Analysis of historical MERIS and MODIS data to evaluate the impact of dredging to monthly mean surface TSM concentration

2013 ◽  
Author(s):  
L. Raag ◽  
R. Uiboupin ◽  
L. Sipelgas
Keyword(s):  
Modis Data ◽  
The Impact

Effects of Dubai coastline extreme urbanization in land and sea on local near-surface climate variables patterns

2021 ◽  
Author(s):  
Emily Elhacham ◽  
Pinhas Alpert
Keyword(s):  
Urban Heat Island ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Modis Data ◽  
The World ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Coastal Urbanization ◽  
The Impact

<p>Over a billion people currently live in coastal areas, and coastal urbanization is rapidly growing worldwide. Here, we explore the impact of an extreme and rapid coastal urbanization on near-surface climatic variables, based on MODIS data, Landsat and some in-situ observations. We study Dubai, one of the fastest growing cities in the world over the last two decades. Dubai's urbanization centers along its coastline – in land, massive skyscrapers and infrastructure have been built, while in sea, just nearby, unique artificial islands have been constructed.</p><p>Studying the coastline during the years of intense urbanization (2001-2014), we show that the coastline exhibits surface urban heat island characteristics, where the urban center experiences higher temperatures, by as much as 2.0°C and more, compared to the adjacent less urbanized zones. During development, the coastal surface urban heat island has nearly doubled its size, expanding towards the newly developed areas. This newly developed zone also exhibited the largest temperature trend along the coast, exceeding 0.1°C/year on average.</p><p>Overall, we found that over land, temperature increases go along with albedo decreases, while in sea, surface temperature decreases and albedo increases were observed particularly over the artificial islands. These trends in land and sea temperatures affect the land-sea temperature gradient which influences the breeze intensity. The above findings, along with the increasing relative humidity shown, directly affect the local population and ecosystem and add additional burden to this area, which is already considered as one of the warmest in the world and a climate change 'hot spot'.</p><p> </p><p><strong>References:</strong></p><p>E. Elhacham and P. Alpert, "Impact of coastline-intensive anthropogenic activities on the atmosphere from moderate resolution imaging spectroradiometer (MODIS) data in Dubai (2001–2014)", <em>Earth’s Future</em>, 4, 2016. https://doi.org/10.1002/2015EF000325</p><p>E. Elhacham and P. Alpert, "Temperature patterns along an arid coastline experiencing extreme and rapid urbanization, case study: Dubai", submitted.</p>

Investigating the impact of the temporal resolution of MODIS data on measured phenology in the prairie grasslands

2020 ◽  
Vol 57 (3) ◽  
pp. 395-410
Author(s):  
Tengfei Cui ◽  
Lawrence Martz ◽  
Liang Zhao ◽  
Xulin Guo
Keyword(s):  
Temporal Resolution ◽  
Modis Data ◽  
The Impact

scholarly journals A novel method for estimating shortwave direct radiative effect of above-cloud aerosols using CALIOP and MODIS data

2014 ◽  
Vol 7 (6) ◽  
pp. 1777-1789 ◽  
Author(s):  
Z. Zhang ◽  
K. Meyer ◽  
S. Platnick ◽  
L. Oreopoulos ◽  
D. Lee ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Optical Depth ◽  
Radiative Forcing ◽  
Orthogonal Polarization ◽  
Radiative Effect ◽  
Cloud Optical Depth ◽  
Modis Data ◽  
Joint Histogram ◽  
The Impact ◽  
Southeastern Atlantic

Abstract. This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and MODIS (Moderate Resolution Imaging Spectroradiometer) data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a precomputed look-up table based on radiative transfer calculations. We verify that for smoke and polluted dust over the southeastern Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 13:30 local time) shortwave DRE of above-cloud aerosol (ACA) that generally agrees with a more rigorous pixel-level computation within 4%. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeastern Atlantic Ocean would increase, from the original value of 6.4 W m−2 based on operational CALIOP AOD to 9.6 W m−2 if CALIOP AOD retrievals are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m−2 if CALIOP AOD retrievals are biased low by a factor of 5 as suggested in Jethva et al. (2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m−2 AOD−1, suggesting a near-linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that given an above-cloud aerosol type the optical depth of the underlying clouds plays a larger role than above-cloud AOD in the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets.

scholarly journals MODIS Derived Sea Surface Salinity, Temperature, and Chlorophyll-a Data for Potential Fish Zone Mapping: West Red Sea Coastal Areas, Saudi Arabia

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2069 ◽  
Author(s):  
Saleh Daqamseh ◽  
A’kif Al-Fugara ◽  
Biswajeet Pradhan ◽  
Anas Al-Oraiqat ◽  
Maan Habib
Keyword(s):  
Linear Regression ◽  
Chlorophyll A ◽  
Red Sea ◽  
High Potential ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Chl A ◽  
Modis Data ◽  
The Impact

