Работы, цитирующие эту работу

Работ: 5

Работа: A review of assessing the accuracy of classifications of remotely sensed data

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. Framework for agricultural performance assessment based on MODIS multitemporal data

   Dimo Dimov, Fabian Löw, Johannes Uhl +4

   СтатьяRemote Sensing in AgricultureJournal of Applied Remote Sensing2019Цитирований: 9

   ABIABI:AkademIndex/openalex/2026.other.201629

3. Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012

   Christopher Conrad, Sarah Schönbrodt‐Stitt, Fabian Löw +2

   СтатьяRemote Sensing in AgricultureRemote Sensing2016Цитирований: 8

   ABIABI:AkademIndex/openalex/2016.article.000040

4. A Comparative Study of Three Supervised Algorithms for Mixed Crop Classification

   Alekhya Padma VVL, Mohammad Suhail, Ibragimov Lutfullo +1

   СтатьяRemote Sensing in AgricultureE3S Web of Conferences2024Цитирований: 1

   ABIABI:AkademIndex/openalex/2024.article.003840

5. Land cover change detection in the Aralkum with multi-source satellite datasets

   Fabian Löw, Dimo Dimov, Shavkat Kenjabaev +3

   СтатьяRemote Sensing in AgricultureGIScience & Remote Sensing2021Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.other.321889