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Finding the seismic pressure is an important parameter to quantify the damages on structures during large earthquakes. Since soil force equilibrium in wedge approach can be used in site conditions there are no finite methods for laboratory experiments to study the seismic earth pressure behavior. A simple demonstration in this research area would help many students to understand its basic concept with good insight.
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Interested to join the launched 'Climate and Environmental Change Network' at the biggest university and research association "Unimed" for multilateral scientific cooperation.
Get more info at https://t.co/bSnMWFIVy7
Deadline : July 30th. Don't miss it ↗️
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Good for sharing, this was an interesting program.
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I'm about to start some analyses of vegetation indexes using Sentinel-2 imagery through Google Earth Engine. The analyses are going to comprise a series of images from 2015/2016 until now, and some of the data won't be available in Level-2A of processing (Bottom-of-Atmosphere reflectance).
I know there are some algorithms to estimate BOA reflectance. However, I don't know how good these estimates are, and the products generated by Sen2Cor look more reliable to me. I've already applied Sen2Cor through SNAP, but now I need to do it in a batch of images. Until now, I couldn't find any useful information about how to do it in GEE (I'm using the Python API).
I'm a beginner, so all tips are going to be quite useful. Is it worth applying Sen2Cor or the other algorithms provide good estimates?
Thanks in advance!
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I would also prefer u use PEPS(CNES) to download the sentinel 2 images then u use Maja corrections for all the images u want. Am also working on time series from 1984 till now combining Landsat 5 TM and landsat 8 Oli togeda. So from 2015 till now I used Sentinel images from PEPs to validate some of the OLI images from 2015 to 2020 which I found Maja corrections to more working good.
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I am working on a project to access the coastal vulnerability. I have different variables like elevation, LULC, bathymetry, etc. of the entire study area.
My analysis steps would loosely be based on the value extraction method followed in this paper ( ). In my understanding, the authors here have extracted the value of different input parameters to some point along the coastline. Then used CVI equation on the attributes of those points to find the CVI value.
My problem is, I have no idea how to transfer these input values to point.
It will be very helpful if anyone could give some hints. I am doing processes in ArcMap.
The image shows part of my study area. The area is covered with elevation raster. The red, green, and yellow points are the points to which I want the data to be extracted.
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Hi
Since you don't have any sample points for calculating Vulnerability for Coastal areas either you can use the MCDM methods or AHP/Fuzzy AHP methods.
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Can in a sole vessel be demonstrated that the air temperature rises when CO2 concentrations rises by sun irridation?
Were there yet any trials to test the effect of increasing C02 concentrations in rates like of 300 ppm, 400 ppm, 500 ppm, 1000 ppm CO2 to prove that CO2 rises also air temperature in an simple experiment?
And how much air temperature rises, when there is the air only zero, 100 ppm and 200 ppm CO2?
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Just shine infra-red light on vessel and temp will rise faster the higher the CO2 conc. This is basically the mechanism for warming in the atmosphere and is so well understood that one way we measure atmospheric CO2 concs is using absorption of infra-red light
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Right now I am studying GRAVSOFT for geoid modeling to use it in my thesis, I tried to read the manual but it was not explaining the GUI Python version (it is explaining the Fortran version), so that I am still confused to understand the software clearly. I would like to understand clearly which data I have to use for determination geoid modeling and the steps (step by step) of doing that using GRAVSOFT programs.
please provide me any documents or any files that can let me understand all the programs inside the GRAVSOFT interface specifically for creating geoid modeling.
Thanks in advance and your comments are appreciated
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Anas Sharafeldin Mohamed Osman GEOCOL and GEOGRID for gross-error detection.
Good luck
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I am currently advising a young student in the National University of El Salvador and he has an interest in working with remote sensing data to study freshwater quality (turbity, pollution, algae blooms, etc). The available data to use is the Copernicus/Sentinels open data from the European Space Agency. The university periodically conducts in-situ studies of the water and collects samples along with the National Ministry of the Environment and Natural Resources.
We think that exploring the correlations between temperature, suspended matter, clorophyll (algae) and data from Sentinel 2/3 (some initial exploration attached). But this is just a very initial/raw idea.
Therefore I would like to be advised on relevant topics in this field of research that are of interest to the global community and not just El Salvador. My ambition is to conduct a research task that can be contributed to international peer-reviewed journals and establish relationships with experts and research groups abroad.
Any suggestions, ideas, contacts will be greatly appreciated.
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Hola Napoleón, actualmente la UCA desarrolla una investigación interdisciplinaria con biólogos, expertos SIG en teledetección y expertos en ciencias de la computación, en un proyecto de monitoreo del crecimiento de algas y toxinas en el embalse del Cerrón Grande, puedes contactar con Metzi Aguilar que coordina la parte de teledetección maguilar@uca.edu.sv y Luis Cierra biólogo jsierra@uca.edu.sv , creo que pueden tener buena sinergia!
Saludos
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Currently, it is difficult to define this type of analytic problem. The key issue is forecasting future global problems. It is necessary to collect additional analytical data over the next years and perhaps in about 100 years in huge Big Data database systems supported by another generation of artificial intelligence, it will be possible to forecast what can happen to the planet Earth in the next 1000 years.
In view of the above, the current question is: Will I be able to precisely forecast in the 21st century what will be the future of planet Earth in the next 1000 years?
Please, answer, comments. I invite you to the discussion.
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Forecasting climatic, geological, natural and other processes that may occur in the next several dozen years is burdened with a very large scope of research error. Despite the progress made in the field of predictive analytics, the impact of the development of civilization on the climate and the biosphere of the planet Earth is still large and growing. Therefore, forecasting the development of climatic, geological and natural processes that may appear in the next several hundred years may border on the proverbial "fortune-telling on tea grounds".
Best regards,
Dariusz Prokopowicz
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I am investigating thermospheric mass density vertical profiles between 300-800 km altitude. I would like to validate/compare the variability with other sources/parameters, including, e.g., temperature, pressure, density, etc.
Thank you
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Dear Andres Calabia, at TU Delft we created a website with neutral mass density from CHAMP, GRACE, GOCE (slightly out of the range you mentioned), and Swarm missions: http://thermosphere.tudelft.nl/
These densities are obtained with satellite high fidelity geometries and updated assumptions on Gas-Surface Interactions.
Maybe it's not entirely what you need, but I hope can be useful somehow!
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In the relativistic theory for synchronization between satellite and ground atomic clocks, the major sources of relativistic effects are relative motion between the two clocks and the movement of clocks in a gravitational potential.
I am looking for the recent research and adapted clock correction models that have been modified on this topic as well as what are factors must be considered when comparing the proper/coordinate time of a clock at rest on the geoid and a clock in Earth orbit satellite?
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When they first sent up GPS satellites, they programmed them with what they believed to be the correct relativistic changes that would be needed which would affect GPS location determinations. They also installed a programmable system within these satellites that can be reprogrammed from the ground, and they could upload any changes when the satellite was overhead.
