the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Annual vegetation maps in Qinghai-Tibet Plateau (QTP) from 2000 to 2022 based on MODIS series satellite imagery
Abstract. The Qinghai Tibet Plateau (QTP), known as the "Third Pole" of the Earth" and the "Water Tower of Asia," plays a crucial role in global climate regulation, biodiversity conservation, and regional socio-economic development. Continuous annual vegetation types and their geographical distribution data are essential for studying the response and adaptation of vegetation to climate change. However, there is very limited data on vegetation types and their geographical distributions on the QTP due to harsh natural environment. Currently, land cover/surface vegetation (LCSV) data are typically obtained using independent classification methods for each period's product, based on remote sensing information. These approaches do not consider the time continuity of vegetation to presence, and leads to a gradual increase in the number of misclassified pixels and the uncertainty of their locations, consequently decreasing the interpretability of the long-time series remote sensing products. To address this issue, this study developed a new approach to long-time continuous annual vegetation mapping from remote sensing imagery, and mapped the vegetation of the QTP from 2000 to 2022 at a 500 m spatial resolution through the MOD09A1 product. The overall accuracy of continuous annual QTP vegetation mapping from 2000 to 2022 reached 80.9 % based on 733 samples from literature, with the reference annual 2020 reaching an accuracy of 86.5 % and a Kappa coefficient of 0.85. The study supports the use of remote sensing data to mapping a long-term continuous annual vegetation.
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Status: open (until 10 Aug 2024)
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RC1: 'Comment on essd-2024-193', Shudong Wang, 05 Jul 2024
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This study developed a new approach to long-time continuous annual vegetation mapping from remote sensing imagery. The new approach is very important and effective for the use of remote sensing data to mapping long-term continuous annual vegetation. Using the new method, this study mapped the vegetation of Qinghai Tibet Plateau(QTP) from 2000 to 2022 at a 500 m spatial resolution through the MOD09A1 product. The valuable dataset facilitates the understanding of the spatial and temporal variations of vegetation in the QTP under the background of global warming. Therefore, I recommend accepting this manuscript. However, there are some minor issues that need to be addressed:
(1) L 39-40 Modify "Over time, the trend of increasing misclassified pixels and their positional uncertainties ultimately reduces the reliability of remote sensing interpretation for LCSV types." to "Over time, there is a trend of increasing misclassified pixels and their positional uncertainties, which ultimately reduces the reliability of remote sensing interpretation for LCSV types."
(2) L 104-106 Sentence structure is incomplete. The suggestion is as follows : "The MOD09A1 dataset provides surface reflectance in seven spectral bands (Red, Blue, Green, NIR, MIR, SWIR 1, and SWIR 2) with 500 m spatial resolution, and all cloud-contaminated pixels are removed."
(3) L 114 Use "were" instead of "was" to match the plural noun "data": "For the QTP within China, climate data at 1,000 m were obtained from..."
(4) L 301 The verb "confirms" should be corrected to "confirm" to match the plural subject".
(5) In the Figure 4, legend text is too small, please revise the font size.Citation: https://doi.org/10.5194/essd-2024-193-RC1
Data sets
500 m annual vegetation maps of Qinghai Tibet Plateau (2000-2022) Zhou, G., Ren, H., Zhang, L., Lv, X., Zhou, M. https://data.tpdc.ac.cn/en/disallow/6304c1a4-efc0-4766-bae3-4148bdf7bcfd
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