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Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction.

This work is focused on the use of line-scan thermography (LST) method for the inspection of an ancient book cover. Three widely used image post-processing techniques (i.e., pulsed phase thermography, partial least square thermography and principal component thermography) were applied to the acquired thermal sequences. Flash thermography (FT) anticipated the LST results in order to have a comparison of the results. It was concluded that LST is an effective technique for paper-based materials, and it can additionally provide a higher image contrast if compared to classical FT technique.

Accurate and quantitative profiling of air particulate matter (PM) compositions is essential for assessing local pollution information. The method combining mobile aerial sampling using unmanned aerial vehicles (UAVs) and prompt analysis excels in this regard as it allows spatiotemporal mapping of air pollution, especially in the vertical direction. However, applications of the method are still scarce as it is limited by a lack of sampling reliability due to insufficient aerial sampling time and a lack of accurate, portable quantification techniques. In this work, by integrating mobile aerial sampling with in-flight tethered charging and smartphone-based colorimetric analysis in a cost-effective paper microfluidic device, we present a method for quantitative, reliable profiling of spatiotemporal variation in air PM compositions. The method extends aerial sampling time to 12–15 flight hours per deployment, thereby significantly improving sampling reliability while maintaining the maneuverability of the UAVs. Also, smartphone-based colorimetric analysis combined with paper-based microfluidics enables portable, economically efficient analysis and is well-suited for using in low-resource settings. We demonstrated the utility of the method by carrying out a spatiotemporal variation study of air PM trace metal components (Fe, Ni, and Mn) at 4 geographical locations in Fuzhou, China, for a period of 21 days, and the results were in good agreement with results obtained from using a commercial instrument. Beside air PM composition study, this method is universally applicable and holds great potential to be extended to multipollutant analysis, such as prompt detection of airborne viruses, bacteria, and others.

All LIDAR instruments are not the same, and advancement of LIDAR technology requires an ongoing interest and demand from the community to foster further development of the required components. The ...

International audience; Coral reefs are an essential source of marine biodiversity, but they are declining at an alarming rate under the combined effects of global change and human pressure. A precise mapping of coral reef habitat with high spatial and time resolutions has become a necessary step for monitoring their health and evolution. This mapping can be achieved remotely thanks to satellite imagery coupled with machine-learning algorithms. In this paper, we review the different satellites used in recent literature, as well as the most common and efficient machine-learning methods. To account for the recent explosion of published research on coral reel mapping, we especially focus on the papers published between 2018 and 2020. Our review study indicates that object-based methods provide more accurate results than pixel-based ones, and that the most accurate methods are Support Vector Machine and Random Forest. We emphasize that the satellites with the highest spatial resolution provide the best images for benthic habitat mapping. We also highlight that preprocessing steps (water column correction, sunglint removal, etc.) and additional inputs (bathymetry data, aerial photographs, etc.) can significantly improve the mapping accuracy.

Emergent tobacco products such as heated tobacco remain largely unregulated in many countries menacing the progress of tobacco control achieved in the last decades. They are being aggressively marketed by the industry as products of “reduced risk” and “smoking cessation tools” or smoke-free alternatives to smoking conventional cigarettes. WHO stresses that heated tobacco products are tobacco products and are therefore subject to the provisions of the WHO-FCTC. To date, there is growing independent research showing that these products are not harmless. However, a dangerous debate has re-launched harm reduction in the field of tobacco control and is splitting scientists, the public health community and society as large. Healthcare professional organizations have a crucial role to play in tobacco control. The European Respiratory Society (ERS), as a leading medical Society, has paved the way on tobacco control advocacy in Europe and worldwide. This presentation will present the ERS position on heated tobacco products, including the evidence regarding their toxicity, addictive potential and potential impact on public health.

This database is the supplementary material of Tasseron et al., (2022): 'Towards Robust River Plastic Detection: Combining Lab and Field-based Hyperspectral Imagery' [Submitted and currently under review], preprint available online at https://doi.org/10.31223/X5RW7V. The dataset contains raw images, MATLAB scripts used for training classifier algorithms, trained pipelines, required toolboxes and labelled training datasets used in subsequent analyses.

