Next Article in Journal
Operational Actual Wetland Evapotranspiration Estimation for South Florida Using MODIS Imagery
Previous Article in Journal
Automated Extraction of Archaeological Traces by a Modified Variance Analysis
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(4), 3588-3612; doi:10.3390/rs70403588

Detecting Clear-Cuts and Decreases in Forest Vitality Using MODIS NDVI Time Series

1
Université de Toulouse, INPT, Ecole d'Ingénieurs de Purpan, UMR 1201 Dynafor, 75 Voie du TOEC, F-31076 Toulouse Cedex 03, France
2
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands
3
INRA, UMR 1201 Dynafor, F-31326 Castanet-Tolosan, France
*
Authors to whom correspondence should be addressed.
Academic Editors: Lars T. Waser, Josef Kellndorfer and Prasad S. Thenkabail
Received: 15 October 2014 / Revised: 21 November 2014 / Accepted: 27 February 2015 / Published: 26 March 2015
View Full-Text   |   Download PDF [4718 KB, uploaded 1 April 2015]   |  

Abstract

This paper examines the potential of MODIS-NDVI time series for detecting clear-cuts in a coniferous forest stand in the south of France. The proposed approach forms part of a survey monitoring the status of forest health and evaluating the forest decline phenomena observed over the last few decades. One of the prerequisites for this survey was that a rapid and easily reproducible method had to be developed that differentiates between forest clear-cuts and changes in forest health induced by environmental factors such as summer droughts. The proposed approach is based on analysis of the breakpoints detected within NDVI time series, using the “Break for Additive Seasonal and Trend” (BFAST) algorithm. To overcome difficulties detecting small areas on the study site, we chose a probabilistic approach based on the use of a conditional inference tree. For model calibration, clear-cut reference data were produced at MODIS resolution (250 m). According to the magnitude of the detected breakpoints, probability classes for the presence of clear-cuts were defined, from greater than 90% to less than 3% probability of a clear-cut. One of the advantages of the probabilistic model is that it allows end users to choose an acceptable level of uncertainty depending on the application. In addition, the use of BFAST allows events to be dated, thus making it possible to perform a retrospective analysis of decreases in forest vitality in the study area. View Full-Text
Keywords: time series; MODIS; NDVI; BFAST; forest decline; clear-cut detection time series; MODIS; NDVI; BFAST; forest decline; clear-cut detection
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Lambert, J.; Denux, J.-P.; Verbesselt, J.; Balent, G.; Cheret, V. Detecting Clear-Cuts and Decreases in Forest Vitality Using MODIS NDVI Time Series. Remote Sens. 2015, 7, 3588-3612.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top