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Lidar Remote Sensing - Science topic

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There are 3 to 5 subdatasets of AOD (047) in the MCD19A2 MODIS 1km Aersol product. Please, someone, help me to choose a subdataset for retrieving AOD. Why there are multiple subdatasets such as "Optical_Depth_047' associated with 3 to 5 subdatasets with the same name?
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Thank you, Oleg Tomshin.
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How often the LIDAR satellites can revisit the same area: for example every day or 3 months? for example the landsat repeat the cycle every 16 days.
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Azzurra Lentini What is your end goal? If you look at the data products from the various platforms, there are also other sensors on the same. Also, not infrequently, observations from other platforms and sensors are used to complement and supplement any given single sensor. Satellite sensor suites are optimized for certain phenomena ( but find uses in other domains ) like atmospheric column characterization and coarse repeatable elevation change. But the mention of drones leads me to think maybe you have another domain in mind, which leads into the myriad of different types of Lidar and relevant signal processing chains in both drone and terrestrial applications. And perhaps Lidar may not be the best solution for what you are looking for.
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Within the 3DForEcoTech COST Action, we want to create a workflow database of all solutions for processing detailed point clouds of forest ecosystems. Currently, we are collecting all solutions out there.
So if you are a developer, tester or user do not hesitate to submit the solution/algorithm here: https://forms.gle/xmeKtW3fJJMaa7DXA
You can follow the project here: https://twitter.com/3DForEcoTech
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Dear Martin Mokros,
Got this Project! I‘ll share this with corresponding workmates
Thanks for sharing this info. Kind Regards!
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I need a global above-ground biomass raster dataset from which I will subset a certain area of southeast Asia. I tried to use GEDI data but couldn't work out how to use this dataset. Is there any other data set that will serve this purpose? or can you point out how can I use GEDI AGB data?
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GEDI aboveground biomass density footprints (GEDI L4A) one year data can be searched and downloaded using python (codehttps://github.com/ornldaac/gedi_tutorials/blob/main/2_gedi_l4a_subsets.ipynb) in jupyter notebook. Then, you can export these footprints in GeoJSON or shapefile format which can be easily analysed and convert into raster in ArcGIS or QGIS. This data is discrete and sparsely distributed so you have to apply any predictive modelling approach like machine learning for the generation of continuous AGB map.
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We want to estimate the canopy volume of trees by 3D mapping using the LiDAR sensors. Please suggest low-cost LiDAR sensors available in India for 3D mapping.
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PhoDar (photogrammetry) or SFM (structure-from-motion) is usually cheaper than LIDAR and can also generate point clouds. I suppose what really counts is the level of accuracy that your task requires. https://www.esri.com/events/transmission-summit/~/media/A36CC282BBCA42ABB06F527A648DF5E6
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I am looking for software that help allow me to process quite a lot LiDAR data. I need to check classification and then prepare a DEM and DSM.
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I develop WhiteboxTools, an open-source geospatial analysis software package that has significant LiDAR processing capabilities.
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Can anyone help me to understand how to diffeentiate a LIDAR point cloud whose different point colours indicate different elevation levels?
The point cloud has different colours corresponding to different elevations. I have a drone image of the same area. How to classify the point cloud image?
Please suggest.
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Hi, When we acquire data from lidar .we have to process that data using various Softwares .As we have .rd and .pcap extension file generated we have to process those files using RT Post process file and then Create .LAS file using Smartprocessing Lidar.You can use Qt modeller to futher analyzing your image .
Las tool is also another option for it ..Likewise there are many softwares to process >LAS files . Erdas imagine and ENVI you can use after this
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Since GEDI data are published now, I am planning to download data that are over Bangladesh. However, I suppose, the locations of the shots are references (i.e. identified) with orbit number, instead of lat-long values. Can anyone help me interpreting the orbit numbers to find data that are located within specific geographic region? I have been searching for orbit number of International Space Station (ISS) as well, but it was of no use. Thanks!
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Meanwhile, you can also check the rGEDI and pyGEDI for many useful tools, including area selection:
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should the reflectance data be resampled to a sensor?
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By asd device you will get .asd file and you can convert that ascii asd file to txt file with help of viewspcpro software. Then import that data into excel sheet.then you can calculate any SVI.
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To apply MCSST algorithm for retrieving sea surface temperature data from Landsat 8 I need a 'sensor zenith angle' value. Unfortunately in the Landsat 8 metadata file (.MTL) only available sun azimuth angle and sun elevation angle?
So, where I can get the sensor zenith angle of Landsat 8 data?
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Landsat 8 has a near NADIR view. Hence, the sensor zenith angle is round zero. There is information in the MTL file about camera ROLL_ANGLE = -0.001 ~ 0
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According to my knowledge of remote sensing the lidar requires insitu measurements and can be interfered with and biased by the climatic conditions of the study area, are there any alternatives to this methodology for the quantification of PM 2.5 and PM 10 and what is the best type of image to quantify these aerosols?
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Dear Mounsif,
Remote sensing has been widely used for environmental application such as for air quality and water quality studies. But the atmosphere affects satellite images of the Earth's surface in the solar spectrum. So, the signal observe by the satellite sensor was the sum of the effects from the ground and atmosphere.
