English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Rice acreage estimation is a key aspect to guarantee food security and also important to support government agricultural subsidysystem. In this paper, we explored a sophisticated method to improve rice estimation accuracy at county scale and we developed ourapproach with China Environment Satellite HJ-1A/B data in Hunan Province, a fragmented area with complex rice cropping patterns.Our approach improved the estimation accuracy by combing supervised and unsupervised classification upon decomposition ofmixed pixels model, and the rice estimation results, validated by ground survey data, showed a close relationship (RMSE≈3.40) withsurvey figures, the estimated accuracy (EA) reached 83.74% at county level according to the sub-pixel method, and the accuracy canbe increased about 12% compared to the pure-pixel method. The results suggest that decomposition of mixed pixels method hasgreat significance to the improvement of rice acreage estimation accuracy, and can be used in mountainous and broken planting area

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Research on rice acreage estimation in fragmented area based on decomposition of mixed pixels