Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Laszlo Mucsi"'
Autor:
Khilola Amankulova, Nizom Farmonov, Enas Abdelsamei, Jozsef Szatmari, Waleed Khan, Mohamed Zhran, Jamshid Rustamov, Sharifboy Akhmedov, Maksudxon Sarimsakov, Laszlo Mucsi
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13694-13707 (2024)
This study aimed to develop a new method for combining Sentinel-2 and PlanetScope (PS) imagery. The normalized difference vegetation indices (NDVI) data were retrieved from the Earth observation satellites S2 Level-2A and PS Level-3 surface reflectan
Externí odkaz:
https://doaj.org/article/a2aab4c8ef234bf8946545c2058c5b43
Autor:
Nizom Farmonov, M. Esmaeili, Dariush Abbasi-Moghadam, Alireza Sharifi, Khilola Amankulova, Laszlo Mucsi
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11969-11996 (2024)
The advent of cloud computing and advanced processing technologies has elevated deep learning (DL) as a leading method for hyperspectral imaging (HSI) classification. Classifying crops accurately is vital for generating precise agricultural data to s
Externí odkaz:
https://doaj.org/article/25bd4e1810a047a3833124f44ec3f944
Autor:
Nizom Farmonov, Khilola Amankulova, Jozsef Szatmari, Alireza Sharifi, Dariush Abbasi-Moghadam, Seyed Mahdi Mirhoseini Nejad, Laszlo Mucsi
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 1576-1588 (2023)
Developments in space-based hyperspectral sensors, advanced remote sensing, and machine learning can help crop yield measurement, modelling, prediction, and crop monitoring for loss prevention and global food security. However, precise and continuous
Externí odkaz:
https://doaj.org/article/d6870c73785b414fb101db92c9a3978f
Autor:
Khoirunisa, Risty, Laszlo, Mucsi
Publikováno v:
Geographica: Science and Education Journal; Vol 2, No 1 (2020): December; 1-9
Forest fire is a hazard that common to happen in Indonesia every year, whether from natural or human-induced factor. These fires can be uncontrollable and destruct the forest. Furthermore, these can affect the health of the people, the biodiversity,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=usnpublisher::71be9034738eb03f59f9cc543d9f2a34
http://www.usnsj.com/index.php/geographica/article/view/1293
http://www.usnsj.com/index.php/geographica/article/view/1293
Effectiveness of machine learning and deep learning models at county-level soybean yield forecasting
Autor:
Nizom Farmonov, Khilola Amankulova, Shahid Nawaz Khan, Mokhigul Abdurakhimova, József Szatmári, Tukhtaeva Khabiba, Radjabova Makhliyo, Meiliyeva Khodicha, László Mucsi
Publikováno v:
Hungarian Geographical Bulletin, Vol 72, Iss 4, Pp 383-398 (2023)
Crop yield forecasting is critical in modern agriculture to ensure food security, economic stability, and effective resource management. The main goal of this study was to combine historical multisource satellite and environmental datasets with a dee
Externí odkaz:
https://doaj.org/article/67772623fc064166bbc667fbef933d9c
Autor:
Nizom Farmonov, Khilola Amankulova, József Szatmári, Jamol Urinov, Zafar Narmanov, Jakhongir Nosirov, László Mucsi
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 1, Pp 847-867 (2023)
Satellite images are widely used for crop yield estimation, but their coarse spatial resolution means that they often fail to provide detailed information at the field scale. Recently, a new generation of high-resolution satellites and CubeSat platfo
Externí odkaz:
https://doaj.org/article/0f6003868b93410fb7788bba70817180
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Timely crop yield information is needed for agricultural land management and food security. We investigated using remote sensing data from the Earth observation mission Sentinel-2 to monitor the crop phenology and predict the crop yield of sunflowers
Externí odkaz:
https://doaj.org/article/656cfcf2e5534d28bd3551efa013db7e
Autor:
Dang Hung Bui, László Mucsi
Publikováno v:
Hungarian Geographical Bulletin, Vol 71, Iss 4, Pp 349-364 (2022)
The main purpose of this study is to simulate future land use up to 2030 and to evaluate the change in landscape pattern due to land-use change from 1995 to 2030 in Binh Duong province, Vietnam. Land-use maps generated from multi-temporal Landsat ima
Externí odkaz:
https://doaj.org/article/75bd12c7b15d4156aa7487261e9d34f2
Publikováno v:
Heliyon, Vol 9, Iss 6, Pp e17432- (2023)
Accurate timely and early-season crop yield estimation within the field variability is important for precision farming and sustainable management applications. Therefore, the ability to estimate the within-field variability of grain yield is crucial
Externí odkaz:
https://doaj.org/article/154fca15308d4d0dbc11f96eb8be9259