What they found was that the relativity program the system was given was not accurate enough for GPS system calculations. They tried to correct these equations and related program for a period of time but finally gave up. Instead they uploaded a programmed algorithm that they believed could make the necessary corrections based upon information from the ground coming from one or more additional GPS satellites. The new system worked. So now all relativity corrections of GPS satellites are now based upon a self-correcting algorithm using new information from the ground and other GPS satellites on an ongoing basis.
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Hello,
Does anyone know any sources of the multispectral/panchromatic satellite imagery, dated before 2000, which provide higher spatial resolution, than 30-60m (Landsat 1-5). We contacted Scanex, and searched in online catalogues, such as Geocento Earth Images, USGS...but couldn't find any images we need, in the catalogues. Unfortunately, the spatial resolution 30-60m is not enough for our studies.
Something like SPOT1-5, Corona, DMC, etc. could be perfect, I think.
If there is a way to get at least several images captured in 1970 ths-1990 ths, please let me know ASAP.
Maria
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Yes, there is, available through NASA EarthExplorer portal:
And more is not available online, you can request scans of those.
That being said, these are not trivial to deal with - it requires an understanding of the entire technical context of the systems.
It's useful to familiarize your self with the histories and technical details of the platforms ( https://www.nro.gov/History-and-Studies/Center-for-the-Study-of-National-Reconnaissance/The-GAMBIT-and-HEXAGON-Programs/ ).
Some are outstanding ( 2 to 4 foot resolution, caveat: the metadata may be completely misleading in the catalog).
These are military reconnaissance imagery which were scanned from photographic film, returned from orbit, and those orbits were not the nice ones of modern remote sensing platforms ( some are taken at times of day to accentuate features of interest, rather than repeatability. The film / mirror mechanism can make georeferencing these 'interesting', some have a waviness from side to side along the track, and the scene parameters may be variable from one end of the image to the other depending on the orbit. I usually start with an oblique Mercator which has an axis perpendicular to the orbital plane, and go from there.
Since Norilsk was foundational to supplying the Soviet military industrial complex, there seems to be a lot imagery.
It was amazing what they did with the technology at the time.
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Dear all, I'd like to open here a sort of forum for understanding how the geodesists community is moving in view of the X-band SAR satellite constellation. The new constellation will offer new "free, near real-time SAR data" with the "latest information about any spot on the planet within the hour". This will open completely new horizons for InSAR monitoring of ground deformation especially for rapid phenomena such as eruptions and seismic crises. The huge amount of so frequent data acquisitions will open also new needs for rapid and automatic processing. My question are: who knows more? Are you planning a routine use of these data? How?
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Wow, thank you. I'm looking for understanding their high-frequency repeated interferometry for ground deformation monitoring. Will data be open or should they be bought?
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Spaceborne Hyperspectral observation (i.e. hyperspectral remote sensing in uv-visible-infrared spectral range) of Earth and for Planetary science, plays a very important role in improving scientific understanding, environmental and resource monitoring.
Signal to Noise ratio (SNR) is a very important parameter (or quality metric) of any Hyperspectral instrument indicating its potential to meets its desired observational goals.
Due to demanding need on higher spectral and spatial resolutions, it become challenging to good / high SNR to meet the desired observational goals.
In view of this I wish to discuss or seek suggestions of various options or ideas by which SNR of Hyperspectral instrument can be improved. Ideas or options may be either for instrument design aspects or for image or data processing aspects.
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Hi
Would you please let me know if the following is accurate as an answer to the question:
Suppose we have sensors which measure the volumetric soil water content of a soil layer for a long period (more than 6 months) and also high temporal resolution (half-hourly). Could I assign the maximum in this dataset to the saturation point?
I understand that we do need to have a lengthy rainfall event, how long the event should be so that the above proposal works?
And if there is any other way that I can get to the saturation point of a soil layer from the volumetric soil water content data/sensors, please let me know.
Mostly focused on the topsoil and preferably only using the dataset.
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There are standard methods for testing soils to consider. Usually soil samples are taken and put into a container of water so the soil is saturated from the bottom, about 24 hours. Unless there is a water table to saturate soils in the field, ability in reaching saturation may vary with the conditions. I remember we had a dry period and wildfire, then a substantial rain, about 3-5 inches. Water was pounded on the surface the next day, but the soil scientist found the soil totally dry about 12-18 inches below the surface. I also learned that an upper clay layer needs to be saturated before the lower sandy layer can effectively gain water and this is related to the tension with which clay holds water as compared to sands. Some soil layers have difficulty becoming saturated, such as well developed forest soils seldom exhibit runoff due to high infiltration and macropores from roots, etc. other soils as hydric soils are saturated frequent enough to exhibit hydric soil indicators due to frequency of high water table. Sampling the soil depth or horizon is probably the most reliable using standard methods to saturate and measure.
I would not use just the high reading in 6 month period, unless at least I reviewed nearby stream gauging stations and the rainfall during the 6 month produced at least a bankfull streamflow event, which occurs generally about every year, and the stream channel is at a level where flooding begins for stable channels that have not aggraded or degraded. I would want to be pretty sure there was a reasonable likelihood of saturation based on evidence like the streams were near or at flooding. The other option might be to set up so the area with the data sensors can be irrigated for long enough so the detectors stabilize after reaching their approximate maximum. Saturating from the surface can apparently leave some air spaces unfilled, but unless the area periodically has a high water table, the air spaces may not be filled easily to saturation by rainfall anyway.
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In common view mode, the ground to ground time transfer by Two- Way satellite Time and Frequency Transfer (TWSTFT), What are the different models which reduces the noise of the space clocks?
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if not then please Suggest/Provide me the URL for further information?
here i am performing Classification of Satellite image, for this purpose i need Ground truth image/Data, can i proceed without having GT information? please share your experience.
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Gautam Kumar , have you published this work? i would love to read it ( i only found your "An Image Processing Tool to Generate Ground Truth Data from Satellite Images using Deep Learning" on "owardsdatascience.com)
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Are environmentalists concerned about global warming because our sun's outer shell is cooling down while the inner shell is heating up, which has a big impact on Earth?
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Simply because Earth is the only planet inhabited by human beings.
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Is EO suitable only to provide global food production monitoring or it can help also to farmers in developing countries? Is the resolution of current EO limitation? Where EO could help to farmers? What could be killing applications? Are this climatic analysis or some other analysis? This and more other questions we are trying to answer in EO4Agri projects http://www.eo4agri.eu/ . See our gap analysis report https://www.researchgate.net/publication/336022413_EO4AGRI_D22-Initial-Workshop-User-Requirements-and-Gap-Analysis-in-Different-Sectors-Report-v10 and try to help us identify additional possibilities or comment our conclusion. During the project we already discussed our ideas with African community during Nairobi INSPIRE Hack https://www.plan4all.eu/2019/04/team-1-progress-report-i/
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Dear Maged,
thanks for this answer. We will try discuss questions of EO for food security on next GEO meeting in Canberra.
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When you look at a waveform and/or a seismograph you will see many oscillation on that. so identifying the waveform of an earthquake is a matter in signal processing. Then doing this job automatically can be more interested. So how we can do that?
