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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Rice is a commodity of rice-producing food crops that plays a vital role in the Indonesian economy. For anticipating increased food needs, accurate information about the amount of harvest becomes very important. Information on the number of harvests, one of which can be known by estimating rice productivity. Rice productivity estimation can be monitored by remote sensing. This study used a remote sensing approach by employing satellite imagery from Sentinel-2A sensors to generate vegetation index. This study used NDVI (Normalized Difference Vegetation Index) to determine rice plants’ age and estimate rice productivity. This study analyzes rice productivity and the spatial distribution of rice crop productivity in the Nagrak Sub-district, Sukabumi Regency. The results of this study are Sentinel 2-A and algorithm could provide rice productivity estimation and know the range of the largest rice productivity is greater than 6 ton per hectare, which is widely spread at an altitude of 500 -1000 meter above sea level and a slope of 8 to 15 percent, and a distance of 0 - 150 meters from the river.

Spatial distribution of rice productivity utilizes sentinel-2A and NDVI algorithm in Nagrak Sub-district, Sukabumi Regency