Next Article in Journal
Hyperspectral Unmixing with Robust Collaborative Sparse Regression
Next Article in Special Issue
Assessment of Automated Snow Cover Detection at High Solar Zenith Angles with PROBA-V
Previous Article in Journal
Surface Energy Balance of Fresh and Saline Waters: AquaSEBS
Previous Article in Special Issue
PROBA-V Mission Exploitation Platform
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Remote Sens. 2016, 8(7), 585;

Crop Area Mapping Using 100-m Proba-V Time Series

Vlaamse Instelling voor Technologisch Onderzoek (VITO), Boeretang 200, B-2400 Mol, Belgium
Département Sciences et Gestion de l’Environnement, Université de Liège, Avenue de Longwy 185, 6700 Arlon, Belgium
Author to whom correspondence should be addressed.
Academic Editors: Clement Atzberger, Magda Chelfaoui and Prasad S. Thenkabail
Received: 25 April 2016 / Revised: 30 June 2016 / Accepted: 5 July 2016 / Published: 11 July 2016
Full-Text   |   PDF [3194 KB, uploaded 11 July 2016]   |  


A method was developed for crop area mapping inspired by spectral matching techniques (SMTs) and based on phenological characteristics of different crop types applied using 100-m Proba-V NDVI data for the season 2014–2015. Ten-daily maximum value NDVI composites were created and smoothed in SPIRITS ( The study sites were globally spread agricultural areas located in Flanders (Belgium), Sria (Russia), Kyiv (Ukraine) and Sao Paulo (Brazil). For each pure pixel within the field, the NDVI profile of the crop type for its growing season was matched with the reference NDVI profile based on the training set extracted from the study site where the crop type originated. Three temporal windows were tested within the growing season: green-up to senescence, green-up to dormancy and minimum NDVI at the beginning of the growing season to minimum NDVI at the end of the growing season. Post classification rules were applied to the results to aggregate the crop type at the plot level. The overall accuracy (%) ranged between 65 and 86, and the kappa coefficient changed from 0.43–0.84 according to the site and the temporal window. In order of importance, the crop phenological development period, parcel size, shorter time window, number of ground-truth parcels and crop calendar similarity were the main reasons behind the differences between the results. The methodology described in this study demonstrated that 100-m Proba-V has the potential to be used in crop area mapping across different regions in the world. View Full-Text
Keywords: 100-m Proba-V; crop area mapping; spectral matching techniques (SMTs); phenology; time series 100-m Proba-V; crop area mapping; spectral matching techniques (SMTs); phenology; time series

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).

Share & Cite This Article

MDPI and ACS Style

Durgun, Y.Ö.; Gobin, A.; Van De Kerchove, R.; Tychon, B. Crop Area Mapping Using 100-m Proba-V Time Series. Remote Sens. 2016, 8, 585.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



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