Monitoring the condition of agricultural lands in the Nukus district based on multispectral vegetation indices and machine learning methods

Aytmuratov , Bakbergen, Orazımbetov , Temurbek

Techscience.uz - техника фанлари долзарб масалалри · 2026-yil

Annotatsiya

The paper presents an automated monitoring system for agricultural lands in the Nukus district (Republic of Karakalpakstan, Uzbekistan). The dataset comprises 1,282 observations spanning January 6, 2023 through February 21, 2026, processed via the Google Earth Engine platform. Four vegetation indices — NDVI, EVI, GNDVI, and CVI — were derived from remote sensing data. Isolation Forest was applied for crop anomaly detection, and both Random Forest and Gradient Boosting algorithms were trained for 60-day index forecasting.

Maqola ma’lumotlari
MualliflarAytmuratov , Bakbergen, Orazımbetov , Temurbek
JurnalTechscience.uz - техника фанлари долзарб масалалри
NashriyotЖиззах политехника институти
ISSN3030-3702, 3030-3702
Nashr sanasi2026-05-14
Jild4
Son5
Betlar30-36
TilIngliz
Ilmiy sohaTexnika
DOI10.47390/ts-v4i5y2026n05
Indeksga qo‘shilgan2026-08-26

DOI: 10.47390/ts-v4i5y2026n05 · Maqolaning asl sahifasi

Kalit so‘zlar

remote sensing; Sentinel-2; NDVI; EVI; GNDVI; CVI; Random Forest; Gradient Boosting; Isolation Forest; crop monitoring, дистанционное зондирование; Sentinel-2; NDVI; EVI; GNDVI; CVI; Random Forest; Gradient Boosting; Isolation Forest; мониторинг посевов

Ilmiy soha

Texnika

Iqtibos keltirish

APAAytmuratov , Bakbergen, & Orazımbetov , Temurbek (2026). MONITORING THE CONDITION OF AGRICULTURAL LANDS IN THE NUKUS DISTRICT BASED ON MULTISPECTRAL VEGETATION INDICES AND MACHINE LEARNING METHODS. Techscience.uz - техника фанлари долзарб масалалри, 4(5), 30-36. https://doi.org/10.47390/ts-v4i5y2026n05
GOST (OAK)Aytmuratov , Bakbergen, Orazımbetov , Temurbek MONITORING THE CONDITION OF AGRICULTURAL LANDS IN THE NUKUS DISTRICT BASED ON MULTISPECTRAL VEGETATION INDICES AND MACHINE LEARNING METHODS // Techscience.uz - техника фанлари долзарб масалалри. – 2026. – T. 4, № 5. – P. 30-36. – DOI: 10.47390/ts-v4i5y2026n05.
MLAAytmuratov , Bakbergen, and Orazımbetov , Temurbek. “MONITORING THE CONDITION OF AGRICULTURAL LANDS IN THE NUKUS DISTRICT BASED ON MULTISPECTRAL VEGETATION INDICES AND MACHINE LEARNING METHODS.” Techscience.uz - техника фанлари долзарб масалалри, 4(5), 30-36, 2026. https://doi.org/10.47390/ts-v4i5y2026n05
ChicagoAytmuratov , Bakbergen, and Orazımbetov , Temurbek. “MONITORING THE CONDITION OF AGRICULTURAL LANDS IN THE NUKUS DISTRICT BASED ON MULTISPECTRAL VEGETATION INDICES AND MACHINE LEARNING METHODS.” Techscience.uz - техника фанлари долзарб масалалри, 4(5), 30-36 (2026). https://doi.org/10.47390/ts-v4i5y2026n05
HarvardAytmuratov , Bakbergen, and Orazımbetov , Temurbek (2026) ‘MONITORING THE CONDITION OF AGRICULTURAL LANDS IN THE NUKUS DISTRICT BASED ON MULTISPECTRAL VEGETATION INDICES AND MACHINE LEARNING METHODS’, Techscience.uz - техника фанлари долзарб масалалри, 4(5), 30-36. https://doi.org/10.47390/ts-v4i5y2026n05
BibTeX
@article{aytmuratovbakbergen2026,
  title = {MONITORING THE CONDITION OF AGRICULTURAL LANDS IN THE NUKUS DISTRICT BASED ON MULTISPECTRAL VEGETATION INDICES AND MACHINE LEARNING METHODS},
  author = {Aytmuratov , Bakbergen and Orazımbetov , Temurbek},
  journal = {Techscience.uz - техника фанлари долзарб масалалри},
  year = {2026},
  volume = {4},
  number = {5},
  pages = {30-36},
  doi = {10.47390/ts-v4i5y2026n05},
  url = {https://doi.org/10.47390/ts-v4i5y2026n05}
}

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