干旱区生态环境知识资源中心(Arid): 利用遥感数据优化物候模型时样本选择的新方法

Arid

	利用遥感数据优化物候模型时样本选择的新方法
其他题名	A new method of sample selections for optimizing phenology model based remote sensing data
	马勇刚; 张弛; 陈曦
来源期刊	植物生态学报
ISSN	1005-264X
出版年	2015
卷号	39 期号:3 页码:264-274
中文摘要	植被物候模型是生态系统模型的重要组成部分, 其精度对准确地模拟陆面和大气之间的能量和物质交换具有重要意义。利用遥感获取空间物候信息并与气候数据进行耦合分析是在中亚干旱区等地面物候观测数据缺乏的地区构建物候模型的重要方法。为减小混合植被像元和气候数据资料的内在误差及二者在空间尺度的不匹配对物候模型构建产生的影响, 该研究提出一种在气象站点周围选取满足规定规则集的代表植被类型像元作为样本点的选择方法, 以代表植被类型像元的遥感物候数据和气象站点数据为基础, 结合经典物候模型和改进物候模型, 在粒子群优化算法支持下, 分别以独立的拟合与评价样本数据, 完成了荒漠草原植被与落叶阔叶林的模型拟合与评价。研究发现中亚干旱区荒漠草原植被的最优模型为温度-降水修正模型, 落叶阔叶林的最优模型为替代模型。通过此方法模型总体精度在8-10 d左右。结果表明此方法在气候数据和植物物候空间匹配方面有改进, 有助于提高物候模型精度。
英文摘要	Aims Phenology model is considered as the most efficient tool to assess the phonological responses of plants to future climate change. Furthermore, as an important component in dynamic ecological models, the performance of phenology model is of significance for the precision in simulating mass and energy exchanges between land and atmosphere. Combining long time series remote sensing data and climate data to construct regional phenology model may be the only way to solve the problem of deficiency in lacking in-situ observational data on phenology and species-specific phenology models. The objective of this study was to develop a new method of sample selections for constructing phenology in the arid zone of Central Asia where only sparse observational data are available. Methods Based the phenology data retrieved from 250 m-resolution MODIS images for the period 2000-2010, a new method is developed for constructing the vegetation phenology model in arid zone. A set of rules were built to select the representative pixels of PFTs (plant function types) surrounding the climate station, making sure that the climate of the representative pixels of PFTs could be represented by the observed meteorological data at the station, and then the phenology data on the representative pixels of PFTs were extracted from the MODIS images and the corresponding climatic data were set as the sample for model fitting and assessment. Forty-six representative pixels of PFTs for desert grassland vegetation and broadleaved deciduous forests were selected under the rules. The phenology model parameters were estimated using data from odd-numbered years and the simulation accuracy was assessed with the independent even-year data. Particle swarm optimization algorithm was used to parameterize the pre-selected model. The root-mean-square error and coefficient of determination were used to examine the performance of model with independent data. Important findings The best model for desert steppe vegetation was the modified temperature-precipitation model and the best model for deciduous broadleaved forest was the alternative model. Compared with other documented findings, the new method was proven feasible, and the results also suggested that this new method may improve the spatial match of climatic data and vegetation phenology data, and therefore contribute to improvement of the phenology model accuracy.
中文关键词	干旱区 ; 物候模型 ; 遥感 ; 中亚
英文关键词	arid zone phenology model remote sensing Central Asia
语种	中文
国家	中国
收录类别	CSCD
WOS类目	BIOLOGY
WOS研究方向	Life Sciences & Biomedicine - Other Topics
CSCD记录号	CSCD:5377969
来源机构	中国科学院新疆生态与地理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/233626
作者单位	中国科学院新疆生态与地理研究所, 荒漠与绿洲生态国家重点实验室, 乌鲁木齐, 新疆 830011, 中国
推荐引用方式 GB/T 7714	马勇刚,张弛,陈曦. 利用遥感数据优化物候模型时样本选择的新方法[J]. 中国科学院新疆生态与地理研究所,2015,39(3):264-274.
APA	马勇刚,张弛,&陈曦.(2015).利用遥感数据优化物候模型时样本选择的新方法.植物生态学报,39(3),264-274.
MLA	马勇刚,et al."利用遥感数据优化物候模型时样本选择的新方法".植物生态学报 39.3(2015):264-274.