Glaciers are considered fundamental natural features as they provide services like water provision, flow regulation, flood mitigation, and biodiversity conservation. Furthermore, due to their complex nature, they provide crucial insights into the ongoing climate change dynamics as they respond to temperature and precipitation variations. Even though this has promoted the increase of glaciology research in the last few years, glacierized regions, such as the Patagonian Andes, are still barely studied due to their harsh environmental conditions and the general lack of interest from international scientific communities. Specifically, the Patagonian Andes, which is an important water supplier and economic driver in South America, is still poorly known, even though it is the largest glacierized area in the region, with more than 20000 km? distributed in the Northern and Southern Patagonian Icefields. Therefore, this research aimed to explore the potential of remote sensing data and techniques, cloud computing, and 3D visualization methods to overcome the lack of studies in the Patagonian Andes and to promote public interest in these natural ecosystems. For this purpose, a Google Earth Engine web application was developed to allow the creation, visualization, and export of remote-sensing and time series products for the Patagonian region. Moreover, with this application, a time-series analysis was performed to estimate the glacier area, Land Surface Temperature, and air temperature changes for 83 Patagonian glaciers, using Landsat 8-9, Sentinel-2, and ERA5-Land Imagery for the summer periods between 2018 and 2023. In addition, a 3D web application was developed using CesiumJS to compare and visualize the outputs from the Google Earth Engine application interactively with a full 3D perspective. As a result of the time-series analysis, with 1245 summer composites and 249 time-series charts generated, an overall retreat of the glaciers and increased temperature were observed. Furthermore, the developed web applications proved to be efficient, attractive, and user-friendly for creating and visualizing glacier remote sensing products. This study is a step toward improving the glaciology knowledge of the Patagonia region by providing insight into the current Patagonian glacier status, delivering customizable open-source web applications, and promoting glaciers' public interest through 3D experiences.Glaciers are considered fundamental natural features as they provide services like water provision, flow regulation, flood mitigation, and biodiversity conservation. Furthermore, due to their complex nature, they provide crucial insights into the ongoing climate change dynamics as they respond to temperature and precipitation variations. Even though this has promoted the increase of glaciology research in the last few years, glacierized regions, such as the Patagonian Andes, are still barely studied due to their harsh environmental conditions and the general lack of interest from international scientific communities. Specifically, the Patagonian Andes, which is an important water supplier and economic driver in South America, is still poorly known, even though it is the largest glacierized area in the region, with more than 20000 km? distributed in the Northern and Southern Patagonian Icefields. Therefore, this research aimed to explore the potential of remote sensing data and techniques, cloud computing, and 3D visualization methods to overcome the lack of studies in the Patagonian Andes and to promote public interest in these natural ecosystems. For this purpose, a Google Earth Engine web application was developed to allow the creation, visualization, and export of remote-sensing and time series products for the Patagonian region. Moreover, with this application, a time-series analysis was performed to estimate the glacier area, Land Surface Temperature, and air temperature changes for 83 Patagonian glaciers, using Landsat 8-9, Sentinel-2, and ERA5-Land Imagery for the summer periods between 2018 and 2023. In addition, a 3D web application was developed using CesiumJS to compare and visualize the outputs from the Google Earth Engine application interactively with a full 3D perspective. As a result of the time-series analysis, with 1245 summer composites and 249 time-series charts generated, an overall retreat of the glaciers and increased temperature were observed. Furthermore, the developed web applications proved to be efficient, attractive, and user-friendly for creating and visualizing glacier remote sensing products. This study is a step toward improving the glaciology knowledge of the Patagonia region by providing insight into the current Patagonian glacier status, delivering customizable open-source web applications, and promoting glaciers' public interest through 3D experiences.