Abstract

The black-odor water has significant negative impacts on the sustainable development of society and survival of mankind. The paper presents a new Urban Black-Odor Water (UBOW) model to identify the urban black-odor water body from high-resolution remote sensing image Gaofen-2(GF-2), to help monitor and control urban black-odor water bodies. The new UBOW model is derived from the analysis of the in-situ observation data and the spectral characteristics of GF-2. It takes advantage of the spectral difference at the blue band, the green band and the red band and has certain theoretical ground. The UBOW model can effectively identify the severe black-odor water and the mild black-odor water. The model is validated by the observation and the overall accuracy can be up to 81%. The UBOW model is used to analyze the dynamics of the urban black-odor water bodies of Beijing China, with monthly GF-2 images from March 2017 to October 2018. Results show that the urban black-odor water bodies, whether it is mild black-odor water bodies or severe black-odor water bodies, have been reduced significantly, which is consistent with the governmental report. This confirms that the Beijing government takes effective measurements to remedy the urban black-odor water bodies.

Details

Title
Urban black-odor water body dynamic analysis with high-resolution remote sensing image
Author
Zhang, Q 1 ; Wang, B W 2 ; Wang, S F 3 ; Guo, T 1 

 Beijing PIESAT Information Technology Co., Ltd. Haidian District, Beijing, 100195, China 
 Beijing National Day School, Haidian District, Beijing, 100039, China 
 Beijing PIESAT Information Technology Co., Ltd. Haidian District, Beijing, 100195, China; School of Engineering, Newcastle University, Newcastle, UK 
Publication year
2019
Publication date
Oct 2019
Publisher
IOP Publishing
ISSN
17551307
e-ISSN
17551315
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2558002022
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.