Abstract
Monitoring forests is important for measuring overall success of the 2030 Agenda because forests play an essential role in meeting many Sustainable Development Goals (SDG), especially SDG 15. Our study evaluates the contribution of three satellite data sources (Landsat-8, Sentinel-2 and Sentinel-1) for mapping diverse forest types in Myanmar. This assessment is especially important because Myanmar is currently revising its classification system for forests and it is critical that these new forest types can be accurately mapped and monitored over time using satellite imagery. Our results show that using a combination of Sentinel-1 and Sentinel-2 yields the highest accuracy (89.6% ± 0.16 percentage point(pp)), followed by Sentinel-2 alone (87.97% ± 0.11 pp) and Landsat-8 (82.68% ± 0.13 pp). The higher spatial resolution of Sentinel-2 Blue, Green, Red, Narrow Near Infrared and Short Wave Infrared bands enhances accuracy by 4.83% compared to Landsat-8. The addition of the Sentinel-2 Near Infrared and three Vegetation Red Edge bands further improve accuracy by 0.46% compared to using only Sentinel-2 Blue, Green, Red, Narrow Near Infrared and Short Wave Infrared bands. Adding the radar information from Sentinel-1 further increases the accuracy by 1.63%. We were able to map the two major forest types, Upper Moist and Upper Dry Mixed Deciduous Forest, which comprise 90% of our study area. Accuracies for these forest types ranged from 77 to 96% depending on the sensors used, demonstrating the feasibility of using satellite data to map forest categories from a newly revised classification system. Our results advance the ongoing development of the National Forest Monitoring System (NFMS) by the Myanmar Forest Department and United Nations-Food and Agriculture Organization (UN-FAO) and facilitates future monitoring of progress towards the SDGs.
Highlights
Forests play an essential role in addressing the Sustainable Development Goals (SDG) set by the United Nations in the 2030 Agenda, by providing goods and services necessary to meet the SDGs [1,2]
The largest forest type by area is Upper Dry MDF followed by Upper Moist MDF, Lower MDF, Swamp, Bamboo and Indaing Forests
This study demonstrates the utility of recent optical (Landsat-8, Sentinel-2) and radar (Sentinel-1) satellite data to map forest types in Myanmar using a revised forest type classification
Summary
Forests play an essential role in addressing the Sustainable Development Goals (SDG) set by the United Nations in the 2030 Agenda, by providing goods and services necessary to meet the SDGs [1,2]. SDG 15 (Life on Land) explicitly mentions forests and sustainable forest management in its targets 15.1 and 15.2, respectively. Afforestation and halting deforestation are recognized as key pathways for countries to reach their mitigation targets, because forests can serve as major carbon sinks (SDG 13). Given the significant contribution of forests to the SDGs, monitoring of forests is critical to measuring overall success of the 2030 Agenda. In the context of SDG 15, accurate information on a country’s forest area, as implied by indicator 15.1.1, is dependent on many factors including definitions of national classifications, data source and methodology [3]. Ensuring high quality data for monitoring and reporting, accurate and up-to-date forest type baseline data, remains a logistic, financial and technical challenge in many countries, including Myanmar [4]
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