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 …

An overview of GeoSpatial Artificial Intelligence technologies for city planning and development

H Ouchra, A Belangour… - 2023 Fifth International …, 2023‏ - ieeexplore.ieee.org
Geo-spatial artificial intelligence (GeoAI) is an interdisciplinary field that combines
techniques and methods from engineering, computer science, statistics, and space science …

[PDF][PDF] Comparison of machine learning methods for satellite image classification: A case study of Casablanca using Landsat imagery and Google Earth Engine

H Ouchra, A Belangour… - … of Environmental & …, 2023‏ - pdfs.semanticscholar.org
Satellite image classification is crucial in various applications such as urban planning,
environmental monitoring, and land use analysis. In this study, the authors present a …

Assessing machine learning algorithms for land use and land cover classification in Morocco using google earth engine

H Ouchra, A Belangour, A Erraissi… - … Conference on Image …, 2023‏ - Springer
Abstract Google Earth Engine constitutes a cloud-based geospatial data processing
platform. It grants free access to vast volumes of satellite data along with unlimited …

Geospatial insights into urban growth and land cover transformation in Anantapur city, India

PK Badapalli, AB Nakkala, S Gugulothu… - Environment …, 2024‏ - Springer
Urbanization often results in the conversion of agricultural land and natural vegetation into
built-up areas, posing challenges for sustainable development and environmental …

[PDF][PDF] Comparing Unsupervised Land Use Classification of Landsat 8 OLI Data Using K-means and LVQ Algorithms in Google Earth Engine: A Case Study of …

H Ouchra, A Belangour, A Erraissi - International Journal of …, 2023‏ - journals.sfu.ca
Accurate and up-to-date land use information is essential for effective urban planning and
environmental management. This paper presents a methodology for the unsupervised …

Unsupervised learning for land cover map** of casablanca using multispectral imaging

H Ouchra, A Belangour… - 2024 ASU International …, 2024‏ - ieeexplore.ieee.org
Precise and current land use data hold immense significance in facilitating efficient urban
planning and appropriate environmental oversight. This paper proposes an approach to the …

[PDF][PDF] Multigenerational Urban Design: Creating Urban Spaces That Support Active Aging and Intergenerational Interaction.

SA Abdulmunem, ME Shok… - International Journal …, 2024‏ - researchgate.net
This demographic shift within cities, specifically in the neighborhood of Al-Adhamiya, in
Baghdad City makes it vital to develop public spaces that accommodate a mix of people …

Exploring google earth engine platform for satellite image classification using machine learning algorithms

H Ouchra, A Belangour, A Erraissi - The Proceedings of the International …, 2023‏ - Springer
Abstract Google Earth Engine is a geospatial data processing platform that runs in the cloud.
It offers free access to massive amounts of satellite data as well as unlimited computing …

[PDF][PDF] Supervised machine learning algorithms for land cover classification in Casablanca, Morocco

H Ouchra, A Belangour, A Erraissi - Ingenierie des Systemes d' …, 2024‏ - researchgate.net
This study embarks on an evaluation of the efficacy of six supervised machine learning
algorithms in the classification of land cover in Casablanca, Morocco, utilizing Landsat …