Hyperspectral remote sensing reflectance (Rrs) derived from PRISMA in the visible and infrared range was evaluated for two inland and coastal water sites using above-water in situ reflectance measurements from autonomous hyper- and multispectral radiometer systems. We compared the Level 2D (L2D) surface reflectance, a standard product distributed by the Italian Space Agency (ASI), as well as outputs from ACOLITE/DSF, now adapted for processing of PRISMA imagery. Near-coincident Sentinel-3 OLCI (S3/OLCI) observations were also compared as it is a frequent data source for inland and coastal water remote sensing applications, with a strong calibration and validation record. In situ measurements from two optically diverse sites in Italy, equipped with fixed autonomous hyperspectral radiometer systems, were used: the REmote Sensing for Trasimeno lake Observatory (RESTO), positioned in a shallow and turbid lake in Central Italy, and the Acqua Alta Oceanographic Tower (AAOT), located 15 km offshore from the lagoon of Venice in the Adriatic Sea, which is characterised by clear to moderately turbid waters. 20 PRISMA images were available for the match-up analysis across both sites. Good performance of L2D was found for RESTO, with the lowest relative (Mean Absolute Percentage Difference, MAPD 25\%) and absolute errors (Bias 0.002) in the bands between 500 and 680 nm, with similar performance for ACOLITE. The lowest median and interquartile ranges of spectral angle (SA 8°) denoted a more similar shape to the RESTO in situ data, indicating pigment absorption retrievals should be possible. ACOLITE showed better statistical performance at AAOT compared to L2D, providing R2 0.5, Bias 0.0015 and MAPD 35\%, in the range between 470 and 580 nm, i.e. in the spectral range with highest reflectances. The addition of a SWIR based sun-glint correction to the default atmospheric correction implemented in ACOLITE further improved performance at AAOT, with lower uncertainties and closer spectral similarity to the in situ measurements, suggesting that ACOLITE with glint correction was able to best reproduce the spectral shape of in situ data at AAOT. We found good results for PRISMA Rrs retrieval in our study sites, and hence demonstrated the use of PRISMA for aquatic ecosystem mapping. Further studies are needed to analyse performance in other water bodies, over a wider range of optical properties.
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Abstract Ants, an ecologically successful and numerically dominant group of animals, play key ecological roles as soil engineers, predators, nutrient recyclers, and regulators of plant growth and reproduction in most terrestrial ecosystems. Further, ants are widely used as bioindicators of the ecological impact of land use. We gathered information of ant species in the Atlantic Forest of South America. The ATLANTIC ANTS data set, which is part of the ATLANTIC SERIES data papers, is a compilation of ant records from collections (18,713 records), unpublished data (29,651 records), and published sources (106,910 records; 1,059 references), including papers, theses, dissertations, and book chapters published from 1886 to 2020. In total, the data set contains 153,818 ant records from 7,636 study locations in the Atlantic Forest, representing 10 subfamilies, 99 genera, 1,114 ant species identified with updated taxonomic certainty, and 2,235 morphospecies codes. Our data set reflects the heterogeneity in ant records, which include ants sampled at the beginning of the taxonomic history of myrmecology (the 19th and 20th centuries) and more recent ant surveys designed to address specific questions in ecology and biology. The data set can be used by researchers to develop strategies to deal with different macroecological and region-wide questions, focusing on assemblages, species occurrences, and distribution patterns. Furthermore, the data can be used to assess the consequences of changes in land use in the Atlantic Forest on different ecological processes. No copyright restrictions apply to the use of this data set, but we request that authors cite this data paper when using these data in publications or teaching events.
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