This study focuses on the risk of pollen allergy due to paper mulberry (Broussonetia papyrifera L.), an Asian invasive plant species now common in large parts of the world. Pollen plays a key role in the pathogenesis of respiratory allergic diseases, particularly rhinitis and asthma, and Islamabad, a major metropolitan city, is severely affected by allergy owing to B. papyrifera pollen. Due to its seasonality and other relationships with climatic variables, we used remote sensing to monitor the trend of pollen count. We also mapped the localisation of patients affected by pollen allergy using geographic information systems. The maximum likelihood algorithm was applied to SPOT-5 satellite imagery for land use/land cover classification. Temporal analysis of remotely sensed data revealed an increasing trend of paper mulberry density towards the southern and south-western part of Islamabad. Although not evident during rainfall, a clear positive correlation was found between patient count and pollen count. Field survey data and hotspot spatial analysis of allergy patients revealed that residents of Shakerperiyan and Lok Virsa areas (Sectors H-8, I-8, I-9, G-8, G-7 and G-6 in Islamabad) had more pronounced symptoms compared to residents of other sectors. The methodology adopted used in this study can be used to map the distribution of similar invasive species in other parts of the country.

Code and Data Availability of the paper: Mapping tree diversity in the tropical forest region of Chocó-Colombia Published at Environmental Research Letters: https://doi.org/10.1088/1748-9326/abf58a J Camilo Fagua1, Patrick Jantz1, Patrick Burns1, Richard Massey1, Jeiner Y Buitrago2, Sassan S. Saatchi3, Christopher Hakkenberg1 and Scott J. Goetz1 1 Global Earth Observation & Dynamics of Ecosystems Lab (GEODE), School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University, Flagstaff, Arizona, US. 2 Department of Agronomy, Faculty of Agricultural Sciences, Universidad Nacional de Colombia. Bogota (Colombia). 3 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA *Corresponding author: J. Camilo Fagua, School of Informatics, Computing, and Cyber Systems (Building #90) 1295 S. Knoles Dr. Flagstaff, AZ 86011. Email: Camilo.Fagua@nau.edu and camilo.fagua77@gmail.com 1) The files “1_Forest_Structure_maps_in_tif” contain seven maps of forest structural metrics for the Chocó region of Colombia at 50m of spatial resolution in the raster format .tif (a) Canopy height (CH) map: CHOCO_MAP_CH (b) 50th percentile of heights (z_50) map: CHOCO_MAP_z_50 (c) Vertical Canopy Heterogeneity (VCH) map: CHOCO_MAP_VCH (d) Standard deviation of normalized heights (z_SD) map: CHOCO_MAP_z_SD (e) Horizontal standard deviation of canopy height (CH_ SD): CHOCO_MAP_CH_SD (f) Horizontal heterogeneity of canopy height (CH_H): CHOCO_MAP_CH_H (g) Rumple Index of canopy height (R_INDEX): CHOCO_MAP_R_INDEX 2) The file “2_Diversity_maps_in_tif” contains five maps of forest structural metrics for the Chocó region of Colombia at 50m of spatial resolutionin the raster format .tif (a) Species richness (Richness): MAPS_MEAN_Richness (b) Shannon’s entropy index (ENS-Shannon): MAPS_MEAN_ENS_shannon (c) Simpson’s concentration index (ENS-Simpson): MAPS_MEAN_ENS_Simpson (d) Shannon diversity index (H): MAPS_MEAN_Shannon (e) Simpson diversity index (D): MAPS_MEAN_Simpson 3) The file “3_LiDAR_processing” contents data and R codes to estimate forest structural metrics from ALS-LiDAR data (.las) in an A

We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimating their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register. ESA support through the COCCON-PROCEEDS and COCCON-PROCEEDS II projects. In addition, this research was funded by the Ministerio de Economía y Competitividad from Spain through the INMENSE project (CGL2016-80688-P). This research has largely benefit from funds of the Deutsche Forschungsgemeinschaft (provided for the two projects MOTIV and TEDDY with IDs/290612604 and 416767181, respectively).