As far as your question is concerned, of course we can monitor air quality by remote sensing satellite imagery. You would know of Aerosols monitoring with the MODIS, MISR, OMI, and VIIRS satellite instruments and various other Application of Satellite Data to Particulate, Smoke and Dust -Monitoring Satellite derived aerosol optical depth-PM 2.5 relationships. However, we have to acknowledge that there is certain uncertainty during the retrieval.
A large number of publications are available on this topic, especially to improve the correlation between satellite data (e.g. AOD) and ground-monitored levels (e.g. PM). They can be easily found online.
Regards,
Tejas
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Any interesting topics related to Geodesy, Astronomy, LIDAR and Remote Sensing
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Have a look at this paper on using UAVs for remote sensing and consider how the field might be expanded.
What has been achieved to date? What are some of the main hurdles to be overcome (hardware and software)? Can you suggest, and perhaps even model, some possible low cost solutions to advance the field?
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Dear all
I have a dense point cloud (.Las) which is consist of 150 million points and I want to create a Raster file (i.e., DSM) from it. The question is: which software can do it? I used the LASTools, ArcGIS and TerraSolid, however; none of them could handle such a big file.
Thank you in advance,
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I would recommend the LAStools software distributed by Rapidlasso (free and commercial versions) that is specially designed to work with large clouds of 3D points.
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I am doing a project on the fusion of hyperspectral and lidar data for image classification in ecognition and I need to convert the point cloud lidar data to be converted to las format.
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.las to .pcd conversion can be done in PDAL,
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UV Photography can reveal another world. For Photographu in UV light i need some equipment such as filters and etc... 
Has anyone ever conduct any experiments with EOS camera in this fields?
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Hello Mohsen. I have personally converted many digital cameras to infrared and wide spectrum. I wouldn't recommend converting a DSLR because of focusing limitations. Converting a mirrorless camera to UV is a much better idea as both the focusing and image recording are carried out by the same image sensor. I would also suggest converting the camera to wide-spectrum and purchasing an UV filter that is screwed on top of the lens. This way you have flexibility regarding the wavelength. Feel free to contact me if you need more advice.
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Dear all,
I am working on chandrayaan-1 hysi data of the moon. The spectral range is between 430-964 nm. I am having problem in adding relab spectral data in ENVI.  When i am adding the relab data, i m getting a straight line in z-profile. I am a beginner. Kindly help me.
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Thank you sir.....can you please share the steps you followed in ENVI.
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I cannot understand the difference between radiance and reflectance when measuring vegetation indices like NDVI.
I checked the definitions of Radiance and Reflectance - radiance is the radiation reaching the sensor and reflected by the surface whereas reflectance is the ratio of radiation striking the surface to the radiation reflected by the surface.
As far as I read, its better to calculate indices using surface reflectance values. Radiances are not suitable because they can be inaccurate due to atmospheric effects until the radiation reaches the sensor.
My question is, even if there were no atmospheric effects, how can vegetation index values calculated from radiance be similar to values calculated from reflectance? The two seem to be different things from their definitions. I would assume we would get highly varying vegetation index values.
So how is it still acceptable that people dont bother to convert radiances to reflectances before calculating vegetation indices?
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Hi Salman,
Even if in general is much convenient to use reflectance at the top of the canopy to better normalize atmospheric effects, it is not always needed. It could depend on what is the use of the NDVI.  For instance, if you want to make a regression with ground information using high resolution data (eg, Landsat), to use a NDVI _rad is perfectly valid. However, if you want to use NDVI for multitemporal estudies  to assess for instances changes in the vegetation canopy, you must use NDVI_ref to assure that observed changes are no affected by atmospheric effects.
Regards,
Fernando
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Dear anyone can guide me? I could not retrieve back scattering coefficient graphs from my data. even I detect distance of clouds with Mie scattering lidar. I might wrong with my data.
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Thank you sir I am very glad and thankful to your suggestions. I will try my best to get desirable results.If you send me  your email I will contact you personally to get your guidance.
Regards
Ghulam Raza
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Schultz, 
Classification might be done through hyperspectral is it
Venkynir
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I regret for the mistake in name it is Hartwig  went as Battery. I am really sorry. See you soon in India.
Have a nice day
Venkynir
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i am looking for EM device with resalable price can detect ground water at higher depth like 350 m and it could be used for other applications such mining exploration etc?
what do you think about
Protn47 from Geonics Limited ?
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BH43-3D TDEM PROBE
In conjunction with a ground-based PROTEM system, the BH43-3D provides three-dimensional time domain electromagnetic data from boreholes. With a 500 x 500 m transmitter loop at surface, data can be received from boreholes to depths of 2.5 kilometres. (At developed mines, the transmitter loop can be laid out within the underground workings.) The BH43-3D probe has three sensors that measure orthogonal components of decay. Measurement intervals are determined by the resolution required; along the hole, spatial resolution as fine as 1 m can be obtained. The wide bandwidth of the probe, coupled with the excellent temporal resolution and large dynamic range of the PROTEM system, provides maximum diagnostic information and a high degree of rejection of powerline and other sources of noise.
The BH43-3D probe is available separately, or as a complete borehole system with cable, main winch, dummy probe, test cable and winch, and retrieval tools.
