Science topics: Terrain
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Terrain - Science topic

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Hello,
I am looking for a terrain elevation database to develop a height-aided navigation algorithm.
In particular, I would provide a coordinate in (lat, lon) then the database could give the height with respect to mean sea level or ellipsoid, etc.
The spacial resolution should be less than 100 m and the vertical height accuracy of fewer than 20 m if possible.
Thank you for your help.
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Hi, you can find the global 15 arc-sec bathymetry in GEBCO - The General Bathymetric Chart of the Oceans (www.gebco.net)
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I came across a document where the authors have generated 2d terrain from an experimental flume. Images are attached. I would like to generate 2D geometry of a tilting flume for 2d analysis. I have dimension/1d geometry of the flume.
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We are trying to optimize the values of DEM of a particular catchment with a view of identifying outliers and predict future values. Thanks
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When I am importing the terrain file, i.e the DEM data, in HEC-HMS and associating the basin model with the same DEM, the DEM data is not showing up in the "Desktop" window of HEC-HMS. May anyone tell me why and what are the possible solutions for it?
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Check the type of cordinate system you use. FYI DEMs are in UTM...
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I search this publication : "Lambert J; 1915 - Description des échinides des terrains néogènes du bassin du Rhône. Abhandlungen der Schweizerischen paläontologischen Gesellschaft, v. 41, no. 3".
If you have it in pdf, please tell me. Thank's
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try sci-hub
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Hi,
Why when I insert the terrain model only a small part of it appears? And when I do streams delineation after sink processing the main river and reaches do not appear even after performing terrain reconditioning?
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for the first part of your question is not clear.
regarding the second part: try to modify the threshold value
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I want to konw the difference of Terrain correction and Ellipsoid correction in SNAP. My study area is the ocean mainly the sea ice. How to terrain correction without DEM or it is not necessary.
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okok
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When I download the terrain corrected high-resolution DEM from ALOS PULSAR data my elevation values are different from the actual values. What is the procedure to correct it? Some values are like -30 to -90 on the land area too. Has anyone experienced this before??
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Dear Wms Priyankara,
It is worth mentioning that ALOS 12.5m DEM data is currently mentioned on the Internet, and some are called ALOS PALSAR 12.5m DEM data, which can be downloaded from NASA ASF (Alaska Satellite Facility) ASF Data Search https://search.asf.alaska.edu/#/ . But in fact, the ALOS satellite DEM data is produced by the stereoscopic images captured by PRISM, and the onboard PALSAR (Phased Array type L-band Synthetic Aperture Radar) is mainly used to obtain orthophotos. The DEM resolution in the ALOS PALSAR Hi-Res Terrain Corrected data provided by NASA ASF is indeed 12.5m, but this DEM data is actually used to perform terrain correction on the original PALSAR data. In the ASF radiometrically terrain corrected ALOS PALSAR products product guide The source of DEM data used for terrain correction is clearly pointed out in the figure below.
Hope this can help anyway,
Kind Regards
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I have line and point data with elevation, & i need to draw a profile for every 2 km of length of the pipe. Theme is to automate the profile (graph) as the data frame moves forwards? Template is:
1st Frame: Upper Portion (will have a basemap with vector data)
&
2nd Frame: Lower Portion (will the bar chart for the above shown terrain)
Using ArcGIS v 10.8.
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In my last working. I saved the profiles in .jpg format for each cross-section and the data driven started changing .jpg files itself, after saving the path of each .jpg file in the attribute table.
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Geochemical background value for trace element is varying for different formation. In hard rock terrain (southern India), geochemical background value will need for geo accumulation calculation.
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You can find everywhere the so-called Clark values describing their mean abundance in the upper crust. There are also standards like PAAS for normalizing these base metal values. But this makes little sense as you are going to make any assessment of the accumulation of these metals in stream sediments, water or any other natural or anthropgenic host. You have firstly to determine these background values, e.g., in the carchment zone of a drainage system under consideration, in the bedrock or parent material of soil and supergene alteration zones. This is your platform to discuss chemical balances upon. Therefore, a careful investigation in terms of geological distribution of host rock lithology by mapping is the first step, then go into the mineralogy covering the full spectrum from light to heavy minerals and clay minerals and last but not least see what the primary and secondary chemical enrichment looks like. If you jump one step and ignore the accumulation processes it will turn into a equation with more than one unknown.
HGD
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In between ALOS PALSAR DEM 12.5m and CartoDEM 10m which DEM is good for landslide susceptibility mapping higher terrain area.
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In addition to the responses from fellow researchers, I would recommend the ALOS Global Digital Surface Model "ALOS World 3D (ALOS DSM) and the TanDEM-X data.
The ALOS World 3D - 30m (AW3D30) is a global digital surface model (DSM) dataset with a horizontal resolution of approximately 30 meters (1 arcsec mesh). The dataset is based on the DSM dataset (5-meter mesh version) of the World 3D Topographic Data.
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ECMWF provides high-resolution analysis for model initialization. Is it fine to use only a single domain over a hilly terrain with 9km grid spacing for rainfall simulation during monsoon season? Will it impact the large-scale systems? Please suggest.
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There is no exact rule to define the grid spacing on the horizontal, but since your study is on mountainous terrain, I recommend that you run the model with at least one nesting (two domains total). You could simulate with 12 and 4 km or with 9 and 3 km of resolution for the parent domain and the nested domain respectively.
Whether this resolution will affect large-scale systems will depend on the boundaries of the study area. Therefore, it is important that you identify the processes that interact with the study area and delimit correctly.
You should review articles about success stories with the WRF model in your study area or in areas with similar characteristics. In addition, it is always recommended to carry out a sensitivity study of the WRF model with different physical parameters so that you can identify the one that best suits your study area.
Finally, the available computing capacity is also important to consider when defining the resolution to implement with the WRF model.
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In the hec ras -RAS Mapper when i try to create a new terrain, a dialoguebox prompts - "Unhandled exception has occured in a component in ur app. You can ignore and continue".
I am not able to understand this .Can anybody help me.Also kindly give some sources from where I can get raster data for hec ras.
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The error is related to system configuration. You can either try to uninstall and reinstall the software.. After reinstalling, if you still get the error, then try to install the latest version of ".NET FRAMEWORK" in your system. This should solve the problem.. All the Best.
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I want to optimize the placement of the sensors on a 3d terrain which is created in the arcmap.
I want to find the optimum no of sensors to be used on the terrain,
can you help me in the algorithm part.
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Try to calculate the lighting and shadow zones from light sources placed at different points on the relief. Naturally, the light sources should be higher than the treetops. The situation is paradoxical in that the points that create the maximum illuminated area are located near the depressions of the relief, and not near the peaks.
