Generated a digital elevation model of Greenland using ICESat-2 products
For my Digital Surface Modeling course project, I developed a method to create digital elevation models (DEMs) of ice sheets using high-resolution altimetry data from the IceSat2 satellite. The goal was to overcome the limitations and costs associated with traditional ground-based or airborne surveys. The method involved the following steps: I implemented this process in Python due to its flexibility and applied it to data sets from the Greenland ice sheet for the first six months of 2019 and 2023. The results showed an accelerating rate of melting on the Greenland ice sheet between the two time periods. In 2019,
Enhancing images using transformations
Negative Transformation: Image inversion or Image negation helps find the details from the darker regions of the image. The negative of an image is achieved by replacing the intensity ‘i’ in the original image with ‘i-1’, i.e. the darkest pixels will become the brightest and the brightest pixels will become the darkest. Image negative is produced by subtracting each pixel from the maximum intensity value. For instance, in an 8-bit grayscale image, the max intensity value is 255, thus each pixel is subtracted from 255 to produce the output image. Log transformation Log transformation is used for image enhancement as
Histogram processing and thresholding target detection
The goal of this project is to find different complications in images. The pictures are related to an airport and the desert area around it, to find the roads we use the thresholding method. To be able to find an appropriate threshold, the print command checked the values of the pixels and then I set my threshold to 200. The results were obtained as follows: The output image where the roads are marked in white: To create the above image, I used the first band, the red band. Because in case of using the green band, other complications besides the
Spatial Filtering
1)Apply low-pass filters and remove noise First, we add “Gaussian” and “Salt&Pepper” noises to the given images and then remove them. The images after adding noise are like this: Now, after adding noise, we add average, median, and Gaussian filters to the images in three different ways. Here are the results: As it is known, the average filter works better in removing Salt&Pepper noise. This filter also works better on Salt&Pepper noise. As can be seen in the pictures, after applying the median filter on the Gaussian noise, there is nothing left of the image. As it is known, the
Image processing in the frequency domain
In this project, we first tried to get acquainted with the behavior of different images and standards in the frequency domain. We got to know the characteristics of the Fourier domain, and finally, we applied the filters in the frequency domain. At first, to prepare the images for later use and perform various processing, we convert all the given images (except the Gradient and Gaussian image) to 0 and 1 values by applying thresholding. Next, we apply a two-dimensional fast Fourier transform (fft2) on all images, And we use the “fftshift” command to accumulate frequencies in the center. According to
Estimating the perimeter of the earth’s ellipsoid using numerical methods such as Runge-Kutta
In many sciences, especially the science of geometric geodesy, we face problems that cannot be solved by analytical methods, or it is very difficult and impossible to solve such problems with analytical methods. Such problems include solving integrals, ordinary differential equations with the initial value (ODE), or calculating the numerical derivative of some functions. For this purpose, the use of numerical methods is considered. In this research project, the goal of solving the integral is to calculate the perimeter of the ellipse. To solve this integral, we first convert it into a differential equation and convert it into an initial
Analyzing the geometric shape of the earth using gravity acceleration observations
This project aims to investigate and analyze the shape of the earth using observations of gravity acceleration. The natural and physical shape of the earth is the shape of the surface of the oceans under the effect of gravity and centrifugal force; This defined surface is an equipotential surface called the geoid. This surface is a complex and irregular surface due to the heterogeneous distribution of mass inside the earth and on its surface. At first glance, the earth can be considered a sphere with an average radius of 6371 km. But we know that the earth’s sphericity is not
Creating a 3D model of Meybod Yazd city
In this project, we obtained 23 aerial photographs of the city of Meybod, Yazd. Then we used the images as input to create a 3D model. This project has been performed using Agisoft Metashape. During this project we did the following steps: Alignment of the input images Used the aligned pictures to create a mesh surface Built orthomosaic from the surface Built dense clouds of points Introduction of ground coordinates of control points Enter camera specifications. The detailed report of this project is in the following file:
Augmented reality and its use in GIS and map preparation
Augmented reality and virtual reality are two terms that have been heard more in the past years and their use in various industries has been increasing. Maybe you have heard the name virtual reality. Augmented reality, like virtual reality, has been known in recent years and many applications have been created for it. For example, in cinema, augmented reality is used to make fictional films. In many exhibitions, users have used augmented reality to display their products and examples. Even in recent years, AR has made its way to some museums. In this article, an attempt has been made to