MAG43-3D FLUXGATE PROBE
MAG43-3D probe is an ideal tool for the survey of highly conductive targets such as nickel sulphide ore bodies. While such targets may produce very little decay to measure with an induction coil, strong secondary magnetic fields can be readily detected with a fluxgate sensor. As with the BH43-3D, measurements from depths to 2.5 km are achievable.
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Hi everyone, what would be a good image fusion method for multispectral images, such as NIR (near infrared) and SWIR (short wave infrared) images? Or in general across the light spectrum? I would really appreciate if you can give some insights and provide/share the codes. Thanks.
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I study the various beam characteristics as (intensity, wandering, broadening) related atmospherically turbulence in horizontal path and wanting this software to satisfy my results
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Dear Dr. Hayder I don't have any software , I wanted the type ALT software.
Regards
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I want to do a new research by using remote sensing and GIS with oil (identifying, detecting, or any other application?
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Dear All,
I am working on the hyperspectral and multispectral remote sensing work on Citrus Orchards. For this purpose, I need ASD Spectroradiometer or Spectral Evolution meter and LAI meter. Can any body can tell from where I can get these instruments?
If some body of any organization has these instruments, pl let me know. we may work on mutual cooperation and understanding?
Ansar
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Thanks to all for helping answer. Actually, as Dharmedra Singh indicated that this instrument is highly pecious/costly so is not easily available from any institute. However, sorted out the solution and hopefully got it. 
Thanks and Regards
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Hi all,
I need to measure the vertical profile (LAI at different heights) in a sparse and heterogeneous canopy. The canopy is around 10-15m tall and we do not have tall enough towers to get to the top of the canopy so measurements must be ground based. 
Does anyone have any advice on the best way to do this? I have been reading a bit and it seems like some people are developing LiDAR techniques to estimate vertical profiles from the ground, but firstly I'm not sure if this technique is totally reliable yet so any input/opinions on this would be very helpful.
I am not sure if we can access to a LiDAR sensor. As an alternative, I've also read about hemispherical photography being used - does anyone know of this being used to estimate vertical profiles, or does this just get you a 'flat' LAI measure?
Thanks so much!
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On satellite images, chlorophyll fluorescence mostly retrieved through Fraunhofer Line Depth (FLD) method by using radiance based measurements. Can we apply FLD method on FLAASH/6S atmospherically corrected image?.
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It also has a table that reviews the methods for retrieving fluorescence from space-borne data. 
Cheers!
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Can anyone recommend an affordable spectroradiometer (model/brand) suitable for spectral hemispherical irradiance measurements in the UVA-Vis range?.
Ideally, a model "similar" to "Black comet" from "Stellarnet" ( http://www.shopstellarnet.com/black-comet-sr-concave-grating-fiber-optic-spectrometer/ ) is what I am looking for...or the "Green wave" ( http://www.shopstellarnet.com/low-cost-green-wave-spectrometer/ ).
I am aware that a lower price usually comes with a lower quality. However, for the time being, my budget requires me to find something around 500 - 1,500 USD.
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Two Ranges: 250-1050nm Broadband and 200-450nm
Its around 500 - 1,500 USD. before buying the instrument you have to check the software capabilities and specifications.
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the current cloud removal algorithms are almost aim to the multispectral or pan remote sensing image,i want to know that does these methods suitable for hyperspectral image.
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If you want to generate method  or algorithm for cloud removal, you may learn about atmospheric window and its interaction with electromagnetic wave. Then, check and learn about EM range of the hyperspectral satelit sensor that used.
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I am trying to classify various indices like NDMIDR, NDMIDIR, and SBI to the same number of classes(5) but I am not able to find any range or any algorithm to classify them. How can I classify them? Please suggest any range for classifying them, if available.
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I am undertaking a project looking at possible ways to identify tree species using satellite data and am considering using near infared imagery provided by Sentinel 2. However to do this I will need a list of individual trees spectral signatures and was wondering if a complete database existed and was accessible? 
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Dear Daniel,
Firoz is right: all (or most) trees look 'green' from space when the leaves are out, and it is not clear that their spectral response in the near-infrared is much different from species to species. You may find a somewhat higher discriminating power in the mid-infrared, where there may be more subtle variations due to the presence of components in variable concentrations such as lignin and cellulose, which exhibit specific vibrational spectroscopic signatures. Of course, this may not be applicable to Sentinel-2: that instrument is great to investigate environmental issues at fairly high spatial resolution, but it is not a hyperspectral sensor.
Instruments like WorldView-3 and others provide a better spatial resolution than Sentinel-2, but feature only a limited number of bands too. It may be worth exploring to what extent these instruments may be useful for your purpose, but don't expect miracles: you may very well reach the conclusion that tree species can't be distinguished this way.
On the other hand, if you want to pursue hyperspectral investigations, consider these leads:
Databases of spectroscopic signatures do exist, but they are often held by projects rather than widely available. One worth mentioning is the 1985 NASA study by Bowker et al., which is available here:
Check also the NASA Jet Propulsion Laboratory site concerning the airborne AVIRIS instrument:
Dr. Robert O. Green, the Principal Investigator for AVIRIS (http://scienceandtechnology.jpl.nasa.gov/people/r_green) and his colleagues have accumulated lots of hyperspectral measurements and generated a number of publications over the years.
