Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990–2005)

Potapov, Peter; Turubanova, Svetlana; Zhuravleva, Ilona; Hansen, Matthew C.; Yaroshenko, Alexey; Manisha, Alexander

doi:10.1155/2012/729614

Cited by 15 publications

(14 citation statements)

References 19 publications

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“…Masek et al (2008) applied a standard disturbance index for North America using such an approach. The study presented here does so as well, and is an extension of previous national-scale forest cover loss characterizations for Indonesia, European Russia and the Democratic Republic of the Congo (Broich et al, 2011;Potapov et al 2012a;Potapov et al, 2012b).…”

Section: Introductionsupporting

confidence: 64%

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Hansen

Egorov

Potapov

et al. 2014

Remote Sensing of Environment

154

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Egorov, A.; Potapov, P V.; Stehman, S V.; Tyukavina, A; Turubanova, S A.; Roy, D. P.; Goetz, S J.; Loveland, T R.; Ju, J; Kommareddy, A.; Kovalskyy, V.; Forsyth, C; and Bents, T, "Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)" (2014 Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ timeseries images were used to validate the products. Mapped forest cover loss totaled 53,084 km 2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km 2 and nearly matched the estimated area from the reference (GoogleEarth™) classification;however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001-2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for nationalscale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs. gov/CONUS_5Y_LandCover/).

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Section: Introductionsupporting

confidence: 64%

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Hansen

Egorov

Potapov

et al. 2014

Remote Sensing of Environment

154

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“…For Russia in particular, the quality of BD data has been previously criticized (e.g. Potapov et al ., ), and the expanse of BD is thought to be considerably underestimated (Selikhovkin, ; Shvidenko et al ., ), since large parts of the country are not surveyed regularly, particularly those in remote, unmanaged Siberian forests (Malysheva et al ., ).…”

Section: Discussionmentioning

confidence: 99%

Biotic disturbances in Northern Hemisphere forests – a synthesis of recent data, uncertainties and implications for forest monitoring and modelling

Kautz

Meddens

Hall

et al. 2016

Global Ecol. Biogeogr.

154

121

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Aim Biotic disturbances (BD, including insects, pathogens and wildlife herbivory) can alter forest structure and the capability of forests to deliver ecosystem services. Impact assessments, however, are limited by the lack of reliable and timely disturbance data at large spatial scales. This review synthesizes empirical data on the magnitude and distribution of spatiotemporal impacts of BD.Location Northern Hemisphere.Methods Based on large-scale, multi-year BD data sets, covering c. 46% of the global forest, we calculated annual disturbance fractions D f (percentage of forest area affected) and their inter-annual variability at a grid cell resolution of 18. The impact of BD on forest carbon pools was determined by overlaying D f with data on forest cover and carbon density.Results Overall, 43.9 million hectares (Mha) (D f 5 2.6%) of forests were affected annually by BD, particularly by insects (36.5 Mha, D f 5 2.2%). Our synthesis demonstrates that fractions affected by BD (1) vary greatly over space and time, mainly in response to ephemeral bark beetle and defoliator outbreaks, (2) show temporal trends that are inconsistent across regions, yet are largely increasing over recent decades, and (3) are substantially higher than D f caused by fire and other abiotic disturbances. Tree mortality was estimated over an area of 3.3 Mha year 21 (medium estimate which assumed mortality at 7.5% of the affected area), with associated committed carbon fluxes from living biomass to litter and the atmosphere at 129.9 Mt C year 21.Main conclusions BD are key drivers of forest dynamics, making a contribution to tree mortality of a similar magnitude to fire. Despite inherent uncertainties, the data reported can be used to improve the representation of BD in global ecosystem models. Our findings call for future forest monitoring approaches to provide accessible, precise and consistent data on the occurrence and severity of BD which are harmonized across jurisdictions.

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“…Healey et al 2005;Potapov et al 2012). However winter satellite images can be very useful when mapping forest types (Liira et al 2006;Tirpak & Giuliano 2010;Wang et al 2009) and harvests in coniferous forests (Tirpak & Giuliano 2010).…”

Section: Introductionmentioning

confidence: 99%

Monitoring selective logging with Landsat satellite imagery reveals that protected forests in Western Siberia experience greater harvest than non-protected forests

et al. 2017

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SUMMARYWhen timber harvesting is an important source of local income and forest resources are declining, even forests that are designated as protected areas may become vulnerable. Therefore, regular monitoring of forest disturbance is necessary to enforce the protection of forest ecosystems. However, mapping forest disturbance with satellite imagery can be complicated if the majority of the harvesting is selective logging and not clearcuts. Our goal was to map both selective logging and clearcuts within and outside of protected areas in Western Siberia, a region with a highly developed timber industry. Combining summer and winter imagery allowed us to accurately estimate not only clearcuts, but also selective logging. Winter Landsat images substantially improved our classification and resulted in a highly accurate forest disturbance map (97.5% overall accuracy and 86% user accuracy for the rarest class, clearcuts). Selective logging and stripcuts were the dominant disturbance types, accounting for 96.3% of all forest disturbances, versus 3.7% for clearcuts. The total annual forest disturbance rate (i.e. disturbance rate for clearcuts, stripcuts and selective logging together) was 0.53%, but total forest disturbance within protected areas was greater than in non-protected forest (0.66% versus 0.50%, respectively), and so was the annual rate of selective logging (i.e. without clearcuts, 0.37% versus 0.25%, respectively). Our results highlight that monitoring only clearcuts without assessing selective logging might result in significant underestimation of forest disturbance. Also, when timber harvesting is important for the local economy and when protected areas have valuable timber resources that have already been depleted elsewhere, then additional protection may be necessary in order to maintain natural forests within protected areas. We suggest that this is the * Correspondence: Alexander Shchur e-mail: alexander.shchur. 1985@gmail.ru situation in our study area in Western Siberia right now and is likely the situation in many other parts of the globe as well.

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Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990–2005)

Cited by 15 publications

References 19 publications

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Biotic disturbances in Northern Hemisphere forests – a synthesis of recent data, uncertainties and implications for forest monitoring and modelling

Monitoring selective logging with Landsat satellite imagery reveals that protected forests in Western Siberia experience greater harvest than non-protected forests

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