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I wonder how many HRU areas should I do in my catchment area. The catchment area of 30,000 ha is divided into 31 sub-basins. Upland area with a slight slope. 14 landuses. The 3 landuses are separated by the split landuses function into 6 additional landuses. Total landuses there are 20. 32 types of soils. 5 groups of terrain slopes. I used filter by landuse, soil, slope (thresholds) 15% landuses, 15% soils, 10% slope. I received 1,000 HRU areas. Is it correct? Should I accept fewer HRU areas?
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Thank you very much for all the answers.
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Hi Everyone,
I am doing research to create adaptable frequency reuse schemes according to real terrains. Will reinforcement learning be a good option for finding the optimal frequency reuse configuration given the locations of base stations and users in a terrain.
I have finite set of action space that is all possible frequency patterns, RL agent can learn by different interference behaviour of the entire network triggered by every action. Can we use half of them for exploration and half of them for exploitation?
Thanks in advance for you reply. If anyone has done similar kind of work, let me know to contact you for further queries.
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Yes. Thanks, I am willing to use RL for it.
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Hi everyone. I am studying the influencing factors of soil organic carbon. In my research, I found that soil water content has a strong correlation with organic carbon content, and plays a very important role in the fitting linear equation. However, the soil water content only represents the soil water condition at the time of sampling, which is affected by climate ( eg. precipitation, temperature) and terrain ( eg. slope , aspect ). This indicates that there may be some uncertainty in the relationship between the single soil moisture content data and the organic carbon content. So how to determine the relationship between soil moisture and organic carbon?
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Good question! The study shared by Nagalakshmi Radhakrishnan is very helpful. This study also highlights the importance of soil texture as a control on soil organic carbon content (more clay + silt = more SOC generally). My guess is that your samples' soil moisture differences are also acting as a proxy for differences in soil texture (more clay + silt = higher soil moisture generally). Texture is more of the direct, soil property control on SOC, for which there is a voluminous scientific literature . It's also true, as you suggest, that lower, generally wetter landscape positions may be associated with more SOC: for example, lower landscape positions may be wetter for longer periods in seasonally dry environments, supporting greater primary productivity, which in turn can support higher SOC contents. Conversely, in wetter climates, these lower landscape positions lead to higher SOC often as a result of periods of soil saturation that limit SOC decomposition, supporting higher SOC contents (think wetlands as the extreme case). It's also possible that these lower landscape positions may also have finer textures (more clay + silt) as a result of erosion/deposition, including erosion and deposition of SOC, which will complicate understanding the exact controls (texture vs. moisture vs. terrain features). So, if I were you, I would definitely determine soil texture on my samples, check the level of correlation between texture and moisture, and then begin to figure out how much additional variance can be explained by other terrain features or perhaps indices of vegetative productivity, using a GIS approach, but caution that in this analysis the "controls" on SOC are likely related to one another also.
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I have weather data for around 35 years for 11 stations, of hilly terrain. two of them are ground station based, the rest of them are satellite-based data. My question is,
1) under what circumstances one should go for homogenization of such weather data?
2) what kind of methods can be adopted for such analysis for a hilly terrain?
I myself have used Mann-Kendal's trend analysis and Sen's slope estimator for analysing the climatic trend.
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Data homogenization is the process of bringing all data into a common geospatial framework to ensure consistency of data, the integrity of analysis, and the validity of results.
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Dear All,
Many authors, recommend the spatial distance to be within 5 to 15 km, between landslide incident and rain gauges in rigid (mountainous ) and gentle terrain catchments respectively (Gariano, Stefano Luigi, et al.(2019) and others).
My question about acceptable vertical distance taking in mind the difference in wind speed.
What is the acceptable range of vertical (morphological) difference between the Landslide incident and related Rain gauges?
Looking forward to have your opinions accordingly.
#rainfall #raingauges #landslides #morphology
Best regards,
OA
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Omar,
Your query is very pertinent. Landslides seldom occur in areas closely monitored for precipitation. Not only that, many landslides occur as the result of intense rainfall of short duration related to thunderstorm activity. I have seen one debris flow triggered on one side of a narrow valley where debris flow activity was historically very low. Yet on the other side of the valley where historically frequent debris flow activity occurred, there was none at at all. Clearly the intense rainfall was highly localised and no rain gauge could have picked it up unless located within a couple of hundred metres of the flow.
There is a way round the problem and that is to look out for river/stream flow patterns over the time when the landslide happened. It may be that the rivers are being monitored on a continuous basis, in which case they may provide circumstantial evidence of the time of the landslide occurrence. I have had recourse to that before now. Otherwise tracking down meaningful rainfall data can prove elusive.
regards
George Strachan
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Hi all, I'm looking for a good pdf file of this reference, texte and atlas : Renier,A., Stockmans, F., Demanet,F., Van Straelen,V., 1938. Flore et Faune Houillères de la Belgique. Introduction à l'étude du Terrain Houiller. Publication of Musée Royale d 'Histoire Naturelle de Belgique, Flora Atlas Pls.1-105, pp. 60-91. May someone has this bibliography and can share it ! Cordially and stay healthy! Bruno
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Devonian and Carboniferous dendroid graptolites from Belgium and their significance for the taxonomy of the Dendroidea
and
19th International Congress on the Carboniferous and
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Binary habitat suitability maps are 2D maps which categorize landscape into suitable and non-suitable habitat for a species. For a species in hilly region, 2D area is underestimation of total area available. Suppose 100 sq km is suitable habitat for a hilly species based on habitat suitability map. But this 100 sq km is foot area of the hill, total surface area is much higher. Can habitat suitability map be projected on topographic map to estimate total suitable habitat for a hilly species?
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Glad my recommendation suited you Mr Ashish Jha Meanwhile, I hope this video might be helpful to explain how to achieve the float feature in ArcGIS Pro. It's from Mr John Nelson, Cartographer, ESRI, himself.
Happy Mapping.
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If the elevation of the study area (DEM) ranges from (20-26 meter), should the terrain be corrected in the image from (Sentinel-1 Level-1 GRD) for the land cover classification ?
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Ismail Mondal you will need Sentinel-1 VV and VH polarization, use SNAP or orfeo-toolbox to do Radiometric correction and speckle filtering -> Geometric correction using DEM , when using orfeo-toolbox you can use both DEM model and Geoid to get the height above the ellipsoid in case there is no DEM available.
The documentation for orfeo-toolbox can be found here:
- Calibraion
- Terrain correction
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I'm aware that in order to perform any vegetation index like NDVI, SAVI or OSAVI you need to do some atmospheric, radiometric and terrain corrections. I'm pretty sure that Level 2 images from EarthExplorer are already atmospheric and radiometric corrected but I'm not sure about the terrain or the topography... If so, do I just oreder them, download them and perform the raster calculation? I'm using QGIS 3.16.1 btw.