Another researcher you may want to follow is Prof. Susan Ustin (http://lawr.ucdavis.edu/people/faculty/ustin-susan), as she has also worked extensively with hyperspectral data for ecological applications.
Other projects that may hold spectral signatures of different vegetation types (including trees) might be the LTER or FluxNet sites, for instance.
Check also the data generated by the Hyperion mission, which acquired over 200 spectral bands from space. In that case, you will need to assess to what extent the small signatures that may exist at the surface may still be distinguishable after the solar radiation has been transmitted through the atmosphere, before reaching the instrument:
Lastly, if you want to (or have to) use Sentinel-2 data, then you may be restricted to differentiate between evergreen and deciduous groups of species (using time series of observations), for example. Good luck, Michel.
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I use MOD11A1(Daily), and after download i multiply with 0.02, i must , turned daily to monthly data but after i turned, More data show lower than 280 that means 9 ° C that is wrong in the spring season in my study area because it is located in dry area . if u guide me, I'm very grateful.
what is wrong?
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Hi Dear yes , Modise Data is correct, Daily data is correct but after i turned monthly, data is wrong. indeed i want calculate soil moisture , NDVI is monthly but Lst is Daily because of it i dont know what should i do with LST, can I use my daily(LST) and monthly data (NDVI),for calculate soil moisture. u think is it true or false ? I am looking forward to your answer
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I have a lidar file with 5 million points for a forest region in America . I must calculate DEM . for this purpose I have to filter the other object except ground but I don't know how . then for the mature trees I must draw crest elevation . can anybody give me any information about these?
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If you want to understand very well you have to start reading ground filtering algorithms. Every software has their own algorithms and probably with some differences in the final result.
LASTools is a very straightforward application with a friendly interface. Even if you would  like to change some parameters concerning the terrain condition, take it done, (tile the data for covering more area). In case of paid software like ENVI you could get everything at one click, but if you want to modify, knowledge for IDL is needed or pay more :) 
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As we konw, if the reference point is inappropriate, the aerosol extinction retrieved is not accurate. Then, how to set this point for getting reasonable extinction?
And, when doing the inversion with Fernald method,there always exist some negative values in the extinction profile, how to deal with these negative values?
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Dear,
there is several days which no one has answered your question!!
Let`s elaborate a bit more so that it be more clear for others, and perhaps one of them be able to response. For example what  does that reference point do? or is there a special software that you are using it for this purpose? and so on..
Be success
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Hii
I have multi-spec camera that provide data in 5 band, R,G,B,Red Edge and NIR, I need to calculate shortwave albedo utilizing the bands.to determine the net shortwave radiation from the imagery? would be great if anyone can help me in this regard.
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Dear Rajasweta,
Your question is too "fuzzy" to provide a simple answer. Please consider the following points, and ask more pointed questions (or pursue this exchange) once your objectives and constraints are clearer.
1. There are many different albedo concepts, including the biconical reflectance factor, the hemispherical-conical reflectance factor, the bi-hemispherical reflectance factor, etc. Although you did not indicate this, it is probable that you are mostly interested in the latter, i.e., in the ratio of the net upward flux of radiation over the net downward irradiance.
2. This, in turn, implies you should have a separate instrument (on the UAV or on the ground) pointing upward to measure the incoming solar irradiance, as well as the capability to measure the outgoing reflectance in a number of directions within the upward hemisphere. A camera mounted on the UAV and pointing at nadir will only give you some estimate of the radiance reflected in the particular direction of the UAV.
3. Could you confirm that your "UAV Multispectral Camera" is an imaging camera (rather than a radiometer), presumably pointing down? In other words, are you taking spatially-explicit pictures of your target of interest?
4. At what altitude are you flying your UAV, and what is the spatial sampling distance afforded by your camera on the ground?
5. Are you trying to estimate surface albedo from a single acquisition, or do you plan to survey some large area? If so, how large is the area of interest?
6. Similarly, are you interested in performing such an estimation once, or do you anticipate to repeat that estimate in time? If so, how frequently and over which period?
7. What type of target are you interested in (sea, land, vegetation, desert, etc.)? Or what would you subsequently like to do with these albedo estimates?
8. What accuracy are you expecting? For instance, what is the largest error in albedo you can tolerate before your ultimate application becomes worthless or the investment is not justified?
9. What processes and procedures are you anticipating to calibrate your instrument?
10. What are the spectral profiles of the various channels on your camera? At a minimum, you should plot those profiles against some typical solar spectral profile, as measured at the surface and for your region of interest. This will show clearly to what extent the few spectral bands you do have adequately cover the solar spectral range (or not, or whether they actually overlap). It is likely that you will need to come up with an extrapolation formula to account for the radiation reflected by the target but not measured by your instrument.
11. Does you UAV also provide information about the position, speed, direction and attitude of the craft during flight? Small changes in inclination can result in large measurement changes.
12. Remember that if you fly your UAV at significant heights above the surface, the role of the atmospheric layers between the UAV and the surface may also need to be taken into account.
I hope these comments may help you plan your investigation. Best regards, Michel.
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I have 2 spectrometers calibrated for irradiation working between 350-1050 nm. I use these to measure simultaneous up-welling and down-welling irradiance measurements at various agricultural fields. One of the spectrometers is with a cosine corrector and mounted upwards for down-welling measurements while the other one uses bare fiber and mounted with 45 degrees facing downwards for up-welling measurements.
