Abstract
Abstract. Global Land cover is essential for ecological study, climate and environmental changes, resources management, human activities as well as sustainable development. With the finer resolution products arising, e.g. GlobeLand30, quantitative analysis of the earth dynamics based on raster data sets is becoming possible. For arbitrary zonal statistics, pixel counting method is an operational practice widely used for area estimation by counting the number of classified pixels and multiplying by the area represented by each pixel, though uncertainty. For large statistical regions, the error of the projection can not be neglect. Thus an rectified PC method is developed for arbitrary zonal statistics of all raster data sets. The test result shows that the method performance is stable and easy to zonal statistics.
Highlights
Globe land cover data set is one of the most important layer for digital earth as id reflects the status and changes about the biophysical material over the surface of the Earth, such as forests, croplands, water bodies and built-up areas(Pielke et al 2005; Running et al.,2008)
With the finer resolution land cover products arising, e.g. GlobeLand30(Jun Chen et al, 2014), quantitative analysis of the earth dynamics based on raster data sets is becoming possible
The developed RPC method correct the error caused by conformal projection
Summary
Globe land cover data set is one of the most important layer for digital earth as id reflects the status and changes about the biophysical material over the surface of the Earth, such as forests, croplands, water bodies and built-up areas(Pielke et al 2005; Running et al.,2008). A number of global land cover products at different spatial resolutions have been produced and widely used in scientific research activities such as ecological study, climate and environmental changes, resources management, human activities and sustainable development(Allen, et al, 2018). The National Agricultural Statistics Services(NASS) of the US Department of Agriculture(USDA) provides timely, accurate, and useful statistical information service for agriculture applications in US through a data access and dissemination application system named “CropScape”(Boryan ,et al,2011; Han,et al, 2012;Han,et al, 2014). It can provide online data navigation, visualization, and analysis capabilities and services. With the finer resolution land cover products arising, e.g. GlobeLand30(Jun Chen et al, 2014), quantitative analysis of the earth dynamics based on raster data sets is becoming possible
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