Global data and tools for local forest cover loss and REDD plus performance assessment: Accuracy, uncertainty, complementarity and impact

Bos, Astrid B. ¹De Sy, Veronique ¹Duchelle, Amy E. ²Herold, Martin ¹Tsendbazar, Nandin-Erdene ¹Martius, Christopher²

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作者信息

1. Wageningen Univ & Res, Lab Geoinformat Sci & Remote Sensing, Droevendaalsesteeg 3, NL-6708 PB Wageningen, Netherlands
2. Ctr Int Forestry Res, Jalan CIFOR, Bogor Barat 16115, Indonesia
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Abstract

Assessing the performance of efforts to reduce emissions from deforestation and forest degradation (REDD +) requires data on forest cover change. Innovations in remote sensing and forest monitoring provide ever-increasing levels of coverage, spatial and temporal detail, and accuracy. More global products and advanced open-source algorithms are becoming available. Still, these datasets and tools are not always consistent or complementary, and their suitability for local REDD + performance assessments remains unclear. These assessments should, ideally, be free of any confounding factors, but performance estimates are affected by data uncertainties in unknown ways. Here, we analyse (1) differences in accuracy between datasets of forest cover change; (2) if and how combinations of datasets can increase accuracy; and we demonstrate (3) the effect of (not) doing accuracy assessments for REDD + performance measurements.

Key words

Accuracy/Deforestation/Measurement/reporting and verification/Performance/REDD/Uncertainty

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出版年

2019

International journal of applied earth observation and geoinformation

SCI

ISSN：0303-2434

被引量2

参考文献量31

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