Thanks everyone for your answers!
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Nasir Hameed Thank you so much!
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I am required to do a project where I have to calculate discharge of streams/ watersheds in a high altitude area with extremely treacherous terrain. Will it be possible to achieve this objective using GIS and remote sensing, without field observations ?
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Dear Bro. Indranil Mondal
You can
Please find the attched manual file, it will help you:
all the best
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I am trying to find the cosine of sun elevation angle on slope terrain, I found the values between -0.9 to 0.9. Should the value be set to 0 - 0.9 or the negative value acceptable?
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Interesting question
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Is there any commercial or open-source DIC (2D or 3D) software which is capable of working on field photographs of terrain or satellite images for deformation and strain analysis in geophysical applications?
What I am looking for, is an equivalent of GOM or Ncorr/MultiDIC that would be suitable for usage with non-calibrated camera images by using automated pixel correlation.
VIC2D can do something of the sort but it is quite expensive and not completely satisfactory.
Thanks
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Dear Catani,
What about CIAS ?
It matches offsets between two images based on normalised cross correlation.
Best regards...
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Out of freely accessible Digital Elevation Model Which one is better suitable for Non-point source pollution modeling? (Indian terrain)
I want to apply hydrological modeling for the study.
The study area is 3000 Sq.km approx.
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If the study area is in India, then DEM provided by NRSC would be best suitable due to its accuracy... You can download dem from Bhuban free of cost...
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Which is the simplest way to remove vegetation from drone based digital elevation model (DEM), or how to prepare digital terrain model from drone-based DEM?
Do you have any experience how to make that reasonably simple?
Any help is appreciated.
Thank you!
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Hi Ivica, 
I think following the article might be useful. And, the answer provided by the previous researcher looks awesome.
Anders N, Valente J, Masselink R, Keesstra S (2019) Comparing Filtering Techniques for Removing Vegetation from UAV-Based Photogrammetric Point Clouds. Drone, 3:61. doi:10.3390/drones3030061
Thank you.
Shivish Bhandari
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When you want to do a project of a wind farm, and you want to be most precious on that, so that your results are very close to reality?
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Unfortunately, there is no free version of the software.
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I seek for general discussion of experts on the preferred usage of ASTER and SRTM digital terrain data, and on what conditions ?
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1. You can use fused DEM (from SRTM & ASTER). It is available as two products: MERIT by yamazaki (uni. Of Tokyo) and EarthEnv DEM90 ( collaborative project of NASA)
2. Choose among TanDEM-X 90m openly accessible DEM from DLR or ALOS PALSAR 12.5m RTC HR DEM dataset depending on application and topography.
3. Try Earthexplorer and other platforms of openly accessible data for some more local option, if available. At places it may be available as: lidar DEM or aerial product.
Best wishes
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My team is interested in scanning trees and smaller plants as part of analyzing how terrain and plant manipulations affect their growth. Can anybody advise of methods for scanning plants in such way as to obtain complete point clouds?
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Depending on the measurements, structure from motion photogrammetry can be an accurate and very inexpensive means of getting measures of stem diameter and such. It suffers from problems with occlusion more than laser scanning.
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In many part of the world there are many unknown economists who might have contributed to economic theory but their contributions remain unknown to the world because they might be living in an area away from the modern world, lack of modern connectivity and even lack of education. In one of my visit to mountainous terrain in northern hills of Pakistan i cam across such a literature. I found it very useful and am writing paper on it. In your opinion which journal could be the best for such papers?
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Hello Ejaz, maybe this link will help you:
It is an article about George Simmel's Philosophy of Money and the journal is Journal of Economic Literature. I believe that you will find more unknown economists article in this journal.
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I just want to know the scene azimuth angle of my ALOS-2 data for the radiometric terrain correction.
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There were correct answers above; if you need more practical ad hoc advice - just add 'north arrow' marker to the screen and use it for measuring azimuths.
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i want to prospect ground water in rocky terrain using satellite imagery. i need to know the most suitable data to be use, the method of extraction and the procedure for achieving it. Thank you in anticipation of your useful contribution.
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For automatic lineament extraction, you can achieve this by applying a combination of the following softwares: Arcmap 10.0+, ENVI 5.1, PCI GEOMATICA 2016, ROCKWORKS 16.
STEP1: Use ENVI software to perform principal component analysis (PCA) on the spectral image band of Landsat8.
STEP2: GEOMATICA is used to perform an automatic lineament delineation from the PC1.tiff generated from ENVI. This is done with the aid of lineament extraction algorithm in the Tool from toolbar
STEP3: ARCMAP is used for handling extracted lineament (splitting compound line into simple lines, editing lineament attribute, exporting lineament as cad file
STEP4: ROCKWORKS is used to process the exported lineament Cad file to determine the trend of the lineament and hence generating rose diagram.
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We recently discovered carbonaceous nodules in some clay-rich sedimentary rocks in Kaele, Far North region of Cameroon. This area is a Precambrian Granites-gneiss- amphibolite schist terrain. The present of sedimentary rocks in this area has yet be mentioned. The recent field survey lead to the identification of sandstones, mudstones and clay-rich rocks partially overlaying a Precambrian granite basement. Mudstones are carbonaceous clay-rich rocks are overlain by alluvial clay deposits.
We collected three groups of samples:
-carbonaceous nodules;
- mudstones and carbonaceous clay-rich rocks
- alluvial clays
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I think its belonginging to mother rocks that is weathering
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Hello all,
I have analyzed the 3H in groundwater samples (the area is mostly granitic terrain) and the value shows 1-8 TU and two samples show 11 and 28 TU. I don't have any results like 3He. So can we infer the age of groundwater here by looking into the tritium units?
Looking forward to seeing your response.
Thanks.
Rudra Mohan Pradhan
IIT Bombay
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Dear Virendra Kumar Saxena Sir, Thanks for the reference. I will go through it.
regards.
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I am using Erdas Imagine-2014. When i try to use 'surfacing tool' inside the 'Terrain Preparation tool' to Perform Surfacing, it stops working. It reads data finely and makes x y z values from image data, but when i hit 'Perform surfacing' button it's not working and closing the active 3D surfacing window. I am looking for solution. Thanks
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You can use erdas 15 to solve the problem,,, some time erads 14 tool not working
you download this link
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Starting a new project modelling potential mangrove restoration sites in Sri Lanka!
Can anyone help me source the following high-resolution spatial data sets :
- Digital Terrain Model (DTM)
- Coastal bathymetry
- Tidal height/currents
- High resolution satellite imagery (raster format)
- Rainfall/Climate zone maps
Thank you greatly for any help!
