scholarly journals ALBEDO RETRIEVING FROM DSCOVR/EPIC DATA AND PRELIMINARY VALIDATION

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 147-152
Author(s):  
Q. Y. Tian ◽  
Q. Liu ◽  
H. W. Zhang ◽  
Y. H. Che ◽  
Y. N. Wen ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Time Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
High Temporal Resolution ◽  
High Time Resolution ◽  
Observation Data ◽  
Climate Change Research ◽  
Wide Range

Abstract. Land surface albedo plays an important role in climate change research. Satellite remote sensing has the characteristic of wide observation range, and it can make repeated observations on the same area. Therefore, using the remote sensing data to retrieve surface albedo becomes a main method to obtain the surface albedo in a wide range or even on a global scale. However, the time resolution of existing albedo products is usually low, which has a great impact on the analysis of rapid changes in surface vegetation and the climate change research. The Deep Space Climate Observatory (DSCOVR) was launched to a sun-earth first Lagrange point (L1) orbit, which is a new and unique vantage point to observe the continuously full, sunlit disk of Earth. DSCOVR can provide observation data with high time resolution, therefore, it is necessary to explore the feasibility of the new sensor DSCOVR/EPIC inversion of the daily albedo product. The relationship between the surface broadband albedo and the surface reflectance was established, and then the surface albedo with high temporal resolution was calculated using the DSCOVR/EPIC data. The Inner Mongolia Autonomous Region and parts of the Sahara Desert were selected to verify the accuracy of DSCOVR albedo compared with MODIS albedo. The results show that the correlation coefficients between DSCOVR albedo and MODIS albedo are greater than 0.7 and RMSE are less than 0.05 both in visible band and shortwave band. It can be seen that this method can be used for the albedo retrieval using DSCOVR/EPIC data.

scholarly journals The Estimation of Surface Albedo from DSCOVR EPIC

2020 ◽  
Vol 12 (11) ◽  
pp. 1897
Author(s):  
Qiuyue Tian ◽  
Qiang Liu ◽  
Jie Guang ◽  
Leiku Yang ◽  
Hanwei Zhang ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Surface Albedo ◽  
Climate Models ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
High Temporal Resolution ◽  
Observation Data ◽  
Climate Change Research ◽  
Narrow Channels ◽  
The Earth

Surface albedo is an important parameter in climate models. The main way to obtain continuous surface albedo for large areas is satellite remote sensing. However, the existing albedo products rarely meet daily-scale requirements, which has a large impact on climate change research and rapid dynamic changes of surface analysis. The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) platform, which was launched into the Sun–Earth’s first Lagrange Point (L1) orbit, can provide spectral images of the entire sunlit face of Earth with 10 narrow channels (from 317 to 780 nm). As EPIC can provide high-temporal resolution data, it is beneficial to explore the feasibility of EPIC to estimate high-temporal resolution surface albedo. In this study, hourly surface albedo was calculated based on EPIC observation data. Then, the estimated albedo results were validated by ground-based observations of different land cover types. The results show that the EPIC albedo is basically consistent with the trend of the ground-based observations in the whole time series variation. The diurnal variation of the surface albedo from the hourly EPIC albedo exhibits a “U” shape curve, which has the same trend as the ground-based observations. Therefore, EPIC is helpful to enhance the temporal resolution of surface albedo to diurnal. Surfaces with a three-dimensional structure that casts shadows display the hotspot effect, producing a reflectance peak in the retro-solar direction and lower reflectance at viewing angles away from the solar direction. DSCOVR observes the entire sunlit face of the Earth, which is helpful to make up for the deficiency in the observations of traditional satellites in the hotspot direction in bidirectional reflectance distribution function (BRDF) research, and can help to improve the underestimation of albedo in the direction of hotspot observation.

scholarly journals Pushing the temporal resolution in absorption and Zernike phase contrast nanotomography: enabling fast in situ experiments

