Plate-like CDots/EuBDC nanocomposite for ratiometric luminescence thermometry

The synthesis of dual-emission nanocomposite materials has emerged as an excellent strategy for designing new and advanced luminescent ratiometric thermometers. In the present work, a dual-emission nanocomposite material based on carbon dots (CDots), with chitosan as the precursor, and Europium–Organic Framework (CDots/EuBDC) was prepared, through ultrasonic synthesis, and applied as a ratiometric thermometer. Whereas the as-synthesized nanocomposite maintains the crystalline structure of EuBDC, its thermal stability increases and the surface area decreases due to the CDots incorporation. The ratio of the CDots/EuBDC emission intensities (ICDots/IEu) is temperature-dependent in the 293 to 348 K range, in which the intensity of the Eu3+ 5D0 → 7F2 transition works as a reference signal. The CDots/EuBDC luminescent thermometer shows a maximum relative thermal sensitivity of 1.58% K−1 at 293 K and a colorimetric temperature response with (x, y) CIE color coordinates ranging from blue (0.36, 0.27), at 293 K, to orange (0.43, 0.30), at 343 K.publishe

Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil