Global General Land Use Cover Datasets with a Time Series of Maps

Abstract

AbstractGeneral Land Use Cover (LUC) datasets provide a holistic picture of all the land uses and covers on Earth, without focusing specifically on any individual land use category. As opposed to the LUC maps which are only available for one date or year, reviewed in Chap. “Global General Land Use Cover Datasets with a Single Date”, the maps with time series allow users to study LUC change over time. Time series of general LUC datasets at a global scale is useful for understanding global patterns of LUC change and their relation with global processes such as climate change or the loss of biodiversity. MCD12Q1, also known as MODIS Land Cover, was the first time series of LUC maps to be produced on a global scale. When it was first launched in 2002, there were already many organizations and researchers working on accurate, detailed global LUC maps, although these were all one-off editions for single years. The MCD12Q1 dataset continues to be updated today, providing a series of maps for the period 2001–2018. Since the launch of MCD12Q1, many other historical series of LUC maps have been produced, especially in the last decade. This has resulted in the LUC map series covering a longer time period at higher spatial resolution. Recent efforts have focused on producing consistent time series of maps that can track LUC changes over time with low levels of uncertainty. GLCNMO (500 m), GlobCover (300 m) and GLC250 (250 m) provide time series of LUC maps at similar spatial resolutions to MCD12Q1 (500 m), although for fewer reference years. GLCNMO provides information for the years 2003, 2008 and 2013, GlobCover for 2005 and 2009 and GLC250 for 2001 and 2010. GLASS-GLC is the dataset with the coarsest spatial resolution of all those reviewed in this chapter (5 km), even though it was released very recently, in 2020. Map producers have focused on this dataset’s long timespan (1982–2015) rather than on its spatial detail. LC-CCI and CGLS-LC100 are the recently launched datasets providing a consistent series of LUC maps, which show LUC changes over time with lower levels of uncertainty. LC-CCI provides LUC information for one of the longest timespans reviewed here (1992–2018) at a spatial resolution of 300 m. CGLS-LC100 provides LUC information for a shorter period (2015–2019) but at a higher spatial resolution (100 m). In both cases, updates are scheduled. The datasets with the highest levels of spatial detail are FROM-GLC and GLC30. These were produced using highly detailed Landsat imagery, delivering time series of maps at 30 m. The FROM-GLC project even has a test LUC map at a spatial resolution of 10 m from Sentinel-2 imagery for the year 2017, making it the global dataset with the greatest spatial detail of all those reviewed in this book. Both FROM-GLC and GLC30 provide data for three different dates: the former for 2010, 2015 and 2017 and the latter for 2000, 2010 and 2020.