An application of 1D convolution and deep learning to remote sensing modelling of Secchi depth in the northern Adriatic Sea

A Ivanda, L Šerić, D Žagar, K Oštir - Big earth data, 2024 - Taylor & Francis
This paper presents a novel approach for predicting the water quality indicator–Secchi disk
depth (ZSD). ZSD indirectly reflects water clarity and serves as a proxy for other quality …

Flood susceptibility mapping through geoinformatics and ensemble learning methods, with an emphasis on the AdaBoost-Decision Tree algorithm, in Mazandaran …

M Jahanbani, MH Vahidnia, H Aghamohammadi… - Earth Science …, 2024 - Springer
Floods, as natural disasters, impose significant human and financial burdens, necessitating
stringent mitigation measures. The recurrent annual incidence of floods precipitates …

Using Deep Learning and Cloud Services for Mapping Agricultural Fields on the Basis of Remote Sensing Data of the Earth

NR Ermolaev, SA Yudin, VP Belobrov… - … and Oceanic Physics, 2023 - Springer
In recent years, research has been conducted in scientific institutions of the Ministry of
Agriculture of the Russian Federation and the Russian Academy of Sciences on introducing …

Development and Research of Models for Optimization Information Flow in Interactive Analysis Big Data in Geographic Information Systems

AAH Alrammahi, FAO Sari, BK Hilal - International Conference on …, 2023 - Springer
A large number of areas of application of geographic information systems (GIS) involves the
continuous accumulation data. The need to record the state of an observed object or …

Use of Deep Learning and Cloud Services for Mapping Agricultural Fields on the Example on the Base of Remote Sensing Data of the Earth

NR Ermolaev, SA Yudin, VP Belobrov… - … Zemli iz Kosmosa, 2023 - journals.rcsi.science
In recent years, research has been conducted in scientific institutions of the Ministry of
Agriculture of the Russian Federation and the Russian Academy of Sciences on the …