scholarly journals Evaluation of SEBS, METRIC-EEFlux, and QWaterModel Actual Evapotranspiration for a Mediterranean Cropping System in Southern Italy

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 345
Author(s):  
Zaibun Nisa ◽  
Muhammad Sarfraz Khan ◽  
Ajit Govind ◽  
Marco Marchetti ◽  
Bruno Lasserre ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Southern Italy ◽  
Cropping System ◽  
Global Scale ◽  
Development Stage ◽  
User Friendly ◽  
Climate Studies ◽  
Cropland Ecosystems ◽  
Statistical Indicators

Remote sensing-based evapotranspiration (ET) models with various levels of sophistication have emerged recently with the possibilities of user-defined model calibrations. Their application for water resources management and climate studies from regional to global scale has been rapidly increasing, which makes it important to validate field scale ET in a complex crop assemblage before operational use. Based on in situ flux-tower measurements by the eddy-covariance (EC) system, this study tested three single-source energy balance models for estimating daily ET from fennel/maize/ryegrass-clover cropland rotations in a Mediterranean context in southern Italy. The sensitivity of three user-friendly ET models (SEBS, QWaterModel, and METRIC-EEFlux) with reference to the EC system over a center pivot irrigated cropland is discussed in detail. Results in terms of statistical indicators revealed that SEBS and METRIC-EEFlux showed reasonable agreements with measured ET (r2 = 0.59SEBS, RMSE = 0.71 mm day−1; r2 = 0.65METRIC, RMSE = 1.13 mm day−1) in terms of trends and magnitudes. At 30 m spatial resolution, both models were able to capture the in-field variations only during the maize development stage. The presence of spurious scan lines due to sensor defects in Landsat L7 ETM+ can contribute to the qualities of the METRIC-Efflux’s ET product. In our observation, the QWaterModel did not perform well and showed the weakest congruency (r2 = 0.08QWaterModel) with ground-based ET estimates. In a nutshell, the study evaluated these automated remote sensing-based ET estimations and suggested improvements in the context of a generic approach used in their underlying algorithm for robust ET retrievals in rotational cropland ecosystems.

scholarly journals Global scale variability of the mineral dust long-wave refractive index: a new dataset of in situ measurements for climate modeling and remote sensing

2017 ◽  
Vol 17 (3) ◽  
pp. 1901-1929 ◽  
Author(s):  
Claudia Di Biagio ◽  
Paola Formenti ◽  
Yves Balkanski ◽  
Lorenzo Caponi ◽  
Mathieu Cazaunau ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Refractive Index ◽  
Size Distribution ◽  
Climate Models ◽  
Mineral Dust ◽  
Complex Refractive Index ◽  
Mineralogical Composition ◽  
Global Scale ◽  
Long Wave

Abstract. Modeling the interaction of dust with long-wave (LW) radiation is still a challenge because of the scarcity of information on the complex refractive index of dust from different source regions. In particular, little is known about the variability of the refractive index as a function of the dust mineralogical composition, which depends on the specific emission source, and its size distribution, which is modified during transport. As a consequence, to date, climate models and remote sensing retrievals generally use a spatially invariant and time-constant value for the dust LW refractive index. In this paper, the variability of the mineral dust LW refractive index as a function of its mineralogical composition and size distribution is explored by in situ measurements in a large smog chamber. Mineral dust aerosols were generated from 19 natural soils from 8 regions: northern Africa, the Sahel, eastern Africa and the Middle East, eastern Asia, North and South America, southern Africa, and Australia. Soil samples were selected from a total of 137 available samples in order to represent the diversity of sources from arid and semi-arid areas worldwide and to account for the heterogeneity of the soil composition at the global scale. Aerosol samples generated from soils were re-suspended in the chamber, where their LW extinction spectra (3–15 µm), size distribution, and mineralogical composition were measured. The generated aerosol exhibits a realistic size distribution and mineralogy, including both the sub- and super-micron fractions, and represents in typical atmospheric proportions the main LW-active minerals, such as clays, quartz, and calcite. The complex refractive index of the aerosol is obtained by an optical inversion based upon the measured extinction spectrum and size distribution. Results from the present study show that the imaginary LW refractive index (k) of dust varies greatly both in magnitude and spectral shape from sample to sample, reflecting the differences in particle composition. In the 3–15 µm spectral range, k is between ∼ 0.001 and 0.92. The strength of the dust absorption at ∼ 7 and 11.4 µm depends on the amount of calcite within the samples, while the absorption between 8 and 14 µm is determined by the relative abundance of quartz and clays. The imaginary part (k) is observed to vary both from region to region and for varying sources within the same region. Conversely, for the real part (n), which is in the range 0.84–1.94, values are observed to agree for all dust samples across most of the spectrum within the error bars. This implies that while a constant n can be probably assumed for dust from different sources, a varying k should be used both at the global and the regional scale. A linear relationship between the magnitude of the imaginary refractive index at 7.0, 9.2, and 11.4 µm and the mass concentration of calcite and quartz absorbing at these wavelengths was found. We suggest that this may lead to predictive rules to estimate the LW refractive index of dust in specific bands based on an assumed or predicted mineralogical composition, or conversely, to estimate the dust composition from measurements of the LW extinction at specific wavebands. Based on the results of the present study, we recommend that climate models and remote sensing instruments operating at infrared wavelengths, such as IASI (infrared atmospheric sounder interferometer), use regionally dependent refractive indices rather than generic values. Our observations also suggest that the refractive index of dust in the LW does not change as a result of the loss of coarse particles by gravitational settling, so that constant values of n and k could be assumed close to sources and following transport. The whole dataset of the dust complex refractive indices presented in this paper is made available to the scientific community in the Supplement.