One of my aims is to generate agricultural indices such as NDVI. But I'm stuck in the process of generating reflectance values out of these irradiance measurements. 
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You can follow the PDF
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Lidar data need for the paralakhemundi area.
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You can check it out on USGS earthExplore sites
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I have a wind-lidar measurement from which by looking at the CNR profile I am trying to estimate the boundary layer height. Unfortunately the wind-lidar did not work throughout the period of the campaign. I have the measurement of the incoming solar radiation throughout the period. Is it advisable if I correlate the ABL height determined from the Lidar measurements to the Incoming solar radiation and then for the missing periods I use that relation to get the ABL height?
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Thank you very much for your help Edward
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Aside downloading ASTER or SRTM DEM, is there anyway I can derive a DEM from a particular study area?
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This question has been asked multiple times in RG. Please search the Q&A section. I have attached one of the links. 
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In the paper Optical Properties of Aerosols and Clouds: The software package OPAC , atmosphere is divided into four layers, the aerosol can be mixed in the first layer. Hmax and Hmin are the boundaries of this layer. Can I figure out the vertical profile of extinction coefficient, scattering coefficient, lidar ratio and optical depth by changing the value of Hmax and Hmin?
For example, I have made a test. The aerosol type is urban. The wavelength is 350nm, the humidity is 50%. First, I set the values of Hmax and Hmin as 0km and 1km; secod, the values is changed to 1km and 2km. Can the result of the test be viewed as the vertical profile of extinction coefficient, scattering coefficient, lidar ratio and optical depth? In addition, In the two steps, the extinction coefficent , scattering ~and lidar ratio remains unchanged. Meanwhile, the optical depth decreased.
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Dear Zhang,
I think it is possible to get the values and you will have the values of the proposed parameters but It is possible that you may not have the true values.
As you said that you have made a test run with the urban aerosols and 50% of RH but as per my knowledge, urban aerosols do not have much advection compare to dust and smoke. Moreover, The meteorological parameters vary with altitude, so you can’t keep RH 50% constant for different altitude. The associated meteorological influence on aerosol vary as per altitude, too. There are numbers of property we should think before the run like mixing of aerosols (internal and external) and hygroscopic growth of aerosols and etc.
As you said that you have made a change only in a height of aerosol layer from 0-1km to 1-2km and other parameters you have kept constant, it means that the incorporated aerosol layer is lifted in same space and time, which is not possible practically. It can be lifted with varying space and time. As well as you are proposing same aerosol layer with different altitude, but in reality, the aerosol layer has fixed height for particular space and time. This is not a correct approach to parametrize the aerosol layers.
Now as you asked that the optical depth is decreasing, which is true because if you will see the definition of optical depth is the integration of extinction of radiation from ground to top of the atmosphere. Here optical depth is directly affected by the altitude or you can say path. Now, when you are changing the aerosol layer height, indirectly you are changing the altitude or path and that’s why the value of optical depth decreased.
According to me, you should go for CALIPSO data or any other ground-based lidar measurements.
One more thing I would like to share with you that you can use SBDART model to estimate the extinction coefficient.
Hope this will help you
Thank You
With Regards,
Piyushkumar Patel
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I got an unfiltered point cloud from vendor and as far as I know I have to calibrate (or correct) the intensity values of this point cloud in order to benefit from them. There are different flight lines which flown on the same day with an overlap. And then I need intensity images. I am not sure is there any other step needed for these images in these sense ? Is there any tool, software or a publication for that ? Is there any experience ?
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I'm a geomorphologist and I live in Costa Rica, but I want to take a LiDAR and Remote Sensing course online or presential. If you know about any course I would be interested. Thank you
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We (OpenTopography) co-organized a pair of courses this past spring in Mexico focused on lidar applications to geomorphology and Earth science. All lecture slides and tutorial materials are freely available:
Lidar Derived DEMs applied to Landslide, Fault, Earthquake Rupture, and Landscape Changes - at UNAM in Mexico City: http://www.opentopography.org/index.php/resources/short_courses/15_UNAM
Applications of High Resolution Topographic Data to the Earth Sciences - at CICESE in Ensenada: http://www.opentopography.org/index.php/resources/short_courses/15_NPAC
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Which algorithm works best while integrating LiDAR with optical image
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I'll assume for part one that you want to pull colour information from images and apply it to a point cloud.
If you have access to the Terrasolid suite, there are tools to first coregister imagery with LiDAR, and then extract colour values for the LIDAR point cloud from coregistered imagery.
For the imagery, you need a way to apply an apriori geolocation - either ground points or camera positions and orientations. I've used the second approach - no ground control, but camera centre location (plus heading, pitch, roll).
I've used this in an airborne context - it's a very good tool but fairly expensive.
If your imagery and LiDAR are already coregistered, LAStools also offers a method to extract colour data and apply it to the point cloud (LAScolor).
For part two, I'll assume you want to drape already-coregistered imagery over a LIDAR cloud to make a pretty terrain model.
Terrasolid also offers this capacity (TerraModel). I am almost certain that FUSION can also do the job, but I'm not a FUSION user, I've just dabbled at the edges.