2020 ◽  
Vol 27 (5) ◽  
pp. 1339-1346 ◽  
Author(s):  
Silja Flenner ◽  
Malte Storm ◽  
Adam Kubec ◽  
Elena Longo ◽  
Florian Döring ◽  
...  
Keyword(s):  
Image Quality ◽  
Temporal Resolution ◽  
Time Resolution ◽  
Phase Contrast ◽  
High Temporal Resolution ◽  
High Time Resolution ◽  
X Ray ◽  
Wide Range ◽  
In Situ Experiments

Hard X-ray nanotomography enables 3D investigations of a wide range of samples with high resolution (<100 nm) with both synchrotron-based and laboratory-based setups. However, the advantage of synchrotron-based setups is the high flux, enabling time resolution, which cannot be achieved at laboratory sources. Here, the nanotomography setup at the imaging beamline P05 at PETRA III is presented, which offers high time resolution not only in absorption but for the first time also in Zernike phase contrast. Two test samples are used to evaluate the image quality in both contrast modalities based on the quantitative analysis of contrast-to-noise ratio (CNR) and spatial resolution. High-quality scans can be recorded in 15 min and fast scans down to 3 min are also possible without significant loss of image quality. At scan times well below 3 min, the CNR values decrease significantly and classical image-filtering techniques reach their limitation. A machine-learning approach shows promising results, enabling acquisition of a full tomography in only 6 s. Overall, the transmission X-ray microscopy instrument offers high temporal resolution in absorption and Zernike phase contrast, enabling in situ experiments at the beamline.

scholarly journals Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

2021 ◽  
Vol 13 (7) ◽  
pp. 1340
Author(s):  
Shuailong Feng ◽  
Shuguang Liu ◽  
Lei Jing ◽  
Yu Zhu ◽  
Wende Yan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Environmental Impacts ◽  
Land Surface ◽  
Vegetation Index ◽  
Highway Construction ◽  
Temporal Changes ◽  
Moisture Index ◽  
Buffer Zones ◽  
Wide Range ◽  
Spatial And Temporal Changes

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

scholarly journals A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

2013 ◽  
Vol 17 (6) ◽  
pp. 2121-2129 ◽  
Author(s):  
N. F. Liu ◽  
Q. Liu ◽  
L. Z. Wang ◽  
S. L. Liang ◽  
J. G. Wen ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
Critical Role ◽  
Radiant Energy ◽  
High Temporal Resolution ◽  
Land Surface Parameter ◽  
Temporal Filter ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

scholarly journals Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges

2019 ◽  
Vol 11 (3) ◽  
pp. 230 ◽  
Author(s):  
Tien Pham ◽  
Naoto Yokoya ◽  
Dieu Bui ◽  
Kunihiko Yoshino ◽  
Daniel Friess
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Mangrove Ecosystem ◽  
Carbon Stocks ◽  
Machine Learning Techniques ◽  
Species Structure ◽  
Mangrove Species ◽  
Mitigation And Adaptation ◽  
Sensing Applications ◽  
Wide Range

The mangrove ecosystem plays a vital role in the global carbon cycle, by reducing greenhouse gas emissions and mitigating the impacts of climate change. However, mangroves have been lost worldwide, resulting in substantial carbon stock losses. Additionally, some aspects of the mangrove ecosystem remain poorly characterized compared to other forest ecosystems due to practical difficulties in measuring and monitoring mangrove biomass and their carbon stocks. Without a quantitative method for effectively monitoring biophysical parameters and carbon stocks in mangroves, robust policies and actions for sustainably conserving mangroves in the context of climate change mitigation and adaptation are more difficult. In this context, remote sensing provides an important tool for monitoring mangroves and identifying attributes such as species, biomass, and carbon stocks. A wide range of studies is based on optical imagery (aerial photography, multispectral, and hyperspectral) and synthetic aperture radar (SAR) data. Remote sensing approaches have been proven effective for mapping mangrove species, estimating their biomass, and assessing changes in their extent. This review provides an overview of the techniques that are currently being used to map various attributes of mangroves, summarizes the studies that have been undertaken since 2010 on a variety of remote sensing applications for monitoring mangroves, and addresses the limitations of these studies. We see several key future directions for the potential use of remote sensing techniques combined with machine learning techniques for mapping mangrove areas and species, and evaluating their biomass and carbon stocks.

