Estimation of Above-ground Biomass Carbon Storage in Hulunbeier Grassland based on Remotely Sensed Data

文献类型: 外文期刊

第一作者: Hasituya

作者: Hasituya;Chen Zhong-xin;Wu Wen-bin;Huang, Qing;Hasituya;Chen Zhong-xin;Wu Wen-bin;Huang, Qing

作者机构:

关键词: Above-ground Biomass Carbon Storage;Remote Sensing;CASA Model;Plant Mortality Model;Hulunbeier Grassland

期刊名称:2015 FOURTH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS

ISSN: 2334-3168

年卷期: 2015 年

页码:

收录情况: SCI

摘要: Grassland biomass carbon storage is one of the most important parts in regulating the carbon cycle and mitigating the global climate change. However, due to the vulnerability and sensibility of grassland in arid and semi-arid regions, grassland degradation and desertification are becoming increasingly serious, and there exist doubt for the carbon source/ sink relationship in grassland ecosystem. To estimate the grassland biomass carbon storage is an important task for the research of carbon cycling and rational utilization of grassland resources. In this paper, based on the purpose of providing local scale information for related study and decision making, MODIS-NDVI and meteorological data in plant growing season (April to September) were used for CASA (Carnegie-Ames-Stanford Approach) Model and Plant Mortality Model to estimate the above-ground biomass carbon storage in Hulunbeier grassland, Inner Mongolia Autonomous Region, China in 2002, 2005, and 2009 respectively. And analyze its spatial and temporal patterns. The results show that the total above-ground biomass carbon storage derived from the above two model were 4.95Tg, 4.53Tg, 4.80Tg (1Tg = 1x10(12)g) and the average carbon density were 43.41, 39.69, 41.36g/m(2) respectively in 2002, 2005 and 2009. The results imply that these two models can provide effective information for the carbon storage estimation and grassland resources management in this research area.

分类号:

  • 相关文献

[1]Flower Species Identification and Coverage Estimation Based on Hyperspectral Remote Sensing Data in Hulunbeier Grassland. Gai Ying-ying,Fan Wen-jie,Xu Xi-ru,Yan Bin-yan,Liu Yuan,Gai Ying-ying,Wang Huan-jiong,Wang Huan-jiong. 2011

[2]Modeling net primary productivity of terrestrial ecosystems in the semi-arid climate of the Mongolian Plateau using LSWI-based CASA ecosystem model. Bao, Gang,Bao, Yuhai,Bao, Yulong,Bao, Gang,Bao, Yulong,Qin, Zhihao,Xin, Xiaoping,Bayarsaikan, Sainbuyin,Zhou, Yi,Chuntai, Bilegtmandakh. 2016

[3]Impacts of urbanization on net primary productivity in the Pearl River Delta, China. Jiang, C.,Wu, Z. F.,Jiang, C.,Cheng, J.,Yu, Q.,Jiang, C.,Rao, X. Q.. 2015

[4]Optimization of Maximum Light Use Efficiency in Inner Mongolian Steppe. Bao Gang,Xin Xiao-ping,Bao Gang,Bao Yu-hai,Wang Mu-lan,Yuan Zhi-hui,Wang Mu-lan,Yuan Zhi-hui,Wulantuya. 2016

[5]Evaluating and Classifying Field-Scale Soil Nutrient Status in Beijing using 3S Technology. Xue, Yong-An,Huang, Lin-Sheng,Zhang, Dong-Yan,Zhao, Jin-Ling,Yang, Hao. 2012

[6]Monitoring of Rapid Urban Sprawl in Beijing with Time Series Remote Sensing Data and Analysis of Driving Forces. Zhao, Jinling,Yang, Yao,Zhang, Dongyan,Huang, Linsheng. 2013

[7]Integrating Remotely Sensed and Meteorological Observations to Forecast Wheat Powdery Mildew at a Regional Scale. Zhang, Jingcheng,Nie, Chenwei,Yang, Guijun,Pu, Ruiliang,Yuan, Lin,Huang, Wenjiang. 2014

[8]Development of a web temporal-spatial information application for main crops based on integration of remote sensing and crop model. Yang Xiaodong,Xu Xingang,Gu Xiaohe,Yang Hao,Yu Haiyang,Yang Fuzeng. 2014

[9]Survey of Support Vector Machine in the Processing of Remote Sensing Image. Li, Su,Wang, Wenchao. 2013

[10]Quick image processing method of HJ satellites applied in agriculture monitoring. Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong,Yu Haiyang,Liu Yanmei,Yang Guijun,Yang Xiaodong. 2016

[11]Agricultural crop harvest progress monitoring by fully polarimetric synthetic aperture radar imagery. Yang, Hao,Zhao, Chunjiang,Yang, Guijun,Yuan, Lin,Yang, Xiaodong,Xu, Xingang,Yang, Hao,Li, Zengyuan,Chen, Erxue. 2015

[12]Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM plus Thermal Infrared Images. Ling, Feng,Ban, Xuan,Li, Xiaodong,Zhang, Yihang,Du, Yun,Foody, Giles M.,Du, Hao. 2017

[13]Remote-Sensing Based Winter Wheat Growth Dynamic Changes and the Spatial-Temporal Relationship with Meteorological Factor. Huang Qing,Zhou Qingbo,Wu Wenbin,Li Dandan. 2014

[14]The Effect of Vegetation on the Remotely Sensed Soil Thermal Inertia and a Two-Source Normalized Soil Thermal Inertia Model for Vegetated Surfaces. Zhang, Renhua,Tian, Jing,Mi, Sujuan,Su, Hongbo,Liu, Kai,Mi, Sujuan,Liu, Kai,Su, Hongbo,He, Honglin,Li, Zhaoliang. 2016

[15]Satellite Observations on Agricultural Adaptation to Drought in Southwestern China. Dong, Yansheng,Li, Cunjun,Chen, Hongping. 2012

[16]Spatial decision supporting for winter wheat irrigation and fertilizer optimizing in North China Plain. Yang Xiaodong,Yang Hao,Dong Yansheng,Yu Haiyang. 2014

[17]EVALUATION OF ARABLE LAND YIELD POTENTIAL THROUGH REMOTE SENSING MONITORING. Song Xiaoyu,Gu Xiaohe,Chang Hong. 2014

[18]Design and implementation of remote sensing extraction system of rural circulation land. Peng Cheng,Wu Hua-rui,Zhu Hua-ji. 2014

[19]Assessing the Soil Fertility using Landsat TM Imagery and Geospatial Statistical Analysis. Zhao, Jinling,Wang, Dacheng,Zhang, Dongyan,Luo, Juhua,Huang, Wenjiang. 2012

[20]SPATIAL VARIABILITY OF WINTER WHEAT GROWTH BASED ON THE INDIVIDUAL INDEX AND THE POPULATION INDEX. Cui, Bei,Song, Xiaoyu,Feng, Meichen. 2014

作者其他论文 更多>>