scholarly journals An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4285 ◽  
Author(s):  
Shubha Sathyendranath ◽  
Robert Brewin ◽  
Carsten Brockmann ◽  
Vanda Brotas ◽  
Ben Calton ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Marine Ecosystem ◽  
Ocean Colour ◽  
Remote Sensing Reflectance ◽  
Resolution Imaging ◽  
In Situ Observations ◽  
Climate Studies ◽  
Reflectance Data

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

scholarly journals Accomplishments of the MUSICA project to provide accurate, long-term, global and high-resolution observations of tropospheric {H<sub>2</sub>O,<i>δ</i>D} pairs – a review

2016 ◽  
Vol 9 (7) ◽  
pp. 2845-2875 ◽  
Author(s):  
Matthias Schneider ◽  
Andreas Wiegele ◽  
Sabine Barthlott ◽  
Yenny González ◽  
Emanuel Christner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Measurement Techniques ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Horizontal Resolution ◽  
Atmospheric Composition ◽  
Remote Sensing Techniques ◽  
Middle Infrared

Abstract. In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

A new method of PWV retrieval over land with remote sensing data: a case of AMSR2

2020 ◽  
Author(s):  
Nan Jiang ◽  
Yan Xu ◽  
Tianhe Xu
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Global Climate ◽  
Weather Prediction ◽  
Remote Sensing Data ◽  
Precipitable Water ◽  
Global Scale ◽  
Brightness Temperatures ◽  
Climate Studies

&lt;p&gt;Precipitable water vapor (PWV) is an important parameter reflecting the amount of solid water in the atmosphere, which is widely utilized in the studies of numerical weather prediction (NWP) and climate change. The microwave radiance measurements made by the space-based remote sensing satellites give us the opportunity to make the climate studies on a global scale. So far, PWV retrieval over the ocean has a long data record and the technology is very mature, but in the case of PWV retrieval over land, it is more challenging to isolate the atmospheric signals from the varied surface signals. In this study, we will apply a new retrieval method over land based on the dual-polarized difference (vertical and horizontal) at 19 GHz and 23 GHz using the brightness temperatures from the Global Change Observation Mission-Water (GCOM-W)/Advanced Microwave Scanning Radiometer 2 (AMSR2). We found polarization difference in brightness temperatures has an exponential relation on the amount of PWV. The validation results of the PWV retrieval from the ground-based GNSS stations show that the proposed method has a mean accuracy of 3.9 mm. Thus, the proposed method can give a possibility to improve the accuracy of data assimilation in the NWP applications and is useful for the studies of global climate change with the long-term data records.&lt;/p&gt;

scholarly journals Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

2019 ◽  
Vol 11 (20) ◽  
pp. 2356 ◽  
Author(s):  
Angela Lausch ◽  
Jussi Baade ◽  
Lutz Bannehr ◽  
Erik Borg ◽  
Jan Bumberger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Cost Effective ◽  
Global Scale ◽  
Soil Characteristics ◽  
Monitoring Methods ◽  
In Situ Techniques ◽  
The Face ◽  
Remote Sensing Techniques

In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

scholarly journals Global scale variability of the mineral dust longwave refractive index: a new dataset of in situ measurements for climate modelling and remote sensing

2016 ◽  
Author(s):  
Claudia Di Biagio ◽  
Paola Formenti ◽  
Yves Balkanski ◽  
Lorenzo Caponi ◽  
Mathieu Cazaunau ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Refractive Index ◽  
Size Distribution ◽  
Climate Models ◽  
Mineral Dust ◽  
Complex Refractive Index ◽  
Mineralogical Composition ◽  
Global Scale ◽  
Source Regions

