the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Annual forest and evergreen forest cover maps in the Brazilian Amazon in terms of FAO's forest definition
Yuanwei Qin
Xiangming Xiao
Ralph Dubayah
Russell Doughty
Diyou Liu
Fang Liu
Yosio Shimabukuro
Egidio Arai
Xinxin Wang
Berrien Moore III
Abstract. Many forest cover maps have been generated by using optical and/or microwave images and various forest definitions, but these forest cover maps have large discrepancies. Both forest definition and validation data used for accuracy assessment of forest cover maps are often considered as two of the major factors for the discrepancy among these forest cover maps. To date, few studies have assessed forest cover maps in terms of two biophysical parameters used in forest definition: (1) tree canopy height and (2) canopy coverage. We generated annual forest cover maps from 2007 to 2010 and evergreen forest cover maps from 2000 to 2021 in the Brazilian Amazon using the images from the Phased Array type L-band Synthetic Aperture Radar and Moderate Resolution Imaging Spectroradiometer, and the forest definition of the Food and Agriculture Organization (FAO) of the United Nations (>5-m tree height and >10 % canopy coverage). The canopy height and coverage datasets from the Geoscience Laser Altimeter System during 2003–2007 were used to assess annual forest cover maps from 2007 to 2010 and evergreen forest cover maps from 2003 to 2007, and the results show high accuracy of these forest and evergreen forest cover maps in the Brazilian Amazon.
Yuanwei Qin et al.
Status: open (extended)
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RC1: 'Comment on essd-2022-379', Anonymous Referee #1, 12 Apr 2023
reply
As per the abstract, the article discusses the discrepancies in forest cover maps generated using different forest definitions and validation data which is affected by two biophysical parameters, tree height and canopy coverage. However, the paper presents the annual and evergreen forest cover maps in the Brazilian Amazon from 2000 to 2021 using PALSAR/MODIS and MODIS. The maps are evaluated using ICESat/GLAS as a reference for canopy height (>5m) and canopy cover (>10%) which is based on the general forest definition.
In general, it is challenging to map forests or trees that are less than 5m using satellite data, whether optical or SAR. Therefore, obtaining 98.5% of forest pixels with canopy height greater than 5 meters in both PALSAR/MODIS and MODIS is not unexpected. Consequently, the author should reconsider the main question of the paper, which should not be solely focused on forest definition but should instead aim to validate the annual forest cover maps. The abstract of the paper needs to be revised since the paper does not emphasize the significant discrepancies among the forest cover maps according to the FAO definition.
Specific comments:
- Some of the figures presented in the paper do not provide substantial information and could be included as supplementary material instead. For instance, Figure 4a and 4b lack distinct spatial information, which could be conveyed by a histogram (4c and 4d) or just by showing the range of values.
- The author stated in line 91 and in Fig 9 that the PALSAR/MODIS forest cover maps and MODIS evergreen forest cover maps had a close to 1:1 linear relationship at a 5-km spatial resolution. Is this because the PALSAR forest cover maps also incorporated MODIS NDVI? If so, does integrating PALSAR/MODIS offer any significant benefits over only using MODIS except for availability of cloud-free images?
Minor
- Citation of fao should be FAO, fra should be FRA.
Citation: https://doi.org/10.5194/essd-2022-379-RC1
Yuanwei Qin et al.
Data sets
Annual PALSAR/MODIS forest and evergreen forest maps in the Brazilian Amazon Yuanwei Qin, Xiangming Xiao https://doi.org/10.6084/m9.figshare.21445590
Model code and software
Codes for forest and evergreen forest mapping in the Brazilian Amazon Yuanwei Qin, Xiangming Xiao https://doi.org/10.6084/m9.figshare.21445626
Yuanwei Qin et al.
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