Study on Industrial Waste Sites Monitoring Based on Remote Sensing Technology

2011 ◽  
Vol 201-203 ◽  
pp. 2607-2610
Author(s):  
Wen Hui Zhao ◽  
She Liu
Keyword(s):  
Industrial Waste ◽  
Large Scale ◽  
Rapid Development ◽  
Dynamic Environment ◽  
High Spectral Resolution ◽  
Ground Vegetation ◽  
High Time Resolution ◽  
Mountainous Area ◽  
Observation Data ◽  
Wide Range

Large scale of the industrial waste is not timely disposed of due to economic rapid development. It is the main reason why environmental pollution problem is getting more and more serious and we should monitor the pollution of industrial waste. A MODIS (Moderate Resolution Imaging Spectroradiometer) senor is used for long-time and dynamic environment monitor because it has advantages of high time resolution and high spectral resolution characteristics etc. SPOT satellite data is used to analyze the ground vegetation for its higher ground resolution and rich product data bases. The influence of industrial waste on environment is analyzed and the result of research is verifyed with the information of local meteorological agent and observation data of site. This method can be used for monitoring wide-range industrial waste and have good performance of monitoring and early warning industrial waste sites which are in mountainous area.

scholarly journals Seasonal Radiocarbon Variation of Surface Seawater Recorded in A Coral from Kikai Island, Subtropical Northwestern Pacific

Radiocarbon ◽  
2004 ◽  
Vol 46 (2) ◽  
pp. 643-648 ◽  
Author(s):  
Maki Morimoto ◽  
Hiroyuki Kitagawa ◽  
Yasuyuki Shibata ◽  
Hajime Kayanne
Keyword(s):  
Time Series ◽  
Time Resolution ◽  
Equatorial Pacific ◽  
High Time ◽  
Northwestern Pacific ◽  
High Time Resolution ◽  
Seasonal Cycles ◽  
Surface Seawater ◽  
Wide Range ◽  
Ocean Atmosphere

A coral radiocarbon (Δ14C) investigation with a high time-resolution is crucial for reconstructing secular and seasonal Δ14C changes in the surface seawater which potentially reflect ocean circulations and dynamic ocean-atmosphere interactions. The Δ14C values of a modern coral (Porites sp.) from Kikai Island, southern Japan, in the subtropical northwestern Pacific, were determined for the period of 1991-1998 at a monthly resolution. A coral Δ14C time series for the 8 yr indicated seasonal cycles superimposed on a secular decreasing trend of 3.8 per yr. The seasonal amplitude of the coral Δ14C was about 18 on the average, and the minimum Δ14C was observed in late spring and summer. The Δ14C changes were tentatively explained by horizontal oceanic advections around Kikai Island or over the wide range of the equatorial and sub-equatorial Pacific.

scholarly journals Spatiotemporal Variability of Land Surface Albedo over the Tibet Plateau from 2001 to 2019

2020 ◽  
Vol 12 (7) ◽  
pp. 1188
Author(s):  
Xingwen Lin ◽  
Jianguang Wen ◽  
Qinhuo Liu ◽  
Dongqin You ◽  
Shengbiao Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Land Cover ◽  
Snow Cover ◽  
Land Surface ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Tibet Plateau ◽  
Land Cover Types ◽  
Yearly Average

As an essential climate variable (ECV), land surface albedo plays an important role in the Earth surface radiation budget and regional or global climate change. The Tibetan Plateau (TP) is a sensitive environment to climate change, and understanding its albedo seasonal and inter-annual variations is thus important to help capture the climate change rules. In this paper, we analyzed the large-scale spatial patterns, temporal trends, and seasonal variability of land surface albedo overall the TP, based on the moderate resolution imaging spectroradiometer (MODIS) MCD43 albedo products from 2001 to 2019. Specifically, we assessed the correlations between the albedo anomaly and the anomalies of normalized difference vegetation index (NDVI), the fraction of snow cover (snow cover), and land surface temperature (LST). The results show that there are larger albedo variations distributed in the mountainous terrain of the TP. Approximately 10.06% of the land surface is identified to have been influenced by the significant albedo variation from the year 2001 to 2019. The yearly averaged albedo was decreased significantly at a rate of 0.0007 (Sen’s slope) over the TP. Additionally, the yearly average snow cover was decreased at a rate of 0.0756. However, the yearly average NDVI and LST were increased with slopes of 0.0004 and 0.0253 over the TP, respectively. The relative radiative forcing (RRF) caused by the land cover change (LCC) is larger than that caused by gradual albedo variation in steady land cover types. Overall, the RRF due to gradual albedo variation varied from 0.0005 to 0.0170 W/m2, and the RRF due to LCC variation varied from 0.0037 to 0.0243 W/m2 during the years 2001 to 2019. The positive RRF caused by gradual albedo variation or the LCC can strengthen the warming effects in the TP. The impact of the gradual albedo variations occurring in the steady land cover types was very low between 2001 and 2019 because the time series was short, and it therefore cannot be neglected when examining radiative forcing for a long time series regarding climate change.

