GE Grids is intended to complement existing remote sensing datasets at local scales. Zoom to your house or anywhere else then dive in for a 360° perspective with Street View. This enabled the analysis of brushstrokes and retrieval of the matching image efficiently without the need for a server. Machine learning and line detection algorithms were used to preprocess all images and identify the dominant lines. The two highest-resolution comparative datasets have the greatest agreement with our own at the regional extent, despite having as low as 44% agreement at the country level. Explore the whole world from above with satellite imagery, 3D terrain of the entire globe and 3D buildings in hundreds of cities around the world. Land Lines lets you explore Google Earth satellite images through gesture. Nearly 30% of East Africa is converted to anthropogenic land cover. Using GE Grids, we manually identified anthropogenic land conversion across East Africa and compared this against available land cover datasets. This tool creates an interactive user-specified binary grid laid over Google Earth's high-resolution imagery. We thus introduce a new tool, GE Grids, to bridge this gap. Additionally, global medium-resolution land use land cover datasets may be insufficient for conservation planning purposes at the scale of a country or smaller.
However, accessing localized information can be difficult or impossible in developing countries. Effective conservation planning relies on the accurate identification of anthropogenic land cover.
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