scholarly journals New methods for the retrieval of chlorophyll red fluorescence from hyperspectral satellite instruments: simulations and application to GOME-2 and SCIAMACHY

2016 ◽  
Vol 9 (8) ◽  
pp. 3939-3967 ◽  
Author(s):  
Joanna Joiner ◽  
Yasuko Yoshida ◽  
Luis Guanter ◽  
Elizabeth M. Middleton

Abstract. Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736 nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683 nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths  >  712 nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths  <  712 nm) over both land and ocean. Red SIF is thought to provide complementary information to that from the far red for terrestrial vegetation. The satellite instruments that we use were designed to make atmospheric trace-gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (0.5 nm). Nevertheless, these instruments, the Global Ozone Monitoring Instrument 2 (GOME-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric and/or solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) γ band that is not affected by SIF. The SIF-free O2 γ band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. Our 8-year record of red SIF observations over land with the GOME-2 allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatiotemporal structure as those in the far red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far red for these areas that are drought sensitive. We also demonstrate that good-quality ocean fluorescence line height retrievals can be achieved with GOME-2, SCIAMACHY, and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.

2016 ◽  
Author(s):  
J. Joiner ◽  
Y. Yoshida ◽  
L. Guanter ◽  
E. M. Middleton

Abstract. Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736 nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region. Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far- red, since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyper-spectral satellite data sets to retrieve red SIF over both land and ocean. Our approach offers noise reductions as compared with previously published solar line filling retrievals by making use of the oxygen (O2) γ-band that is not affected by SIF. The O2 γ-band in conjunction with solar Fraunhofer lines help to anchor the O2 B-band that provides additional information on red SIF. Biases due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. The satellite instruments that we use were designed to make atmospheric trace- gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (∼0.5 nm). Nevertheless, these instruments offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Our eight year record of red SIF observations over land with the Global Ozone Monitoring Instrument 2 (GOME-2) allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatio-temporal structure as those in the far-red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far-red for these areas that are sensitive to soil moisture, although the differences are within the specified uncertainties that are dominated by systematic errors. We also demonstrate that high quality ocean fluorescence line height retrievals can be achieved with GOME-2 and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.


2021 ◽  
Author(s):  
Pauline Verdurme ◽  
Simon Carn ◽  
Andrew Harris ◽  
Diego Coppola ◽  
Andrea Di Muro ◽  
...  

&lt;p&gt;Piton de la Fournaise (La R&amp;#233;union, France) is one of the most active volcanoes in the world, producing frequent effusive basaltic eruptions of varying duration. These eruptions are accompanied by strong thermal infrared (TIR) signals and significant sulfur dioxide (SO&lt;sub&gt;2&lt;/sub&gt;) emissions detected by satellite instruments. The high frequency of eruptions provides an extensive dataset, which allows us to explore the relationships between eruptive heat, mass and gas fluxes. Five eruptions with different temporal trends of erupted mass flux have been selected for this study: April 2007, May 2015, August-October 2015, February 2019 and April 2020. For each of them, we estimated SO&lt;sub&gt;2&lt;/sub&gt; emission from three ultraviolet satellite instruments (the Ozone Monitoring Instrument OMI, the Ozone Mapping and Profiler Suite OMPS and the Tropospheric Monitoring Instrument TROPOMI). The total SO&lt;sub&gt;2&lt;/sub&gt; emission for each eruption has been estimated for an extensive range of sulfur (S) content within melt inclusions and the matrix using a petrological approach and the erupted magma masses obtained from MODIS TIR satellite data. Preliminary results show that, assuming the estimated SO&lt;sub&gt;2&lt;/sub&gt; emission falls within the 30% error of the SO&lt;sub&gt;2&lt;/sub&gt; mass detected by each satellite instrument, the implied magmatic sulfur contents are in good agreement with expected values for basaltic eruptions. Given pre-eruptive S contents between 200 and 750 ppm, estimated SO&lt;sub&gt;2&lt;/sub&gt; emissions for the May 2015 eruption are consistent with an eruption largely fed by degassed magma. However, for the February 2019 eruption, there is a discrepancy between the three satellite sensors. Whereas the TROPOMI and the OMI instruments provide almost the same range of magmatic sulfur content (300-1100 ppm), the OMPS gives a higher range (700 to 1900 ppm) suggesting that fresh, undegassed magma was also involved in this eruption. Petrologic analysis of the pre-eruptive sulfur content will allow us to validate the satellite data and, in turn, to validate the ground-based SO&lt;sub&gt;2&lt;/sub&gt; data from the NOVAC network operated by the&amp;#160;Observatoire Volcanologique du Piton de la Fournaise&amp;#160;(OVPF). Our approach yields insights into the characteristics of the magma reservoir supplying effusive events (e.g., eruptive degassing processes and the ratio of intrusive to extrusive magma) from space-based sensors.&lt;/p&gt;