In this study, a multi-linear regression model for potential fishing zone (PFZ) mapping along the Saudi Arabian Red Sea coasts of Yanbu’ al Bahr and Jeddah was developed, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived parameters, such as sea surface salinity (SSS), sea surface temperature (SST), and chlorophyll-a (Chl-a). MODIS data was also used to validate the model. The model expanded on previous models by taking seasonal variances in PFZs into account, examining the impact of the summer, winter, monsoon, and inter-monsoon season on the selected oceanographic parameters in order to gain a deeper understanding of fish aggregation patterns. MODIS images were used to effectively extract SSS, SST, and Chl-a data for PFZ mapping. MODIS data were then used to perform multiple linear regression analysis in order to generate SSS, SST, and Chl-a estimates, with the estimates validated against in-situ data obtained from field visits completed at the time of the satellite passes. The proposed model demonstrates high potential for use in the Red Sea region, with a high level of congruence found between mapped PFZ areas and fish catch data (R2 = 0.91). Based on the results of this research, it is suggested that the proposed PFZ model is used to support fisheries in determining high potential fishing zones, allowing large areas of the Red Sea to be utilized over a short period. The proposed PFZ model can contribute significantly to the understanding of seasonal fishing activity and support the efficient, effective, and responsible use of resources within the fishing industry.

scholarly journals Less rain, more water in ponds: a remote sensing study of the dynamics of surface waters from 1950 to present in pastoral Sahel (Gourma region, Mali)

2010 ◽  
Vol 14 (2) ◽  
pp. 309-324 ◽  
Author(s):  
J. Gardelle ◽  
P. Hiernaux ◽  
L. Kergoat ◽  
M. Grippa
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Regional Scale ◽  
Aerial Photographs ◽  
Modis Data ◽  
Maximal Area ◽  
Flooded Area ◽  
Shallow Soils ◽  
The Impact ◽  
Flooded Areas

Abstract. Changes in the flooded area of ponds in the Gourma region from 1950 to present are studied by remote sensing, in the general context of the current multi-decennial Sahel drought. The seasonal and interannual variations of the areas covered by surface water are assessed using multi-date and multi-sensor satellite images (SPOT, FORMOSAT, LANDSAT-MSS, –TM, and -ETM, CORONA, and MODIS) and aerial photographs (IGN). Water body classification is adapted to each type of spectral resolution, with or without a middle-infrared band, and each spatial resolution, using linear unmixing for mixed pixels of MODIS data. The high-frequency MODIS data document the seasonal cycle of flooded areas, with an abrupt rise early in wet season and a progressive decrease in the dry season. They also provide a base to study the inter-annual variability of the flooded areas, with sharp contrasts between dry years such as 2004 (low and early maximal area) and wetter years such as 2001 and 2002 (respectively high and late maximal area).The highest flooded area reached annually greatly depends on the volume, intensity and timing of rain events. However, the overall reduction by 20% of annual rains during the last 40 years is concomitant with an apparently paradoxical large increase in the area of surface water, starting from the 1970's and accelerating in the mid 1980's. Spectacular for the two study cases of Agoufou and Ebang Mallam, for which time series covering the 1954 to present period exist, this increase is also diagnosed at the regional scale from LANDSAT data spanning 1972–2007. It reaches 108% between September 1975 and 2002 for 91 ponds identified in central Gourma. Ponds with turbid waters and no aquatic vegetation are mostly responsible for this increase, more pronounced in the centre and north of the study zone. Possible causes of the differential changes in flooded areas are discussed in relation with the specifics in topography, soil texture and vegetation cover over the watersheds that feed each of the ponds. Changes in rain pattern and in ponds sedimentation are ruled out, and the impact of changes in land use, limited in the area, is found secondary, as opposed to what has often been advocated for in southern Sahel. Instead, major responsibility is attributed to increased runoff triggered by the lasting impact of the 1970–1980's droughts on the vegetation and on the runoff system over the shallow soils prevailing over a third of the landscape.

scholarly journals Less rain, more water in ponds: a remote sensing study of the dynamics of surface waters from 1950 to present in pastoral Sahel (Gourma region, Mali)

2009 ◽  
Vol 6 (4) ◽  
pp. 5047-5083 ◽  
Author(s):  
J. Gardelle ◽  
P. Hiernaux ◽  
L. Kergoat ◽  
M. Grippa
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Aerial Photographs ◽  
Water Volume ◽  
General Context ◽  
Modis Data ◽  
Flood Regime ◽  
Maximal Area ◽  
Shallow Soils ◽  
The Impact

