Broadband emissivity (BBE) is an important variable in the evaluation of the energy budget and can be provided by the remote sensing products. As one of the commonly used BBE products, global land surface satellite (GLASS) AVHRR BBE and MODIS BBE are quite different. In this study, a new framework of AVHRR BEE estimation based on GLASS MODIS BBE is developed by introducing the more detailed soil datasets, the consideration of hemisphere and season, and the global selection of sampling points into the modeling. After our modification of the original GLASS AVHRR BBE, the modified BBE significantly eliminates the discrepancies between GLASS AVHRR and MODIS BEEs during 2001–2019, especially in summer and winter (0.004 decline of discrepancies), in the extreme arid and moist region [0.002 decline of discrepancies when aridity index (AI)4], in the high altitude area (0.01 decline of discrepancies when DEM >5000 m) and in some desert regions (0.005 decline of discrepancies when albedo >0.5). In addition, the application of our framework can significantly improve the performance of the original GLASS AVHRR BBE before 2000 when the GLASS MODIS BEEs is unavailable. Our framework is helpful for the reliable application of GLASS BBE and can provide a more satisfactory BBE product in a long time series (near to 40 years).

Mobile apps have become indispensable in our daily lives, but many apps are not designed to be energy-aware that they may consume the constrained resources on mobile devices in a wasteful manner. Blindly throttling heavy resource usage, while helps reducing energy consumption, prohibits apps from taking advantages of the resources to do useful work. We argue that addressing this issue requires mobile OS to continuously assess if a resource is still truly needed even after it is granted to an app.