Ciao,
Dan..
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Dear researchers, I would like to ask you if you have the digital terrain models of Wankama and Tondi Kiboro basins. I'm looking for DTMs with a good resolution, a resolution higher, and more reliable, than the freely available online.
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Dear Sir,
I cannot provide information and answers not using DTM on these watersheds.
You can consult the AMMA Catch website:
you will find attached a publication : Évaluation de l'érosion du site de Wankama (Niger) par comparaison de différents MNT.
All the best for your research,
Yours sincerely,
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Hi everyone,
As a convener, I would like to invite you to submit an abstract to the session: 08a: Metal Mobility in the Critical Zone and its Implications to Geochemical Exploration in Weathered Terrains in the Goldschmidt 2020.
The description of the session is below:
Shallow mineral deposit discoveries are becoming less common and those world-class deposits are either mined out or decreasing in production. One of the fundamental challenges for mineral exploration industry in this century is targeting deeper concealed mineral deposits under the critical zone. The increase in demand for mineral resources worldwide is driving investment in developing new geochemical exploration methods for vectoring concealed mineral deposits in deeply weathered and covered terrains. Extensive older terrains of Australia, India, West Africa, Brazil and China are deeply weathered and others such as Canada and Fennoscandia are overlain by recent glacial sediments. Thus, geochemical signatures of the mineralisation and the host rock can be obscured by deep weathering and transported cover providing challenges for exploring these terrains. The purpose of this session is to bring together a number of contributions showing interdisciplinary integrated approaches for understanding physical and biogeochemical mechanisms for metal mobility from the mineralised source through the critical zone to surface. The session also invites topics discussing recent advances in developing or improving geochemical and analytical (isotopic and dating) techniques, numerical modelling and experimental methods applied for mineral exploration through the critical zone. Geochemistry of supergene ore deposits, indicator mineral chemistry, and hydrogeochemical studies are also part of this session.
Please visit the following link for more detail: https://goldschmidt.info/2020/program/programViewThemes
Finally, I appreciate your quick response to my message and if you are not able to attend, could you please circulate this invitation to other colleagues working in the same field.
Best regards
Dr Walid Salama
Senior Research Scientist
CSIRO Mineral Resources
Australian Resources Research Centre
26 Dick Perry Avenue,
Kensington, WA 6151, Australia
T +61 8 6436 8745
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one week from the deadline of abstract submission.
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In preparing a series of academic illustrations we're looking for an open source DTM for the Croatian islands of Palagruza. If anyone has, or knows of such a model, we would be very grateful
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Hi Leandro,
Many thanks indeed for this
Vince
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An Unmanned Aerial Veichle (UAV) based survey is being conducted for an area which is more or less a flat terrain type. The post processing of the UAV images results into a digital elevation map which shows the height of buildings along with the surrounding agricultural areas.
So, could anyone please suggest the procedure for separation of the surface heights from the raster file to create the actual elevation of the region?
Thank you in advance
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Hi Saroj Kumar Dash, you could work directly with UAV point clouds and exporting them in CloudCompare, after that try to get the DTM using the CSF plugin.
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Hydrochemical processes that will release HCO3 ion in groundwater.
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you welcome Ebenezer
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How much does it cost and how much time in administrative procedures is needed FOR GETTING PLANNING PERMISSION ON AGRICULTURAL LAND for future industrial development on a terrain approx. 1 ha (10 000 sq.m.)?
e.g. in Bulgaria the price vary depending of the land category and infrastructure circumstances from 15 000 euro to more than 30 000 euro and the time needed in administrative permissions more than one year (mainly depending on the location of the governing institution).
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I assume it greatly depends on many factors like, social, economic, cultural, even diplomatic backgrounds.
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I want to perform a WRF simulation, but I am unsure whether I should spinup as I am also doing nudging. So I have these questions basically.
1. Should I do model spinup if I am doing nudging along with it?
2. Several studies show different spinup time. What will be the optimal spinup period?
3. Whether spectral or analysis nudging is best for simulating precipitation in a very complex terrain?
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If the length of the simulations are only one month, the only spin-up that needs to be accounted for is the atmospheric one, which is typically only a few days. If I understand well, you are nesting two domains, the first one at 27km resolution (which is about the same as ERA5), and the second one at around 9km. In this situation, I would suggest to use 5 days spin-up in the beginning of each nested integration (so adding up both spin-up would lead to 10 days), and then begin the one-month simulation.
Maybe you could find the following paper of interest :
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Presently, I am working in the sedimentary terrains which comes under the eastern part of the Vindhyan Supergroup of rocks, Eastern India. The studied area is mainly composed of gritty to coarse grained arenite sandstone of the Ghaghar Formation and greywacke sandstone with thinly bedded siltstone of the Scarp Formation belonging to the Kaimur Group. Therefore, I would like to know that, in which environments these sandstone units are probably formed.
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Greywackes consist of a sand-size framework component floating in a finer-grained pasty matrix of grains finer than 0.03 millimeter whose overall abundance exceeds 15 percent by volume. Arenites consist of a sand-size framework component surrounded by pore spaces that are either empty or filled with crystalline chemical cement. Further subdivision of both arenites and greywackes into three specific sandstone families is based on the relative proportions of three major framework grain types: quartz (Q), feldspar (F), and rock fragments. Greywacke formation is attributed to submarine avalanches or strong turbidity currents. These actions churn sediment and cause mixed-sediment slurries, in which the resulting deposits may exhibit a variety of sedimentary features. Supporting the turbidity current origin theory is that deposits of greywacke are found on the edges of the continental shelves, at the bottoms of oceanic trenches, and at the bases of mountain formational areas. They also occur in association with black shales of deep sea origin. The two primary sedimentary depositional environments that produce quartz arenites are beaches/upper shore face and aeolian processes, due to their high residence time, high transport distance, and/or high energy of the environment. Most of the time, these sediments are reworked over and over, even being eroded out of a lithified rock and becoming a brand new sediment and rock. This is known as a multicycle sandstone.
Best regards
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Hi all,
I am studying a coarse grained staurolite-garnet-sillimenite (fibrolitic) bearing quartzo-feldspathic schist (quartz-feldspar-biotite-muscovite-garnet-staurolite-sillimenite) from a deformed and metamorphosed Precambrian terrain. Previous authors have described them as pelitic schists. However, these schists have nearly 10-12 modal% feldspar indicating they are not pelites. 
The feldspar grains are extremely coarse and subhedral (not rounded) like those from deformed igneous rocks (photomicrographs attached). I have a suspicion that they may not be detrital and the original rock was a granite (peraluminous) rather than a quartzo-feldspathic sediment. Is there any way to identify its possible source from the whole rock analysis of this rock or from any other aspect? The original texture and mineral assemblage is partially modified due to deformation and metamorphism. 
