Agritrop
Home

A remote sensing approach for regional-scale mapping of agricultural land-use systems based on NDVI time series

Bellon De La Cruz Beatriz, Bégué Agnès, Lo Seen Danny, Aparecido de Almeida Claudio, Simoes Margareth. 2017. A remote sensing approach for regional-scale mapping of agricultural land-use systems based on NDVI time series. Remote Sensing, 9 (6):600, 17 p.

Journal article ; Article de recherche ; Article de revue à facteur d'impact Revue en libre accès total
[img]
Preview
Published version - Anglais
License CC0 1.0 Public Domain Dedication.
remotesensing-09-00600.pdf

Télécharger (5MB) | Preview

Quartile : Q2, Sujet : REMOTE SENSING

Abstract : In response to the need for generic remote sensing tools to support large-scale agricultural monitoring, we present a new approach for regional-scale mapping of agricultural land-use systems (ALUS) based on object-based Normalized Difference Vegetation Index (NDVI) time series analysis. The approach consists of two main steps. First, to obtain relatively homogeneous land units in terms of phenological patterns, a principal component analysis (PCA) is applied to an annual MODIS NDVI time series, and an automatic segmentation is performed on the resulting high-order principal component images. Second, the resulting land units are classified into the crop agriculture domain or the livestock domain based on their land-cover characteristics. The crop agriculture domain land units are further classified into different cropping systems based on the correspondence of their NDVI temporal profiles with the phenological patterns associated with the cropping systems of the study area. A map of the main ALUS of the Brazilian state of Tocantins was produced for the 2013–2014 growing season with the new approach, and a significant coherence was observed between the spatial distribution of the cropping systems in the final ALUS map and in a reference map extracted from the official agricultural statistics of the Brazilian Institute of Geography and Statistics (IBGE). This study shows the potential of remote sensing techniques to provide valuable baseline spatial information for supporting agricultural monitoring and for large-scale land-use systems analysis. (Résumé d'auteur)

Mots-clés Agrovoc : Télédétection, Analyse d'image, Analyse en composantes (statist), Système de culture, Stratification, Cartographie de l' utilisation des terres, Système d'information géographique, Couverture végétale, Terre agricole, Utilisation des terres, Plante de culture, Agriculture, Élevage

Mots-clés géographiques Agrovoc : Brésil

Classification Agris : U30 - Research methods
F01 - Crops
L01 - Animal husbandry
B10 - Geography
P31 - Soil surveys and mapping
U10 - Computer science, mathematics and statistics

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Bellon De La Cruz Beatriz, CIRAD-ES-UMR TETIS (FRA)
  • Bégué Agnès, CIRAD-ES-UMR TETIS (FRA)
  • Lo Seen Danny, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0002-7773-2109
  • Aparecido de Almeida Claudio, INPE (BRA)
  • Simoes Margareth, EMBRAPA (BRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/584881/)

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2021-02-27 ]