The impact of near-real-time deforestation alerts across the tropics

Moffette, Fanny; Alix‐Garcia, Jennifer; Shea, Katherine M.; Pickens, Amy

doi:10.1038/s41558-020-00956-w

Cited by 40 publications

(26 citation statements)

References 16 publications

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“…It may also have included areas of forest or mining concession or other areas where monitoring was not intended to prevent clearing. The study noted that when a one-year lag effect was applied, the correlation between availability and deforestation was negative, although not statistically significant (Moffette et al, 2021).…”

Section: Quantitative Evaluationmentioning

confidence: 91%

Measuring the Impact of Monitoring: How We Know Transparent Near-Real-Time Data Can Help Save the Forests

Shea

2022

Transformational Change for People and the Planet

Self Cite

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Global Forest Watch (GFW) is an online platform that distills satellite imagery into near-real-time forest change information that anyone can access and act on. Like other open-data platforms, GFW is based on the idea that transparent, publicly available data can support the greater good—in this case, reducing deforestation. By its very nature, the use of freely available data can be difficult to track and its impact difficult to measure. This chapter explores four approaches for measuring the reach and impact of GFW, including quantitative and qualitative approaches for monitoring outcomes and measuring impact. The recommendations can be applied to other transparency initiatives, especially those providing remote-sensing data.

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Section: Quantitative Evaluationmentioning

confidence: 91%

Measuring the Impact of Monitoring: How We Know Transparent Near-Real-Time Data Can Help Save the Forests

Shea

2022

Transformational Change for People and the Planet

Self Cite

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“…Though it was reported also that the early 2020 RADD alerts in Asia may be overestimated due to the forest baselining of the RADD product [33]. On the other hand, there can still be potential commission errors (false positives) for an alert product since they detect losses based on single-date images instead of image composites [21]. Nevertheless, both (high-confidence) alert products would be useful for future hotspot mapping i.e., GLAD alerts in areas outside primary forests, where radar signals decrease in sensitivity e.g., flooded forest, mangroves and peatlands.…”

Section: Hotspot Mapping and Deforestation Detectionmentioning

confidence: 99%

“…Some other recent EO products are near-real time forest disturbance alerts: the Global Land Analysis and Discovery alert system (GLAD, 2015-present), which uses terrain and atmospherically corrected Landsat 7 and 8 data to create weekly alerts of tree cover loss in Amazon, Congo and insular Southeast Asia [20]; and the Radar for Detecting Deforestation (RADD) alerts where Sentinel 1 is used to classify forest disturbances for a minimum of 0.1 ha within African (since 2019) and Asian (since 2020) countries. A recent study showed that alert systems could trigger immediate interventions in forest management and conservation by environmental stakeholders [21].…”

Section: Introductionmentioning

confidence: 99%

Intra-Annual Identification of Local Deforestation Hotspots in the Philippines Using Earth Observation Products

Araza

Castillo²,

Buduan³

et al. 2021

Forests

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Like many other tropical countries, the Philippines has suffered from decades of deforestation and forest degradation during and even after the logging era. Several open access Earth Observation (EO) products are increasingly being used for deforestation analysis in support of national and international initiatives and policymaking on forest conservation and management. Using a combination of annual forest loss and near-real time forest disturbance products, we provide a comprehensive analysis of the deforestation events in three forest frontiers of the Philippines. A space-time pattern mining approach was used to map quarterly deforestation hotspots at 1 km pixel size (100 hectares), where hotspots are classified according to the spatial and temporal variability of the 2000–2020 deforestation in the study area. Our results revealed that 79–81% of the hotspots overlap with primary forests and 27–29% are inside the state-declared protected areas. The intra-annual analysis of deforestation in 2020 revealed an alarming trend, where most deforestation occurred between the 1st and 2nd quarter (92–94% in hotspot forests; 87–89% in non-hotspot forests), highly overlapping within the slash-and-burn farming season. We also found “new” hotspots (2020) formed mostly from landslide scars and partly from selective logging, the latter is believed to be underestimated. Our study paves the way for rapid and regular assessment of the country’s deforestation, useful for the respective environmental institutions who convene several times a year. Moreover, our findings assert the imperative of alternative livelihoods to upland farmers, efficient forest protection activities, and even the mitigation of landslide risks.

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“…Recent improved availability and processing of satellite imagery data on land use and land use change have been an important step forward to help identify production locations and monitor production activities. There has been an explosion of both civil society and researcher-based land use change products and commercial offerings (Moffette et al, 2021). However, there are still gaps in the availability of data on commodity driven deforestation.…”

Section: Identifying Suppliers and Business Partners In Supply Chainsmentioning

confidence: 99%

Data requirements to tackle global deforestation through mandatory due diligence

Wood¹,

Gauttier²,

Bellfield³

et al. 2021

Preprint

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The world’s forests are highly threatened, mainly by agricultural expansion, driving biodiversity loss and greenhouse gas emissions, and disproportionately impacting rights and livelihoods of indigenous peoples and local communities. Zero-deforestation voluntary commitments to address deforestation have not significantly reversed deforestation and have made even less progress in related human rights violations. A regulation to address deforestation in agricultural supply chains will likely be prepared in the European Union (EU) to mandate due diligence requirements. We summarize how adequate risk identification and assessment require availability of and access to specific data. We review current data landscapes, flexibility required to adapt to supply chain complexities and capacities, required investments in current data systems, and constraints associated with data. We provide recommendations for forest risk commodity due diligence regulations, including: (1) To improve baseline data, prioritize sub-national data generation and access, improve remotely sensed maps of sourcing areas, and prioritize investment in public data platforms; (2) to adapt to supply chain complexities, regularly review commodities in the scope of the regulations; (3) for implementation, existing tools such as certification schemes can play a role for risk assessment, though cannot be a prerequisite to conduct due diligence. We outline data needs to allow for sufficient mitigation measures; (4) finally we recommend financial and technical support for developing countries and producers, which should improve the availability and quality of data. We conclude that increased data availability and quality to successfully implement a EU due diligence regulation on forest-risk commodities would benefit many demand-side market policies.

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The impact of near-real-time deforestation alerts across the tropics

Cited by 40 publications

References 16 publications

Measuring the Impact of Monitoring: How We Know Transparent Near-Real-Time Data Can Help Save the Forests

Measuring the Impact of Monitoring: How We Know Transparent Near-Real-Time Data Can Help Save the Forests

Intra-Annual Identification of Local Deforestation Hotspots in the Philippines Using Earth Observation Products

Data requirements to tackle global deforestation through mandatory due diligence

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