zhang2020esip.pdf (1.5 MB)
Exploring U.S. Cropland Using AgKit4EE Toolkit
posterposted on 2020-07-02, 23:33 authored by Chen Zhang, Liping Di, Zhengwei Yang, Li Lin, Pengyu Hao
Google Earth Engine (GEE) is an ideal platform for large-scale geospatial agricultural and environmental modeling. However, using GEE to prepare agricultural land use data for geospatial agricultural and environment modeling requires not only the programming skills of GEE APIs but also the knowledge of the data. This paper presents a toolkit AgKit4EE to facilitate the use of the Cropland Data Layer (CDL) products over GEE platform. The toolkit contains a variety of frequently used functions for use of CDL products including crop sequence modeling, crop frequency modeling, confidence layer modeling, and land use change analysis, which can significantly reduce the workload for modelers who perform geospatial agricultural and environmental modeling with CDL data as well as developers who build the GEE-enabled cyberinfrastructure for agricultural land use modeling of the conterminous United States. This presentation was given at the Earth Science Information Partners (ESIP) Summer Meeting held online in July 2020.