Forest Land Cover Mapping at a Regional Scale Using Multi-Temporal Sentinel-2 Imagery and RF Models

Laura Alonso,Juan Picos,Julia Armesto

doi:10.3390/rs13122237

Abstract

Over the last several decades, thanks to improvements in and the diversification of open-access satellite imagery, land cover mapping techniques have evolved significantly. Notable changes in these techniques involve the automation of different steps, yielding promising results in terms of accuracy, class detection and efficiency. The most successful methodologies that have arisen rely on the use of multi-temporal data. Several different approaches have proven successful. In this study, one of the most recently developed methodologies is tested in the region of Galicia (in Northwestern Spain), with the aim of filling gaps in the mapping needs of the Galician forestry sector. The methodology mainly consists of performing a supervised classification of individual images from a selected time series and then combining them through aggregation using decision criteria. Several of the steps of the methodology can be addressed in multiple ways: pixel resolution selection, classification model building and aggregation methods. The effectiveness of these three tasks as well as some others are tested and evaluated and the most accurate and efficient parameters for the case study area are highlighted. The final land cover map that is obtained for Galicia has high accuracy metrics (an overall accuracy of 91.6%), which is in line with previous studies that have followed this methodology in other regions. This study has led to the development of an efficient open-access solution to support the mapping needs of the forestry sector.

Highlights

The observation and monitoring of the Earth’s surface has been revolutionized in the last several decades thanks to advancements in satellite remote sensing technologies [1].Today, the scientific community is putting a great deal of effort into exploring the utility of open-access satellite data for providing robust standardized classifications and applications across various scientific fields [2].One area of focus in this endeavor is land cover mapping and monitoring
The final land cover map that is obtained for Galicia has high accuracy metrics, which is in line with previous studies that have followed this methodology in other regions
Several authors have even reported the superiority of Sentinel-2 for land cover mapping and monitoring purposes when compared to other similar sensors [5]

Summary

Introduction

The observation and monitoring of the Earth’s surface has been revolutionized in the last several decades thanks to advancements in satellite remote sensing technologies [1]. One area of focus in this endeavor is land cover mapping and monitoring. The possibility of mapping large areas has become a reality thanks to the development of open-access Earth observations, in conjunction with other factors such as the development of big data analysis techniques and capabilities [4]. Open-access Earth observations provide up-to-date information that is useful for assessing changes and performing land-cover-evolution studies [4]. Landsat was the most commonly used open-access satellite data for land cover mapping and monitoring studies. Several authors have even reported the superiority of Sentinel-2 for land cover mapping and monitoring purposes when compared to other similar sensors [5]

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Conclusion