Right now I'm working on a quick-and-dirty program to coarsely coregister (direct georeferencing) some images and LiDAR over a flat surface - but it is not such an easy task. Preferably I'd use an existing tool but I have operational (no ground control, which most methods require) and funding constraints.
I hope my assumptions are somewhat correct, and you find this useful!
Regards
Adam
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According to Müller, D., et al. "Aerosol‐type‐dependent lidar ratios observed with Raman lidar." Journal of Geophysical Research: Atmospheres (1984–2012) 112.D16 (2007). Basically Lidar ratio of 20-30 sr are categorized as marine aerosol, 30-40 sr are for polluted marine aerosol, 40-60 sr are for urban aerosol, 50-80 sr are for wood (biomass) burning aerosol. But how about Lidar ratio smaller than 20 sr and greater than 80 sr? Are there any aerosol types corresponding to these Lidar ratio?
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Check my publications. There is one in IEEE in 2010 that my be of help
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Furthermore: What are the best sites to obtain AOD data and how to validate ?How can one characterize Aerosols from Satellite and Ground based data on the basis of their shape, size, etc? Which would be the most relevant sites for this purpose?
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Salam Brother,
Please check MOD06_L2 for Cloud Optical Depth (COD) and MOD04_L2 for Aerosol Optical Depth (AOD). You can download these products from LAADS Web: https://ladsweb.nascom.nasa.gov/data/search.html 
For Aerosol Size distribution, please check AEORNET data:
Hope this information will be useful for you.
Regards,
Bilal
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High-end photogrammetric applications are where plan (xy) accuracy and heightening (z) accuracy are tightest and include precision mapping, engineering mapping, topographic mapping, deformation mapping among others.  The characteristics of imagery captured by the camera mounted on the UAV determines the accuracy output (ie issues of vibrations, crabbing, among others). Is a fixed-wing craft more advantageous than a VTOL craft versus in this application domain?
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In order to map the habitat of a bird species, using the understory layer of forest fragments, I thought that airborne LiDAR data (point clouds) would represent a promising tool. The issue is that the forest fragments (woodlots) in question are located in private lands, in south of Ottawa. Is there anyone aware of airborne LiDAR data in Eastern Ontario or further, or an alternative option ?
Thanks a lot.
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Have you checked geogratis?
At least you can dowload the Canadian Digital Surface Model (CDSM) or the Canadian Digital Elevation Data  (CDED).
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We have a Riegl VQ 580 and are thinking of building or buying a pod for a long ranger or a jet ranger.  Any experiences?
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We have the IGI Litemapper 6800 since 2010, coupled to a digital camera for photogrammetric acquisitions. The system is mounted on a pod certified to fly on helicopters EUROCOPTER AS 350. We are satisfied of this choice, because we can transport the system to the helicopter base near the target to be investigated, and thus decrease the helicopter transfer costs.
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I intend to take samples of wood in order to determine density and apply to biomass estimations. Some approaches suggest taking cores of wood, and that imply cutting the tree. In this case the alternative is to not do this as invasive/damage activity is used as an increment borer. Can anyone help me with some advice?
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dear victor
The best method of density should each  component tree species taked some sample then optain whit method density common that used the articles.
The volume was measured by the water displacement method. Dry mass, obtained by drying at 85°C ( leaf )and 105°C(wood) for 3 days.
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I want to detect the boundary wall of an area.
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Hi there,
You can use CloudCompare together with the Canupo plugin:
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I am interested in rating different methods according to their cost, efficiency and speed and everyone's field or research experience will valuable.
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A Green-Lidar survery such as EAARL (http://coastal.er.usgs.gov/lsrm/tech/tech1-eaarl.html) would probably be a great tool. It is a narrow beam laser http://www.fs.fed.us/rm/boise/AWAE/projects/RBT/RBT_lidar_hydro_downloads.shtml
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Can anyone suggest to me on technical aspect of how to extract forest biomass from full waveform lidar and hyperspectral imagery (in fusion). Should I run modelling? or software processing by validating with ground data? software? algorithm? I need a general idea
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Hi, I used discrete lidar data combined with hyperspectral data to map forest structural properties for my master thesis, here i combined the height metrics from lidar and the spectral bands as the input variables. I am using R software for the statistical analysis using multivariate statistic such as stepwise linear regression and induction based decision tree with the ground data as the training and validation data. as a good point for reference, I suggest this reading material : http://www.sciencedirect.com/science/article/pii/S0034425707004270. hope this will help you.
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In particular, using a doppler beam swinging method to measure wind speed, would be influenced by rain, e.g. different turbulence field, and how?
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There are different Doppler Lidars. If you mention DOPPLER effect on molecular scattering to measure wind in the range 10-50 km, then rain is a limiting factor because ligth can not go through efficiently.
Ref:
- Chanin M.L., A. Garnier, A. Hauchecorne et J. Porteneuve, 1989, A Doppler lidar for measuring winds in the middle atmosphere, Geophy.
Res. Let., vol 16, n°11, 1273.
- Souprayen C. A. Garnier, A. Hertzog, A. Hauchecorne and .J. Porteneuve, 1999, Rayleigh-Mie Doppler wind lidar for
atmospheric measurement. I. Instrumental set-up, validation and first climatological results, Appl. Opt., 38, 2410-2421.