scholarly journals Special Issue on Remote Sensing of Snow and Its Applications

Geosciences ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 277 ◽  
Author(s):  
Ali Nadir Arslan ◽  
Zuhal Akyürek
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Land Surface ◽  
Climate Models ◽  
Weather Forecasting ◽  
Special Issue ◽  
Carbon Cycles ◽  
Wide Range ◽  
Remote Sensing Techniques

Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water, and carbon cycles. Remote sensing provides a good understanding of snow cover and enable snow cover information to be assimilated into hydrological, land surface, meteorological, and climate models for predicting snowmelt runoff, snow water resources, and to warn about snow-related natural hazards. The main objectives of this Special Issue, “Remote Sensing of Snow and Its Applications” in Geosciences are to present a wide range of topics such as (1) remote sensing techniques and methods for snow, (2) modeling, retrieval algorithms, and in-situ measurements of snow parameters, (3) multi-source and multi-sensor remote sensing of snow, (4) remote sensing and model integrated approaches of snow, and (5) applications where remotely sensed snow information is used for weather forecasting, flooding, avalanche, water management, traffic, health and sport, agriculture and forestry, climate scenarios, etc. It is very important to understand (a) differences and similarities, (b) representativeness and applicability, (c) accuracy and sources of error in measuring of snow both in-situ and remote sensing and assimilating snow into hydrological, land surface, meteorological, and climate models. This Special Issue contains nine articles and covers some of the topics we listed above.

Phenology-induced energy and carbon fluxes in land surface models

2020 ◽  
Author(s):  
Jan De Pue ◽  
José Miguel Barrios ◽  
Fabienne Maignan ◽  
Liyang Liu ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Land Surface Models ◽  
Energy Fluxes ◽  
Wide Range ◽  
Surface Models ◽  
Modelling Strategies ◽  
Phenological Cycle

&lt;p&gt;The annual phenological cycle is of key importance for the carbon and energy fluxes in terrestrial ecosystems. Although the processes controlling budburst and leaf senescence are fairly well known, the connection between plant phenology and the carbon fluxes remains a challenging aspect in land surface modelling (LSM). In this study, the modelling strategies of three well stablished LSM are compared. The LSM considered in this study were: ORCHIDEE, ISBA-A-gs and the model driving the LSA-SAF evapotranspiration product (https://landsaf.ipma.pt). The latter model does not simulate the carbon fluxes but focuses on the computation of evapotranspiration and energy fluxes.&lt;br&gt;The phenological cycle is simulated explicitly in the ORCHIDEE model, using empirical relations based on temperature sum, water availability, and other variables. In the ISBA-A-gs model, phenology and LAI development is fully photosynthesis-driven. The phenology in the LSA-SAF model is driven by remote sensing forcing variables, such as LAI observations. Alternatively, the assimilation of remote sensing LAI products is a convenient method to improve the simulated phenological cycle in land surface models. A dedicated module for this operation is available in ISBA-A-gs.&lt;br&gt;Simulations were performed over a wide range of climatological conditions and plant functional types. The results were then validated with in-situ measurements conducted at Fluxnet stations. In addition to the comparison between measured and modelled carbon fluxes, the validation in this study included the intra-annual variation in the simulated phenological cycle.&lt;/p&gt;

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