Feldspar compositions vary roughly between Ab70An30 to Ab60An40 (Or component is 0.1-0.3).
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Dear Mrs. Chaudhuri,
I take in this case a tripartite approach.
1. Have a look at the metamorphic lithologies associated with your rock under study; are there meta-carbonates, metabiolites...etc. Sometimes you can get an impression of the hidden paleoenvironment. Even by the presence of strange minerals like scapolite (ref. palaeo-sabkha..) you can get a hint.
2. Use ACF and AFK diagrams where the protoliths are shown by reference fields
3. Try and find ultrastable minerals like rutile, tourmaline and zircon. A very subtle investigation of them microchemically and morphological may in some cases shed some light on the parent material.
Take a multiple approach encompassing a geological (1.), chemical (2) and mineralogical (3) method.
I wish you much success
H.G.Dill
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How reliable and applicable is the DEM derived drainage system for a particular terrain. What could be the agents that causes the different drainage patterns besides water cycle?
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In my researchgate, there are a few papers I and associates worked on, that might be interesting to you. Check out Stream Types and Management Implications which used and compared stream densities based on 1:24000 and 1:100000 scale based DEMs. A couple more recent papers (James ET al, and Maceyka and Hansen) used LiDAR based DEMs with much greater detail for gully, channel and watershed boundaries. LiDAR in one of my projects in Georgia was able to detect intermittent or ephemeral channel detail of an added two to three orders, as compared to 1:24000 topographic map based DEM. LiDAR based DEM in heavy forest also detected old drainage ditches, areas of past channel relocation for farming, old skid roads and other features. LiDAR gives a much truer georeferencing of stream network location and even roads on topographic maps. Field work and experience in area of interest helps to identify the likelihood of flow permanence, recognizing there can be substantial variation in size of headwater catchments that produce ephemeral, intermittent or perennial flow.
Concerning your our basic question, I am probably not the expert on how a DEM works, but basically the conversion of a topographic map into a DEM, divides the land into small pixels, such as 30m x 30m or 10m x 10m. Each pixel is part of a detailed raster network, with its own elevation, location, etc. The hydro models are designed to help find the flow path as the water accumulates as it flows downhill seeking the lowest direction as it moves downhill. Expect to find some mistakes if not using LiDAR based DEM. Cartographers are not perfect in photo interpretation, especially in heavily forested areas. LiDAR can also be helpful as water absorbs the laser beams, useful for identifying surface water at time of survey, such as streams, wetlands, etc.
As mentioned, subsurface flow is another subject that can be important in some situations As karst geology, but LiDAR or aerial photo DEMs might give some indicators as sinkhole terrain. Experienced geologists, soil scientists, ecologists and hydrologists can sometimes read photos and topographic indicators with greater intensity and interpretative meaning.
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Pls tell me a source to download the land use map and terrain for Australia for free?
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Sujatha Mayadunnage Your question reads LULC Maps for Australia.
You can use the ESA CCI landcover data. It is a compositely processed data from different satellite sources such as as MERIS, PROBA-V and ENVISAT ASAR. It is an annual data series from 1992 to 2015 yielding 23 year consecutive data for various analysis. The spatial resolution is 300 m which is equivalent to three football stadiums as a pixel size. That is the limitation. However, it is a global data and Australia is fully captured.
You will need to register to be able to download the data.
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An extension station is located on sloping terrain of a minor hill. There is flat land at Hill top, slope of 50 feet level difference and steep gradient of 60 degree and at the foots, there is strip of hill foot, cut to form a terrace for cultivation.
This is tropical climate near West coast of Maharashtra, India, receiving ~2000 mm rainfall for the season.
This bottom strip receive heavy inflow of runoff water and also the rainfall. Therefore water logging type Condition occur. There are two type of soil in the region, the black clayey soil is suitable for paddy cultivation and this crop is grown in water logged condition. However the soil at mentioned site is not black clayey soil and is less fertile, loamy light brown to yellow red soil. Kindly suggest a crop suitable under such conditions?
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Upland rice or eucalyptus trees for energy or timber. In a wet climate, eucalyptus trees can provide either wood for cooking, construction, or pulp for paper. With rice, you will need some sort of soil conservation plan.
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Hi everybody!
Can anyone suggest me species of plants that usually grow slowly in an in-vitro plant tissue culture?
Or better: i'm looking for plants that can stay up to 1-2 years in the same terrain without growing too much and without the need of changing the media or adding nutrients. Even in small eppendorf with a small amount of terrain (1-2 ml of terrain).
Someone suggested me the Drosera rotundifolia species, but i'm looking for additional ones.
Thanks a lot!
P.S. we are using murashige and skoog media + sucrose + agar
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In addition to the first comment by Ghanbari, I have had good results adding mannitol as osmoticum, which helps slow down growth. In this case cultures as fast growing as Ficus species were stored for 2 years.
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Strong impact of topography on Land Surface Temperature (LST) has limited its use on flat terrain. I am currently working on extracting LST data from band 10 Landsat 8 for a mountainous area. I have read that it is necessary to apply topographic normalization to the LST if the study area has a complex terrain. Is there any recommendation on what method or tools I should use?
Do topographic correction methods for LST differ from the ones used for surface reflectance?
The only reference I could find for topographic correction for LST is from Malbéteau et al. (2017)
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The radial collector well is on perennial river on a alluvial terrain. The river is a braided one. The water channels on the stream bed are separated by sand stretches.
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Well,
thats depend on the values of the hydraulic coefficients of the sediments(water bearing horizons) and the design of the radial well.
regards
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For long, I am looking for the Sm-Nd analytical facility. My terrain has mafic, felsic and metasediments. So far there is no age data available for the mafic rocks. The rocks are having compositions like gabbro- anorthosite, amphibolite, dolerite and traps. In gabbro-anorthosite suite, platinum occurrence has been recorded recently.
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@Dr. Dilip Majumdar, My paper is in press which is about the Radiometric dates from Mikir hills...Soon it will be published.
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I carried out a geophysical survey identifying surface anomalies (fractures). The data was acquired through several lines of orientation profile W-E and N-S
Due to the topography of the terrain the profile lines are not equidistant (50m-200m) and have different orientations (W-E and N-S are preferential directions). However, the distance between measurement points of each profile is uniform (10m). In summary I have scattered data but with linear tendencies pertaining to the orientation of each profile.
In summary, I want to do an interpolation that takes into account two preferential directions (North-South and Norwest-Southeast interpolation) to generate a trend map within a GIS. An example is in Figure 1.
For the interpolation I have used the ArcGis and Surfer with several interpolation methods (Kriging, IDW, next neighboor, etc) but they do not produce good results because they interpolate data in unwanted directions (Figure 2)
I would like to know which method to use and which parameters I have to enter to perform the desired interpolation.
