Algorithms and Applications in Grass Growth Monitoring
Joint Authors
Yang, Xi
Qiao, Zhi
Liu, Hao Long
Liu, Jun
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-18
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Monitoring vegetation phonology using satellite data has been an area of growing research interest in recent decades.
Validation is an essential issue in land surface phenology study at large scale.
In this paper, double logistic function-fitting algorithm was used to retrieve phenophases for grassland in North China from a consistently processed Moderate Resolution Spectrodiometer (MODIS) dataset.
Then, the accuracy of the satellite-based estimates was assessed using field phenology observations.
Results show that the method is valid to identify vegetation phenology with good success.
The phenophases derived from satellite and observed on ground are generally similar.
Greenup onset dates identified by Normalized Difference Vegetation Index (NDVI) and in situ observed dates showed general agreement.
There is an excellent agreement between the dates of maturity onset determined by MODIS and the field observations.
The satellite-derived length of vegetation growing season is generally consistent with the surface observation.
American Psychological Association (APA)
Liu, Jun& Yang, Xi& Liu, Hao Long& Qiao, Zhi. 2013. Algorithms and Applications in Grass Growth Monitoring. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-477217
Modern Language Association (MLA)
Liu, Jun…[et al.]. Algorithms and Applications in Grass Growth Monitoring. Abstract and Applied Analysis No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-477217
American Medical Association (AMA)
Liu, Jun& Yang, Xi& Liu, Hao Long& Qiao, Zhi. Algorithms and Applications in Grass Growth Monitoring. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-477217
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-477217