Relação entre os constituintes do solo e seu comportamento espectral Relationship between the soil constituents and its spectral behavior

A reflectância espectral de solos é a expressão que registra o fluxo de radiação eletromagnética refletida pelo solo em relação ao fluxo radiante. Como os solos apresentam diferentes constituintes, os mesmos podem ser identificados e em certos casos quantificados pela análise de sua resposta espectral. Os principais constituintes dos solos que influenciam seu comportamento espectral são a matéria orgânica, óxidos de ferro, argilominerais, além da distribuição granulométrica e umidade. A utilização da reflectância espectral visando obter informações na identificação e quantificação de características do solo de maneira rápida e não invasiva, tanto em nível laboratorial como em nível orbital, tem ocorrido principalmente em países desenvolvidos. No Brasil, o interesse de pesquisadores pelo estudo do comportamento espectral de solos vem crescendo desde a década de 80 do século passado, sendo esta linha de pesquisa relativamente jovem e necessitada de suporte de pesquisa para melhor entendimento dos efeitos da interação da energia eletromagnética entre os diferentes componentes do solo.<br>The spectral soil reflectance is an expression that characterizes the electromagnetic radiation reflected by soil surface. Most of the soil constituents can be identified and sometimes quantified by the spectral behavior. The main soil constituents that influence its spectral behavior are the organic matter, iron oxides, mineralogy and clay content and moisture. The use of soil reflectance allows to obtain information to quickly identify and quantify the soil characteristics, both in laboratory and orbital levels, but it has been tested and used mainly in developed countries. In Brazil, the research interest for the study of the soil spectral reflectance started in the 1980’s, being a recent research area which needs research support to achieve a better understanding of the spectral interaction among the different components of the soil

Mapping tropical forest degradation with deep learning and Planet NICFI data

International audienceTropical rainforests from the Brazilian Amazon are frequently degraded by logging, fire, edge effects and minor unpaved roads. However, mapping the extent of degradation remains challenging because of the lack of frequent high-spatial resolution satellite observations, occlusion of understory disturbances, quick recovery of leafy vegetation, and limitations of conventional reflectance-based remote sensing techniques. Here, we introduce a new approach to map forest degradation caused by logging, fire, and road construction based on deep learning (DL), henceforth called DL-DEGRAD, using very high spatial (4.77 m) and bi-annual to monthly temporal resolution of the Planet NICFI imagery. We applied DL-DEGRAD model over forests of the state of Mato Grosso in Brazil to map forest degradation with attributions from 2016 to 2021 at six-month intervals. A total of 73,744 images (256 × 256 pixels in size) were visually interpreted and manually labeled with three semantic classes (logging, fire, and roads) to train/validate a U-Net model. We predicted the three classes over the study area for all dates, producing accumulated degradation maps biannually. Estimates of accuracy and areas of degradation were performed using a probability design-based stratified random sampling approach (n = 2678 samples) and compared it with existing operational data products at the state level. DL-DEGRAD performed significantly better than all other data products in mapping logging activities (F1-score = 68.9) and forest fire (F1-score = 75.6) when compared with the Brazil's national maps (SIMEX, DETER, MapBiomas Fire) and global products (UMD-GFC, TMF, FireCCI, FireGFL, GABAM, MCD64). Pixel-based spatial comparison of degradation areas showed the highest agreement with DETER and SIMEX as Brazil official data products derived from visual interpretation of Landsat imagery. The U-Net model applied to NICFI data performed as closely to a trained human delineation of logged and burned forests, suggesting the methodology can readily scale up the mapping and monitoring of degraded forests at national to regional scales. Over the state of Mato Grosso, the combined effects of logging and fire are degrading the remaining intact forests at an average rate of 8443 km2 year−1 from 2017 to 2021. In 2020, a record degradation area of 13,294 km2 was estimated from DL-DEGRAD, which was two times the areas of deforestation

Safety of hospital discharge before return of bowel function after elective colorectal surgery

© 2020 BJS Society Ltd Published by John Wiley & Sons LtdBackground: Ileus is common after colorectal surgery and is associated with an increased risk of postoperative complications. Identifying features of normal bowel recovery and the appropriateness for hospital discharge is challenging. This study explored the safety of hospital discharge before the return of bowel function. Methods: A prospective, multicentre cohort study was undertaken across an international collaborative network. Adult patients undergoing elective colorectal resection between January and April 2018 were included. The main outcome of interest was readmission to hospital within 30 days of surgery. The impact of discharge timing according to the return of bowel function was explored using multivariable regression analysis. Other outcomes were postoperative complications within 30 days of surgery, measured using the Clavien–Dindo classification system. Results: A total of 3288 patients were included in the analysis, of whom 301 (9·2 per cent) were discharged before the return of bowel function. The median duration of hospital stay for patients discharged before and after return of bowel function was 5 (i.q.r. 4–7) and 7 (6–8) days respectively (P < 0·001). There were no significant differences in rates of readmission between these groups (6·6 versus 8·0 per cent; P = 0·499), and this remained the case after multivariable adjustment for baseline differences (odds ratio 0·90, 95 per cent c.i. 0·55 to 1·46; P = 0·659). Rates of postoperative complications were also similar in those discharged before versus after return of bowel function (minor: 34·7 versus 39·5 per cent; major 3·3 versus 3·4 per cent; P = 0·110). Conclusion: Discharge before return of bowel function after elective colorectal surgery appears to be safe in appropriately selected patients