This article focuses on the computation of the GNDVI and CVI vegetation indices, which exhibit high sensitivity to vegetation condition, particularly to chlorophyll content. It is also noted that the module architecture is based on a pipeline approach, which ensures modularity, scalability, and robustness in the processing of large volumes of satellite imagery. The implementation includes computational optimization as well as integration with a geospatial PostgreSQL/PostGIS database.
| Mualliflar | Seitnazarov, K.K., Madirimova, S.M., Turemuratova, B.K., Aitmuratov, B.B., Сеитназаров, К.К., Мадиримова, С.М., Туремуратова, Б.К., Айтмуратов, Б.Б., Сеитназаров, К.К., Мадиримова, С.М., Туремуратова, Б.К., Айтмуратов, Б.Б. |
|---|---|
| Jurnal | Ilim ha’m ja’miyet |
| Nashr sanasi | 2026-02-16 |
| Son | 1-1 |
| Betlar | 36-39 |
| Til | Rus |
дистанционное зондирование Земли, мультиспектральные изображения, предварительная обработка данных, вегетационные индексы, GNDVI, CVI, атмосферная коррекция, экспертные системы, геоинформационные технологии, ернинг масофадан зондланиши, мультиспектрал тасвирлар, маълумотларни даслабки қайта ишлаш, вегетацион индекслар, GNDVI, CVI, атмосфера коррекцияси, эксперт тизимлари, геоинформацион технологиялар, earth remote sensing, multispectral imagery, data preprocessing, vegetation indices, GNDVI, CVI, atmospheric correction, expert systems, geoinformation technologies
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