Characterizing Tropical Forest Cover Loss Using Dense Sentinel-1 Data and Active Fire Alerts

Fire use for land management is widespread in natural tropical and plantation forests, causing major environmental and economic damage. Recent studies combining active fire alerts with annual forest-cover loss information identified fire-related forest-cover loss areas well, but do not provide detailed understanding on how fires and forest-cover loss are temporally related. Here, we combine Sentinel-1-based, near real-time forest cover information with Visible Infrared Imaging Radiometer Suite (VIIRS) active fire alerts, and for the first time, characterize the temporal relationship between fires and tropical forest-cover loss at high temporal detail and medium spatial scale. We quantify fire-related forest-cover loss and separate fires that predate, coincide with, and postdate forest-cover loss. For the Province of Riau, Indonesia, dense Sentinel-1 C-band Synthetic Aperture Radar data with guaranteed observations of at least every 12 days allowed for confident and timely forest-cover-loss detection in natural and plantation forest with user’s and producer’s accuracy above 95%. Forest-cover loss was detected and confirmed within 22 days in natural forest and within 15 days in plantation forest. This difference can primarily be related to different change processes and dynamics in natural and plantation forest. For the period between 1 January 2016 and 30 June 2017, fire-related forest-cover loss accounted for about one third of the natural forest-cover loss, while in plantation forest, less than ten percent of the forest-cover loss was fire-related. We found clear spatial patterns of fires predating, coinciding with, or postdating forest-cover loss. Only the minority of fires in natural and plantation forest temporally coincided with forest-cover loss (13% and 16%) and can thus be confidently attributed as direct cause of forest-cover loss. The majority of the fires predated (64% and 58%) or postdated forest-cover loss (23% and 26%), and should be attributed to other key land management practices. Detailed and timely information on how fires and forest cover loss are temporally related can support tropical forest management, policy development, and law enforcement to reduce unsustainable and illegal fire use in the tropics

Biodiversity Conservation in the REDD

Deforestation and forest degradation in the tropics is a major source of global greenhouse gas (GHG) emissions. The tropics also harbour more than half the world's threatened species, raising the possibility that reducing GHG emissions by curtailing tropical deforestation could provide substantial co-benefits for biodiversity conservation. Here we explore the potential for such co-benefits in Indonesia, a leading source of GHG emissions from land cover and land use change, and among the most species-rich countries in the world. We show that focal ecosystems for interventions to reduce emissions from deforestation and forest degradation in Indonesia do not coincide with areas supporting the most species-rich communities or highest concentration of threatened species. We argue that inherent trade-offs among ecosystems in emission reduction potential, opportunity cost of foregone development and biodiversity values will require a regulatory framework to balance emission reduction interventions with biodiversity co-benefit targets. We discuss how such a regulatory framework might function, and caution that pursuing emission reduction strategies without such a framework may undermine, not enhance, long-term prospects for biodiversity conservation in the tropics

The heart of Borneo and the spatial progression of logging since 1973 depicting a logging ‘frontier’ moving steadily upward and inland, from the lowland coasts to the highlands.

<p>In many areas, logging roads are surrounding and abutting against the edges of highland protected forests – the last contiguous bastions of intact forest.</p

Intact, logged and cleared forest area by country and elevation, 1973 and 2010.

<p>Intact, logged and cleared forest area by country and elevation, 1973 and 2010.</p

Expansion of the primary logging road network in Borneo from 1973 until 2010.

<p>Expansion of the primary logging road network in Borneo from 1973 until 2010.</p

Accuracy results of 1973 ‘Forest’, and ‘Non-forest’ classification.

<p>Overall accuracy = 89.0%.</p

A close-up view of an area in West Kalimantan province, Borneo (see top-right inset for location).

<p>In this example, an intact forest in year 1973 was logged in 1990 and became converted to an industrial oil Palm Plantation in 2010. On the 1973 LANDSAT MSS imagery (false color composite: 3-4-2) forest appears dark green (panel A). The resulting forest non-forest supervised classification is shown in panel D. On the 1990 LANDSAT TM imagery (false color composite: 5-4-3) primary logging roads are seen carving through the forest (panel B). The logging roads (yellow lines) and public roads (black lines) are shown in panel E. An aerial view of a primary logging road (Photo by R. Butler <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0101654#pone.0101654-Butler1" target="_blank">[53]</a>) is shown the inset of panel B. On the 2010 LANDSAT TM imagery), the forest has become converted to an industrial oil palm plantation (grid-like patterns). The boundary of the plantations was digitized by visual interpretation (Panel F).</p

Length and density of primary logging roads by country.

<p>Length and density of primary logging roads by country.</p