The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

International audienceForest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (aGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. aGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. all plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities

Forest zones of Siberia as determined by climatic zones and their possible transformation trends under global change.

Part I Climate ChangeA system of zonality in Siberia has been formed under the control of continentality, which provides the heat and humidity regimes of the forest provinces. Three sectors of continentality and four to six boreal subzones form a framework for the systematisation of the different features of land cover in Siberia. Their climatic ordination provides the fundamental basis for the principal potential forest types (composition, productivity) forecasting the current climate. These are useful in predicting the future transformations and successions under global changes

Improvement of fire danger rating and vegetation fire behaviour prediction on protected areas

Protected areas (PAs) are established to conserve biological diversity, to maintain nature complexes and objects in their natural condition. Strict nature reserves prevail in Russia by their total area. The whole nature complex is forever extracted from economic use in nature reserves. Here it is prohibited to pursue any activity which might disturb or damage the nature complexes. Even under the existing strict protection from anthropogenic ignition sources, vegetation fires do occur on their territory. Besides, lightnings − these natural ignition sources − are impossible to exclude. Since large destructive fires are impermissible in nature reserves, the later especially need vegetation fire behavior prediction for fire management. Fire behavior prediction includes fire spread rate, development (from surface fire into crown or ground one) and fire effects. All this is necessary for taking optimal decisions on how to control each occurring fire and how to suppress it. The Sukachev Institute of Forest SB RAS has developed a method to improve forest fire danger rating and a technique of vegetation fire behavior prediction using vegetation fuel maps (VF maps)

Diversity of Pinus sibirica forest types in different bioclimatic sectors of Sayan Mountains

The typological diversity of the three climatic facies of Siberian pine forests is considered in various bioclimatic sectors of the Prienisseysky Sayans. In each of the Sayan bioclimatic sectors, Siberian pine forests have a number of characteristic features of floristic composition and phytocenotic structure, restoration-age dynamics, productivity, and renewal process

Satellite Monitoring of Sayan Mountain Forest Ecosystems

В статье предлагается новый подход к использованию данных дистанционного зондирования низкого и среднего пространственного разрешения для картирования и сезонного мониторинга лесного покрова. Приводятся результаты исследований структуры и динамики растительности, с 1960 г. проводимых на трех ключевых участках, расположенных в Западном и Восточном Саяне. Спутниковые данные (NOAA/AVHRR and TERRA/Modis imagery) о районе исследования доступны за 1996-2009 гг. Характеристики различных лесных поясов и формаций были показаны в контексте их идентификации и изменения спектральных характеристик в течение периода вегетации. Детальная характеристика горных лесных высотно-поясных комплексов с потенциально различным составом лесообразователей важна для организации эффективного управления лесами и мониторинга на региональном и локальном уровне.New approach to use remote sensing data of low and moderate spatial resolution is suggested for forest cover mapping and for its seasonal monitoring. The researches of forest structure and dynamics are conducted on three test sites of the Western and Eastern Sayan mountains since 1960. Satellite remote data for the territory (NOAA/AVHRR and TERRA/Modis imagery) are available for 1996 - 2009. After description of the data base the features of different forest zones and formations are shown in context of their identification and spectral characteristics changing during phenological seasons. Specification of mountain forest zones with different potential composition is important for forest management and monitoring on regional and local levels

Satellite Monitoring of Sayan Mountain Forest Ecosystems

В статье предлагается новый подход к использованию данных дистанционного зондирования низкого и среднего пространственного разрешения для картирования и сезонного мониторинга лесного покрова. Приводятся результаты исследований структуры и динамики растительности, с 1960 г. проводимых на трех ключевых участках, расположенных в Западном и Восточном Саяне. Спутниковые данные (NOAA/AVHRR and TERRA/Modis imagery) о районе исследования доступны за 1996-2009 гг. Характеристики различных лесных поясов и формаций были показаны в контексте их идентификации и изменения спектральных характеристик в течение периода вегетации. Детальная характеристика горных лесных высотно-поясных комплексов с потенциально различным составом лесообразователей важна для организации эффективного управления лесами и мониторинга на региональном и локальном уровне.New approach to use remote sensing data of low and moderate spatial resolution is suggested for forest cover mapping and for its seasonal monitoring. The researches of forest structure and dynamics are conducted on three test sites of the Western and Eastern Sayan mountains since 1960. Satellite remote data for the territory (NOAA/AVHRR and TERRA/Modis imagery) are available for 1996 - 2009. After description of the data base the features of different forest zones and formations are shown in context of their identification and spectral characteristics changing during phenological seasons. Specification of mountain forest zones with different potential composition is important for forest management and monitoring on regional and local levels

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS- based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.</p