A contemporary review on deep learning models for drought prediction
Deep learning models have been widely used in various applications, such as image and
speech recognition, natural language processing, and recently, in the field of drought …
speech recognition, natural language processing, and recently, in the field of drought …
Drought classification and prediction with satellite image-based indices using variants of deep learning models
S Chaudhari, V Sardar, P Ghosh - International Journal of Information …, 2023 - Springer
Drought factors vary with climate regions. Drought prediction and classification require
vegetation indices, which are computed based on these characteristics. Satellite images can …
vegetation indices, which are computed based on these characteristics. Satellite images can …
Vineyard gap detection by convolutional neural networks fed by multi-spectral images
This paper focuses on the gaps that occur inside plantations; these gaps, although not
having anything growing in them, still happen to be watered. This action ends up wasting …
having anything growing in them, still happen to be watered. This action ends up wasting …
Sustainable management for healthy and productive watersheds in Indonesia
Indonesian watershed management continues to struggle with various problems caused by
natural disasters, particularly hydrometeorological disasters, which are worsened by the …
natural disasters, particularly hydrometeorological disasters, which are worsened by the …
Web Scraping of Disease Information from social media Twitter
Environmental degradation caused by land conversion, trash (both domestic and industrial),
and natural catastrophes is all variables that contribute to the establishment of disease …
and natural catastrophes is all variables that contribute to the establishment of disease …
The application of machine learning using Google Earth Engine for remote sensing analysis
MI Habibie - Jurnal Teknoinfo, 2022 - ejurnal.teknokrat.ac.id
The spatial dimensions and temporal resolutions of the change detection analyses have
been limited by traditional methodologies (ie, desktop computing, open source). For …
been limited by traditional methodologies (ie, desktop computing, open source). For …
Active actions in the extraction of urban objects for information quality and knowledge recommendation with machine learning
Due to the increasing urban development, it has become important for municipalities to
permanently understand land use and ecological processes, and make cities smart and …
permanently understand land use and ecological processes, and make cities smart and …
The assessment of random forest algorithm in identifying paddy growth stage in Karawang, West Java
E Gunawan, NF Masnur, NI Afkharinah… - … and Remote Sensing …, 2022 - ieeexplore.ieee.org
This study tried to estimate distribution and area of land cover by focusing on the area of the
paddy growing phase using the Random Forest model on Sentinel 1A data and Area Frame …
paddy growing phase using the Random Forest model on Sentinel 1A data and Area Frame …
A Multicriteria Index using Neural Network to Evaluate the Potential Lands of Maize
MI Habibie, N Nurda - Jurnal Teknoinfo, 2022 - ejurnal.teknokrat.ac.id
The criteria for planting maize should be consistent with sensible and ecological criteria to
determine the potential lands. However, there is still a lack of proven methodology for this …
determine the potential lands. However, there is still a lack of proven methodology for this …
Mapping and Monitoring Urban Areas Using Sentinel 1 and Sentinel 2
City expansion is characterized by population increase and advancement in space
requirements, which results in a city's inability to accommodate its people's activities …
requirements, which results in a city's inability to accommodate its people's activities …