中国科学院东北地理与农业生态研究所机构知识库
Advanced  
NEIGAE OpenIR  > 湿地与全球变化学科组  > 期刊论文
Title: Remote estimation of K-d (PAR) using MODIS and Landsat imagery for turbid inland waters in Northeast China
Author: K. S. Song, J. H. Ma, Z. D. Wen, C. Fang, Y. X. Shang, Y. Zhao, M. Wang and J. Du
Corresponding Author: 宋开山
Source: Isprs Journal of Photogrammetry and Remote Sensing
Issued Date: 2017
DOI: 10.1016/j.isprsjprs.2016.11.010
Volume: 123, Pages:159-172
Abstract: Light availability for photosynthetically active radiation (PAR) is one of the major factors governing photosynthesis in aquatic ecosystems. Conventional measurements of light attenuation in the PAR domain (K-d(PAR)) is representative for only small areas of water body. Remotely sensed optical imagery can be utilized to monitor K-d(PAR) in large areas of water bodies, based on the relationship between water leaving radiance and K-d(PAR). In this study, six field surveys were conducted over 20 lakes (or reservoirs) across Northeast China from April to September 2015. In order to derive the K-d(PAR) at regional scale, the Landsat/TM/ETM+/OLI and the MODIS daily surface reflectance data (MOD09GA similar to 500 m, Bands 17) were used to establish empirical inversion models. Through multiple stepwise regression analysis, the band difference (Red-Blue) and band ratio (NIR/Red) were used in Landsat imagery modeling, and the band difference (Red-Blue) and ratio (Red/Blue) were used in MODIS imagery modeling. The accuracy of the two models was evaluated by 10-fold cross-validation in ten times. The results indicate that the models performed well for both Landsat (R-2 = 0.83, RMSE = 0.95, and MRE = 0.33), and MODIS (R-2 = 0.86, RMSE = 0.91, and MRE = 0.19) imagery. However, the K-d(PAR) derived by MODIS is slightly higher than that estimated by Landsat (slope = 1.203 and R-2 = 0.972). Consistency of model performance between the MODIS daily (MYDO9G A) and the 8-Day composite reflectance (MYDO9A1) data was verified by K-d(PAR) estimations and regression analysis (slope = 1.044 and R-2 = 0.966). Finally, the spatial and temporal distribution of K-d(PAR) in Northeast China indicated that specific geographical characteristics as well as meteorological alterations can influence K-d(PAR) calibrations. Specifically, we have revealed that the wind speed and algal bloom are the major determinants of K-d(PAR) in Lake Hulun (2050 km(2)) and Xingkai (4412 km(2)). (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iga.ac.cn/handle/131322/7538
Appears in Collections:湿地与全球变化学科组_期刊论文

Files in This Item:

There are no files associated with this item.

Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[K. S. Song, J. H. Ma, Z. D. Wen, C. Fang, Y. X. Shang, Y. Zhao, M. Wang and J. Du]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[K. S. Song, J. H. Ma, Z. D. Wen, C. Fang, Y. X. Shang, Y. Zhao, M. Wang and J. Du]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Powered by CSpace