This database is the supplementary material of Tasseron et al., (2021): Advancing floating plastic detection from space using hyperspectral imagery.

Many long-term geomagnetic observation results recorded on photographic bromide paper have not yet been fully digitized. To that end, we developed a method to automatically convert photographic records to one-minute digital data. We applied our method to the observation records of Kakioka Magnetic Observatory and confirmed that the resolution of time and amplitude could be greatly improved by numerical conversion compared with conventional data conversion by hand scaling. Our results suggest that highly precise digitization of analog magnetograms is possible.

A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Spaceborne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on Bayesian optimal estimation relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission, and uses an empirically corrected absorption continuum in the O2 A-band. For airmasses below 3.0, XCO2 retrievals successfully capture the latitudinal variations of CO2, as well as its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a difference of 1.33 ± 1.29 ppm, which is similar to the standard deviation of the Atmospheric CO2 Observations from Space (ACOS) official products. We show that the systematic differences between 5AI and ACOS results can be fully removed by adding an average calculated – observed spectral residual correction to OCO-2 measurements, thus underlying the critical sensitivity of retrieval results to forward modelling. These comparisons show the reliability of 5AI as a Bayesian optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry-air mole fractions of greenhouse gases. This work has received funding from CNES and CNRS.

Due to sampling restrictions in the analysis of cultural heritage materials, non-destructive approaches are intensively sought for. While NIR spectrometry has rarely been used for this purpose due to the complexity of the spectra, chemometric methods can be used to extract the necessary information. For the purpose of determination of mechanical properties of historical paper, partial least squares approach was used and it is shown that tensile strength, and tensile strength after folding, can be estimated based on NIR spectra. As the mechanical properties of paper-based objects define their accessibility, a new dispersive portable instrument was built, which will enable us to rapidly survey the condition of library and archival collections.

In this study, 33 pieces of WSP were placed along three lines in a paddy. An M-18B Dromader AG aircraft flew and sprayed over the field, and the spray deposits were collected by water sensitive paper. Seven greyscale parameters were used to compare the color depth, deviation and homogeneity of digital water sensitive images. The greyscale images were converted to binary images with five threshold selection methods. The results of recognition of seven greyscale parameters and five threshold methods were compared to analyze the droplets in different scanned images on water sensitive paper. The effects of the threshold on the computation of deposit density and the stain size were evaluated. The most suitable grey scale was found to be luminosity. Finally, a manual validation was performed, and the relationship between the threshold and the stain size of was analyzed.

We have investigated the problem of underwater hazy image enhancement and restoration in this paper studied. Underwater image processing has several applications in the field of oceanic research work and scientific applications such as archaeology, geology, underwater environmental assessment, laying of long distance gas pipelines and communication links across the continents which demand geo-referential surveying of the oceanic bed and prospection of ancient shipwreck. There are many difficulties for undersea optical imaging. To submerging a camera in underwater enough space is required. The maneuvering of the camera with the help from remote place or in person at the site is likewise a complex task. However, the major challenge is imposed by underwater medium properties. Underwater haze image enhancement has gained widespread importance with the rapid development of modern imaging equipment. Though, the contrast enhancement of single underwater hazy image is a cumbersome task for scientific exploration and computational application. At extreme depth, because of attenuation in light propagation, the underwater images are susceptible to inferior visibility.

