A Relationship Between Blue and Near‐IR Global Spectral Reflectance and the Response of Global Average Reflectance to Change in Cloud Cover Observed From EPIC

Wen, Guoyong; Marshak, Alexander; Song, Wanjuan; Knyazikhin, Yuri; Mõttus, Matti; Wu, Dong L.

doi:10.1029/2019ea000664

Cited by 10 publications

(9 citation statements)

References 26 publications

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“…We used two different MODIS products (Table 1), totaling seven optical spectral bands (i.e., blue, green, red, NIR, SWIR5, SWIR6, and SWIR7). Contrary to the case of Vegetation Indices, cloud contamination produces higher reflectance values than expected from vegetation in all spectral bands [49]. Therefore, during the preprocessing of the spectral bands coming from the Vegetation Index product (i.e., blue, red, NIR, and SWIR7), we combined the images from both satellites and created a composite, keeping pixels with the lowest values, (corresponding to the highest absorption), resulting in 23 images per band and per year.…”

Section: Preprocessingcontrasting

confidence: 69%

Inter-Annual Climate Variability Impact on Oil Palm Mapping

2022

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The contribution of oil palm plantations to the economic growth of tropical developing countries makes it essential to monitor their expansion into the tropical forest; consequently, most studies focus on improving mapping accuracy while using satellite imagery. However, accuracy can be hampered by atmospheric phenomena that can drastically change climatic conditions in tropical regions, affecting the spectral properties of the vegetation. In this sense, we studied the accuracy of palm plantation mapping by using features from different regions of the electromagnetic spectrum and a data fusion approach, and then compared the changes in accuracy over the years 2016, 2017, and 2018 (two of them with reported climatic anomalies). Optical-based maps obtained higher accuracy than thermal- and microwave-based maps, but they were the most affected by inter-annual climate variability (error margin between 5 and 10%), while thermal-based maps were the least affected (error margin between 8 and 9%). Data fusion combinations improved accuracy and reduced dissimilarities between years (e.g., phenology-based map accuracy changed by up to 20.8%, while phenology fused with microwave features changed by up to 6.8%). We conclude that inter-annual climate variability on land-cover mapping should be considered, especially if the outputs will be used as input in future studies.

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Section: Preprocessingcontrasting

confidence: 69%

Inter-Annual Climate Variability Impact on Oil Palm Mapping

2022

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“…The rainforests play a uniquely important role in carbon and water cycles across regional to global scales as it contains nearly 50% of the tropical forest carbon stocks and is the most productive and biodiverse of terrestrial ecosystems (Saatchi et al, 2011). It was found that the green vegetation contributes significantly to the NIR global average reflectance when the South America appears in the EPIC's field of view (Wen et al, 2019) suggesting a significant contribution from the equatorial forests. The left panel in Figure 9 demonstrates BRF of Amazonian forests derived from Terra MISR data acquired on August 28, 2016, at 10:30 local solar time.…”

Section: Forest Brfmentioning

confidence: 99%

Effect of Scattering Angle on Earth Reflectance

Marshak

Delgado-Bonal

Knyazikhin

2021

Front. Remote Sens.

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After March 2020 the range of scattering angle for DSCOVR EPIC and NISTAR has been substantially increased with its upper bound reaching 178°. This provides a unique opportunity to observe bi-directional effects of reflectance near backscattering directions. The dependence of the top-of-atmosphere (TOA) reflectance on scattering angle is shown separately for ocean and land areas, for cloudy and clear pixels, while cloudy pixels are also separated into liquid and ice clouds. A strong increase of TOA reflectance towards backscattering direction is reported for all components (except cloudless areas over ocean). The observed increase of reflectance is confirmed by cloud and vegetation models. The strongest correlation between TOA reflectance and scattering angle was found near IR where contribution from vegetation dominates. Surface Bidirectional Reflectance Factor (BRF) acquired by DSCOVR EPIC and Terra MISR sensors over the Amazon basin is used to demonstrate the bi-directional effects of solar zenith and scattering angles on variation of reflected radiation from rainforest.

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“…Our research supports the idea that clouds and albedo, which ultimately determine the SW radiation, are variables of the utmost importance for current climate change, in agreement with previous research about the changes in stratocumulus or energy imbalance in the last four decades for example. An increase in cloud coverage of 0.1 would, on average, lead to a 7% increase in spectrally integrated global average reflectance of shortwave radiation 55 . The Decadal Survey for Earth Science and Applications from Space (2018) lists as one of the key science questions "how changing cloud cover and precipitation will affect climate, weather and Earth's energy balance in the future".…”

Section: Discussionmentioning

confidence: 99%

Analyzing changes in the complexity of climate in the last four decades using MERRA-2 radiation data

Delgado-Bonal

Marshak

Yang

et al. 2020

Sci Rep

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the energy balance of the earth is controlled by the shortwave and longwave radiation emitted to space. Changes in the thermodynamic state of the system over time affect climate and are noticeable when viewing the system as a whole. In this paper, we study the changes in the complexity of climate in the last four decades using data from the Modern-era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). First, we study the complexity of the shortwave and longwave radiation fields independently using Approximate Entropy and Sample Entropy, observing that the rate of complexity change is faster for shortwave radiation. Then, we study the causality of those changes using Transfer Entropy to capture the non-linear dynamics of climate, showing that the changes are mainly driven by the variations in shortwave radiation. the observed behavior of climatic complexity could be explained by the changes in cloud amount, and we research that possibility by investigating its evolution from a complexity perspective using data from the international Satellite cloud climatology Project (ISCCP). Climate is a complex system 1 composed of many different processes operating at all spatiotemporal scales, showing non-linear relations between its variables in long time spans 2 or its acceleration in the last four decades 3. Understanding the changes in these non-linear relations is of the utmost importance for understanding current climate change and its implications for the future 4,5. Great efforts have been made in the last years to characterize those variations due to its importance for future abrupt changes in the structure of climate, being it potentially harmful to biodiversity and society 6,7. The atmosphere of the Earth can be considered as a closed non-linear thermodynamic system which basically only exchanges radiation with its environment 8. The solar radiation flux maintains the atmosphere in a non-equilibrium thermodynamics situation, generating a climate dynamics which has an influence on the temperature of the planet. The energy balance is modulated by the incoming solar radiation and the outgoing shortwave and longwave Earth's radiation. Changes in the energy balance of the atmosphere are the drivers of climate change. Nowadays, it is believed that the Earth absorbs more energy from the Sun than it is emitted to the space, creating a situation of energy imbalance 9,10. Although those differences can be monitored from the ground, the use of satellite sensors to provide measures of the fluxes of energy to and from Earth offers a more precise view of the system 11. The evolution of the energy imbalance has been investigated using satellite data and models, and it seems to be increasing in the last decades 12,13. While those changes have been argued to be due to human activities 14 , the questions of which of the parameters are changing faster and if that is affecting the dynamics of the system are still open. When reaching the Earth, part of the incoming solar radiation is reflected off clouds and the...

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A Relationship Between Blue and Near‐IR Global Spectral Reflectance and the Response of Global Average Reflectance to Change in Cloud Cover Observed From EPIC

Cited by 10 publications

References 26 publications

Inter-Annual Climate Variability Impact on Oil Palm Mapping

Inter-Annual Climate Variability Impact on Oil Palm Mapping

Effect of Scattering Angle on Earth Reflectance

Analyzing changes in the complexity of climate in the last four decades using MERRA-2 radiation data

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