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Machine learning algorithms for satellite image classification using Google Earth Engine and Landsat satellite data: Morocco case study
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 …
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
Geo-spatial artificial intelligence (GeoAI) is an interdisciplinary field that combines
techniques and methods from engineering, computer science, statistics, and space science …
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
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 …
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
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 …
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
Urbanization often results in the conversion of agricultural land and natural vegetation into
built-up areas, posing challenges for sustainable development and environmental …
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 …
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 …
environmental management. This paper presents a methodology for the unsupervised …
Unsupervised learning for land cover map** of casablanca using multispectral imaging
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 …
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 …
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
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 …
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
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 …
algorithms in the classification of land cover in Casablanca, Morocco, utilizing Landsat …