Special Issue "Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011)"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 June 2013)
Prof. Ranga B. Myneni
Department of Geography & Environment, Boston University, Boston, MA 20115, USA
Interests: remote sensing of vegetation; satellite data analysis; radiative transfer in vegetative media; algorithms for biophysical variables from satellite data; climate/vegetation interactions; terrestrial carbon cycle
Dr. Jorge E. Pinzón
Science Systems and Applications, Inc., Code 618, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Phone: +301 614 6685
Fax: +301 614 6695
Interests: feature extraction from large geophysical temporal, multi- and hyper-spectral data; quality assurance and calibration of geophysical observations; image analysis, image compression, image classification; remote sensing applications for monitoring eco-climatic conditions associated with emerging infectious diseases
Vegetation indices are radiometric measures of photosynthetically active radiation absorbed by chlorophyll in the green leaves of vegetation canopies and are therefore good surrogate measures of the physiologically functioning surface greenness level of a region. In a series of articles during the early 1980s, Compton J. Tucker, demonstrated how the Normalized Difference Vegetation Index (NDVI) generated from NOAA’s Advanced Very High Resolution Radiometer (AVHRR) data can be used to map land cover and monitor vegetation changes and desertification at continental and global scales. These papers opened a whole new avenue of investigations regarding monitoring vegetation changes at a host of spatial resolutions and time scales. A simple search on the Web of Science reveals over 5000 articles containing NDVI either in the title or in the abstract. Compton J. Tucker continued to generate the NDVI time series over the past 30 years, in the framework of the Global Inventory Monitoring and Modeling System (GIMMS) project, carefully assembling it from different AVHRR sensors and accounting for various deleterious effects, such as calibration loss, orbital drift, volcanic eruptions, etc. The latest version of the GIMMS NDVI data set spans the period July 1981 to December 2011 and is termed NDVI3g (third generation GIMMS NDVI from AVHRR sensors). The goal of this special issue is to understand variability, long-term trends and changes in vegetation on our planet at a host of spatial scales over the past 30 years using this new, improved data set. Although the NDVI3g data set has not yet been released, scientists interested in contributing to this special issue are encouraged to contact the guest editors with a tentative title and two-line abstract to obtain access to the data set. The following is a tentative list of papers to appear in this special issue.
Prof. Ranga B. Myneni
Dr. Jorge E. Pinzón
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.
- remote sensing
- vegetation trends
- climate change
- arctic vegetation
- sahelian vegetation
- land degradation
- carbon cycle
- dynamics vegetation models