Use of SAR and Optical Time Series for Tropical Forest Disturbance Mapping

Manuela Hirschmugl,Mathias Schardt,Stéphane Mermoz,Carina Sobe,Alexandre Bouvet,Janik Deutscher

doi:10.3390/rs12040727

Abstract

Frequent cloud cover and fast regrowth often hamper topical forest disturbance monitoring with optical data. This study aims at overcoming these limitations by combining dense time series of optical (Sentinel-2 and Landsat 8) and SAR data (Sentinel-1) for forest disturbance mapping at test sites in Peru and Gabon. We compare the accuracies of the individual disturbance maps from optical and SAR time series with the accuracies of the combined map. We further evaluate the detection accuracies by disturbance patch size and by an area-based sampling approach. The results show that the individual optical and SAR based forest disturbance detections are highly complementary, and their combination improves all accuracy measures. The overall accuracies increase by about 3% in both areas, producer accuracies of the disturbed forest class increase by up to 25% in Peru when compared to only using one sensor type. The assessment by disturbance patch size shows that the amount of detections of very small disturbances (< 0.2 ha) can almost be doubled by using both data sets: for Gabon 30% as compared to 15.7–17.5%, for Peru 80% as compared to 48.6–65.7%.

Highlights

The mapping of forest disturbances is an important component in sustainable forest management and in implementing climate policy initiatives, such as the UN’s Reducing Emissions from Deforestation and Forest Degradation (REDD+) programme
Recent developments have led to automated forest monitoring systems that are based on medium to high spatial resolution Earth Observation (EO) data and allow tracking forest changes in near real-time (NRT), such as Global Forest Watch Alerts for the humid tropical forests [4] and the DETER system in Brazil [5]
The study is performed at two test sites in humid tropical forest regions: one test site is located in Peru, near the city of Yurimaguas, and the second test site is located in Gabon, near the city of Fougamou

Summary

Introduction

The mapping of forest disturbances is an important component in sustainable forest management and in implementing climate policy initiatives, such as the UN’s Reducing Emissions from Deforestation and Forest Degradation (REDD+) programme. We use the term forest disturbance as an umbrella term for all forest changes that result from both deforestation and from forest degradation. Most tropical forest monitoring systems are based on optical data sets and focus on large-deforestation areas, for which user accuracies around 90% and producer accuracies above 75% are reported [1,2,3]. While methods for large area deforestation monitoring have improved considerably over the last years, there still is a lack of methods that accurately detect forest degradation and small forest changes. To accurately detect small patches of forest disturbance from selective logging and other degradation drivers, EO data of both high spatial and temporal resolution is required because gaps left by e.g., individual tree extraction are very small and quickly overgrow in tropical climates. EO data that have the potential to map forest degradation are available: the Sentinel missions provide data at 10 m spatial resolution both in the optical and Synthetic Aperture Radar (SAR) domain and data are provided every five to 12 days

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Methods

Results

Discussion

Conclusion