Wetland identification through remote sensing: insights into wetness, greenness, turbidity, temperature, and changing landscapes

RW Aslam, H Shu, K Javid, S Pervaiz, F Mustafa… - Big Data Research, 2024‏ - Elsevier
Wetlands are important in many ways, including hydrological cycles, ecosystem diversity,
climate change, and economic activity. Despite the Ramsar Convention's awareness …

Modelling of land use and land cover changes and prediction using CA-Markov and Random Forest

M Asif, JH Kazmi, A Tariq, N Zhao… - Geocarto …, 2023‏ - Taylor & Francis
Abstract We used the Cellular Automata Markov (CA-Markov) integrated technique to study
land use and land cover (LULC) changes in the Cholistan and Thal deserts in Punjab …

ResMorCNN model: hyperspectral images classification using residual-injection morphological features and 3DCNN layers

M Esmaeili, D Abbasi-Moghadam… - IEEE Journal of …, 2023‏ - ieeexplore.ieee.org
Hyperspectral imagery is widely used for analyzing substances and objects, specifically
focusing on their classification. The advancement of processing capabilities and the …

Machine learning algorithms for satellite image classification using Google Earth Engine and Landsat satellite data: Morocco case study

H Ouchra, A Belangour, A Erraissi - IEEE Access, 2023‏ - ieeexplore.ieee.org
Earth observation data have proven to be a valuable resource of quantitative information
that is more consistent in time and space than traditional land-based surveys. Remote …

Road extraction from satellite images using attention-assisted UNet

A Akhtarmanesh, D Abbasi-Moghadam… - IEEE Journal of …, 2023‏ - ieeexplore.ieee.org
These days, extracting information from remote sensing data has a great impact on various
aspects of our lives, such as infrastructure and urban planning, transportation and traffic …

[HTML][HTML] Evaluation of soil texture classification from orthodox interpolation and machine learning techniques

L Feng, U Khalil, B Aslam, B Ghaffar, A Tariq… - Environmental …, 2024‏ - Elsevier
The current investigation examines the effectiveness of various approaches in predicting the
soil texture class (clay, silt, and sand contents) of the Rawalpindi district, Punjab province …

[HTML][HTML] Assessment of climatic influences on net primary productivity along elevation gradients in temperate ecoregions

K Mehmood, SA Anees, A Rehman, NU Rehman… - Trees, Forests and …, 2024‏ - Elsevier
Elevation gradients significantly influence net primary productivity (NPP), but the relationship
between elevation, climate variables, and vegetation productivity remains underexplored …

A methodology to assess and evaluate sites with high potential for stormwater harvesting in Dehradun, India

S Pathak, S Sharma, A Banerjee, S Kumar - Big Data Research, 2024‏ - Elsevier
The urgency to protect natural water resources in a sustainable manner has risen as water
scarcity and global climate change continue to worsen. Among various methods of collecting …

Wind turbine gearbox oil temperature feature extraction and condition monitoring based on energy flow

X Bai, S Han, Z Kang, T Tao, C Pang, S Dai, Y Liu - Applied Energy, 2024‏ - Elsevier
Abstract Supervisory Control and Data Acquisition (SCADA) data is widely used for wind
turbine gearbox condition monitoring (WTGCM) due to its easy access and low cost, thus …

Assessing climatic impacts on land use and land cover dynamics in Peshawar, Khyber Pakhtunkhwa, Pakistan: a remote sensing and GIS approach

RW Aslam, I Naz, A Quddoos, MR Quddusi - GeoJournal, 2024‏ - Springer
This study investigates the land use and land cover (LULC) changes in Peshawar, Pakistan,
from 2002 to 2022, and their relationship with local climate patterns. Utilizing a combination …