Questions related to Lidar Remote Sensing
I am working on lane line detection using lidar point clouds and using sliding window to detect lane lines. As lane lines have higher intensity values compared to asphalt, we can use the intensity values to differentiate lane lines from the low intensity non-lane-line points. However my lane detection suffers from noisy points i.e. high intensity non-lane line points. I've tried intensity thresholding, and statistical outlier removal based on intensity, but they don't seem to work as I am dealing with some pretty noisy point clouds. Please suggest some non-AI based methods which i can use to get rid of the noisy points.
I'm analyzing a point cloud dataset captured by a lidar sensor and have a question regarding its Vertical Field Of View (VFOV) channel configuration. The dataset documentation suggests the VFOV configuration shown in the attached image (lidar_beam.png), but my analysis (Screenshot.png) of the data implies a different setup. Specifically, the data near the origin (where the lidar is located) was captured by channel/lidar_beam 63, and as the distance from the origin increases, the channel number decreases sequentially down to channel 0. This pattern suggests that the channels are arranged vertically from bottom to top in the order of 63 to 0 rather than the even/odd pattern suggest by the lidar_beam.png. Can you provide insights or confirm if my understanding of the channel configuration being 63 (lowest) to 0 (highest) along the z-axis is correct?
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.
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
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?
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.
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?
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!
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?
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?
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,
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.
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?
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.
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?
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.
I study the various beam characteristics as (intensity, wandering, broadening) related atmospherically turbulence in horizontal path and wanting this software to satisfy my results
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?
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!
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?.
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.
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.
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.
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?
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?
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?
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?
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.
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?
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.
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 ?
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
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?
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?
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?
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.
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?
I am interested in rating different methods according to their cost, efficiency and speed and everyone's field or research experience will valuable.
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
In particular, using a doppler beam swinging method to measure wind speed, would be influenced by rain, e.g. different turbulence field, and how?
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.
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
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.
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.
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.
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.
There is a need in my project to identify the tree canopy cover percentage at village level using the remote sensing images
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?
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.
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.