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Most of the remote sensing data is captured for the earth surface 2D and I could not find any technique or available data to measure the thermal response for the vertical features like walls. If you know any type of data or technqiue that might be used to the get the full urban thermal real representation.
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Hi,
There are some plate-forms to perform this. My research group is involved in the development of a car which is equipped with :
- a thermal infrared scanner (push broom) that scans the wall temperature along the track of the vehicle
- a LIDAR, that scans building walls, trees and whatever is on the way along track
- a high quality GPS
- an odometer
You'll find attached a picture of the vehicle. Combining all this gives a 3D rendering of the brightness temperature of the walls, and is very useful to diagnose the heat lost by buildings. One of the biggest challenge remains to deal with the actual emissivity of building walls, since there's a very strong heterogeneity in terms of materials. Moreover, we cannot get a single picture of an entire city at a time, of course.
It's still rather experimental. We'll make a new measurement campaign in the coming months in the city of Strasbourg, France.
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Forest degradation remains a very complex issue. Forest degradation is understood in different ways in different geographical and cultural contexts. Its measurement and quantification of its intensity and extent remain a matter of scientific debate, and one of the main issues about it is how to "measure" forest degradation (loss of productivity, carbon, biodiversity, etc ) using remote sensing techniques
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We are offering an excellent forum for this type of discussions? Why not attending ForestSat 2014? Deadline for abstracts on April 30th, visit http://forestsat2014.com
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Whether Lidar is ok? The accuracy is needed to be better than the tag-based system and if possible, it is best that speed could be tracked in real-time simultaneously.
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Depending on the environmental restrictions you might consider UWB technology (short, up to 50-60m range but good at reducing multipath, at current stage scalling over 10 units is problematic) (http://ukgrads.thalesgroup.com/Files/TRT%20UWB%20radar.pdf) or Locata technology for example (much more complex but offer bigger range, few km easy and almost no restriction on number of units), especially their vray looks interesting (http://www.locata.com/article/vray-antenna/). Both methods will give you cm level accuracy.
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From AERONET, we can directly obtained AOD. Then, from lidar data, we use Klett inversion to obtained the backscatter coefficient. Then using the backscatter coefficient and the predicted lidar ratio we get the extinction coefficient and hence determine the AOD from there. But the question is, the AOD we get from lidar data are generally higher than that obtained by AERONET. But I thought it should be smaller than that obtained by AERONET? From our method, the predicted lidar ratio have to goes to as low as 15 sr to obtained AOD smaller than AOD obtained by AERONET, which I think is not possible for us who live at south east asia to have such low lidar ratio.
Update: Our Lidar is a backscatter lidar, operating at 355nm, pointing at zenith. we usually operate from 10am to 5pm (local time). The main aerosol we observe are the urban pollutant, or some researcher termed it as south east asia aerosol, since I'm from Malaysia, where it is part of south east asia.
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You say that you mainly observe urban pollusion. Could it simply be that you are closer to the source of the said pollutants than the AERONET station, so that you could actually have a higher AOD at your location on the average?
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I did few scans, but if I use the laser intensity to differentiate leaves and branches, it did not give me good results as it is affected by distance.
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Hi Nayani, I've had some experience with this and found that once you have your XYZ coordinates, it's useful to project them into orthographic coordinates, which appear like a fish-eye image. From this, you can calculate LAI. Have a look at the attached link to the IGARSS conference proceedings. Hope that helps.
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A dense plume afar and a close dilute one may exhibit the same back scatter signals. How can we discriminate those plumes? Assuming similar spectra.
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Dear Parviz,
actually it is possible to distinguish the two objects.
Despite of the same temperature giving you similar continnuum spectra, the atmosphere of a more compact and a more diffuse stars will be different. Either by a density change, or by a matter of the local surface gravity, these effects end up generating different spectral line profiles (absorption lines, in general).
Therefore, by checking the widths of spectral lines you can separate gigant stars and dwarf stars that present similar surface temperatures.
Variable stars, as the Cepheids, also can be used, but are not the most commom method. This is what is done for most cases.
Kind regards
Diego
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What spatial resolution is required for mapping kelp "forests" with satellite imagers? Can kelp biomass be estimated using data from multispectral or hyperspectral imagers on satellites or aircraft?
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Hi there,
I agree with the previous comments. First, you should identify the depth of the kelp forest. So long it is located within the depth of penetration (DOP) of the image data that you will use, it should work. However, since each wavelenght has different DOP, as the water goes deeper, the number of usable band will be limited to the shorter wavelenghts.
The spatial resolution is also another issue. Depending on the nature of the kelp forest, at lower resolution, you may got a lot of mixed pixel. This can hinder the process of biomass estimation since the variation in kelp pixel is not only the function of kelp forest variation, but also due to the variation of other objects composing the same pixel. Also, if the kelp forest is narrow, using lower resolution may not be effective. my suggestion is to match the specification of the image that you will use with the environmental condition of the kelp forest.
Water quality in the environment should also be considered.
If the water is clear, then it is fine. But, if the water is turbid, it would be problematic since most downwelling irradiances will be scattered by the suspended material before reaching the kelp.
sunglint should be minimized, and you need infrared band to do that (See Hedley et al. 2005). Water column correction may or may not be necessary depending on the depth of the kelp forest.