Author(s):  
Muhammad Danish Siddiqui ◽  
Arjumand Z Zaidi

<span>Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of <span>this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite <span>data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastal<br /><span>waters of Karachi. The continuous monitoring and mapping of this precious marine plant and their <span>breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote <span>Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient <span>solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both <span>temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image <span>enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of <span>seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation <span>wasachieved with WV-2 data that shows 15.5Ha (0.155 Km<span>2<span>)of seaweed cover along Karachi coast that is <span>more representative of the field observed data. A much larger area wasestimated with Landsat 8 image <span>(71.28Ha or 0.7128 Km<span>2<span>) that was mainly due to the mixing of seaweed pixels with water pixels. The <span>WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat<br /><span>8 in mapping seaweed patches</span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span>


2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. Mendes ◽  
J. C. B. da Silva ◽  
J. M. Magalhaes ◽  
B. St-Denis ◽  
D. Bourgault ◽  
...  

AbstractInternal waves (IWs) in the ocean span across a wide range of time and spatial scales and are now acknowledged as important sources of turbulence and mixing, with the largest observations having 200 m in amplitude and vertical velocities close to 0.5 m s−1. Their origin is mostly tidal, but an increasing number of non-tidal generation mechanisms have also been observed. For instance, river plumes provide horizontally propagating density fronts, which were observed to generate IWs when transitioning from supercritical to subcritical flow. In this study, satellite imagery and autonomous underwater measurements are combined with numerical modeling to investigate IW generation from an initial subcritical density front originating at the Douro River plume (western Iberian coast). These unprecedented results may have important implications in near-shore dynamics since that suggest that rivers of moderate flow may play an important role in IW generation between fresh riverine and coastal waters.


Author(s):  
Gary Sutlieff ◽  
Lucy Berthoud ◽  
Mark Stinchcombe

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field


2018 ◽  
Vol 610 ◽  
pp. A84 ◽  
Author(s):  
Iker S. Requerey ◽  
Basilio Ruiz Cobo ◽  
Milan Gošić ◽  
Luis R. Bellot Rubio

Context. Photospheric vortex flows are thought to play a key role in the evolution of magnetic fields. Recent studies show that these swirling motions are ubiquitous in the solar surface convection and occur in a wide range of temporal and spatial scales. Their interplay with magnetic fields is poorly characterized, however. Aims. We study the relation between a persistent photospheric vortex flow and the evolution of a network magnetic element at a supergranular vertex. Methods. We used long-duration sequences of continuum intensity images acquired with Hinode and the local correlation-tracking method to derive the horizontal photospheric flows. Supergranular cells are detected as large-scale divergence structures in the flow maps. At their vertices, and cospatial with network magnetic elements, the velocity flows converge on a central point. Results. One of these converging flows is observed as a vortex during the whole 24 h time series. It consists of three consecutive vortices that appear nearly at the same location. At their core, a network magnetic element is also detected. Its evolution is strongly correlated to that of the vortices. The magnetic feature is concentrated and evacuated when it is caught by the vortices and is weakened and fragmented after the whirls disappear. Conclusions. This evolutionary behavior supports the picture presented previously, where a small flux tube becomes stable when it is surrounded by a vortex flow.


2012 ◽  
Vol 5 (1) ◽  
pp. 223-230 ◽  
Author(s):  
S. Saux Picart ◽  
M. Butenschön ◽  
J. D. Shutler

Abstract. Complex numerical models of the Earth's environment, based around 3-D or 4-D time and space domains are routinely used for applications including climate predictions, weather forecasts, fishery management and environmental impact assessments. Quantitatively assessing the ability of these models to accurately reproduce geographical patterns at a range of spatial and temporal scales has always been a difficult problem to address. However, this is crucial if we are to rely on these models for decision making. Satellite data are potentially the only observational dataset able to cover the large spatial domains analysed by many types of geophysical models. Consequently optical wavelength satellite data is beginning to be used to evaluate model hindcast fields of terrestrial and marine environments. However, these satellite data invariably contain regions of occluded or missing data due to clouds, further complicating or impacting on any comparisons with the model. This work builds on a published methodology, that evaluates precipitation forecast using radar observations based on predefined absolute thresholds. It allows model skill to be evaluated at a range of spatial scales and rain intensities. Here we extend the original method to allow its generic application to a range of continuous and discontinuous geophysical data fields, and therefore allowing its use with optical satellite data. This is achieved through two major improvements to the original method: (i) all thresholds are determined based on the statistical distribution of the input data, so no a priori knowledge about the model fields being analysed is required and (ii) occluded data can be analysed without impacting on the metric results. The method can be used to assess a model's ability to simulate geographical patterns over a range of spatial scales. We illustrate how the method provides a compact and concise way of visualising the degree of agreement between spatial features in two datasets. The application of the new method, its handling of bias and occlusion and the advantages of the novel method are demonstrated through the analysis of model fields from a marine ecosystem model.


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