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Dear Colleagues, In 2008 I have made an algorithm for prediction… With it was written the tides of Moon, Venus, and Mercury, described in my article: ‘Tényekkel igazolható a gravítáció valós oka’,… The algorithm was not published, for research and business purposes…: Venus tidal effect: ‘116 days 17 hours 45 minutes (the data is on a terrestrial scale) Mercury tidal effect: 175 Days, 23 Hours, 20 Minutes (Data on Earth Scale)’ The Vyecheslav prediction method is very good but seems he did not present all in his paper a very important phenomenon is not mentioned, perhaps similar reasons like in case of mine…
Regards, Laszlo, P.S. Today I was in Church… Exactly they read gospel was connected to the researchers who do promote such a person like Vjacheslav Nagorny Luke 10:25-37 English Standard Version (ESV) ‘The Parable of the Good Samaritan 25 And behold, a lawyer stood up to put him to the test, saying, “Teacher, what shall I do to inherit eternal life?” 26 He said to him, “What is written in the Law? How do you read it?” 27 And he answered, “You shall love the Lord your God with all your heart and with all your soul and with all your strength and with all your mind, and your neighbor as yourself.” 28 And he said to him, “You have answered correctly; do this, and you will live.” 29 But he, desiring to justify himself, said to Jesus, “And who is my neighbor?” 30 Jesus replied, “A man was going down from Jerusalem to Jericho, and he fell among robbers, who stripped him and beat him and departed, leaving him half dead. 31 Now by chance a priest was going down that road, and when he saw him he passed by on the other side. 32 So likewise a Levite, when he came to the place and saw him, passed by on the other side. 33 But a Samaritan, as he journeyed, came to where he was, and when he saw him, he had compassion. 34 He went to him and bound up his wounds, pouring on oil and wine. Then he set him on his own animal and brought him to an inn and took care of him. 35 And the next day he took out two denarii[a] and gave them to the innkeeper, saying, ‘Take care of him, and whatever more you spend, I will repay you when I come back.’ 36 Which of these three, do you think, proved to be a neighbor to the man who fell among the robbers?” 37 He said, “The one who showed him mercy.” And Jesus said to him, “You go, and do likewise.”’
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What satellite images/bands should I use for this purpose?
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Hi Mannan,
Are the qanat's track superficial or underground? if they are superficial, you can use thermal bands. If the qanat are underground, I think you can use Ground Penetrating Radar for this purpose.
Good Luck,
Reda
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Unlike Optically thick clouds, Cirrus Clouds are thin, high altitude clouds formed in the upper troposphere layer of the Earth's Atmosphere. These Cirrus Clouds are not easily identifiable in the satellite images acquired with Passive Remote Sensing Sensors such as Landsat MSS, TM, ETM+, ASTER, SPOT, etc. Although there are different kinds of Cirrus Clouds, the sub-visible Cirrus Clouds are particularly of interest because they can be hiding in plain sight and affect the measurements. However, they can be detected within the Short-wave infrared (SWIR) portion of the electromagnetic spectrum, specifically at ~1.38 µm bouncing off of the ice-crystals in these clouds but are absorbed by water vapor in the lower part the atmosphere. Due to the benefits of this wavelength at 1.38 µm, MODIS (1999 onwards), VIIRS (2011 onwards), Landsat 8 (2013 onwards) and Sentinel 2 (2015 onwards) were introduced with their respective Cirrus Cloud detection bands.
However, in the absence of Cirrus detection bands in passive satellite sensors operating before 1999, is there anyway to pin-point the presence of Cirrus Clouds in historical satellite images? It may be possible to identify Cirrus Clouds in satellite images acquired without cirrus band by comparing it with contemporary/concurrent satellite images acquired with sensors having cirrus band. But otherwise, is there any other alternative way? Is anybody aware of any operational tool/algorithm/products that can identify cirrus clouds in past satellite imagery and provide means for their masking/correction?
This topic may be of particular relevance in time-series studies where historical satellite images are frequently compared with the present. For example, if cirrus scattering affects are not corrected, they can lead to incorrect interpretation in Vegetation Indices such as NDVI.
Sources:
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It really depends on the type of imaging. If, as mentioned before, there is spectrally resolved information, one can make use of the fact that the contribution functions of some channels peak at different altitudes and apply some kind of minimization technique (e.g. see our algorithm for IR sounders https://bit.ly/2VAG2NZ).
However, if the image was obtained only at one wavelength or the contribution functions are too broad or they do not "scan" the whole altitude range then it's more difficult. One can train neural network using this kind of images and a combination of active and passive sounders (e.g. AIRS + CALIOP) serving as a reference, but it's easier to say than to make :)
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I am doing a research to get an overview about EO-Systems which help companies to fulfil their commitments towards Zero Deforestation.
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More and more research centers operating in different countries and investigating climate change state that the progressing greenhouse effect on Earth is already a fact. As a result, the risk of increasingly frequent and increasingly dramatic climate disasters is increasing. Man has less and less time to counteract these negative processes.
It is necessary to change the development strategy based on intensifying the exploitation of the Earth's resources on the sustainable development strategy. It is necessary to develop new energy technologies based on renewable energy sources to slow down the progressing greenhouse effect of the Earth in order to reduce the risk of dramatic natural cataclysms. It is necessary to develop ecological innovations, while it may not be too late. It is necessary to save the Earth through destruction for future generations.
In view of the above, I am asking you to answer the following question: Is the greenhouse effect on Earth already objectively recognized by the climate research centers as an irreversible process?
I invite you to the discussion
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The greenhouse effect has long been recognized by research centers and in the past, from the age of 60. Since the 1990s, many international researchers have come together under the auspices of the United Nations to work on this rapid and global climate change and its evolution. Regarding the cycle I totally agree with my colleague Kenneth M Towe
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Recently, many scientific applications such as:
In geology, the inversion of the geoid is used for Petroleum Exploration.
I am looking for studies and research in this field
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Dear Abd-Elrahim , I suggest reading this book:
Best regards
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I am new for Generic Mapping Tool (GMT), but I would like to work through a few simple examples of generating legends (ie. multiple points or lines plotted on a single figure using psxy). In the following example, I want a set the location of Legend in the southwest (Inside bottom-left of axes).
gmt psbasemap -R-108/-105/31/35 -JM6i -Ba0.5 -K -P> New_Mexico.ps
gmt pscoast -R -J -Df -Gwhite -O -K -P>> New_Mexico.ps
gmt psxy Data1.txt -R -J -Sc0.5c -Gblue -O -K -P >>New_Mexico.ps
gmt psxy Data2.txt -R -J -St0.5c -Gred -O -K -P>>New_Mexico.ps
gmt psxy Data3.txt -R -J -Ss0.5c -Ggreen -O -K -P>>New_Mexico.ps
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Dear Abd-Elrahim Ruby,
I am also new in GMT, but I have found a good manual "Getting Sterted with GMT: An Introduction to Seismologists" by Matthew R. Agius, you can request a full-text, hope it will help you.
Best regards,
Katerina
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HI, all
I want to get the program to extract Digital terrain models (DTM’s) or
Digital height models (DHM’s) for a certain area from Global Gravity Field Models related to Topography For example  dV_ELL_RET2012 
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In Mathcad writing
Elevation ==
Sum, for n = 1 to 2190,
for m = 1 to n, of
Coefficient C.m Cosine Lamda + Coefficient S.m Sine Lamda
is so easy, since the proper notation is available, but in Mathcad, we can *write*
d^n / d cos^n (theta) inline but it won't expand, even with Live Symbolics *on*.
