[HTML][HTML] Google Earth Engine: a global analysis and future trends

A Velastegui-Montoya, N Montalván-Burbano… - Remote Sensing, 2023 - mdpi.com
The continuous increase in the volume of geospatial data has led to the creation of storage
tools and the cloud to process data. Google Earth Engine (GEE) is a cloud-based platform …

The application of hyperspectral remote sensing imagery (HRSI) for weed detection analysis in rice fields: A review

N Sulaiman, NN Che'Ya, MH Mohd Roslim… - Applied Sciences, 2022 - mdpi.com
Weeds are found on every cropland across the world. Weeds compete for light, water, and
nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and …

Modelling, map** and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote …

A Tariq, Y Jiango, Q Li, J Gao, L Lu, W Soufan… - Heliyon, 2023 - cell.com
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 …

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

M Majeed, L Lu, MM Anwar, A Tariq, S Qin… - Frontiers in …, 2023 - frontiersin.org
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 …

Multiscale dual-branch residual spectral–spatial network with attention for hyperspectral image classification

S Ghaderizadeh, D Abbasi-Moghadam… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
The development of remote sensing images in recent years has made it possible to identify
materials in inaccessible environments and study natural materials on a large scale. But …

Assessing spatio-temporal map** and monitoring of climatic variability using SPEI and RF machine learning models

SS Wahla, JH Kazmi, A Sharifi, SA Shirazi… - Geocarto …, 2022 - Taylor & Francis
Droughts may inflict significant damage to agricultural and water supplies, resulting in
substantial financial losses as well as the death of people and livestock. This study intends …

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 …

Map** and monitoring of spatio-temporal land use and land cover changes and relationship with normalized satellite indices and driving factors

SS Wahla, JH Kazmi, A Tariq - Geology, Ecology, and Landscapes, 2023 - Taylor & Francis
Climate change has become a severe threat all around the world. Pakistan is also affected
by climate change. It has become a severe problem in any part of the country. It is land …

Crop classification for agricultural applications in hyperspectral remote sensing images

L Agilandeeswari, M Prabukumar, V Radhesyam… - Applied Sciences, 2022 - mdpi.com
Hyperspectral imaging (HSI), measuring the reflectance over visible (VIS), near-infrared
(NIR), and shortwave infrared wavelengths (SWIR), has empowered the task of classification …

Modeling and predicting land use land cover spatiotemporal changes: A case study in chalus watershed, Iran

S Jalayer, A Sharifi… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Land use and land cover (LULC) change is a main driver of global environmental change
and has destructive effects on the structure and function of the ecosystem. This study …