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!2014ǯ12·î16Æü 17:00¡Á18:00 ȯɽ, 18:30¡Á ˺ǯ²ñ
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ȯɽ¼Ô¡§Xu Xinwanghao¡ÊNanjing University¡Ë

*Title: Seasonal and spatial dynamics of greenhouse gas emissions under various vegetation covers in a coastal saline wetland in southeast China

*Abstract: Coastal saline wetlands are recognized as prominent sources of greenhouse gas emissions. However, insufficient attention has been paid to the effect of coastal wetlands in mitigating global warming caused by greenhouse gases in China. This study aims to investigate how vegetation and soil parameters affect greenhouse gas emissions in a coastal saline wetland. Fluxes of CO2, CH4, and N2O were measured simultaneously in situ using the closed static chamber technique in four different coastal tidal flats, namely, mud flat, Spartina alterniflora flat, Suaeda glauca flat, and grass flat. The measurements were obtained from September 2012 to August 2013 in the Yancheng coastal wetland, southeast China. The average fluxes across all seasons and flats varied from 10.7 to 2297.6 mg CO2 m-2 h-1 (ecosystem respiration), from 0.368 to 4.959 mg CH4 m-2 h-1, and from 1.5 to 65.7 ug N2O m-2 h-1. Higher CO2 and CH4 fluxes were observed during the summer and autumn seasons. However, the seasonal change of the N2O fluxes was complicated. For the S. alterniflora and grass flats, the highest emissions were observed during summer. For the mud and S. glauca flats, the emissions peaked during winter. The spatial variations of the three greenhouse gas fluxes in the coastal saline wetland primarily depended on vegetation type. The greenhouse gas fluxes from the three tidal flats with vegetation covers (S. alterniflora, S. glauca, and grass flats) were higher than those from the mud flat. Higher CO2 emissions were observed in the S. alterniflora flat than those in the other flats because of the higher carbon sequestration rate, together with higher net primary production and aboveground biomass. However, CH4 and N2O emissions were highest in the grass flat, followed by the S. alterniflora flat. The effects of tidal flats on the CH4 and N2O emissions differed according to the season. The S. alterniflora invasion increased the CO2 emission while slightly lowering the CH4 fluxes, compared with that of native plant communities dominated by Phragmites. Results also suggested that S. alterniflora had the highest global warming potential among the tidal flats in the coastal saline wetland.

18:30¡Á
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!2014ǯ12·î9Æü 17:30-19:00
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ȯɽ¼Ô¡§Izaya Numata (Geospatial Sciences Center of Excellence)

*Title: Monitoring deforestation and forest degradation in the Amazon using remote sensing

*Abstract: In recent decades, human development pressures have results in conversions of vast tracts of Amazonian tropical rain forests to agriculture and other human land uses. In addition to the loss of large forest cover, it has not generally been understood about remaining Amazonian forests been degraded by fire, selective logging and fragmentation. These forest ecosystems disturbed by human may become more vulnerable to ongoing climate change and extreme drought. Therefore, monitoring of spatio-temporal dynamics of deforestation and forest degradation is critically important to estimate its impacts on the Amazon ecosystem such as carbon fluxes and biodiversity. This presentation covers the topics of deforestation, forest degradation in the Amazon and its implication for the Amazonian ecosystems based upon remote sensing.

!2014ǯ12·î2Æü
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!2014ǯ11·î25Æü 17:30-19:00
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!2014ǯ11·î18Æü 17:30-19:00
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ȯɽ¼Ô¡§Shi yusheng¡Ê¹ñΩ´Ä¶­¸¦µæ½ê GOSAT-2 Project Team¡Ë

*Title: High-resolution mapping of biomass burning emissions in Southeast Asia during 2001-2010.

*Abstract: Biomass burning (BB) emissions from forest fires, agricultural waste burning, and peatland combustion contain large amounts of greenhouse gases (e.g., CO2, CH4, and N2O), which significantly impact ecosystem productivity, global atmospheric chemistry, and climate change. With the help of recently released satellite products, biomass density based on satellite and observation data, and spatiotemporal variable combustion factors, this study developed a new high-resolution and multi-year emissions inventory for BB in Southeast Asia (SEA) during 2001-2010. The 1-km grid was effective for quantifying emissions from small-sized fires that were frequently misinterpreted by coarse grid data due to their large smoothed pixels. The average annual BB emissions in SEA during 2001-2010 were 277 Gg SO2, 1125 Gg NOx, 55,388 Gg CO, 3831 Gg NMVOC, 553 Gg NH3, 324 Gg BC, 2406 Gg OC, 3832 Gg CH4, 817,809 Gg CO2, and 99 Gg N2O. Emissions were high in western Myanmar, Northern Thailand, eastern Cambodia, northern Laos, and South Sumatra and South Kalimantan of Indonesia. Emissions from forest burning were the dominant contributor to the total emissions among all land types. The spatial pattern of BB emissions was consistent with that of the burned areas. In addition, BB emissions exhibited similar temporal trends from 2001 to 2010, with strong interannual and intraannual variability. Interannual and intraannual emission peaks were seen during 2004, 2007, 2010, and January-March and August-October, respectively.