So what is needed is to write it out of line, with Live Symbolics on, Evaluate Symbolically, and Paste the result. However, even at order 5, the result may be what Mathcad calls Huge. Too big. So we shall see.
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Does anyone know how frequently sand storms and dust storms that arise from middle east or north africa travel to Pakistan and North India? I was wondering, in view of the already worsening air pollution levels in North India, events such as dust and sand storms reaching the subcontinent may exacerbate the situation. How rare or common are such sand and dust storms being carried from their place of origin (usually middle east and north africa) and intermix with fog or haze intensified by smoke or other atmospheric pollutants in another far off location? Has there been any similar, possible mixing of phenomena (dust storm and smog) reported/documented/studied anywhere around the globe at any time, preferably that was also caught by polar or geostationary satellites?
I was looking at a true-color or natural color satellite image acquired on 29th Oct. 2017 by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the joint NASA/NOAA Suomi-National Polar orbiting Partnership (S-NPP) satellite around early afternoon. I've attached a screenshot of the image as well as provided the full link to access the satellite imagery. These satellite images have been stitched together to create a global mosaic. Unlike MODIS, VIIRS do not show any data gaps (except sun glints!). I found this satellite image particularly compelling because it clearly shows the sand storm picking up over northern Saudi Arabia and moving around Iraq, Iran, Caspian Sea towards Afghanistan with the movement of wind. I also think the Earth's rotation from west to east has a role to play in the movement and direction of the wind laden with sand and dust. But it seems difficult to understand their dynamics. The smog over North India and parts of Pakistan can be differentiated from the sand storm over middle east in this satellite image. In North India this is the time of the year when there are intentional crop fires due to the traditional slash-and-burn agriculture practice.
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The SRTM90m v4.1 is a digital elevation model with a resolution of 90 metres (3'' Arc-Sec) and available through the CGIAR-CSI data centre web page at http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp.
While, the SRTM30_Plus v10 is a 30'' Arc-Sec resolution global topography and bathymetry model and available through the Satellite Geodesy Research Group web page at http://topex.ucsd.edu/WWW_html/srtm30_plus.html
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Hi,
what you mean by synonymous? As you pointet out they have a different spatial resolution. Are you asking what is the source of original data? It's the famous SRTM mission.
Best.
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there are some user-friendly softwares to manage and study time series from satellite imagines (e.g. sentinel-2 data) with the implementation of change detection analysis?
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If you are looking for a freeware for Sentinel-2 time series data managements, I would suggest using SNAP, the Sentinel toolbox and there are some tutorials about that.
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Hello everyone!
I try to select nighttime images of Landsat 8 through the option "night" in the browser: https://earthexplorer.usgs.gov/ (Additional Criteria tab) and the answer is always "No Results Found". Anyone knows if it's possible to download nighttime images of Landsat (in general)? by google engine/lv.eosda.com/usgs... I thought that some time ago it was possible to download Landsat nightime images.
Thank you in advance!
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Joan, just wanted to share an update. All the Landsat 8 night time scenes that were acquired in the past are back online available for download on the Earthexplorer database. Out of the 17607 night time scenes acquired with Landsat 8 globally, there are around 5 scenes covering Barcelona for the time period July-Sept. 2015.
Cheers!
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I processed, using SeaDAS, a complete year of L2 files (with hi-res - 500 m). Also using the seaDAS software, I created the L3 bin files with 8 days temporal average but the .hdf file is completely different from the .hdf of the level 2 and I can't understand how to open it and map the ocean color products using the matlab software.
Without using seadas, is it correct doing a weekly average just with gridded and interpolated L2 files with matlab software. If yes, how is the correct procedure to do it?
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I write this scrip long ago to read Modis Aqua files in matlab, i hope someone else could help.
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I am looking for a research about:
Comparison between the three dedicated gravity fields mapping mission, [CHAMP (1996), GRACE (2002) and GOCE (2009)], in geoid modeling (when using the satellite-only model related to these three mission)
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Dear, Dr. Basem
Many thanks for helping me and also for this answer
Can you help me to get more details about these three missions in a gravity field?
Regards
Abdel Rahim
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Conversion between different permanent tide systems involves either modifying one spherical harmonic coefficient or adding a zonally uniform correction to the geoid undulations.
 More information sees
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Recollection
Imagine the 3 gravity fields:
(1) the gravity field of the Earth, described in the rotating Earth-fixed coordinate
system, under the assumption that Moon and Sun do not exist ==> tide free gravity field model
(2) the gravity field of the Earth, described in the rotating Earth-fixed coordinate
system, plus the gravity fields of the Moon and the Sun averaged over a long time (which is called the permanent tidal effect), plus the effect of Earth's deformation, caused by Moon and Sun, on the gravity field (also averaged over time)   ==> mean tide gravity field model
(3) the gravity field of the Earth, described in the rotating Earth-fixed coordinate
system, without the gravity fields of the Moon and the Sun, but, with the indirect effect of Earth's deformation ==> zero tide gravity field model
The differences of these three gravity fields can be described (as the gravity
field itself) in terms of spherical harmonics. Strictly, these spherical harmonic series go up to infinity.
But, because the permanent (i.e. averaged over time) tidal effects change the gravity field only very globally, it turned out that it is sufficient to change only the coefficient C20, which describes the flattening of the equipotential surfaces of the gravity field.
This answer I received from Dr. Franz Barthelmes (Section 1.2: Global Geomonitoring and Gravity Field, Department 1: Geodesy and e-mail:    bar@gfz-potsdam.de)
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Hello. i would like to ask it here because i have found values between 9-11.5 degrees. Where could i find some guaranteed number? Thanks a lot.J.
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There is no specific number save at a specific time, as the magnetic pole is constantly moving relative to the rotational pole, as discussed below, and any number that is correct now will be incorrect within a year or two.
A century or so ago the north magnetic pole was twenty degrees from the rotational pole, in northern Canada; but it has been moving more or less steadily northward and is currently less than 4 degrees from the North Pole. This change in the position of the magnetic pole causes the direction that compasses point to change by a significant amount in as little as a few years (the error is called the magnetic declination). Also, the south magnetic pole is normally not directly opposite the north magnetic pole, so its angle with the South Pole of the rotational axis is not the same as the angle between the north rotational and magnetic poles.
Over very long periods of time the magnetic pole moves more or less randomly relative to the rotational pole, sometimes being (as now) very close to it, and at other times being (as a century or so ago) twenty or more degrees from the pole, though on the "average" it seems to be a good indicator of the position of the continents relative to each other and the Pole, so the average position of the magnetic pole in any given million-year period appears to be nearer the rotational pole than far from it. The speed at which the magnetic pole's position changes ranges from nearly zero (over a century ago) to more than 30 miles per year (over most of the last decade or two).
