaders participating in the meeting contributed to the completion of the results with in situ day-to-day reports, offering hypotheses for some phenomena observed on the assessment, such as the deforestation observed in 2010. After that, it became clear that actions directly focused on the Population Zone, and mainly related to the use of fire in years of extreme drought, can improve the conservation outcome for this protected area. Integrated socio-environmental diagnosis, such as this pilot project, can be an important tool, allowing a broader version of the monitoring strategies.</p>


2014 ◽  
Vol 72 (1) ◽  
pp. 33-45 ◽  
Author(s):  
Even Bergseng ◽  
Hans Ole Ørka ◽  
Erik Næsset ◽  
Terje Gobakken

2020 ◽  
Vol 73 (1) ◽  
pp. 77-97
Author(s):  
Mait Lang ◽  
Allan Sims ◽  
Kalev Pärna ◽  
Raul Kangro ◽  
Märt Möls ◽  
...  

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.


2018 ◽  
Vol 39 (14) ◽  
pp. 4830-4844 ◽  
Author(s):  
Alfredo Fernández-Landa ◽  
Jesús Fernández-Moya ◽  
Jose Luis Tomé ◽  
Nur Algeet-Abarquero ◽  
María Luz Guillén-Climent ◽  
...  

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