Mornitoring dalta changes of yellow river by using remote sensing rechniques

Institute of Geographical Scienceand Natural Resources Reseach, Chinese Academy of Sciences2005 International Symposium on Environmental Mornitoring in East Asia -Remote Sensing and Forests-,Hosted The EMEA Project, Kanazawa University 21st=Century COE Program -Environmental Monitoring and Predicition of Long- and Short- Term Dynamics of Pan-Japan Sea Area- ,予稿集, EMEA 2005 in Kanazawa, 国際学術研究公開シンポジウム『東アジアの環境モニタリング』－リモートセンシングと森林－,年月日：200511月28日～29日, 場所：KKRホテル金沢, 金沢大学自然科学研究科, 主催：金沢大学EMEAプロジェクト, 共催：金沢大学21世紀COEプログラム「環日本海域の環境変動と長期・短期変動予測

6.EMEA International Symposium in Kanazawa, Japan

Institute of Geograpical Sciences and Natural Resources Research, CASProject Number 14404021, Peport of Research Project ; Grant-in-Aid for Scientific Research(B)(2), from April 2002 to March 2006, Edited by Muramoto,Ken-ichiroKamata, NaotoKawanishi, TakuyaKubo, MamoruLiu, JiyuanLee, Kyu-Sung , 人工衛星データ活用のための東アジアの植生調査、課題番号14404021, 平成14年度～平成17年度科学研究費補助金, 基盤研究（B)(2)研究成果報告書, 研究代表者：村本, 健一郎, 金沢大学自然科学研究科教

4.EAFES International Congress in Mokpo, Korea

Institute of Geograpical Sciences and Natural Resources Research, CASProject Number 14404021, Peport of Research Project ; Grant-in-Aid for Scientific Research(B)(2), from April 2002 to March 2006, Edited by Muramoto,Ken-ichiroKamata, NaotoKawanishi, TakuyaKubo, MamoruLiu, JiyuanLee, Kyu-Sung , 人工衛星データ活用のための東アジアの植生調査、課題番号14404021, 平成14年度～平成17年度科学研究費補助金, 基盤研究（B)(2)研究成果報告書, 研究代表者：村本, 健一郎, 金沢大学自然科学研究科教

Improving Carbon Mitigation Potential through Grassland Ecosystem Restoration under Climatic Change in Northeastern Tibetan Plateau

To protect the water tower’s ecosystem environment and conserve biodiversity, China has been implementing a huge payment program for ecosystem services in the three rivers source region. We explored here the dynamics of grassland degradation and restoration from 1990 to 2012 and its relationships with climate mitigation in the TRSR to provide a definite answer as to the forcing and response of grassland degradation and restoration to climate change. Then we estimated its potential of climate mitigation benefits to address the question of whether ecological restoration could be effective in reversing the decline of ecosystem carbon mitigation service. The trend of average annual temperature and precipitation observed by meteorological stations were approximately increased. Compared before and after 2004, the area of grassland degradation was increased slightly. However, nearly one-third of degraded grassland showed improvement, and the grassland vegetation coverage showed significant increase. Comparing current grassland vegetation coverage with healthy vegetation cover with the same grass type, nearly half of the area still needs to further restore vegetation cover. The grassland degradation resulted in significant carbon emissions, but the restoration to its healthy status has been estimated to be technical mitigation potential

Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar

Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns

Using vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings

A novel seam detection approach based on vector building maps is presented for low-attitude aerial orthoimage mosaicking. The approach tracks the centerlines between vector buildings to generate the candidate seams that avoid crossing buildings existing in maps. The candidate seams are then refined by considering their surrounding pixels to minimize the visual transition between the images to be mosaicked. After the refinement of the candidate seams, the final seams further bypass most of the buildings that are not updated into vector maps. Finally, three groups of aerial imagery from different urban densities are employed to test the proposed approach. The experimental results illustrate the advantages of the proposed approach in avoiding the crossing of buildings. The computational efficiency of the proposed approach is also significantly higher than that of Dijkstra’s algorithm