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i need to find the value (on x-axis ) of the  first intersection point between two line by matlab
See attached for (data ,code and output )
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Dear Ricardo
Thanks for clarification
I found another solution where:the function "polyxpoly" used for Intersection points for lines or polygon edges
Many Thank
Regards
Abdel Rahim
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Global warming = Ice melting = Sea level rise = More water availability for evaporation and (possible) decrease of salinity = More evaporation = More clouds = Less solar radiation to earth = Global cooling = Fresh ice formation = Sea level fall = Less water availability for evaporation and (possible) increase of salinity = Less evaporation = Less atmospheric clouds = More incoming solar radiation = Global warming again.
(1) Are these consequences always true?
(2) If not, then what are the alternative circumstances?
(3) How does ever-changing Global Climate maintain its Dynamic Equilibrium with Global Water Cycle? Which one is the initiator of Change? Any evidence?
and,
(4) Is there any long term record of salinity of oceanic water?
**Note: Above are the physical factors (components) for global change and associated consequences... excluding biological factors such as changes of concentration of Oxygen/Carbon-dioxide/Methane etc. and their inter-relation which also influence the global cycle.
----------------------------------------------------------------------------------------------
UPDATE: Few Related & Interesting References (referred by the experts with their answers)
(IPCC Working Group Reports, referred by Harry ten Brink and Commenter)
http://isthereglobalcooling.com/ (referred by Yuri Yegorov)
https://nsidc.org/cryosphere/sotc/ (referred by Yuri Yegorov)
https://en.wikipedia.org/wiki/Past_sea_level   (referred by Yuri Yegorov)
http://www.antarcticglaciers.org/glaciers-and-climate/ (referred by Steingrimur Stefansson)
https://en.wikipedia.org/wiki/Greenhouse_gas  (referred by Henrik Rasmus Andersen)
http://www.giss.nasa.gov/research/ (referred by Alastair Bain McDonald)
https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/education-outreach [Click Introduction to Paleoclimatology] (Commenter)
http://www.ncdc.noaa.gov/sotc/ [For Global and Regional Analysis of (1) Climate, (2) Hazards, (3) Snow & Ice, (4) Upper Air, and (5) ENSO events .....during late 1990s to till date] (Commenter)
...for refence see the Global Major Climate Events (originally source & compiled map credit NOAA-NCDC and WMO) during year 2012, 2013, 2014, 2015 and some images related to historical trend of global temperature (Images collected from various webpages referred here)...
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Dear Sumanta, you are asking a complex question for which there might be no exact answer today. While in economic literature the statement about temperature growth in the last 100 years by only anthropogenic influence dominates, physicists are still in doubt; see for example https://www.newscientist.com/article/dn11639-climate-myths-the-cooling-after-1940-shows-co2-does-not-cause-warming/ . There exists also a hypothesis about global cooling, but on much larger time scale; see http://isthereglobalcooling.com/ . The graph about global temperature and CO2 dynamics is the last 450,000 years is attached (from this source). If this graph is correct, we have an interesting observation: warming went faster (about 10,000 years) than cooling (100,000 years). It is unclear whether triggering is caused by some shocks or some mechanism of dynamic equilibrium on the Earth. But is is also clear that we observe anthropogenic contribution to this process for the 1st time.
The problem however is that we cannot wait too long without making actions to combat global warming. Less carbon emissions would indeed work towards speed reduction of this process, but it might happen that other greenhouse gases (like methane) will continue working in its favor while increase of volcanic activity (observed in the last 10 years) will work towards reduction.
As for the rise of ocean level, the effect is still small today, and is caused not so much by ice melting but more by change of water density with temperature and salinity. However, melting of all Antarctic ice will cause a catastrophic rise of the ocean level by 60 meters; see https://nsidc.org/cryosphere/quickfacts/icesheets.html . Melting of Greenland will have much lower effect (6 meters), but here we observe catastrophic melting in the last years.
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W0: defines the vertical datum of a height system ,Also it can be introduced as a primary parameter for the definition of a reference mean Earth ellipsoid (hence, level ellipsoid that best fits the geoid.)
So, How to estimation of W0 and best value?
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Dear Abdel Rahim, methods of estimating the geoid geopotential value W0, in addition to the previous and recent estimates have been described in some details in our paper "A conventional value for the geoid reference potential W0, doi:10.1007/s00190-016-0913-x" . This paper would satisfy your question. Nadim
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For Earth the formula is: r = cos(L)i + sin(L)cos(e)j + sin(L)sin(e)k
Where L is the Sun's ecliptic longitude, and e is the axial tilt. 
I need a way to quickly estimate unit direction vectors from Sun to other planets throughout the year. I tried to use the same formula, but when I compared results with ephemerics data I observed high discrepancies, with k being the worst. 
I calculated Sun's ecliptic longitudes using ephemeris data
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what do you want now?
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I currently analyzing diurnal and seasonal pattern of sporadic-E occurrence over Indonesia (equatorial or low-latitude region) and found that the occurrence drop at 12:00 local time during which solar irradiation is maximum. It is hard for me to find specific reference related to this subject. Is there anyone who can discuss about this matter?
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I am beginning research into using Earth observations to identify current streams and water bodies in Idaho. I am looking for suggestions/recommendations for different satellites and sensors to use that I may have not know about. Thanks in advance. 
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Please have a look at the discussion following Mustak Ali's question "Can we automatically classify only the rivers from satellite images using any programming or different methods?", last year on Research Gate.
Open water you can map with both optical and radar remote sensing, but flooded forest you see much better on radar imagery. In optical imagery you may  see some texture differences between the flooded and the non-flooded forest, which is more related to forest type and its location in the floodplain, but with radar you can map the actual extent of water below the canopy at that particular time. Have a look of at the use of SAR imagery over the Amazon forest to find examples. You can add "varzea" or "flooded forest" or "floodplain" to limit the results.
Success,
Wietske
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Which one is correct: weather variables or weather parameters?
For example: Air temperature is a weather variable or weather parameter? 
Air Temperature: A measure of the average kinetic energy of air molecules at 2 meters (~6 feet) above the surface.
Thanks!
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In general, quantaties Y that vary in time t, are called variables. They are usually dependent variables Y(t) = cX1 + ...  A parameter, here e.g. "c" is a constant. Both, variables and constants can be the result of measurements. Parameters can be also empirical or physically based.
In climate modeling, you often have a "parameter table" which defines typically used constants used in simulations. These parameters are sometimes changed for different experiments but are constant during the given simulation. In some cases however, you may use also a variable/timeseries e.g. for the solar constant or the orbital forcing etc to simulate changes in these forcings over time. In that case, although they vary in time, they are not dependent variables (at least not in the context of Earth, so external parameters). So I would still tend to say that these are parameters of the climate system which vary in time. I hope that helps.
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Please suggest clear sky models/techniques/formulas which can be employed using a dataset containing the following given meteorological measurements to identify clear sky days in a year. 
  1. Daily Global Solar Radiation (GHI)         : Avg,Max,Min
  2. Daily Extraterrestrial Solar Radiation     : Avg
  3. Daily Air Temperature                            : Avg, Max, Min
  4. Daily Relative Humidity                          : Avg, Max, Min
  5. Daily Sunshine Duration                        : Avg, Max
  6. Daily Wind Speed                                  : Avg, Max, Min
I intend to implement the suggested equations/formulas/models in matlab.
