Author_Institution :
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
Abstract :
Global land cover data plays an important role on the global change research. At present, there are a variety of global land cover datasets. Those datasets are based on different classification systems and employ different methodologies. The inconsistencies may be a problem for studies of global change. This study analyzes the consistency of MCD12Q1 and Globcover datasets using type area consistency and spatial consistency at a national level and regional level. The results show that at the national level, the correlation coefficient of the type area totals of the two datasets is 82.98% and Kappa coefficient is 27.21%. Correlation coefficient of the type area totals of the two datasets at Northeast region, North China, Southwest region, Northwest region, Central and Southeast region and Qinghai-Tibet Plateau are 43.84%, 69.30%, 18.53%, 92.98%, 42.40%, 91.10%, respectively and Kappa coefficient are 7.41%, 20.45%, 6.33%, 32.63%, 16.37%, 26.15%, respectively.
Keywords :
data analysis; radiometry; terrain mapping; China; MERIS Globcover land cover dataset; MODIS MCD12Q1 land cover dataset; Qinghai-Tibet Plateau; classification systems; global change research; global land cover data; land cover dataset consistency analysis; Accuracy; Correlation; Ice; MODIS; Snow; Spatial resolution; Vegetation; MERIS Globcover; MODIS Land Cover (MCD12Q1); spatial consistency; type area consistency;