Arhanghelul

Hello, I would like to be added to active members. Thank you. Arhanghelul

Where can i find some GIS & RS jobs, working from home ? Thanks

Here is an interesting review: http://www.50northspatial.org/uav-image-processing-software-photogrammetry/ 😉😊

When I try to add PyQt5 to the Project interpreter in PyCharm, I get the error from the image attached bellow. I am new to Python, so who can help me solve this problem, step by step ? ? Thank you !

I am trying to run a Python script in PyCharm using Pytnon 2.7 ArcGIS 10.6 as the project interpreter, but wen i run the script it stops after a short time and i get this message: "Process finished with exit code -1073741819 (0xC0000005)". What is this ? How can i solve this problem ? Thank you.

In would like 2 things: 1) to add the thickness of each polygon to the DEM. The result should look like a waste pile in 3D. 2) to create individual bloks (TIN's) overlapping in ArcScene 3D. In don't know how to sort the layers based on the date of the deposit, then how to intersect and union the values for each polygon so that each block inherits the values from bellow. It should look like a geological deposit, each layer overlapping on top of each other. How cam i create something like that ?

I have a shape file containing around 300 polygons and a DEM. Every polygon represents a waste layer about 10 inch thickness added on the field and marked by a date. I would like to add each layer to the DEM value. How can i do this ? I would also like to create a 3D view in ArcScene for this waste pile, so that each layer can be selected individualy from the waste pile. How can I do that ? I managed to converted the polygons to features, but i don't know how to continue my project...... One problem is that the polygons have no Z values (altitude), only an estimated 10 inch tichness each polygon. And the polygons are overlapping. So, how can i make an 3D view ? Thank you.

I have found the solution to my problem.

Hello friends ! I am trying to create a map in QGIS using Google Hybrid plug-in as a basemap. When i export my map from Map Composer in QGIS, the labels from the basemap (street names, places, locations, etc) are not exportet on the map. So, how can i keep the labels on the exported basemap ? Thank you.

Yes, I know that my question has no connection to your topic. But i was curious to know: what methods/softwares do you use for semi-automatic/vectorizing and image post-processing ?

What about image processing softwares ? Drones/UAV sistems produce a large volume of information (optical images, LIDAR, etc). For example, how do you extract all the elements from a large orthomosaic over an urban area or a less complex landscape (forest & built up areas) ? Manual vectorization or semi/automatic vectorization ?

In EarthExplorer i see that SPOT 1-4 archive images are free to download only for US, but for Europe are not. So, is there another way to search and download the SPOT 1-4 archive satellite images for Europe ?

Question: Where can I find and donwload free SPOT satelite images ? I have read a year ago that the SPOT1-4 archive will be free, similar to Landsat archive. What is the status for SPOT images ? Download links for SPOT ?

I don't think so. If satellite imagery with <2 m in spatial resolution would be free to download like Landsat, then private company like DigitalGlobe, Aibuse and others what they will sell to coustomers ?

And remember that you will also need to learn how to use the softwares. eCognition Developer it has a lot of algorithms and functions, good for change detection using high resolution images (under 5 m, from commercial satellites and images from UAV/drones).

260/250 mb/s This is almost half of the maximum speeds of my ADATA Pro SP550 series SSD, because my laptop mainboard is limited to max. 3Gb/s. But still, is much faster compared to my HDD...

I have just replaced my 320 GB HDD-drive 5400 rpm with a 240 SSD from ADATA in my leptop. Now the multiresolution segmentation algorithm in eCognition Developper is working better, is much more faster and the maximum image size to process has increased from 4000x4000 pixels to 7000x7000 pixels (I am using the same CPU and RAM configuration). So, now i see that SSD's are more efficient thant classic HDD's.

Where do you have ERDAS 2016 ? Share a download link, please.

Hello ! I would like to know what would be the best and the medium PC configuration required to run eCognition Developer in good performance. I read on eCognition forum that this software needs a lot of RAM memory, especially when we use the Multiresolution segmentation algorithm (MRS). It also needs a good CPU and plenty of hard drive space on the computer. These problems can be solved by using eCognition Server, but most of us have a crack license only for eCognition Developer. So we are limited to the performance of our PC's. I am looking to buy a new PC and I would like to know what would be the best configuration to run eCognition Developer in good performance. Can you give me some general tips ? What CPU to use (Intel, AMD, Gz) ? Mainboard, the type and the RAM producer ? HDD or SSD ? My budget: @1500 USD (without the LCD monitor or any other peripherals parts) Thanks, my friends !

Where can I find some international online GIS & Remote Sensing courses organized by institutions or companies that issue graduation diplomas for their students ? Thank you !

Maybe there is a problem of content of moisture in the soil that makes buildings and soil very similar, so maybe you should select another Landsat scene from a dry season. Have you tested with another Landsat scene for your area of interest ?

NDBI = Normalized Difference Built-up Index search the formula for Landsat in Google You can't escape the problem of mixt pixels between built-up and bare soil. These 2 elements have similar spectral signatures. You can only maximize the spectral differentiation by using derivates like NDVI, NDBI, NDWI, etc.... as aditional bands in Landsat scene classification. There is some other supervised methos to better separate the elements, like Spectral Angle Mapper (SAM) , etc, etc. search on internet and on ENVI help page, on sub-pixel classification methos. Another method is to use OBIA > eCognition. OBIA is based on image segmentation. Segmentation is grouping similar spectral pixels into objects. Then you classify these pixel groups based on their spectral signature, shape, area, texture, position into the image, etc. OBIA is similar to visual image interpretation and classification But some research articles say that OBIA is inferior to traditional per-pixel classification methods (supervised and unsupervised) in the case of medium and low spatial resolution images like Landsat, ASTER, SPOT 1-4, MODIS, etc. OBIA works better on high-resolution images like WorldView-2&3, Quickbird, Pleiades, IKONOS, orthophotos, etc (<5 m spatial resolution). These images are much better for built-up area extraction compared to Landsat. So, in your case, my friend, it depends on the accuracy of the classification that you want to obtain !

This is an interesting topic. I have also asked myself how to integrate landscape metrics into eCognition to classify different building shapes in urban areas from high-resolution images and to estimate the degree of urban landscape fragmentation. If someone has a solution to this problem, please share !

I have found this: https://event38.com/product/custom-ngb-filter-glass-for-diy-camera-conversion/ and this: http://mosaicmill.com/products/hardware/NDVI-cameras.html?gclid=CLeNrpGHu8wCFTUW0wodsJoPaQ and this: http://www.mapir.camera/blogs/news/49522051-the-leaf-filter-test Who is using one of the filters to his UAV ?

Lurker, how do you place Ground Control Points (GCP's) if for example you must fly your drone above a dense forest or a wetland with low or no accessibility ?