The main purpose of this work is to explore a reproducible way of replacing manual digitalizations of urban agglomerations using textural image processing from free high-resolution Google Earth images. Photo-interpretation from very high-resolution satellite images is a reliable method for extracting ...
Discover how to enhance these images for better clarity and insight into weather patterns.Spaceship earth What's up with the light and dark areas, the monotony, and the dull shades of grey? Or moving gray patches in a satellite photo? It would be more obvious if you increased the contrast...
Google Earth is the right choice. You can essentially view detailed satellite images of the area, and explore the location on the ground. It’s a great way to plan out your walking tours, choose the best locations to see in person and identify hidden gems you’d have a hard time finding...
A new interactive approach is presented and implemented for constructing 3D city models from Google Earth and ground images. Using the roof size provided by Google Earth and the image coordinates of the four corner points of the building rectangular facade, without any prior knowledge about the par...
In this guide we summarize how to use the Best Available Pixel (BAP) image compositing application in Google Earth Engine (GEE): GEE-BAP. This GEE application enables the generation of annual BAP image composites for large areas combining multiple Landsat sensors and images. Herein we describe ...
For this purpose, supported by the Google Earth Engine (GEE) platform and machine-learning approach, our study selected the long-term series remote sensing images, and used Support Vector Machine (SVM) classifier to extract land use datasets, both multiple linear regression (MLR) and random ...
I have noticed that, from Google Maps page, you can get an "embed" link to put inside an iframe and load the map in a browser. (no news here) The image size can be adjusted to be very large, so I am interested in getting som big images as single .PNGs. More specifically, I ...
A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping - giswqs/earthengine-py-notebooks
(900 m2) resolution pixels to our 50 km × 50 km resolution pixels using Google Earth Engine. For each 50 km × 50 km pixel, we calculated the total area lost between 2000 and 2013 and the area lost as a proportion of the area in 2000. We restricted our analysis...
The images were downloaded from the Copernicus Open Access Hub, but are also available as cloud-masked mosaics using Google Earth Engine (Schmitt et al., 2019) and via the Sentinelsat API. A common scaling factor was applied to all the S2 images, and all of the bands were then resampled ...