Abstract. Modelling the interaction of dust with longwave (LW) radiation is still a challenge due to the scarcity of information on the complex refractive index of dust from different source regions. In particular, little is known on the variability of the refractive index as a function of the dust mineralogical composition, depending on the source region of emission, and the dust size distribution, which is modified during transport. As a consequence, to date, climate models and remote sensing retrievals generally use a spatially-invariant and time-constant value for the dust LW refractive index. In this paper the variability of the mineral dust LW refractive index as a function of its mineralogical composition and size distribution is explored by in situ measurements in a large smog chamber. Mineral dust aerosols were generated from nineteen natural soils from Northern Africa, Sahel, Middle East, Eastern Asia, North and South America, Southern Africa, and Australia. Soil samples were selected from a total of 137 samples available in order to represent the diversity of sources from arid and semi-arid areas worldwide and to account for the heterogeneity of the soil composition at the global scale. Aerosol samples generated from soils were re-suspended in the chamber, where their LW extinction spectra (2–16 µm), size distribution, and mineralogical composition were measured. The generated aerosol exhibits a realistic size distribution and mineralogy, including both the sub- and super-micron fractions, and represents in typical atmospheric proportions the main LW-active minerals, such as clays, quartz, and calcite. The complex refractive index of the aerosol is obtained by an optical inversion based upon the measured extinction spectrum and size distribution. Results from the present study show that the LW refractive index of dust varies greatly both in magnitude and spectral shape from sample to sample, following the changes in the measured particle composition. The real part (n) of the refractive index is between 0.84 and 1.94, while the imaginary part (k) is ~ 0.001 and 0.92. For instance, the strength of the absorption at ~ 7 and 11.4 µm depends on the amount of calcite within the samples, while the absorption between 8 and 14 µm is determined by the relative abundance of quartz and clays. A linear relationship between the magnitude of the refractive index at 7.0, 9.2, and 11.4 µm and the mass concentration of calcite and quartz absorbing at these wavelengths was found. We suggest that this may lead to predictive rules to estimate the LW refractive index of dust in specific bands based on an assumed or predicted mineralogical composition, or conversely, to estimate the dust composition from measurements of the LW extinction at specific wavebands. Based on the results of the present study, we recommend using refractive indices specific for the different source regions, rather than generic values, in climate models and remote sensing applications. Our observations also suggest that the refractive index of dust in the LW does not change due to the loss of coarse particles by gravitational settling, so that a constant value could be assumed close to sources and during transport. The results of the present study also clearly suggest that the LW refractive index of dust varies at the regional scale. This regional variability has to be characterized further in order to better assess the influence of dust on regional climate, as well as to increase the accuracy of satellite retrievals over regions affected by dust. We make the whole dataset of the dust complex refractive indices obtained here available to the scientific community by publishing it in the supplementary material to this paper.

scholarly journals A framework for accurate, long-term, global and high resolution observations of tropospheric H<sub>2</sub>O-δD pairs – a MUSICA review

2016 ◽  
Author(s):  
M. Schneider ◽  
A. Wiegele ◽  
S. Barthlott ◽  
Y. González ◽  
E. Christner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Measurement Techniques ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Horizontal Resolution ◽  
Atmospheric Composition ◽  
Sensing Data ◽  
Middle Infrared

Abstract. Abstract. In the lower/middle troposphere H2O-δD pairs are good proxies for moisture pathways, however their observation is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating remote sensing with in-situ measurement techniques. The aim is to retrieve accurate tropospheric H2O-δD pairs from the middle infrared spectra measured from ground by the FTIR (Fourier Transform InfraRed) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper we review the MUSICA framework, present the final MUSICA products, and outline the NDACC/FTIR’s and METOP/IASI’s potential for observing accurate and consistent H2O-δD data pairs. First, we briefly resume the particularities of an H2O-δD pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in-situ profile references measured in the subtropics, between 0 and 7 km. Third, we empirically demonstrate that the calibrated remote sensing H2O-δD pairs can identify different lower/middle tropospheric moisture pathways and advert to the risk of misinterpretations caused by an incorrect processing of such remote sensing data. Fourth, we reveal that the different sensors (NDACC/FTIR instruments, MetOp/IASI-A, and MetOp/IASI-B) provide consistent H2O-δD pairs for very distinct atmospheric clear sky conditions. Fifth, we document the unique possibilities of the NDACC/FTIR instruments for providing long-term records (important for climatological studies) and of the MetOp/IASI sensors for observing diurnal signals on quasi global scale and with high horizontal resolution.

