Next Article in Journal
Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring
Previous Article in Journal
Derivation of High-Resolution Bathymetry from Multispectral Satellite Imagery: A Comparison of Empirical and Optimisation Methods through Geographical Error Analysis
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(12), 16274-16292;

Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

Facultad de Ingenierías, Universidad de Medellín, Carrera 87 Nro. 30–65, Medellín 050026, Colombia
National Commission for the Knowledge and Use of Biodiversity (CONABIO), Av. Liga Periférico-Insurgentes Sur 4903, Parques del Pedregal, Tlalpan 14010, Ciudad de México, D.F., Mexico
Facultad de Ingenierías, Universidad de San Buenaventura, Carrera 56C Nro. 51-90, Medellín 050010, Colombia
Author to whom correspondence should be addressed.
Academic Editors: Parth Sarathi Roy and Prasad S. Thenkabail
Received: 9 July 2015 / Revised: 22 October 2015 / Accepted: 5 November 2015 / Published: 3 December 2015
Full-Text   |   PDF [3441 KB, uploaded 3 December 2015]   |  


Generating annual land cover maps in the tropics based on optical data is challenging because of the large amount of invalid observations resulting from the presence of clouds and haze or high moisture content in the atmosphere. This study proposes a strategy to build an annual time series from multi-year data to fill data gaps. The approach was tested using the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index and spectral bands as input for land cover classification of Colombia. In a second step, selected ancillary variables, such as elevation, L-band Radar, and precipitation were added to improve overall accuracy. Decision-tree classification was used for assigning eleven land cover classes using the International Geosphere-Biosphere Programme (IGBP) legend. Maps were assessed by their spatial confidence derived from the decision tree approach and conventional accuracy measures using reference data and statistics based on the error matrix. The multi-year data integration approach drastically decreased the area covered by invalid pixels. Overall accuracy of land cover maps significantly increased from 58.36% using only optical time series of 2011 filtered for low quality observations, to 68.79% when using data for 2011 ± 2 years. Adding elevation to the feature set resulted in 70.50% accuracy. View Full-Text
Keywords: quality assessment; time series; tree classifiers; land cover quality assessment; time series; tree classifiers; land cover

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

Anaya, J.A.; Colditz, R.R.; Valencia, G.M. Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series. Remote Sens. 2015, 7, 16274-16292.

Show more citation formats Show less citations formats

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