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Conference Agenda

Overview and details of the sessions and sub-session of this conference. Please select a date or session to show only sub-sessions at that day or location. Please select a single sub-session for detailed view (with abstracts and downloads if available).

Session Overview
E2: ID.10350 Forest Fires & Emissions
Tuesday, 05/Jul/2016:
11:30am - 12:30pm

Session Chair: Christiana Cornelia Schmullius
Session Chair: Yong Pang
Workshop: Forest Mapping & Retrievals
Location: Sun Moon Room -1, 5.5 Floor, Junyi Dynasty Hotel

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Oral presentation

Analysing Forest Fires in China

Jose Luis Casanova1, Julia Sanz1, Pablo Salvador1, Miguel García1, Qin Xianlin2, Li Zengyuan2, Yin Lingyu2, Sun Guifen2, Johann Goldammer3

1LATUV, University of Valladolid, Spain; 2Institute of Forest Resources Information Technique. The Chinese Academy of Forestry. China; 3Global Fire Monitoring Center. Max Planck Institute for Chemistry, Germany;

Forest fires are a major concern in China because of the economical and biodiversity looses and because the emission of trace gases into the atmosphere. During the 12 years DRAGON-Programme, LATUV has been working in the development of forest fires algorithms, especially in North China in order to get useful products able to understand fire characteristics. A catalog of products has been generated taking into account different remote sensing platforms like, forest fire detection and risk, burnt area mapping, CO and CO2 emissions, severity or burnt biomass.

Forest fires can be detected by different platforms and sensor but the rate of false alarms is high because of industrial activity; this uncertainty can be achieved by taking into account land cover and land change information. The CO and CO2 emissions are important, because of the forest fires inside China and because forest fires in the edge between China and Russia that have a considerable impact in the atmosphere composition in North China. The burnt biomass product can be improved with new ground data in order to optimize the algorithm retrieve.

The availability of new sensors on board Sentinel platforms will improve the product quality making them more accurate and increasing the periodicity information.

Casanova-Analysing Forest Fires in China_Cn_version.pdf

Oral presentation

Burned forest biomass estimation methodology using satellite Remote Sensing

Xianlin Qin1, Zengyuan Li1, Guifen Sun1, Lingyu Yin1, Xiaofeng Zu1, Guang Deng1, Xu Zhang1, Zihui Zhang2, Casanova Joseluis3, Sanz Julia3, Georg Goldammer Johann4

1Research Institute of Forest Resource Information Technique, The Chinese Academy of Forestry, China, People's Republic of; 2Information Center of Forest Fire Prediction and Monitoring, State Forestry Administration, Beijing, China; 3Remote Sensing Laboratory,University of Valladolid. Faculty of Sciences; 4Global Fire Monitoring Centre (GFMC), Max Planck Institute for Chemistry, Freiburg;

Vegetation biomass burning has been identified as a significant source of aerosols, carbon fluxes, and trace gases, which pollute the atmosphere and contribute to radiative forcing responsible for global climate change. To develop techniques and algorithms to estimate the burned forest biomass using satellite images in Dragon 3, basing on the analysis of spatial patterns and temporal trends according to the burned forest types in China using the Collection 5 MODIS active fire product (MOD14/MYD14) and the MODIS burned area production (MCD45A1), the annual burned forest biomass of China has been estimated from year 2001 to 2014 by using the methodology of FRP power law distribution and forest fire emissions model estimation respectively. At the same time, to meet the needs on the information of burned fuel type and burned biomass for Chinese forest fire prevention management in forest fire incident, the burned forest biomass estimation method at the subcompartment level has been developed and compared with the results by using the NO.1 High-resolution satellite (GF-1) images and HJ-1B CCD image of Chinese with the digital forest resources reference datasets respectively.

Qin-Burned forest biomass estimation methodology using satellite Remote Sensing_Cn_version.pdf


Burned Forest Vegetation Recovery Monitoring Method Using Satellite Remote Sensing

Guifen Sun1, Xianlin Qin1, Lingyu Yin1, Xiaofeng Zu1, Guang Deng1, Casanova Joseluis2

1Chinese Academy Of Forestry Sciences, China, People's Republic of; 2Remote Sensing Laboratory,University of Valladolid. Faculty of Sciences;

To the monitoring technology needs for the effect on forest growth and restoration of alpine region by forest fires, Yajiang County and Muli County in Sichuan province of People Republic of China have been selected as the experimental areas. By means of the analysed results on the factors, such as the vegetation spectral characteristics, vegetation index and vegetation coverage of the burned forest area and the other region by using the time-series images of the NO.1 high-resolution satellite (GF-1), the monitoring method has been developed for meeting the assessment of burned forest vegetation recovery. At the same time, the monitoring results has been validated using the selected samples of different serious (light, moderate and severe) and normal vegetation of the GF-1 images. The results showed that the trends of the burned forest recovery was correlated with the damage degree by forest fire. The more serious the burned forest by the forest fire, the slower the restoration.

Sun-Burned Forest Vegetation Recovery Monitoring Method Using Satellite Remote Sensing_Cn_version.pdf


Sentinel Mission: Forest Fire Products Evaluation Over China

Victor Molina1, Pablo Salvador1, Julia Sanz1, Miguel García1, José Luis Casanova1, Qin Xianlin2

1LATUV, University of Valladolid, Spain; 2IFRIT, CAF, China;

Sentinel-2a and Sentinel-3a were launched on 23rd June 2015 and 16th February 2016 respectively. These two platforms constitute a great improvement in the land monitoring, especially in forest fires emergency management, evaluation and recovery.

The multispectral sensor on board Sentinel-2a is a perfect tool to delineate burnt areas and identify severity with great spatial and temporal resolution while the surface thermal information provided by Sea and Land Surface Temperature Radiometer (SLSTR) on board Sentinel-3a could be an excellent source of hotspots. Both platforms will be complemented with their respective twins Sentinel-2b and Sentinel-3b in order to improve temporal resolution.

This work tries to evaluate the constellation capacity to provide reliable forest fires products over China by comparison with Earth Observing System (EOS) and Landsat constellation products.

Molina-Sentinel Mission_Cn_version.pdf

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