Regards,
Ibrahim
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Your question is difficult because there is no accepted definition of what a "clear-sky day" actually is in terms of sunshine or global irradiation. There is even possible confusion between the terms "clear sky" and "cloudless sky". The latter is precise (0% cloud fraction), whereas the former is not because some authors consider cloudless but hazy conditions as "not clear". Then of course you need to define the threshold of what hazy conditions are in practice _for you_, which introduces variance. This question of haze is important here if you talk about conditions over UAE, for instance, because the aerosol optical depth (AOD) may be very high at times, e.g. during dust storms. This greatly complicates the issue.
In any case, there are two possible avenues: Use either (1) GHI or (2) sunshine data.
1. You can calculate GHIc (GHI during an ideal cloudless day) using a clear-sky radiation model. Selecting the best one for your application is not trivial, since you have to trade off accuracy vs. ease of use. This recent study should give you the background info you need about this: http://www.sciencedirect.com/science/article/pii/S0038092X11004221
Usually, the best radiation models require many inputs that describe the atmospheric conditions (such as AOD) for each specific day. One rarely has such information with the required accuracy and spatio-temporal resolution, which forces us to rely on interpolation, extrapolation, approximation, etc., resulting in errors in the calculated GHIc for any specific day. Therefore, you need to accept some uncertainty limits. For example, you can decide that a clear-sky day has a daily global irradiation of at least 90% (or 95%, etc.) of the ideal GHIc you calculated for that day. This margin of error must be evluated empirically for your location/model combination, and will account for actual hazy situations, etc., that are not reflected in your input assumptions, and for any model shortcoming.
2. Similarly, you can calculate the ideal daylength and compare it to the measured sunshine duration for each day. But here again, this idealization can be a source of error. The WMO convention is to consider a threshold of 120 W/m2 to define daylength as sensed by Campbell-Stokes sunshine recorders. This is ideal, since this value can change drastically over time or location for a variety of reasons. See discussion and method of effective daylength calculation for various theresholds in http://www.sciencedirect.com/science/article/pii/0038092X9390075Y
In practice, you can define a clear day as having an observed sunshine duration equal to the calculated effective daylength within some "reasonable" margin of error. The latter is to take the effects of actual instrumental threshold variance and haze into consideration.
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Good day, can anyone please share the equations and the methodology which is employed for calculating the empirical coefficients for the Bristow-Campbell model? 
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Dear Muhammad Munir;
The answers of your specific questions as:
1. These coefficients are dependent on the site of where they calculated, for example: if you calculate them in Algeria, and apply them in UAE, the models with these coefficients will give you lower performances than in Algeria.
2. Not always, just in very specific cases.
3.This depend on the correlation used, in some cases it is the first, and in others it is the second. Therefore you need to check the equation.
I hope this can help
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Hello ladies & gentlemen,
Does anyone know where I can source high resolution chlorophyll concentration data for the North Sea region from present day back to 2004 for free other than NASA Earth Observations (NEO)?
Any help would be greeted with the upmost appreciation.
Thank you,
Edward Lavallin
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Give a lool to the Copernicus Marine Environmental Monitoring Service (CMEMS), formerly MyOcean.
There are various bio-physical parameters - including chlorophyll -  obtained both from Earth Observation data and models which are provided at different resolutions. In some cases the data series start from earlier than 2000.
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I am looking for a program to compute into Theoretical (Normal) Gravity (γ) value on the surface of the ellipsoid (WGS84) and Free-Air Anomaly (Δgf) with knowing Observed (or measured) Gravity (g) on the earth surface
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Hi, all
 i have excel program sheet based on Gravity definitions & anomaly computations (NGA document)
Download  file :- Gravity definitions & anomaly computations (NGA document)
and the latest version of World Geodetic System (WGS) 1984
see attached for excel sheet
Please testing the excel program sheet... when there are errors Contact with me
 Regards
Abdel Rahim
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I have some questions about Global Gravity Field Models (ICGFM).
Where How to Calculate Coefficients of this model? I.e. I need the program to compute spherical harmonic analysis of EGM model.
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Dear Eng, Ahmed
Thanks for adding your answer
this paper Failure during download
It can be sent to email (abd_roby87@yahoo.com)
Thanks
Abdel Rahim
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Hi everyone,
I need classification, construction phases, dimensions of board cameras on earth observation satellites
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Dear Fatima,
Further to your question and your subsequent email, and to summarize the information collected so far, here is some additional input for you to consider:
1. Classification:
1.1 Earth Observation (EO) satellites can be classified according to their orbits, as hinted by V. K. Srivastava. In this case, the relevant criteria are
- orbit altitude (and eccentricity, perigee and apogee, if the orbit is not nearly circular), and
- orbit inclination.
Two main categories emerge in this case: Polar-Orbiting and Geostationary satellites. Read this page https://en.wikipedia.org/wiki/Orbit for a general introduction, and then search the Internet with those specific terms to find links to further information.
1.2 Satellite instruments are typically classified in two major categories:
- passive instruments measure radiation quantities emitted by other sources
- active instruments emit their own radiation, and measure how much of that emitted radiation returns to the instrument, and when.
1.3 Satellite instruments can also be classified according to the remote sensing technology used to retrieve information on the planet, and in particular the range of electromagnetic radiation in which they operate. As already pointed out by Jianjiang Wang, you can distinguish between
- instruments operating in the visible and near-infrared spectral range, which take advantage of the Sun as a source of light and therefore measure
- instruments operating in the thermal spectral range, typically to measure the temperature of targets of interest, or
- instruments operating in the microwave spectral domain, such as synthetic aperture radars.
Hyperspectral instruments feature more spectral bands than typical multispectral instruments, but otherwise operate similarly.
2. As far as construction phases are concerned, I suggest you study the materials prepared by NASA's Jet Propulsion Laboratory (JPL) and available here:
This web site is specifically addressing the design of planetary or outer space missions, but most of the content is also applicable to EO missions.
3. Satellite and instrument dimensions vary widely, from 10 cm and 1 kg for a CubeSat, to 120 m and 450 tonnes for the International Space Station. See https://en.wikipedia.org/wiki/CubeSat and http://www.nasa.gov/mission_pages/station/main/onthestation/facts_and_figures.html for more details on these extremes.
Best regards, Michel.
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I want to access Sentinel 1 level 2 data but I cannot seem to find it on the website (https://scihub.esa.int). Anyone know if there is any available data?
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Dear Miguel,
The OCN should soon come now.
The L2 processing is slightly more complex to organise as it requires exteranl information (ECMWD WIND, WW3, Ice information). It took us a bit of time to have these properly used at PDGS level.
The WV mode acquistion is being currently made global. We will soon have enough gobal data to fine tune the MTF for swell retrieval.
I would say that first OCN should available this summer
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in the program GRAVSOFT , two Sub programmes
- Python Interface to “EMPCOV” (Program empirical covariance functions)
- Python Interface to “COVFIT” (Fit empirical functions to analytic models)
in figure below , what is empirical covariance functions and analytical covariance functions
I know how to be compute empirical covariance, but How can be obtained analytical covariance functions
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I have no idea what these words stand for.  They sound like names of some computer programs.  Possibly the people above are more knowledgeable, so you should listen to them.
