Estimating vegetation phenological trends using MODIS NDVI time series

Markus Törmä; Mikko Kervinen; Saku Anttila

doi:10.1117/12.898062

26 October 2011 Estimating vegetation phenological trends using MODIS NDVI time series

Markus Törmä, Mikko Kervinen, Saku Anttila

Proceedings Volume 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II; 81810P (2011) https://doi.org/10.1117/12.898062
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

The method to extract phenological information for different land cover types is presented. Phenological features are two different start dates of growing season, date of maximum growth, end of growing season and two growing season lengths. Also, quality indicators are estimated for some phenological features. The method is based on NDVI-time series extracted from MODIS-images. The errors between extracted dates and in-situ measurements are reasonably small. For example, the residuals of the estimation of the start of Flux Growing Season are on only 2 days for broadleaf forest in one Southern Finland hydrological drainage basin. The method has been tested on Northern Boreal forest zone, where there are freezing temperatures and snow during winter.

Citation Download Citation

Markus Törmä, Mikko Kervinen, and Saku Anttila "Estimating vegetation phenological trends using MODIS NDVI time series", Proc. SPIE 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II, 81810P (26 October 2011); https://doi.org/10.1117/12.898062

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available