Работы, цитирующие эту работу

Работ: 3

Работа: Satellite-based soybean yield forecast: Integrating machine learning and weather data for improving crop yield prediction in southern Brazil

1. Sunflower crop yield prediction by advanced statistical modeling using satellite-derived vegetation indices and crop phenology

   Khilola Amankulova, Nizom Farmonov, Uzbekkhon Mukhtorov +1

   СтатьяRemote Sensing in AgricultureGeocarto International2023Цитирований: 7

   ABIABI:AkademIndex/openalex/2023.article.000152

2. Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation

   Nizom Farmonov, Khilola Amankulova, József Szatmári +4

   СтатьяRemote Sensing in AgricultureInternational Journal of Digital Earth2023Цитирований: 3

   ABIABI:AkademIndex/openalex/2023.article.000160

3. Comparison of PlanetScope, Sentinel-2, and landsat 8 data in soybean yield estimation within-field variability with random forest regression

   Khilola Amankulova, Nizom Farmonov, Parvina Akramova +2

   СтатьяRemote Sensing in AgricultureHeliyon2023Цитирований: 0

   ABIABI:AkademIndex/openalex/2023.article.000187