Estimate the price of preparing a map of Bandar-e Deylam
Open and closed meters are used to estimate costs in any project. In this project, we calculated the cost of mapping Deylam city located in Bushehr province by closed meter method and based on the mapping service tariff.In this projetor to prepare a 1:1000 scaled map with a contour of half a meter, it is necessary to estimate the price by two methods of direct ground mapping and photogrammetry of the urban area, convex hull, and 1000 meters of the convex hull, and then we got the insurance and tax costs for both methods. The report of this project is
Controlling the project of preparing a map of Bandar-e Deylam by the method of direct ground survey and photogrammetric survey
The goal of the project is to design a Gantt chart and CPM table and chart for Bandar-e Deylam. According to the first project, the area of Bandar Dilam is equal to 506.46403 hectares. Also, the district coefficient of this city is determined as 2.13 according to the instructions. The report and detailed calculations of this project can be found in the link below:
Transforming different coordinate systems and calculating the evolute of an ellipsoid
The evolute of an ellipse is the locus of all the centers of the ellipse curves. In general, this case is investigated for all curves, but in this text, we will specifically investigate the ellipse. The eccentricity parameter has a great effect on the width of the ellipse because this parameter can determine the shape and stretch of the ellipse. This parameter is expressed for all conical sections. If we want to specifically check the ellipse, its eccentricity must be a number between zero and one. The closer this value is to zero, the ellipse will become a circle, and
Creating and displaying the spatial data of users in QGIS
This project is the final sequence of a couple of researches that I did in the course of Principle of Database. In this project, we aimed to use Oracle database more efficiently and easily. the first step was to create a store procedure that can get the information of the users of the application as inputs, and add it to the database. The next step was to create a View in the Oracle database that can show the number of users in order of their residential city. Next, we used QGIS program to better display the results, grouped by different
Fourier Analysis using MATLAB
Fourier analysis is a method of defining periodic waveforms in terms of trigonometric functions. In this project, the goal is to analyze and calculate the Fourier coefficients. This project consists of different parts such as Fourier analysis, Audio signal analysis, and image analysis in the frequency domain. 1. Fourier analysis The following steps have been taken: calculated Fourier coefficients for 4 different signals displayed the plot of each Fourier signal calculated Fourier transform of the above-mentioned signals analyzed the difference between the Fourier transform of each signal, when various changes occur in its arguments The principle of Signal Sampling 2.
Designing four routes according to AASHTO standards using Civil 3D
A road is a linear way for the conveyance of traffic that mostly has an improved surface for use by vehicles. In this project, we designed 4 routes with different slopes along the way. We used the AASHTO standard for designing our roads. Contours of a specific area had been given to us. first, we transformed the contours to a surface using Civil 3D options. then designed four routes with different parameters. The full article is available through the following link:
Convergent Technologies Research Center
In this course, with the consent of Dr. vahhabi, I participated in the article reading program and reviewed the below-mentioned articles.
Image Classification: Supervised, Unsupervised and decision tree methods
Classification is a process during which different classes of an image are separated from each other. Usually, the classification result is displayed using different colors. There are two main types of classification. The difference between these two methods is in the type of input data and the classification algorithm. When we use supervised classification, we have to give a series of labels along with input images to the program. Using the given labels, the algorithm learns the characteristics of our class and by generalizing it, it can use the trained classification in the whole set of the input image. But
Filtering and Masking satellite images using ENVI
In this project, we aimed to apply different filters and masks to a spatial subset of a satellite image. We use Landsat 8 meta-data file to obtain the image. Then some remote sensing indices have been created using the “band math” option in the ENVI program. After creating the desired indicators, we will use them to specify each of the complications and coverages. We need to separate the five desired land coverages using indicators and each of the bands. These five land covers are: To obtain each of these land covers, we act as follows: Noise removal and edge extraction in panchromatic images
Land use Classification using Deep Learning
Recently, I did a project about land use classification using deep learning. In this project, I used AlexNet-based architecture. I am still working on obtaining better accuracy. The details about this project are in the link below.