Thank you very much for your comments
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For anyone to give you really useful information you need to be more specific about your data and why you want to interpolate. According to the graph/plot you have made measurements on some characteristic at each of the "dots"but it is not clear what the characteristic is. With respect to interpolation does this mean you want to generate more curves of dots or does it mean you want to generate values at some prescribed non-data points. What will you use the "interpolated data" for? It is premature to simply recommend that you use spatial analyst or specific algorithms such as IDW or kriging. Although there is no theoretical basis for IDW using it still makes some presumptions about the nature of the data, i.e you have a set of data locations and at each you have a measurement or recorded value, the objective is to generate a value at some pre-selected non-data locations.
Several respondents say or imply that you have to use GIS or GIS software, that is not true. Munir's comment about "drawing a trend" is wrong and also irrelevant but he is correct that there are always interpolation errors. As for kriging, in general it is better than IDW but it is based on various statistical assumptions and there are several different forms of kriging (Simple, Ordinary, Universal, Cokriging). If you are not already familiar with it, you should not just treat the software as a black box. The documentation is not enough to understand how to use it nor how to interpret the results.
Do a search on Google for "variograms and fractures"
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I have purchased LISS-IV data with standard processing level. The data is in radiometric values. ToA conversion should be done for each of the bands. Hence I think first the atmospheric correction should be done and then the layers may be stacked to do georeferencing or terrain related corrections. Am I right?
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Atmospheric correction should be done first because it is the first layer of influence that you can eliminate. Only after atmospheric correction, you are advised to play with your data.
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I am looking for the DTM of the Queensland state, Australia. Where do you guys think I can get it from? I really need it for my project!
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Hi,
Two things must be considered:
1. A free DTM or paid one;
2. What is the spatial resolution of the DTM required for your project.
For free you can get AW3D30 - a very good model (one sigma approx. 0.8m), and a much more popular SRTM somehow less accurate (one sigma approx. 2m). Both are at 1" resolution and both are DSMs.
Best regards,
KB
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I have derived a slope map, normalized DEM, aspect, plan and curvature maps from a DEM in ArcMap. Now I would like to use this maps in eCognition in order to identify landform components. Can anyone help me with the steps to follow or rule sets.
Thank you
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some tools offering automated landform classification based on DEMs:
GRASS
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Majuli is a wonder of nature. Situated in the midst of the mighty Brahmaputra river, Majuli is the largest freshwater river island in the world. There are numerous tribes living in the island, maintaining their folk culture and continuing a tradition that is unique and remarkable. The island is populated by different colourful communities, majority of them abide by the tenets of the Vaishnavite Guru, Saint Srimanta Sankaradeva. My book titled ‘Majuli: Resources and Challenges’ is an edited volume that gives a comprehensive view of the resources and challenges of Majuli. It is published by Authorspress India. Majuli remains largely an unfamiliar terrain for most of the Indians. Majuli’s efforts for world heritage conservation has not succeeded yet. Majuli is characterised by Sattras and Their Heritage. There are issues like Protecting Majuli from dominating Brahmaputra, Sustainable Design Solutions for the Mitigation of Flooding and Riverbank Erosion in Majuli Island, Eco-restoration of Majuli Island, Land-use/Land-cover in Majuli etc. For more about Majuli, one can check the site http://majulilandscape.gov.in
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Majuli is the world’s largest riverine island situated in mid of river Brahmaputra in Assam state of Northeastern India. It is a site having extreme historical and cultural importance, and warrants immediate exposure to the scientific community. The island faces an acute erosion problem at rate of 1.9 km2/year. If the situation remains unattended, the island will soon be engulfed by the Brahmaputra river and will become extinct from the world map. Please take a look at the following RG links.
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KML files usually relates to digital elevation data for a terrain.
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I am not sure what you mean by a LM elevation map, but here is my proceedure or down loading a binary flat flle from the USGS web site to get a one degree by one degree map. For a specific example
Here I downloaded the map based on 1 arc sec. of resolution. In addition to the “.flt” and “.hdr” files, the picture file “jpg” file is useful. The picture file can be used to verify one has appropriately got the elevation map correct. The :.hdr” file contains the following information:
ncols 3612
nrows 3612
xllcorner -81.00166666667
yllcorner 38.99833333333
cellsize 0.000277777777778
NODATA_value -9999
byteorder LSBFIRST
The longitude and latitude of the lower left hand corner of the 1deg. by 1 deg. elevation map are given by xllcorner and yllcorner, respectively. Now set a variable Lon0=xllcorner and construct a vector for the longitude for n=1:ncols;lonvec(n)=Lon0+cellsize*(n-1);end The vector for the longitudes is straight forward, not so for the latitude vector. The data are indexed starting in the upper left-hand corner; whereas our lat-lon are indexed in the lower left-hand corner. This means to define our latitude vector in reverse order. Set a variable Lat0=yllcorner and construct a vector for the latitude for n=1:nrows;latvecinv(n)=Lat0+cellsize*nrows-cellsize*(n-1);end
Now read in the flat file for the elevations
fid=fopen(‘****.flt’,’r’) e
ev=fread(fid,inf,’real*4’);
elev=reshape(elev,ncols,nrows);
This should put the elevation map in the form elev(long,lat); however, we want x-axis to be pointing North, thus
elev=permute(elev,[2 1]);
This gives our elevation map in the form elev(lat,long). If we want to view our elevation map using MATLAB imagesc we need to understand that the normal way MATLAB indexes the array is like a matrix; i.e., (1,1) is in the upper left hand corner. However, we want to index our image starting in the lower left-hand corner. This is accomplished by using the call axis xy. Our call to imagesc is: imagesc(lonvec,latvecinv,elev);colorbar;axis xy;
To see if one has the map correct, compare to the jpg picture of the map given in the download.
Hope this helps
Lewis C. Bartel
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I am currently working in a flat terrain area with no rock outcrops for determining the geology of the area. Also, the said area has no detailed lithology map and therefore am looking at developing one. However, the only information i have at my disposal are the XRF and XRD aanalysis results from soil samples collected across the study area.
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XRF and XRD measurements are used to determine the chemical and mineralogical constituents in the rocks. With the help of Core hole (diamond core) drilling, we can know the vertical extension of the rock formation. Core samples give immense information for lithological assessment.
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Advices and indications about types of microphones or recorders (and their location in terrain) and software for processing data are wellcome.
Thanks!
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He ojeado la página y me parece un proyecto interesantísimo! Muchísimas gracias por el dato. Me pondré en contacto con Juanjo Palacios para saber más y enriquecer el estudio que quiero desarrollar.
