DOI: 10.1016/j.jag.2014.09.004
Scopus记录号: 2-s2.0-84924416776
论文题名: Dynamic simulation of vegetation abundance in a reservoir riparianzone using a sub-pixel markov model
作者: Gong Z ; , Cui T ; , Pu R ; , Lin C ; , Chen Y
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 35, 期: PB 起始页码: 175
结束页码: 186
语种: 英语
英文关键词: LSMA
; Reservoir riparian zone
; Sub-pixel markov
; Vegetation abundance
Scopus关键词: abundance
; Landsat thematic mapper
; Markov chain
; pixel
; plant community
; riparian zone
; satellite imagery
; vegetation dynamics
英文摘要: Vegetation abundance is a significant indicator for measuring the coverage of plant community. It is alsoa fundamental data for the evaluation of a reservoir riparian zone eco-environment. In this study, a sub-pixel Markov model was introduced and applied to simulate dynamics of vegetation abundance in theGuanting Reservoir Riparian zone based on seven Landsat Thematic Mapper/Enhanced Thematic MapperPlus/Operational Land Imager data acquired between 2001 and 2013. Our study extended Markov model'sapplication from a traditional regional scale to a sub-pixel scale. Firstly, Linear Spectral Mixture Analysis(LSMA) was used to obtain fractional images with a five-endmember model consisting of terrestrialplants, aquatic plants, high albedo, low albedo, and bare soil. Then, a sub-pixel transitive probabilitymatrix was calculated. Based on the matrix, we simulated statuses of vegetation abundance in 2010and 2013, which were compared with the results created by LSMA. Validations showed that there wereonly slight differences between the LSMA derived results and the simulated terrestrial plants fractionalimages for both 2010 and 2013, while obvious differences existed for aquatic plants fractional images, which might be attributed to a dramatically diversity of water level and water discharge between 2001and 2013. Moreover, the sub-pixel Markov model could lead to an RMSE (Root Mean Square Error) of0.105 and an R2 of 0.808 for terrestrial plants, and an RMSE of 0.044 and an R2 of 0.784 for aquatic plantsin 2010. For the simulated results with the 2013 image, an RMSE of 0.126 and an R2 of 0.768 could beachieved for terrestrial plants, and an RMSE of 0.086 and an R2 of 0.779 could be yielded for aquatic plants. These results suggested that the sub-pixel Markov model could yield a reasonable result in a short period. Additionally, an analysis of dynamics of vegetation abundance from 2001 to 2020 indicated that thereexisted an increasing trend for the average fractional value of terrestrial plants and a decreasing trendfor aquatic plants. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79605
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: College of Resource Environment and Tourism, Capital Normal University, Beijing, China; Key Laboratory of 3D Information Acquisition, Application of Ministry of Education, Beijing, China; Key Laboratory of Resources Environment, GIS of Beijing Municipal, Beijing, China; Base of the State Laboratory of Urban Environmental Processes and Digital Modeling, Beijing, China; School of Geosciences, University of South Florida, Tampa, United States
Recommended Citation:
Gong Z,, Cui T,, Pu R,et al. Dynamic simulation of vegetation abundance in a reservoir riparianzone using a sub-pixel markov model[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,35(PB)