The recent paper by Morillas et al. [Morillas, L. et al. Using radiometric surface temperature for surface energy flux estimation in Mediterranean drylands from a two-source perspective, Remote Sens. Environ. 136, 234–246, 2013] evaluates the two-source model (TSM) of Norman et al. (1995) with revisions by Kustas and Norman (1999) over a semiarid tussock grassland site in southeastern Spain. The TSM - in its current incarnation, the two-source energy balance model (TSEB) - was applied to this landscape using ground-based infrared radiometer sensors to estimate both the composite surface radiometric temperature and component soil and canopy temperatures. Morillas et al. (2013) found the TSEB model substantially underestimated the sensible H (and overestimated the latent heat LE) fluxes. Using the same data set from Morillas et al. (2013), we were able to confirm their results. We also found energy transport and exchange behavior derived from primarily the observations themselves to differ significantly from a number of prior studies using land surface temperature for estimating heat fluxes with one-source modeling approaches in semi-arid landscapes. However, revisions to key vegetation inputs to TSEB and the soil resistance formulation resulted in a significant reduction in the bias and root mean square error (RMSE) between model output of H and LE and the measurements compared to the prior results from Morillas et al. (2013). These included more representative ground-based vegetation greenness and local leaf area index values as well as modifications to the coefficients of the soil resistance formulation to account for the very rough (rocky) soil surface conditions with a clumped canopy. This indicates that both limitations in remote estimates of biophysical indicators of the canopy at the site and the lack of adjustment in soil resistance formulation to account for site specific characteristics, contributed to the earlier findings of Morillas et al. (2013). This suggests further studies need to be conducted to reduce the uncertainties in the vegetation and land surface temperature input data in order to more accurately assess the effects of the transport exchange processes of this Mediterranean landscape on TSEB formulations.

Telescope slew and settle time markedly reduces the efficiency of wide-field multi-epoch surveys for sensitive interferometers with small fields of view. The overheads can be mitigated through the use of On-the-Fly Mosaicing (OTFM), where the the antennas are driven at a non-sidereal rate and visibilities are recorded continuously. Here we introduce the OTFM technique for the VLA, and describe its implementation for the Caltech-NRAO Stripe 82 Survey (CNSS), a dedicated 5-epoch survey for slow transients at S band (2-4 GHz). We also describe the OTFSim tool for planning dynamically-scheduled OTFM observations on the VLA, the latest imaging capabilities for OTFM in CASA, and present a comparison of OTFM observations with pointed observations. Using the subset of our observations from the CNSS pilot and final surveys, we demonstrate that the wide-band and wide-field OTFM observations with the VLA can be imaged accurately, and that this technique offers a more efficient alternative to standard mosaicing for multi-epoch shallow surveys such as the CNSS and the VLA Sky Survey (VLASS). We envisage that the new OTFM mode will facilitate new synoptic surveys and high-frequency mapping experiments on the VLA., 15 pages, 14 figures, Accepted for publication in ApJ

This short film, “From a Sheet of Paper to the Sky”, grew out of research that I conducted for an essay of the same title, written for the catalogue accompanying the Paul Nash exhibition at Tate Britain (October 2016 to March 2017). In that essay, I argued against the traditional art historical tendency to review an artist’s work in different media separately, and instead proposed that a consideration of Paul Nash’s painting alongside his three-dimensional and textile designs, his printmaking, and photography, resulted in a fuller understanding of both the conceptual underpinnings and the recurring visual motifs in Nash’s work.

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies.

In order to determine the absolute accuracy of SRMT model on Polish area the research work has been performed on the basis of reference terrain profiles measured by GPS technique. The flat and hilly terrains were examined in administrative borders of fourteen provinces. It was not reference data for mountainous terrains. For the analysis of accuracy of the SRTM model 332 terrain profiles and 29,308 points have been measured. The accuracy of SRTM model presented by RMSE was computed on the basic of the height differences between profiles and models homolog points. The analyses have been done in Modular GIS Environment Intergraph software. The absolute accuracy of SRTM model on Polish area RMSE Z = 2.9 m for flat regions and RMSE Z = 5.4 m for hilly regions were achieved. It was affirmed that this accuracy is depend on the resolution of grid points of DEM and terrain inclination. The statistic estimation showed systematic shift between SRTM data and reference profiles. The RMSE Z without systematic part was found to be 1.0 m for flat regions and 2.7 m for hilly regions of Polish area. The data of SRTM level DTED-1 could be used for DEM and contour lines generation on the topographic maps in scales smaller then 1:50,000 and for SRTM system calibration.