Gracias, saludos!
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I would like to know the currently available instruments and tools for mapping the karst terrain to map the extent of voids/ weak zones in the underground depths ranging from 10 to 30 meters
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If measuring from the surface, most commonly GPR and ERI are used.
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Hello! I need to estimate the storage of carbon in a landscape with different coverages over time. I know there are jobs where they estimate the carbon with the NDVI and terrain data, but I do not have terrain data. Does anyone know if it is possible to estimate carbon using only spectral data?.
For the moment, the only thing that has occurred to me is to look in the literature for information on carbon storage in the different coverages, and then model it with the NDVI to spatialize it.
Any recommendation about it is welcome.
Thank!
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Thank you very much for sharing these publications Ivan. I recommend your publication when it is accepted, I would like to read it. For now I will continue exploring methodologies to solve my concern.
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Hello,
I am looking for an essential fossil shark reference that is impossible for me to find:
Contribution a l'etude des faunes ichthyologiques marines des terrains tertiaires de la plaine cotiere Atlantique et du centre des Etats-Unis. Memoires de la Societe Geologique de France (Nouvelle Serie) 45:1-111
The problem was solved in the meantime. Thank you! The issue is closed :)
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Hi Nicolae,
the best way is to have a look at shark-references :-) Attached is the downloadlink Greetings Jürgen
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I am using multi temporal Sentinel1 SLC IW data for classifying crop types. And to process them in SNAP, i am using the following steps:
1. Tops-Split/Deburst/Merge
2. Apply Orbit file
3. Callibrate (output sigma band for VV and VH)
4. Speckle filter (filter Gamma map (3/3))
5. Multilook
6. Terrain Correction
Can anybody confirm the steps to be correct and appropriate for crop classification. Thanks in advance.
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Dear Yajnaseni Palchoudhuri
Why are you using S1 SLC product for crop classification? Off-course you can use it, but I think you can save time using directly S1 GRD product, I have been working with S1 for crop classification in several European regions and the results are pretty good. Regarding the pre-processing steps there are many ways in doing this, and the choice for the "best and universal" chain processing do not exist at all, it depends mostly on your study area (e.g. landscape topography) and your goals. For example the selection of the speckle filter algorithm is relevant, and again, depends on your study area, for example, if you are working on a agricultural landscape were small farm system is dominant and if you want to preserve the crop edges you need to test different algorithms and moving windows, because this will impact significantly your results. For this you can subset a small part of your study area and run different speckle filters and windows, check the differences and select the best for your case. Bellow you can find a tutorial with the basics for crop classification.
Have a nice S1 processing!!
Regards
Sérgio Godinho
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reasons why we usually sectorize our water distribution networks
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interesting question Sir. Orkaido
following
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Can someone refer me to a local PhD networking support group in the Northern Dallas Texas area. It certainly would prove effective to communicate face-to-face with someone else walking through this terrain.
Beverlyn Banks
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For my research purpose I need to construct urban terrain model. But In india, LiDAR data are not affordable enough as well as hard to find for a researcher with middle class background. There are some papers where researchers used that model. But they did not provide detail procedure of making that. One of them modified of DEM by using of ground clearance among buildings. The process itself is not clear enough to follow.(DOI: 10.1007/s11442-011-0844-7)
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given the tight legal restrictions in India, using drones to acquire the data you need will likely not work. Best bet are indeed satellite data. Here India is very well equipped: the Cartosat stereo satellites provide very good data for elevation extraction. While the first Cartosat generation still has 2.5 m spatial resolution, the latest one (Cartosat-2C, launched in 2016) bring that down to about 0.6 m. Cartosat 3 is expected to bring this down further to about 25 cm in the panchromatic.
good luck, Norman
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The classical expression for turbulent dissipation rate states u*3/l, where, l = kz in the flat terrain. I want to calculate dissipation rate in a complex terrain but as per my knowledge, l = kz doesn't work in complex terrains.
Is there an alternative method to calculate turbulent dissipation rate in complex terrains?
Any suggestions would be much appreciated.
Thanks in advance!
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My aim is to use Landsat data (surface reflectance) for large-scale land cover classification tasks. As various regions of the area under investigation is in mountainous terrain I am planning to apply a radiometric correction of the topography effects.
Does anybody have experience with that or even a ready to use code snippet? Ideally I would apply such a correction within a ".map" routine over entire image collections.
Thanks very much for any help in advance,
Teja
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I found this script from the EarthEngine user 'kasparhurni', maybe it helps:
//Topographic correction of all Landsat satellite imagery
//USER INPUTS
var startYear = 2015;
var endYear = 2015;
var targetDay = 350;//day of the year around which the mosaic of good observations is built
//startSeason and endSeason define the window to search for 'good' observations for the mosaic
//around the targetDay.