Cheers,
PV
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Can anybody help tell where I can find the data of Length of Day for the past 40 years or more?
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You should check the International Earth Rotation Service web page:
The yearly values (since 1623) are available here:
If you want daily solutions (since 1962) for UT1-TAI and delta LOD (together with the EOP), go to:
I hope this helps.
Cheers,
Demián
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I would like to interpret mechanisms driving vegetation change particularly structure and composition in arid rangelands using multi-temporal data acquired by the sensors onboard the Landsat Satellites.
If it is possible, I am interested in getting information to explain some of catastrophic vegetation change for the last 40+ years corresponding with the Landsat History & Legacy.
The sensors are Multi-Spectral Scanner (MSS) onboard Landsat 1-3, Multi-Spectral Scanner (MSS)/Thematic Mapper (TM) onboard Landsat 4-5, Enhanced Thematic Mapper Plus onboard Landsat 7 and Operational Land Imager and Thermal Infrared Sensor (TIRS) onboard Landsat 8. 
I would appreciate suggestions on methods of data processing, models to study long term vegetation dynamics in arid environments and sharing of references. 
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Dear Mohamed,
There is a vast literature on your topic of interest. You may want to start by browsing journals that specialize on arid and semi-arid regions, such as
- Journal of Arid Environments [Elsevier]
- Land Degradation & Development [Wiley]
In particular, you may be interested in the following special issues:
* Land Degradation & Development [Wiley]
Special Issue on Understanding Dryland Degradation Trends
March/April 2011, Volume 22, Issue 2, Pages 145–312.
* Global and Planetary Change [Elsevier]
Special Issue on Climate Change and Desertification
December 2008, Volume 64, Issue 3-4, Pages 105-252.
To characterize vegetation dynamics, you may want to use accurate, quantitative remote sensing products such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), which is much more reliable than traditional (and obsolete) vegetation indices. To get started on that, have a look at the following web site:
it provides plenty of documentation and papers, as well as data products.
I hope this will help you. Cheers, Michel.
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I would like to subtract the contribution from a global gravity model (here EGM96 and EGM08) from the free-air anomalies (Δg) . And the height anomalies (ζ) .
Can you suggest a program to do this?
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the second  program are Harmonic_Synth_v02 (Version 05/01/2006)
                       Simon A. Holmes and Nikolaos K. Pavlis
                                                       Harmonic_Synth
HARMONIC_SYNTH is a FORTRAN 77 program for very-high-degree harmonic synthesis.
HARMONIC_SYNTH combines and expands the capabilities of three related programs that existed in Richard H. Rapp's software library at the Department of Geodetic Science and Surveying of The Ohio State University. These three programs and their functions are:
 
(a) F477: harmonic synthesis of point values over arbitrarily scattered locations (Rapp, 1982).
(b) F388: harmonic synthesis over regular grids of regional or global extent, using Chris Rizos' (1979) algorithms.
(c) F431: harmonic synthesis of point or area-mean values over grids of global extent, using Oscar Colombo's (1981) algorithms.
For more information, please visit the following website
But I need to help run this program .... who wants to help, please send me a message
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I am doing the Atmospheric correction of Compact Airborne Spectrometer Imager Data.
and also is the Refined Empirical Line Method in ENVI performed better or not?
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Atmospheric interference creates artifacts in observational data. Ground targets useful for minimizing the impact of atmosphere or to minimize the error extent.
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I'm looking for a program to converted  ellipsoidal to spherical harmonic coefficient .
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Dear friend Reda
Where the answer to question?
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The GSI Inventory is the most accepted inventory for Indian Himalaya but if compared with the ICIMOD inventory the data does not seem to match for most of the glaciers.
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Dear N. Dkhar,
Whenever two or more individuals or organizations decide to tackle the same task, it is actually very likely that their results will exhibit mismatches and discrepancies. Difference in methodology, instrumentation, recording practices, quality control, human errors, archiving, maintenance, documentation, and many other factors will inevitably lead to different outcomes or interpretations. This is even more the case with potentially "controversial data", e.g., involving issues linked to national or commercial interests.
Remember also that different inventories may have been assembled for different purposes, with different accuracy requirements, and--most importantly--with possibly quite different levels of financial support. In any case, each inventory or data source should be independently evaluated with regards to the quality and performance of the measurement protocols, the methodologies followed, the practices, etc. That should give you a first indication of their intrinsic value.
If you have access to multiple independent sources, you may trust one that is closer to the average, but even that type of selection is potentially subject to biases: it all depends on whether they are truly independent, and there is always the possibility that the "outlier" stands out because it is actually better designed... So the next step is to conduct direct comparisons, as well as benchmarks against well-know cases that have been amply documented in situ.
By the way, you may also want to look at the world glacier monitoring service, hosted in Switzerland:
Last but not least, noticing differences between inventories is important to remain aware of the intrinsic limitations of each, but you need to be clear also about your own objectives, your expected outcomes, the acceptable degree of uncertainty, etc. Perhaps some or most of the differences you witness are not critical for your application?
I hope this helps. Cheers, Michel.
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There are number of algorithms available in the literature for soil moisture down scaling especially derived from satellite data. Can these algorithms be used for soil nutrients also? what corrective actions should be taken in that case?
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Another paper I think that could be of some relevance is
"A spatially explicit methodology to quantify soil nutrient balances and their uncertainties at the national level" by J. P. Lesschen et al
Nutr Cycl Agroecosyst (2007) 78:111–131
DOI 10.1007/s10705-006-9078-y
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For example, I was trying to get a initial condition for the date of 1998-01-01. If I firstly ran a case using the default forcing CLM4.0CN to get the initial condition of 1998-01-01. And then using my own atmospheric forcing to drive the initial condition as the spinup, how long do I need to spinup the model?
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hi Xiaolu,
the spinup time depends whether you start from a coldstart or from a realistic initial conditions
from a cold start you need about 2000 year of accelerated spinup plus 2000 without acceleration in order to fill the carbon and nitrogen pools
in both cases you need to run a transient simulation using the observed forcings till 1998
the restart produced at the end of 1997 will be the initial condition for your simulation
Matteo
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I am using Landsat 7 for water body extraction in in QGIS.
But I am not able to get enhanced results. Which software will be more effective?
I have ERDAS 10 and Arc-Gis 9.3.
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Hi Reshama,
Supporting all, who said its the matter of the algorithms and programs, and not the software, I would like to recommend you following papers, which I used during my study similar to yours.
Ji, L., Zhang, L., & Wylie, B. (2009). Analysis of Dynamic Thresholds for the Normalized Difference Water Index. Photogrammetric Engineering & Remote Sensing, 75(11), 1307-1317.
Nath, R. K. (n.d.). Water-Body Area Extraction from High Resolution Satellite Images-An Introduction , Review , and Comparison. Image Processing, (3), 353-372.
If we speak about algorithms, or techniques there are many, however, I found water indices method best suitable for my study using Landsat 7 images. Longer the wavelengths, more is the absorption of water, so easier to differentiate water pixels from others (if it is not mixed with vegetation/ suspended matters). For me, the best index was the ratio of band 7 and band 4 for both landsat 7 and 8. With proper thresholding, you can even differentiate clear water/ water with vegetation/ suspended matter (you can refer my paper and one of Zhang and Wylie (2009)).
