Monitoring monthly tropical humid forest disturbances with planet NICFI images in Cameroon

Zhang, Y. and Wang, X. and Li, X. and Du, Y. and Atkinson, P.M. (2023) Monitoring monthly tropical humid forest disturbances with planet NICFI images in Cameroon. Agricultural and Forest Meteorology, 341: 109676. ISSN 0168-1923

Text (Planet NICFI monthly forest disturbance mapping AFM)
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Abstract

Selective logging and smallholder clearing are the dominant drivers of tropical forest disturbances in Cameroon (CAM). However, they are difficult to monitor accurately by satellite remote sensing because openings in the canopy can be very small, the vegetation is generally fast-growing, and cloud cover is common. Norway's International Climate and Forest Initiative (NICFI) provides access to monthly and biannual collections of 5 m Planet images in the tropics, creating a great opportunity for mapping tropical forest disturbances. In this paper, we develop a method to monitor monthly small-scale tropical humid forest disturbances using 2021 Planet NICFI images. First, a cloud mask for each of the monthly Planet NICFI images was predicted by integrating a cloud cover possibility map with a haze optimal transformation (HOT) index image. Second, possible monthly forest disturbances were mapped from a self-referenced Hue_forest (rHue_forest) index image. Finally, an adjusted monthly forest disturbance map was produced by eliminating many false positives with a spatio-temporal filter. Results in CAM demonstrated that the method applied to monthly Planet NICFI images was effective in identifying numerous small-scale tropical forest disturbances that were short-lived, lasting only a few months. After filtering out new possible forest disturbances in 2021 which did not meet a temporal permanence criterion based on the monthly images, the adjusted user´s and producer´s accuracies for CAM were 84.7 ± 2.9% and 61.5 ± 46.4%, respectively (±95% confidence intervals). Our results provide much greater spatial detail than forest disturbance methods based on Sentinel-1 and Landsat images. The adjusted disturbed area of humid forests in CAM was estimated as 1,168 ± 882 km2 in 2021. The proposed method for monthly mapping of forest disturbance using Planet NICFI images has great potential to complement existing forest cover change products and monitor hitherto neglected tropical forest disturbances due to small-scale clearing.