TY - JOUR
T1 - AgKit4EE
T2 - A toolkit for agricultural land use modeling of the conterminous United States based on Google Earth Engine
AU - Zhang, Chen
AU - Di, Liping
AU - Yang, Zhengwei
AU - Lin, Li
AU - Hao, Pengyu
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/7
Y1 - 2020/7
N2 - Google Earth Engine (GEE) is an ideal platform for large-scale geospatial agricultural and environmental modeling based on its diverse geospatial datasets, easy-to-use application programming interface (API), rich reusable library, and high-performance computational capacity. However, using GEE to prepare geospatial data requires not only the skills of programming languages like JavaScript and Python, but also the knowledge of GEE APIs and data catalog. This paper presents the AgKit4EE toolkit to facilitate the use of the Cropland Data Layer (CDL) product over the GEE platform. This toolkit contains a variety of frequently used functions for use of CDL including crop sequence modeling, crop frequency modeling, confidence layer modeling, and land use change analysis. The experimental results suggest that the proposed software can significantly reduce the workload for modelers who conduct geospatial agricultural and environmental modeling with CDL data as well as developers who build the GEE-enabled geospatial cyberinfrastructure for agricultural land use modeling of the conterminous United States. AgKit4EE is an open source and it is free to use, modify, and distribute. The latest release of AgKit4EE can be imported to any modeling workflow developed using GEE Code Editor (https://code.earthengine.google.com/?accept_repo=users/czhang11/agkit4ee). The source code, examples, documentation, user community, and wiki pages are available on GitHub (https://github.com/czhang11/agkit4ee).
AB - Google Earth Engine (GEE) is an ideal platform for large-scale geospatial agricultural and environmental modeling based on its diverse geospatial datasets, easy-to-use application programming interface (API), rich reusable library, and high-performance computational capacity. However, using GEE to prepare geospatial data requires not only the skills of programming languages like JavaScript and Python, but also the knowledge of GEE APIs and data catalog. This paper presents the AgKit4EE toolkit to facilitate the use of the Cropland Data Layer (CDL) product over the GEE platform. This toolkit contains a variety of frequently used functions for use of CDL including crop sequence modeling, crop frequency modeling, confidence layer modeling, and land use change analysis. The experimental results suggest that the proposed software can significantly reduce the workload for modelers who conduct geospatial agricultural and environmental modeling with CDL data as well as developers who build the GEE-enabled geospatial cyberinfrastructure for agricultural land use modeling of the conterminous United States. AgKit4EE is an open source and it is free to use, modify, and distribute. The latest release of AgKit4EE can be imported to any modeling workflow developed using GEE Code Editor (https://code.earthengine.google.com/?accept_repo=users/czhang11/agkit4ee). The source code, examples, documentation, user community, and wiki pages are available on GitHub (https://github.com/czhang11/agkit4ee).
KW - Crop mapping
KW - Cropland Data Layer
KW - Geospatial cyberinfrastructure
KW - Google Earth Engine
KW - Land use modeling
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U2 - 10.1016/j.envsoft.2020.104694
DO - 10.1016/j.envsoft.2020.104694
M3 - Article
AN - SCOPUS:85083431167
SN - 1364-8152
VL - 129
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
M1 - 104694
ER -