2015 global 30m surface coverage fine classification products
Land-cover is indispensable basic information for climate change research, ecological environment assessment and geographical situation monitoring. In recent years, with the continuous improvement of remote sensing science and technology and computer storage and computing capacity, the application demand for long time-series global 30m land-cover dynamic monitoring products is becoming more and more urgent. To achieve the goal of automatically monitoring long time-series global 30m land-cover dynamics, we used our newly global 30m land-cover products with fine classification system in 2020 (GLC_FCS30-2020) as the benchmark dataset, and then proposed a novel and automatic land-cover monitoring strategy by coupling with continuous land-cover change detection models with the dynamic updating algorithms, and finally produced the time-series global 30m land-cover dynamic monitoring products (every 5-year) using the continuous time-series Landsat imageries. It should be noted that our global land-cover dynamic monitoring products inherited the classification system of GLC_FCS30-2020, containing 29 land-cover types. Zhang, X., Liu, L., Chen, X., Gao, Y., Xie, S., Mi, J., 2021. GLC_FCS30: global land-cover product with fine classification system at 30m using time-series Landsat imagery. Earth Syst. Sci. Data 13, 2753-2776 , https://doi.org/10.5194/essd-13-2753-2021. Zhang, X., Liu, L., Wu, C., Chen, X., Gao, Y., Xie, S., & Zhang, B. (2020). Development of a global 30m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform. Earth System Science Data, 12, 1625-1648, https://doi.org/10.5194/essd-12-1625-2020. Liu, L., Zhang, X., Gao, Y., Chen, X., Shuai, X., Mi, J., 2021. Finer-Resolution Mapping of Global Land Cover: Recent Developments, Consistency Analysis, and Prospects. Journal of Remote Sensing 2021, 1-38.
Spatial Resolution: 30m
Time Resolution: 5 years
Product Number: XDA19090125_008
Create Institution: Aerospace Information Research Institute, Chinese Academy of Sciences
Created By: Liangyun Liu, Xiao Zhang
Creation Date: 2021-09-22T16:00:00.000Z
File Size: 963
Data Format: GeoTiff
Type Of Data: Raster
Data Label: