Skip to main content

A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication

Dates

Publication Date

Citation

Chong Liu, Qian Zhang, Shiqi Tao, Jiaguo Qi, Mingjun Ding, Qihui Guan, Bingfang Wu, Miao Zhang, Mohsen Nabil, Fuyou Tian, Hongwei Zeng, Ning Zhang, Ganbat Bavuudorj, Emmanuel Rukundo, Wenjun Liu, José Bofana, Awetahegn Niguse Beyene, and Abdelrazek Elnashar, 2020-12-15, A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication: Remote Sensing of Environment, v. 251.

Summary

Accurate estimation of cropping intensity (CI), an indicator of food production, is well aligned with the ongoing efforts to achieve sustainable development goals (SDGs) under diminishing natural resources. The advancement in satellite remote sensing provides unprecedented opportunities for capturing CI information in a spatially continuous manner. However, challenges remain due to the lack of generalizable algorithms for accurately and efficiently mapping global CI with a fine spatial resolution. In this study, we developed a 30-m planetary-scale CI mapping framework with the reconstructed time series of Normalized Difference Vegetation Index (NDVI) from multiple satellite images. Using a binary crop phenophase profile indicating [...]

Contacts

Attached Files

Communities

  • National and Regional Climate Adaptation Science Centers
  • North Central CASC

Tags

Categories
Types

Provenance

Data source
Input directly

Additional Information

Citation Extension

citationTypeJournal
journalRemote Sensing of Environment
parts
typeDOI
valuehttps://doi.org/10.1016/j.rse.2020.112095
typeVolume
value251

Item Actions

View Item as ...

Save Item as ...

View Item...