Abstract and Applied Analysis

Algorithms and Applications in Grass Growth Monitoring

Jun Liu, Xi Yang, Hao Long Liu, and Zhi Qiao

Full-text: Open access

Abstract

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.

Article information

Source
Abstr. Appl. Anal., Volume 2013, Special Issue (2013), Article ID 508315, 7 pages.

Dates
First available in Project Euclid: 26 February 2014

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1393449784

Digital Object Identifier
doi:10.1155/2013/508315

Citation

Liu, Jun; Yang, Xi; Liu, Hao Long; Qiao, Zhi. Algorithms and Applications in Grass Growth Monitoring. Abstr. Appl. Anal. 2013, Special Issue (2013), Article ID 508315, 7 pages. doi:10.1155/2013/508315. https://projecteuclid.org/euclid.aaa/1393449784


Export citation