Latest Contributions by CodyBenkelman

Kushendra - there are no specific tools or "magic method" for removing shadows from extremely high resolution imagery within ArcGIS, but our Segmentation tools may be relatively effective at highlighting areas of shadow vs. non shadow, and allowing you to combine shaded areas into their appropriate groundcover class.  (See these links to Help for Pro or ArcMap.  What version are you using?) However, I think it is worth expanding this to discuss other issues.   First, what resolution is your imagery?  I'm assuming centimeters, but if you are flying high and capturing ~1 meter data, the workflow may be somewhat different. Second and critically important, what sensor are you using?  If it is a Bayer array (single CCD sensor), the spectral content of the red band includes NIR energy that cannot be completely removed, so your NDVI values will be questionable.  If you are using a multi-sensor camera like frpm Micasense, TetraCam, or a hyperspectral imager (e.g. from Resonon, you should be getting good quality spectral imagery.  Third, how did you create your mosaic?  If you are using a Mosaic Dataset and are rectifying each image "on the fly" into a virtual mosaic, you have not disrupted your original pixel values by resampling.  Otherwise, if you have used Drone2Map, Pix4D, or similar software to create a single orthomosaic, your spectral values have already been modified by both multi-scene averaging and resampling such that an NDVI will be less accurate.  (If you add this onto the Bayer array issue #2, I'd say your NDVI will be qualitative at best - not a highly accurate quantitative measurement). All together, my experience is that NDVI dramatically reduces the effects of shadow.  Since the shadow diminishes the brightness value of both the NIR and Red bands, the ratio in the NDVI should not show a dramatic difference in shadowed vs. non-shadowed regions.  e.g. you may want to review this paper: "An Analysis of Shadow Effects on Spectral Vegetation Indexes Using a Ground-Based Imaging Spectrometer" In fact, I have used NDVI specifically for the purpose of compensating for shadow.  If your data seems to show dark shadows in the NDVI, I suspect your sensor is not providing good quality measurements in the two bands.   ... View more

Forest As with so many questions, the simple (but not helpful) answer is "it depends".   To be more helpful, I'll expand on some of the considerations - but as Dan indicated, you should test IDW vs. NaturalNeighbor on a small sample to see which will work best for you.  In general IDW will leave you with a rougher DEM (although possibly more accurate), whereas NatNeighbor will be smoother - but there are other considerations: Do your XYZ files have values at every XY location, or are there gaps?  (and are the XY values regularly spaced?)  IDW may not interpolate across large gaps (depending on settings) whereas NatNeighbor will fill your tiles to the edges. How much time have you invested in your current files?  If you've done a lot of editing and QC (I'm assuming these are bare earth ground points from LAS) and the file boundaries are very specific, you can proceed with this workflow, but I'm concerned about doing anything one tile at a time without considering neighbors - you may end up with slight artifacts at every edge that will give you an unpleasant result when all are combined. Is processing time a concern?  The support doc you reference will take more processing time than the alternative I describe below, although realistically the learning curve and setup time on my recommended workflow will likely take you longer overall. Who will use the outputs, and in what software?  (see end for explanation of this) The above should guide you to pick a good area to test - I'd suggest finding an area with some larger "NoData" gaps (if you have any) especially at tile boundaries, and process either 4 tiles in 2x2 arrangement or perhaps more, and look at a hillshade of the resulting outputs to see if there are edge effects.  If any of your tiles have NoData at the edges (and you do fill the NoData voids), I'm sure you'll find discontinuities if you process these files separately to create DEMs. If you have not invested a lot of effort thus far in the files, and/or if a small test does not work out well, I'd encourage you to look at our recommended workflow for generating DEMs from Lidar in the Image Management Guidebook (look for the Aerial Lidar section here:  Image Management ).  This would presume you have good ground classification for your points in the LAS files, but I'm suggesting you may not want to use the XYZ point files and just use our workflow to go from LAS to tiled DEMs in Tiff format.  This would process all of your data as one logical project (or several large projects, if it's really not contiguous data) to avoid edge artifacts, and the downloadable tool referenced in this workflow (LAS Dataset to Tiled Rasters) gives you a lot of flexibility for creating DEM tiles including file names, boundaries, and metadata to go with the tiles. re: my question #4 above, an option that some organizations use is NOT to fill the NoData voids (or "not if greater than XX pixels"), and then when the DEM tiles are used (presuming users have either ArcGIS Desktop/Pro or a web client built with our APIs), if you manage them with a Mosaic Dataset and add the "Elevation Void Fill" function, you can have a watertight DEM but allow the user to control the parameters of the void filling that best suit their application, and also explicitly see where the voids are so they know which values are being interpolated.  I wouldn't suggest this if you have public users, but if you are serving technical staff in your organization, they may prefer to see the data voids before proceeding. I hope that is helpful.  Cody B. ... View more