Application of machine learning in water resources management: A systematic literature review
In accordance with the rapid proliferation of machine learning (ML) and data management,
ML applications have evolved to encompass all engineering disciplines. Owing to the …
ML applications have evolved to encompass all engineering disciplines. Owing to the …
Crop type classification by DESIS hyperspectral imagery and machine learning algorithms
N Farmonov, K Amankulova, J Szatmári… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Developments in space-based hyperspectral sensors, advanced remote sensing, and
machine learning can help crop yield measurement, modelling, prediction, and crop …
machine learning can help crop yield measurement, modelling, prediction, and crop …
Land change modeler and CA-Markov chain analysis for land use land cover change using satellite data of Peshawar, Pakistan
Urbanization is a global phenomenon that caused many regions worldwide to face dramatic
Land Use Land Cover (LULC) changes associated with urban sprawl and significant …
Land Use Land Cover (LULC) changes associated with urban sprawl and significant …
Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of …
This research aims to assess the urban growth and impact on land surface temperature
(LST) of Lahore, the second biggest city in Pakistan. In this research, various geographical …
(LST) of Lahore, the second biggest city in Pakistan. In this research, various geographical …
[HTML][HTML] Spatio-temporal variation in surface water in Punjab, Pakistan from 1985 to 2020 using machine-learning methods with time-series remote sensing data and …
A Tariq, S Qin - Agricultural Water Management, 2023 - Elsevier
Pakistan is home to many natural and artificial bodies of water, which are inevitable for
agriculture, domestic use, recreation, etc. In the arid, semi-arid, and wet areas of the land …
agriculture, domestic use, recreation, etc. In the arid, semi-arid, and wet areas of the land …
Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data
Flash floods are the most dangerous kinds of floods because they combine the destructive
power of a flood with incredible speed. They occur when heavy rainfall exceeds the ability of …
power of a flood with incredible speed. They occur when heavy rainfall exceeds the ability of …
Modelling, map** and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote …
The present study is designed to monitor the spatio-temporal changes in forest cover using
Remote Sensing (RS) and Geographic Information system (GIS) techniques from 1990 to …
Remote Sensing (RS) and Geographic Information system (GIS) techniques from 1990 to …
Spatial downscaling of GRACE data based on XGBoost model for improved understanding of hydrological droughts in the Indus Basin Irrigation System (IBIS)
Climate change may cause severe hydrological droughts, leading to water shortages which
will require to be assessed using high-resolution data. Gravity Recovery and Climate …
will require to be assessed using high-resolution data. Gravity Recovery and Climate …
Hyperspectral image band selection based on CNN embedded GA (CNNeGA)
Hyperspectral images (HSIs) are a powerful source of reliable data in various remote
sensing applications. But due to the large number of bands, HSI has information …
sensing applications. But due to the large number of bands, HSI has information …
Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms
The landscape of Pakistan is vulnerable to flood and periodically affected by floods of
different magnitudes. The aim of this study was aimed to assess the flash flood susceptibility …
different magnitudes. The aim of this study was aimed to assess the flash flood susceptibility …