//Window size needs to be a trade-off between availability of good observations
//(large temporal window) while minimizing phenological changes (small temporal window)
var startSeason = '-12-01';
var endSeason = '-12-31';
var studyArea = ee.Geometry.Polygon(
[[[85.1, 27.9], [85.5, 27.9],
[85.5, 27.5], [85.1, 27.5]]]);
////////////////////////////////////////////////////////////////////////////////////////////////
//------------------------------------END OF USER INPUTS--------------------------------------//
////////////////////////////////////////////////////////////////////////////////////////////////
// Definition of Landsat 5/7/8 bands and default band names
var LC8_BANDS = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7'];
var LE7_BANDS = ['B1', 'B2', 'B3', 'B4', 'B5', 'B7'];
var LT5_BANDS = ['B1', 'B2', 'B3', 'B4', 'B5', 'B7'];
var DEF_BANDS = ['blue', 'green', 'red', 'nir', 'swir1', 'swir2'];
//CONVERT TO RADIANS AND CONSTANTS
function radians(img) {
return img.toFloat().multiply(Math.PI).divide(180);}
//SR TIME SERIES SELECTION
//LANDSAT 8 TIME SERIES, MASK CLOUDS USING FMASK, ASSIGN DEFAULT BAND NAMES, SCALE
var getLedapsLC8 = function(year, sensor, box){
var srCollectionT = ee.ImageCollection('LANDSAT/'+sensor+'_SR')
.filterBounds(box)
.filterDate(year+startSeason, year+endSeason)
.map(function(img){
var cloudMask = img.select('cfmask').eq(0);
return img.mask(img.mask().and(cloudMask));
})
.select(LC8_BANDS, DEF_BANDS)
.map(function(img){
return img.select([]).addBands(img.multiply(0.0001));
});
var cloudCollection = ee.ImageCollection('LANDSAT/'+sensor+'_L1T')
.filterBounds(box)
.filterDate(year+startSeason, year+endSeason)
.filterMetadata('CLOUD_COVER', 'less_than', 50)
.map(function(img){
return img.select([]);
});
var innerJoin = ee.Join.inner();
var filterTimeEq = ee.Filter.equals({
leftField: 'system:time_start',
rightField: 'system:time_start'
});
var joinedCollection = innerJoin.apply(srCollectionT, cloudCollection, filterTimeEq);
var srCollection = joinedCollection.map(function(feature){
return ee.Image.cat(feature.get('primary'), feature.get('secondary'));
});
return ee.ImageCollection(srCollection);
};
//LANDSAT 5 and 7 TIME SERIES, MASK CLOUDS USING FMASK AND SR_*_QA, ASSIGN DEFAULT BAND NAMES, SCALE
var getLedapsLT5LE7 = function(year, sensor, box){
var srCollectionT = ee.ImageCollection('LANDSAT/'+sensor+'_SR')
.filterBounds(box)
.filterDate(year+startSeason, year+endSeason)
.map(function(img){
var timg = img.unmask();
var mask = timg.select('sr_cloud_qa')
.add(timg.select('sr_adjacent_cloud_qa'))
.add(timg.select('sr_cloud_shadow_qa'))
.add(timg.select('sr_snow_qa'));
var cloudMask = img.select('cfmask').eq(0).and(mask.eq(0));
return img.mask(img.mask().and(cloudMask));
})
.select(LT5_BANDS, DEF_BANDS)
.map(function(img){
return img.select([]).addBands(img.multiply(0.0001));
});
var cloudCollection = ee.ImageCollection('LANDSAT/'+sensor+'_L1T')
.filterBounds(box)
.filterDate(year+startSeason, year+endSeason)
.filterMetadata('CLOUD_COVER', 'less_than', 50)
.map(function(img){
return img.select([]);
});
var innerJoin = ee.Join.inner();
var filterTimeEq = ee.Filter.equals({
leftField: 'system:time_start',
rightField: 'system:time_start'
});
var joinedCollection = innerJoin.apply(srCollectionT, cloudCollection, filterTimeEq);
var srCollection = joinedCollection.map(function(feature){
return ee.Image.cat(feature.get('primary'), feature.get('secondary'));
});
return ee.ImageCollection(srCollection);
};
//C TOPOGRAPHIC ILLUMINATION CORRECTION
var correctTopo = function(year, box){
//DEM, SLOPE, ASPECT
var DEM = ee.Image("USGS/SRTMGL1_003").clip(box);
// Define a boxcar or low-pass kernel.
var boxcar = ee.Kernel.square({
radius: 3, units: 'pixels', normalize: true
});
// Smooth DEM by convolving with the boxcar kernel.
var DEMs = DEM.convolve(boxcar);
var SLP = radians(ee.Terrain.slope(DEMs));
var ASP = radians(ee.Terrain.aspect(DEMs));
function iteration(img, imglist){
imglist = ee.List(imglist);
img = ee.Image(img);
var emptyImage = img.select([]);
//STUDY AREA AND IMAGE
var footprint = ee.Geometry.Polygon(ee.Number(ee.List(img.get('system:footprint'))));
//VARIABLES FROM METADATA
var AZ = ee.Number(img.get('solar_azimuth_angle'));
var ZE = ee.Number(img.get('solar_zenith_angle'));
var AZ_R = radians(ee.Image(AZ));
var ZE_R = radians(ee.Image(ZE));
//CALCULATE LOCAL ILLUMINATION AND COS OF THE ZENITH ANGLE
var IL = AZ_R.subtract(ASP).cos().multiply(SLP.sin()).multiply(ZE_R.sin())
.add(ZE_R.cos().multiply(SLP.cos()));
var cos_ZE = ZE_R.cos();
//GET REGRESSION COEFFICIENTS (B & M) AND CORRECTION FACTOR FOR EACH BAND & PIXEL
//C for the blue band
var clippedImg1 = img.addBands(1).addBands(IL);
var resultBlue = clippedImg1.select('constant', 'constant_1', 'blue')
.reduceRegion({
reducer: ee.Reducer.linearRegression(2,1),
geometry: footprint,
scale: 30,
maxPixels: 2e9
});
var blueC = (ee.Array(resultBlue.get('coefficients')).get([0,0]))
.divide(ee.Array(resultBlue.get('coefficients')).get([1,0]));
var blueCorr = (cos_ZE.add(blueC)).divide(IL.add(blueC));
//C for the green band
var clippedImg2 = img.addBands(1).addBands(IL);
var resultGreen = clippedImg2.select('constant', 'constant_1', 'green')
.reduceRegion({
reducer: ee.Reducer.linearRegression(2,1),
geometry: footprint,
scale: 30,
maxPixels: 2e9
});
var greenC = (ee.Array(resultGreen.get('coefficients')).get([0,0]))
.divide(ee.Array(resultGreen.get('coefficients')).get([1,0]));
var greenCorr = (cos_ZE.add(greenC)).divide(IL.add(greenC));
//C for the red band
var clippedImg3 = img.addBands(1).addBands(IL);
var resultRed = clippedImg3.select('constant', 'constant_1', 'red')
.reduceRegion({
reducer: ee.Reducer.linearRegression(2,1),
geometry: footprint,
scale: 30,
maxPixels: 2e9
});
var redC = (ee.Array(resultRed.get('coefficients')).get([0,0]))
.divide(ee.Array(resultRed.get('coefficients')).get([1,0]));
var redCorr = (cos_ZE.add(redC)).divide(IL.add(redC));
//C for the nir band
var clippedImg4 = img.addBands(1).addBands(IL);
var resultNir = clippedImg4.select('constant', 'constant_1', 'nir')
.reduceRegion({
reducer: ee.Reducer.linearRegression(2,1),
geometry: footprint,
scale: 30,
maxPixels: 2e9
});
var nirC = (ee.Array(resultNir.get('coefficients')).get([0,0]))
.divide(ee.Array(resultNir.get('coefficients')).get([1,0]));
var nirCorr = (cos_ZE.add(nirC)).divide(IL.add(nirC));
//C for the swir1 band
var clippedImg5 = img.addBands(1).addBands(IL);
var resultSwir1 = clippedImg5.select('constant', 'constant_1', 'swir1')
.reduceRegion({
reducer: ee.Reducer.linearRegression(2,1),
geometry: footprint,
scale: 30,
maxPixels: 2e9
});
var swir1C = (ee.Array(resultSwir1.get('coefficients')).get([0,0]))
.divide(ee.Array(resultSwir1.get('coefficients')).get([1,0]));
var swir1Corr = (cos_ZE.add(swir1C)).divide(IL.add(swir1C));
//C for the swir2 band
var clippedImg6 = img.addBands(1).addBands(IL);