Assessment of Falanghina vine status at different spatial and temporal scales by means of a smart multiple spatial and temporal resolution system

2020 ◽  
Author(s):  
Anna Brook ◽  
Antonello Bonfante ◽  
Nicola Damiano ◽  
Chiara Cirillo ◽  
Giovanna Battipaglia ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Health Status ◽  
Southern Italy ◽  
Environmental Changes ◽  
Dynamic Assessment ◽  
Physiological Status ◽  
Vitis Vinifera L ◽  
Campania Region

&lt;p&gt;Sustainable grapevine cultivation and the stable production of high-quality wine is endangered by climate change in many areas of the Mediterranean region. Climate change is expected to induce rising temperatures, changes in precipitation frequency and increasing occurrence of extreme events such as severe and prolonged drought with direct effects on berry production and composition, and consequently wine quality. In this context, the monitoring and dynamic assessment of vine status with an early detection of health decline signs are needed to evaluate and adopt mitigation actions oriented to precision and sustainable agriculture (e.g., irrigation).&lt;/p&gt;&lt;p&gt;Several indicators are reported in literature to evaluate plant health status (e.g., Ref. MAES reports), based on remote sensing, UAV techniques or in situ data collection. With remote sensing technologies, standardized information, over large areas, at low costs and with high temporal coverage, can be acquired, allowing assessment of plant indicators trends in a practical, repetitive and comparative way. However, data processing techniques do not fully reflect the overall physiological status and healthiness of plant systems. On the other hand, in situ morpho-physiological analyses at the single plant level are time-consuming and restricted to a low number of individuals compared to remote sensing or UAV techniques, not always covering the whole variability of the vineyards.&lt;/p&gt;&lt;p&gt;This study aimed to apply an integrated multidisciplinary conceptual approach for vine health assessment, based on a systematic process for a multi-source, multi-scale and multi-temporal synergic interpretation of data with different techniques in order to cover the gaps of the single disciplines. This approach was recently developed and successfully tested on an Aglianico vineyard in Southern Italy and its applicability needs to be tested on other terroirs.&lt;/p&gt;&lt;p&gt;Therefore, in this study, the multidisciplinary approach was calibrated and applied in a hilly environment in southern Italy (La Guardiense farm, Guardia Sanframondi, Benevento, Campania region) on Vitis vinifera L. subsp. vinifera &amp;#8216;Falanghina&amp;#8217; in order to assess the ability of the system to evaluate the plant status during the various phenological phases. The plant status results obtained from four sites were compared with data collected from different techniques including the monitoring of plant growth and ecophysiology as well as the reconstruction of past eco-physiological behavior through the analysis of tree rings in the stemwood.&lt;/p&gt;&lt;p&gt;The overall results confirmed the applicability of such an approach to achieve a comprehensive assessment of the vine health status considering the continuum soil-plant-atmosphere, thus furnishing information on possible plant responses to expected environmental changes as valuable inputs to manage cultivation factors in various terroirs.&lt;/p&gt;

scholarly journals Using Remote Sensing and in situ Measurements for Efficient Mapping and Optimal Sampling of Coral Reefs

2021 ◽  
Vol 8 ◽  
Author(s):  
Alberto Candela ◽  
Kevin Edelson ◽  
Michelle M. Gierach ◽  
David R. Thompson ◽  
Gail Woodward ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Coral Reefs ◽  
Decision Theory ◽  
Sample Selection ◽  
Global Scale ◽  
Global Mapping ◽  
And Performance ◽  
Reef Condition

Coral reefs are of undeniable importance to the environment, yet little is known of them on a global scale. Assessments rely on laborious, local in-water surveys. In recent years remote sensing has been useful on larger scales for certain aspects of reef science such as benthic functional type discrimination. However, remote sensing only gives indirect information about reef condition. Only through combination of remote sensing and in situ data can we achieve coverage to understand reef condition and monitor worldwide condition. This work presents an approach to global mapping of coral reef condition that intelligently selects local, in situ measurements that refine the accuracy and resolution of global remote sensing. To this end, we apply new techniques in remote sensing analysis, probabilistic modeling for coral reef mapping, and decision theory for sample selection. Our strategy represents a fundamental change in how we study coral reefs and assess their condition on a global scale. We demonstrate feasibility and performance of our approach in a proof of concept using spaceborne remote sensing together with high-quality airborne data from the NASA Earth Venture Suborbital-2 (EVS-2) Coral Reef Airborne Laboratory (CORAL) mission as a proxy for in situ samples. Results indicate that our method is capable of extrapolating in situ features and refining information from remote sensing with increasing accuracy. Furthermore, the results confirm that decision theory is a powerful tool for sample selection.

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