Abstract. Changes in the flood regime of ponds in the Gourma region from 1950 to present are studied by remote sensing, in the general context of the current multi-decennial Sahel drought. The seasonal and interannual variations of the areas covered by surface water are assessed using multi-date and multi-sensor satellite images (SPOT, FORMOSAT, LANDSAT-MSS, -TM, and -ETM, CORONA, and MODIS) and aerial photographs (IGN). Water body classification is adapted to each type of spectral resolution, with or without a middle-infrared band, and each spatial resolution, using linear unmixing for mixed pixels of MODIS data. The high-frequency MODIS data document the seasonal cycle, with an abrupt rise early in wet season and a progressive decrease in the dry season. They also provide a base to study the inter-annual variability of the flood regime, with sharp contrasts between dry years such as 2004 (low and early maximal area) and wetter years such as 2001 and 2002 (respectively high and late maximal area). The highest water level reached annually greatly depends on the volume, intensity and timing of rain events. However, the overall reduction by 20% of annual rains of the current period, compared to the 50' and 60', is concomitant with an apparently paradoxical large increase in the area of surface water, starting from the late 1980's. Spectacular for the two study cases of Agoufou and Ebang Mallam, for which time series covering the 1954-present period exist, this increase also reaches 98% between 1975 and 2002 for 92 ponds identified in central Gourma. Ponds with turbid waters and no aquatic vegetation are responsible for this increase, more pronounced to the north of the study zone. Possible causes of this change in surface water volume and regime are discussed based on differential changes in ponds dynamics related to the specifics in topography, soil texture and vegetation cover over the watershed. Changes in rain pattern and in ponds sedimentation are ruled out, and the impact of changes in land use, limited in the area, is found secondary, as opposed to what has often been advocated for in cultivated Sahel. Instead, major responsibility is attributed to increased runoff triggered by the lasting impact of the 1970–1980's droughts on the vegetation and on the hydric system over shallow soils.

scholarly journals Impact of satellite viewing-swath width on global and regional aerosol optical thickness statistics and trends

2014 ◽  
Vol 7 (7) ◽  
pp. 2313-2335 ◽  
Author(s):  
P. R. Colarco ◽  
R. A. Kahn ◽  
L. A. Remer ◽  
R. C. Levy
Keyword(s):  
Optical Thickness ◽  
Radiative Forcing ◽  
Aerosol Optical Thickness ◽  
Spatial Sampling ◽  
Sampling Strategies ◽  
Data Set ◽  
Modis Data ◽  
Aerosol Loading ◽  
The Impact ◽  
Single Pixel

Abstract. We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Along-track and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (~ 400–800 km) and single pixel width (~ 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal–regional mean AOT. These AOT spatial sampling artifacts comprise up to 60% of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10°) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5°) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal–regional spatial sampling artifact in AOT. Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-of-atmosphere aerosol radiative forcing of 2–3 W m−2. These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

A Study of the Characteristics and Assimilation of Retrieved MODIS Total Precipitable Water Data in Severe Weather Simulations

2008 ◽  
Vol 136 (9) ◽  
pp. 3608-3628 ◽  
Author(s):  
Shu-Hua Chen ◽  
Zhan Zhao ◽  
Jennifer S. Haase ◽  
Aidong Chen ◽  
Francois Vandenberghe
Keyword(s):  
Near Infrared ◽  
Positive Impact ◽  
Storm Track ◽  
Precipitable Water ◽  
The United States ◽  
Severe Weather ◽  
Moist Atmosphere ◽  
Modis Data ◽  
Total Precipitable Water ◽  
The Impact

Abstract This study determined the accuracy and biases associated with retrieved Moderate Resolution Imaging Spectroradiometer (MODIS) total precipitable water (TPW) data, and it investigated the impact of these data on severe weather simulations using the Weather Research and Forecast (WRF) model. Comparisons of MODIS TPW with the global positioning system (GPS) TPW and radiosonde-derived TPW were carried out. The comparison with GPS TPW over the United States showed that the root-mean-square (RMS) differences between these two datasets were about 5.2 and 3.3 mm for infrared (IR) and near-infrared (nIR) TPW, respectively. MODIS IR TPW data were overestimated in a dry atmosphere but underestimated in a moist atmosphere, whereas the nIR values were slightly underestimated in a dry atmosphere but overestimated in a moist atmosphere. Two cases, a severe thunderstorm system (2004) over land and Hurricane Isidore (2002) over ocean, as well as conventional observations and Special Sensor Microwave Imager (SSM/I) retrievals were used to assess the impact of MODIS nIR TPW data on severe weather simulations. The assimilation of MODIS data has a slightly positive impact on the simulated rainfall over Oklahoma for the thunderstorm case, and it was able to enhance Isidore’s intensity when the storm track was reasonably simulated. The use of original and bias-corrected MODIS nIR TPW did not show significant differences from both case studies. In addition, SSM/I data were found to have a positive impact on both severe weather simulations, and the impact was comparable to or slightly better than that of MODIS data.

Sign in / Sign up

Export Citation Format

Share Document