Hope that helps. Thanks
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Here is a question on choosing of "remote sensing factor" when do Suspended Sediment Concentration retrieval by empirical method: how can i decide the so called "remote sensing factor" (a band or a band ratio selected for the build of the empirical model). i know some,but not very sure .using correlation  coefficient?   Is there any experienced one can answer me ?
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You may also like to visit the site of International Ocean Colour Coordinating Group (IOCCG) for some  outstanding Reports.  IOCCG is an affliated program of the Scientific Committee on Oceanic Research (SCOR) of the International Council for Science (ICSU) 
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Part of my research presently is using ArcGIS 10.0 in Hypsometric analysis. But I need to know how the relative area (a/A) and relative elevation (h/H) are calculated so as to obtain hypsometric curve.
Please answer in regards to
where a = area above a particular contour, (how this is calculated)
          A = total area of the sub watershed above the outlet
Also, I would like to know does h represent minimum elevation of a sub-basin and H the maximum basin or sub-basin elevation.
I will be glad if someone can give me detail explanation on how to do this using ArcGIS or any other methods.
 
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There is an excellent freeware script for ArcGIS called Calhypso by the Unersity of Granada and UGR-CSIC (Spain) that does an easy and automated hypsometric analysis and can compute multiple hypsometric curves for basins.
You can find the softare here
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Could somebody please tell me where can I find the recommended standards and specifications for the installation of CORS station? What size area can a station serve and how do we select the next point in the vicinity of the first station for the installation of a new coarse station.
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I think that Silburn listed all the relevant requirements of any network of GNSS stations.
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I want to create a database of background of SO2 vertical profiles for different parts of the world. These should be over different regions and different seasons. They should cover the troposphere, stratosphere and mesosphere. Do you know of any such information? If so, please let me know.
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Dear Maria: We have a global network named NOVAC. Please visit our website: www.novac-project.eu
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I would like to use cdo in UBUNTU 14.04. I built and installed the required libraries (zlib-1.2.8, hdf5-1.8.12,grib_api-1.9.18, jasper-1.900.1, netcdf-4.2.1.1, cdo-1.6.4rc4) by the following suggestion:
When I tested cdo by a grib file using cdo sinfo test.grb operator, I got the following message: cdo is not installed. I reviewed the ubuntu software center and I installed cdo.
So now the cdo 1.6.2+dfsg.1-1 version is installed. I tested it again with the above mentioned operator and the following error message was written:
Error (gribapiGetGrid): unsupported grid type: lcc
I do not understand what the problem is? Could someone please tell me what I should to do?
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Dear Beata,
1. open terminal (terminal or konsole) and type
sudo -s -H
and after enter your root password for root privilege (for possibilty to install a package)
2. after, type line:
add-apt-repository "deb http://archive.ubuntu.com/ubuntu trusty main universe restricted multiverse"
3. after, type line:
apt-get update
4. after, type line:
apt-get install cdo
and press y to install
Hope this helps you!
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How can I obtain deflection of vertical at that point?
Thanks in advance.
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You can try ICGEM home page (http://icgem.gfz-potsdam.de/ICGEM/ICGEM.html) for geoid heights and other quantities. There you can find all geopotential models available, e.g., EGM08, GOCE-based ones, etc. For deflection of the vertical, I can provide to you a MatLab code if you need. The best of luck!
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I'm trying to understand the effect on the backscattering C-Band polarized SAR data of the budding. I have data before, during and after the bud opening of Fagus Sylvatyca and Quercus Robus (L.) on some areas. HH and VV signals don't seem to be affected, but HV does. But it seems that the backscattering of HV goes down despite my intuition. My intuition is, since bud opening is happening, biomass is growing, and in the case of SAR data, volumic backscattering is growing too. And this volumic backscattering plays on HV polarimetric backscattering by growing it. Is that correct? I joined some data with dayly pluviometry. The incidence angle of the first two data is about 20° the 3 lasts are at about 40°. Bottom figure is the bud opening visualisation. Any hints of what's really happening in terms of interaction forest-backscaterring. And moreover, bud opening-backscattering? Thank you very much!
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It is important to realize that there are 2 major mechanisms to think about when dealing with SAR In forests: scattering and absorption. The intuition is that if an object is wet and about the same size as the wavelength of the SAR data (or larger), then that object will generate scattering. Objects smaller than the wavelength will be responsible for absorption. So, the size of your buds in wavelengths is a key parameter for making sense of your data. You should calculate this. Based on your data, I would guess that the buds are fairly wet and small, causing more absorption than scattering. One can think of this like the beam of light is getting less bright as it propagates down through the branches, and witht he buds this happens faster. Hence objects that used to backscatter significantly are backscattering less because there is less "light" to backscatter. Ideally one would like to use a physics-based model to simulate such complex interactions.
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I'm interested in any alternative methods of definition of the date of a satellite view in cases when this data is absent from the archive.
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Sometimes when such metadata is missing the name of the file can be an indicator if not already renamed. Landsat is a good example. The amount of cloud cover may also help or looking at the vegetation from the images (seasonal information). These would only give a possible range within a year and not information on what year it may be. The information source (not data producer) would be the recommeded option but in many developing countries you'd be challenged. If you had images of the same extent for comparison, global statistics could help reduce the number of possible matches. Essentially you are faced with a complex problem which is more policy, organizational and culture related as most other frustrating situations. It would be great if NASA could have a tool similar to google image search, but I've not come across anything such tool.
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GPS receivers are regarded as a cost-effective means in estimating TEC (Total Electron Content). Using dual-frequency GPS receivers, we managed to obtain STEC (Slant TEC) and subsequently we made use of a F2 height peak to geometrically convert STEC to VTEC (Vertical TEC). Well, nothing seems challenge here. However, how can I specify an exact TEC value to a station? We've already managed to get VTEC for each satellite. Since a ray penetrates through different ionospheric conditions, the VTEC values are not the same. Now, is it any specific formula to estimate a VTEC value using all the mentioned measurements for a given time?
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Thank you very much Sheetal, I've already converted STEC to VTEC; however VTEC values also are not the same, since both ionosphere pierce point and ionospheric condition in the path between a receiver and a satellite are changing!
I've skimmed through your paper; as you have already outlined in the paper, you were obliged to set cut angle to 50 to have more relevant and homogeneous VTECs. But in above paper, the authors made us of a weighted average to regard lower elevation angles as well.
Bests
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Is it possible to detect passenger vehicles and trucks with standard Single Look Complex (SLC) SAR data? By standard I mean:
9.0 x 13m slant range resolution
7.7m Nominal azimuth resolution
11.8 x 5.1m Pixel Spacing
1 equivalent No. of independent looks
-29+-2 dB noise equivalent sigma 0
< 1dB radiometric error
(Standard SLC from Radarsat-2)
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Just one question..why you call standard data something is not. Surely is a multi-look SAR image and in my humble opinion you should not use multi-look data ! Why do you want to waste your full-resolution? It sounds a bit crazy, don't you think?