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2 results for “Cloud-gap-filled”
MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022)
<p>The Asia Water Tower region, with the Qinghai-Tibet Plateau at its core, is the most widespread region of snow cover on Earth, except for the North and South Poles. The topographic heterogeneity of the Asian Water Tower region is so great that the snow cover is thin and patchy, resulting in a highly time-varying snow cover in the region, and therefore daily-scale fractional snow cover data are urgently needed. This dataset is based on the MODIS surface reflectance product MO/YD09GA product, and the MODIS daily cloud-free fractional snow cover dataset for the Asian Water Tower region from 2000 to 2022 was produced using the MESMA-AGE algorithm and the MSTI algorithm. The high spatial resolution Landsat-8 image was taken as the "ground truth", the RMSE was 0.16, and the MAE was 0.10. This dataset has a time series from 26 February 2000 to 31 December 2022 with a spatial resolution of 0.005°, which can provide quantitative snow cover information on the spatial distribution of snow for mountain hydrological models, land surface models, numerical weather forecasts, etc.</p>
Daily cloud-gap-filled Terra–Aqua MODIS NDSI dataset over High Mountain Asia (2000-2024)
<p>1. The daily cloud-gap-filled (CGF) MODIS normalized difference snow index (NDSI) dataset over High Mountain Asia (HMA) (2000-2024) is generated by combining of the cubic spline interpolation (CSI) method and the Spatio-Temporal Weighted (STW) method. This dataset is derived from daily 500 m MOD10A1 (Terra) and MYD10A1 (Aqua) products.</p> <p>2. The cloud persistence days (CPD) dataset is also provided. The CPD represents the number of consecutive days of cloud observed for a pixel from the last cloud-free observation to the next cloud-free observation. And the CPD is used to determine the combination of CSI and STW method, which is expressed as: when CPD < 8 d, the CSI method is used; when CPD ≥ 8 d, the STW is used.</p> <p>3. The CGF MODIS NDSI dataset is provided in ENVI standard format (.img) and the CPD dataset is provided in Geotiff format. And they are all provided in a geographic projection using the WGS84 coordinate system at a 0.005° (about 500 m) resolution. The NDSI value ranges from 0~100 and the CPD value ranges from 0~366. The fill value of both dataset is set to 255 (outside the track coverage of MODIS product).</p> <p>4. The CGF MODIS NDSI dataset contains 25 compressed packages (named after the normal year) of the daily CGF MODIS NDSI dataset over HMA (2000-2024), and after uncompressing the files are named as “YYYYDDD_HMA_MODIS_NDSI_0.5km.img”. The CPD dataset contains 25 compressed packages (named after the normal year) of the daily CPD dataset over HMA (2000-2024), and after uncompressing the files are named as “YYYYDDD_CPD.tif”. The YYYY represents the year and the DDD represents Julian day (001-365/366).</p> <p>5. The accuracy of this dataset has been well evaluated based on in-situ snow depth (SD) observations and high-resolution snow cover maps derived from Landsat images. The detailed information can be found in the paper (Deng, G., Tang, Z., Dong, C., Shao, D., & Wang, X. (2024). Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia. <em>Remote Sensing</em>, <em>16</em>(1), 192. https://doi.org/<a href="https://doi.org/10.3390/rs16010192">10.3390/rs16010192</a>).</p>
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