دورية أكاديمية

Contribution of multispectral (optical and radar) satellite images to the classification of agricultural surfaces

التفاصيل البيبلوغرافية
العنوان: Contribution of multispectral (optical and radar) satellite images to the classification of agricultural surfaces
المؤلفون: C. Marais Sicre, R. Fieuzal, F. Baup
المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 84, Iss , Pp 101972- (2020)
بيانات النشر: Elsevier, 2020.
سنة النشر: 2020
المجموعة: LCC:Physical geography
LCC:Environmental sciences
مصطلحات موضوعية: Agriculture, Classification, Random Forest, Land use and land cover, Optical, Radar, Physical geography, GB3-5030, Environmental sciences, GE1-350
الوصف: The monitoring of different crops (cultivated plots) and types of surface (bare soils, etc.) is a crucial economic and environmental issue for the management of resources and human activity. In this context, the objective of this study is to evaluate the contribution of multispectral satellite imagery (optical and radar) to land use and land cover classification.Object-oriented supervised classifications, based on a Random Forest algorithm, and majority zoning post-processing are used. This study emerges from the experiment on multi-sensor crop monitoring (MCM'10, Baup et al., 2012) conducted in 2010 on a mixed farming area in the southwest of France, near Toulouse. This experiment enabled the regular and quasi-synchronous collection of multi-sensor satellite data and in situ observations, which are used in this study. 211 plots with contrasting characteristics (different slopes, soil types, aspects, farming practices, shapes and surface areas) were monitored to represent the variability of the study area. They can be grouped into four classes of land cover: 39 grassland areas, 100 plots of wheat, 13 plots of barley, 20 plots of rapeseed, and 2 classes of bare soil: 23 plots of small roughness and 16 plots of medium roughness. Satellite radar images in the X-, C- and L-bands (HH polarization) were acquired between 14 and 18 April 2010. Optical images delivered by Formosat-2 and corresponding field data were acquired on 14 April 2010.The results show that combining images acquired in the L-band (Alos) and the optical range (Formosat-2) improves the classification performance (overall accuracy = 0.85, kappa = 0.81) compared to the use of radar or optical data alone. The results obtained for the various types of land cover show performance levels and confusions related to the phenological stage of the species studied, with the geometry of the cover, the roughness states of the surfaces, etc. Performance is also related to the wavelength and penetration depth of the signal providing the images. Thus, the results show that the quality of the classification often increases with increasing wavelength of the images used.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1569-8432
Relation: http://www.sciencedirect.com/science/article/pii/S0303243418308948; https://doaj.org/toc/1569-8432
DOI: 10.1016/j.jag.2019.101972
URL الوصول: https://doaj.org/article/83ec64216efa4e338376645e731ef662
رقم الأكسشن: edsdoj.83ec64216efa4e338376645e731ef662
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15698432
DOI:10.1016/j.jag.2019.101972