TO perform biomass mapping, you can try to empirically model field biomass data and various image transformation i.e. visible-based vegetation index and PCA.
You can use the resultant regression function to convert image pixel value into biomass.
you can see my publication about seagrass LAI mapping as reference. Thank you.
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There is a need in my project to identify the tree canopy cover percentage at village level using the remote sensing images
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Hi there,
Depending on your term of canopy cover percentage, the analysis may varies. If you're talking about cover percentage, then, you should consider the nature (i.e. diameter, composition) of the tree that you want to identify. It will determine the specification of image that can be effectively used.
using very high spatial resolution data won't be effective because each pixel is sub-canopy extent, and thus, at per-pixel analysis, there will be many pixels that have 100% cover because the pixel consist only tree leaves.
the term percentage itself means that it is the percentage of area covered by tree canopy per unit area. Thus, you should define your unit of analysis before progressing. If not, quantifying the percentage will be difficult and the result will be difficult to compare.
If you have already finish with the aforementioned issues, there are many method that can be used to improve satellite-based canopy cover percentage identification such as vegetation index and unmixing. Furthermore, to obtain a real quantiative estimate of canopy cover, you should at least perform field survey, or if you use medium spatial resolution image, you can use higher resolution data to get canopy cover information. Afterward, you can perform empirical modeling using vegetation index, PC bands, image fractions or other approach.
And if you want to separate tree from background reflectance i.e. grass, you can try applying PCA with vegetation mask on. This will maxed out the variation of vegetation pixels and object separation will be easier.
Hope this help.
Thank you.
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I have found in some journals that some researchers predict AOD value for 355nm using AERONET AOD data from 340nm and 380nm. By doing so they can minimize error when doing Klett inversion to obtain the backscatter coefficient from Lidar data. Can anyone teach me how to do it?
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The Angstrom exponent is a quotient of two AODs (in this case, at 340 and 440 nm). I think you'll find the definition under the Wikipedia link cited by Peggy.
Actually, the AOD at 355 will almost certainly deviate only very little from the one at 340; I'm guessing less than 5% for small aerosols...
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I have a ground based backscatter lidar, operating at vertical (90 degree zenith) everyday during day time. The Lidar manufacturer advise us not to operate it when the sun disc enter our Lidar's field of view. However, I found many programs that calculate the sun position at a certain latitude during a certain time. But the problem is, I cannot determine whether or not the sun disc will enter my Lidar field of view. So is there anybody who can suggest a method or program or software that can do so? Thank you.
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You can do that in GRASS GIS
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Need to know most recent accuracies of lidar beach profiles.
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Thanks, I'll contact Jamin
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Can anyone direct me to the most useful textbooks and papers on the subject?
I'm interested so far in pulsed and coherent methods.
A good source on data recovery and processing would be well received.
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As the tehnology of LIDAR for wind resource assessment is in its infancy, there is probably few textbooks on the topic yet, but there is more than a handful PhD thesis on the topic and their introductory chapters may be of help, such as Bingol's dissertation "Complex terrain and Wind Lidars" (see attachment 1) and "Fiber based coherent Lidars for remote wind sensing (PhD thesis Petter Lindeløw), DTU Risoe.
The Lidars in use for wind resource assessment in the industry are Leosphere, www.leosphere.com, Zephir www.zephir.com and the Galion lidar at SgurrEnergy www.galionlidar.com and there are some new interesting technologies coming up, such as the Spidar at Pentalum technologies www.pentalum.com. My group recently did an assessment of the uncertainty of the three first mentioned LIdars in complex terrain, see . https://www.researchgate.net/publication/234164268_Uncertainty_of_Lidars_in_complex_terrain
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How can I quantify minerals in a soil sample using a spectrometer in a laboratory (FieldSpec 3)?
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Do you have reference measurements?
Then you can use a regression technique like PLSR.
You can use spectral preprocessing like continuum removal or the derivative to remove baseline effects.
Or you could study the depth, area, and shape of specific absorption features.
See papers like
Viscarra Rossel, R.A., & Behrens, T. (2010). Using data mining to model and interpret soil diffuse reflectance spectra. Geoderma, 158, 46-54
Viscarra Rossel, R.A., & Chen, C. (2011). Digitally mapping the information content of visible–near infrared spectra of surficial Australian soils. Remote Sensing of Environment, 115, 1443-1455
Udelhoven, T., Emmerling, C., & Jarmer, T. (2003). Quantitative analysis of soil chemical properties with diffuse reflectance spectrometry and partial least-square regression: A feasibility study. Plant and Soil, 251, 319-329.
Farifteh, J., Van der Meer, F.D., Atzberger, C., & Carranza, E.J.M. (2007). Quantitative analysis of salt-affected soil reflectance spectra: A comparison of two adaptive methods (PLSR and ANN). Remote Sensing of Environment, 110, 59-78
or our paper
Steffens, M., & Buddenbaum, H. (2013). Laboratory imaging spectroscopy of a stagnic luvisol profile - High resolution soil characterisation, classification and mapping of elemental concentrations. Geoderma, 195-196, 122-132
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Signal level: 10-100 photons per pulse
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The PerkinElmer C30956EH is an enhanced silicon avalanche photodiode. Perhaps that's a better option for detecting optical signals at 1064 nm, though I don't really know it compares to indium gallium arsenide.