Работы, цитирующие эту работу

Работ: 4

Работа: Efficiency and accuracy of per-field classification for operational crop mapping

1. Multi-temporal monitoring of cotton growth through the vegetation profile classification for Tashkent province, Uzbekistan

   Jasmina Gerts, Mukhiddin Juliev, Alim Pulatov

   СтатьяRemote Sensing in AgricultureGeoScape2020Цитирований: 30

   ABIABI:AkademIndex/openalex/2026.other.059251

2. Reconstructing the Spatio-Temporal Development of Irrigation Systems in Uzbekistan Using Landsat Time Series

   Jana Edlinger, Christopher Conrad, John P. A. Lamers +2

   СтатьяRemote Sensing in AgricultureRemote Sensing2012Цитирований: 11

   ABIABI:AkademIndex/openalex/2026.other.016375

3. Satellite based calculation of spatially distributed crop water requirements for cotton and wheat cultivation in Fergana Valley, Uzbekistan

   Christopher Conrad, Maren Rahmann, Miriam Machwitz +3

   СтатьяRemote Sensing in AgricultureGlobal and Planetary Change2013Цитирований: 7

   ABIABI:AkademIndex/openalex/2026.other.016447

4. Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches

   Amit Kumar Basukala, Carsten Oldenburg, J. Schellberg +2

   СтатьяRemote Sensing in AgricultureEuropean Journal of Remote Sensing2017Цитирований: 0

   ABIABI:AkademIndex/openalex/2017.article.000037