Sieve Analytics
for global solutions
Land Mapper is a web application that greatly simplifies remote sensing analyses of land use land cover mapping. The user will have access to images from a diversity of sensors, without having to download or process them. In addition, Land Mapper provides tools for defining classes, creating model training and validation samples, creating maps, and evaluating map accuracy. You can try the system here, and if you need more information, please Contact Us.
Land Use Land Cover Mapping
Land Mapper
DESCRIPTION
Land Mapper web application
The Land Mapper web application provides you with tools for creating maps of land cover land use from a diversity of remote sensing data sources (e.g. MODIS, Landsat, QuickBird). The application includes an easy and intuitive interface for creating classification algorithms that will allow you to map land use change across continents to the details of urban expansion. There is no cost for using the web application, but we will charge when you download classification rasters. The cost will be based on the number of pixels (US$ pixel $0.001) in your study region. Please request a quote for country or regional scale projects.
The recent explosion of private satellites and drones are generating a massive amount of remote sensed images. Similar, to the problem of too many acoustic recording to analyze, there are now millions of images from around the world, but no good way to organize and process them. Our research has used satellite images to study land use change (e.g. deforestation) in Latin America, urban expansion in Latin America and Africa, and agricultural expansion in South America. These studies have used medium resolution images (MODIS – 250 m resolution) to study processes at the continental scale to very high resolution images (Quickbird < 2 m resolution) for urban planning. These are just a few of the many ways that remote images can be used. Unfortunately, there are very high barriers for conducting analyses of satellite imagery. Some of the most important barriers are the need for a high level of remote sensing expertise and expensive computer storage and processing capacity. We have made major steps to reduce these barriers with our web application Land Mapper.