!2014ǯ11·î11Æü 17:30-19:00
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!2014ǯ10·î28Æü 17:30-19:00
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!2014ǯ10·î21Æü 17:30-19:00
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ȯɽ¼Ô¡§¥Æ¥à¥ë¥ó¡ÊÃÞÇÈÂç³Ø M2¡Ë

*Title: Land cover change analysis in Ulagai region from 1986 to 2014

*Abstract: The Ulagai region is in the semi-arid northern part of Inner Mongolia. In last decades this region has experienced severe land degradation. To investigate this, we first made land cover maps of 1986, 2000 and 2014 using Landsat images. Then we made change analysis based on grid cell method. The results showed that cropland and barren area increased, and large area of grassland degraded. We also made correlation analysis among land cover classes. The detailed results will be presented and discussed.

!2014ǯ10·î14Æü 17:30-19:00
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*Title: Wetland shrinkage and its possible causes: A case study in Wulagai region, Inner Mongolia
*Abstract: The Wulagai region, which is located in the northern part of Inner Mongolia, has been under much pressure in recent decades. Grassland degradation and wetland shrinkage happened there. Both human activities and climate change can affect the local ecosystem. In my study, I plan to use Landsat satellite images from period of 1986 to 2014, to do the land cover change analysis of this region, combine with statistical data. My goal is to find out how the land cover changes and its possible causes. I will talk about my research progress, field work (in Wulagai region) and future study plans in my presentation.

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*³µÍס§Global products of leaf area index (LAI) usually show large uncertainties in sparsely vegetated areas. The reason is that the understory contribution is not negligible in reflectance modeling for the case of low to intermediate canopy cover. Retrieval of forest understory property from satellite data can largely help solve this problem. Consequently, we proposed a simple method to retrieve understory NDVI (NDVIu) for sparse boreal forests using MODIS BRDF data. Performance of the method was verified by noise-free simulation and in situ collected datasets. Application of the retrieved NDVIu to estimate overstory LAI (LAIo) for sparse boreal forests will also be demonstrated in this presentation.

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*Title: Models for aboveground forest carbon stock estimation in a tropical region using airborne lidar
*Abstract: Quantifying amount of carbon stored in tropical forests remains challenging and retains greatest uncertainties in understanding their role in the global carbon cycle. This uncertainty demands methods that precisely measure forest carbon dynamics and provide carbon density map for a larger geographic extent. In this talk, I would share our research experiences in Sumatran tropical forests for quantifying aboveground forest carbon stock using LiDAR and field measurement data. We calibrated general models including natural and plantation forests and forest specific models for peat swamp and dry moist forests, regrowth, mangrove, rubber, acacia, oil palm, and coconut.
*Keywords: Forest carbon; AFCS; AGB; biomass modeling; REDD+; natural forest; plantation forest, LiDAR

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*³µÍס§The need of global disaster assessment and environment monitoring from countries all over the world is intensifying. In recent years, the trend of global warming has accelerated considerably, which results in more frequent extreme weather events and poses direct threats to disaster, health, energy, climate changes, ecological system, agriculture, biodiversity, water resource and meteorology. It is therefore necessary to improve our capabilities of observing global environment, conduct detailed analysis of environmental changes to gain a better understanding of the causality among various factors, integrate the techniques of knowledge management with geospatial information systems, and turn environmental threats triggered by global changes to opportunities of sustainable development. Formosat-2, the first high-spatial-resolution satellite operated on a daily-revisit orbit, has been providing high spatiotemporal optical imagery for most of the world in the past nine years, Professor Cheng-Chien Liu developed an automatic image processing system that is able to process a large amount of Formosat-2 imagery to support the requirements of rapid response to global disasters and environmental events. Recently, Professor Liu also introduced and developed various remote sensing platforms, geospatial information systems and knowledge management techniques, with the intention to establish a research team dedicated to global earth observations and data analysis, as well as rapid response to global disasters and environmental events. This presentation will review the applications of Formosat-2 high spatiotemporal imagery on natural disasters, including (1) rapid responses to global disasters, (2) preparation of Taiwan's landslide inventory, (3) landslide susceptibility and hazard index, and (4) the nowcast system of slope hazards. Recent progresses in employing unmanned aerial vehicles (UAVs) will be reported as well, including (5) rapid mapping of slope hazards with photos acquired from a low-cost fixed-wing UAV using the automatic mission planning and image processing system (AMPIPS), (6) rapid mapping of inundated areas with photos acquired from a low-cost Six-Rotor UAV Helicopter, and (7) landscape variations analysis and management efficiency assessment using UAV and car-based panorama. Some discussions and our research strategy for the future works would be given, and hopefully, more collaboration could be initiated after this seminar.


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