David Savory

GEOGRAPHIC information systems (GIS) and related technologies are changing the way soils-related data are compiled and used. Digital elevation models, image processing, and integration of multiple data sources with GIS are currently providing valuable information in the soils mapping process ( 4 ). The spatial analysis capability of GIS is suited for modeling and monitoring soil and water conservation related phenomena ( 2, 6 ). GIS plays an increasingly important role in the implementation and enforcement of soil and water conservation regulations ( 7, 8 ). The automation of soils maps has provided a wealth of information for a variety of applications, including land management, planning, site selection, construction regulations, zoning, and taxation. GISs are not without problems, however. They can be costly to implement and operate. In addition to hardware and software, data automation and maintenance costs can be substantial. GISs are technically complex, requiring staff with sk...

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the...