Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements

Accurate land cover information is required for science, monitoring, and reporting. Land cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring and mapping of land cover and land cover change in a consistent and robust manner over large areas is made possible with Earth Observation (EO) data. Land cover products satisfying a range of science and policy information needs are currently produced periodically at different spatial and temporal scales. The increased availability of EO data—particularly from the Landsat archive (and soon to be augmented with Sentinel-2 data)—coupled with improved computing and storage capacity with novel image compositing approaches, have resulted in the availability of annual, large-area, gap-free, surface reflectance data products. In turn, these data products support the development of annual land cover products that can be both informed and constrained by change detection outputs. The inclusion of time series change in the land cover mapping process provides information on class stability and informs on logical class transitions (both temporally and categorically). In this review, we present the issues and opportunities associated with generating and validating time-series informed annual, large-area, land cover products, and identify methods suited to incorporating time series information and other novel inputs for land cover characterization

Light detection and ranging (LiDAR) technology provides horizontal and vertical information at high spatial resolutions and vertical accuracies. Forest attributes such as canopy height can be directly retrieved from LiDAR data. Direct retrieval of canopy height provides opportunities to model above-ground biomass and canopy volume. Access to the vertical nature of forest ecosystems also offers new opportunities for enhanced forest monitoring, management and planning.