Automatic Classification Satellite images for weather Monitoring
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This document discusses a system for automatically classifying satellite images to monitor weather patterns and provide early warnings of adverse weather. It describes segmenting images, calculating centroids and distances between regions to identify cloud movement, and setting an alarm if clouds move in a way that indicates potential adverse weather. Algorithms are provided for displaying images, segmenting regions of interest, computing centroids and distances, matching images to estimate cloud models, determining cloud proximity above earth regions, and setting an alarm based on cloud movement patterns. The goal is to develop an early warning system by analyzing successive satellite images at hourly intervals and predicting future cloud patterns and weather.
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F:\Electromagnetic Spectrum
Presentation on the elctromagnetic spectrum prepared at Wilson´s Hospital School. Suitable for senior Physics.
Media Object File Flt Ops Adv Wx Seq07
The document provides guidance on optimally using weather radar to avoid adverse weather conditions. It discusses weather radar capabilities and limitations, cumulonimbus cloud structures and hazards like hail and turbulence, radar technology, and operational best practices. Key recommendations include understanding radar principles, interpreting shapes over colors, using multiple display ranges, adjusting antenna tilt based on altitude and range, and utilizing auto-tilt or auto-scanning functions when available.
Field Trash2007
The document is a catalog titled "Composite Catalog of Oil Field Trash 2007 Edition" that contains photos and descriptions of homemade or modified tools, equipment, and other devices that pose safety risks. It aims to illustrate examples of unsafe oil field equipment to identify them and eliminate their use. The catalog contains six volumes that cover homemade lifting devices, modified tools and equipment, inadequate rigging tools and attachment points, electrical devices with wiring issues, low and high pressure fittings with problems, and equipment with inadequate repairs. The conclusion emphasizes that oil field trash is widespread and must be eliminated to improve safety through employee involvement in identifying unsafe items.
Weather Protection
The document provides information about ways for human beings to protect themselves from adverse weather conditions. It discusses having a disaster supply kit, a disaster family plan, and listening to radio or TV for weather updates. It then prompts the reader to research and describe watches versus warnings, protective actions, photos, stories, and supply kit items for two different weather topics like floods, hurricanes, tornadoes, etc. and create a short animation about one of the topics. It concludes with true/false questions about supply kits and family plans.
OSHA record keeping update
The document summarizes new OSHA reporting requirements for employers that take effect on January 1, 2015. All work-related fatalities must be reported within 8 hours, and all inpatient hospitalizations, amputations, and losses of an eye must be reported within 24 hours. Employers can report to OSHA by phone or online. The new reporting rules will help OSHA identify workplaces with greater risks and target enforcement and assistance efforts. The Midwest region estimates receiving reports of 3,000 amputations and 10,000 hospitalizations in 2015 due to the new rules.
Effective response to adverse weather conditions using SolarPulse
In this case study, we have demonstrated how SolarPulse can help PV plants to provide a quick response to such natural events and thus minimize losses.
Adverse Weather
The document discusses various heat-related illnesses including heat cramps, heat exhaustion, and heat stroke. It notes that heat stroke is the most severe and can result in brain damage, coma, or death if core body temperature reaches 104°F or higher. It also discusses conditions that contribute to heat illnesses and methods for regulating body heat. Cold-related emergencies like frostbite and hypothermia are covered as well as treatments. Work practices and breaks are outlined to prevent heat illnesses.
Planning For Adverse Weather
This document discusses best practices for planning construction schedules to account for adverse weather conditions. It recommends using a weather calendar based on historical data from sources like the National Weather Service. The calendar applies estimated non-work days to weather-dependent activities. This allows the schedule to automatically adjust as weather conditions change over time. Other methods like contingency buffers have disadvantages like reducing schedule transparency and accuracy.
High resolution dem dtm
Today very high resolution DEM from satellite image data with resolution of about one meter allows to depict very detailed surface changes.
High resolution DEM increase accurate satellite image geometry and adding DGPS ground control points increases x.y.z accuracy.
Wrong positioning of objects or bad parameters calculation often result in bad image geometry.
From along track stereo pairs of VHR satellite optical data it’s possible to generate an automatic DEM.
Applications :
Ortho-rectification of satellite images, 3D display.
Creation of accurate topographic reference, relief maps.
Topographic profiles and contour generation.
Surface analysis.
Calculations of slope, orientation and shading.
Calculations of volume and elevation
Extraction of terrain and morphometric parameters.
Geomorphology and structural analysis.
Geological quantifications (dips, lithological thicknesses, faults and folds of geometry, etc.).
3D Reference map of resources extraction zones (quarries, open-pits).
Calculation of hydrographic networks and watershed basin.
Determination of hypsometric curves, knickpoints, etc.
Characterization of eroded areas.
Floods simulation, risks evaluation.
Volume calculation for restraints of dams.
Use of remote sensing for land cover monitoring servir science applications
This document discusses land cover mapping using remote sensing. It provides background on land cover mapping and monitoring in the Himalayan region, where deforestation and forest degradation have been issues. Remote sensing using satellite imagery and tools like GIS allows accurate land cover mapping over large areas. The document discusses different remote sensing platforms and sensors, as well as image classification techniques including unsupervised, supervised and object-based classification. It provides examples of software used for object-based image analysis, and outlines the steps involved in land cover mapping projects using remote sensing.
Baseline Schedules 1
The document discusses baseline scheduling basics and the critical path method (CPM) of scheduling. It covers why schedules are important, different types of schedules and scheduling methodologies. The key aspects of developing a CPM schedule are outlined, including schedule components, logic, and ensuring the schedule is feasible and has buy-in from all parties. Common areas of conflict in scheduling and developing a schedule with the appropriate level of detail and ownership of float are also addressed.
Winter Driving Safety
The document provides information on winter driving safety. It discusses adverse weather conditions like black ice, snow and fog and their effects on traction and visibility. It also covers cold weather injuries, preventive vehicle maintenance, driving techniques for conditions like ice and snow, and communication techniques like using turn signals and adjusting speed based on conditions. Preventive measures include dressing in layers, maintaining proper tire pressure and fluid levels, and driving defensively by allowing extra space between vehicles.
Presentation working at height
Working at height remains a major cause of injuries and fatalities. Employers must properly plan work at height, use the right equipment, and provide fall protection training to competent workers. Simple precautions like performing work from ladders safely and avoiding fragile surfaces can reduce risks. Workers should avoid working at unprotected heights whenever possible.
The Electromagnetic Spectrum
The document discusses the electromagnetic spectrum and different types of electromagnetic waves. It provides information on light as an electromagnetic wave that can travel through vacuum, and describes the various types of electromagnetic waves including gamma rays, x-rays, ultraviolet, infrared, visible light, microwaves and radio waves. It then discusses some common applications of these different electromagnetic waves such as their use in communication technologies, medical imaging, food heating, remote controls and more.
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
This presentation by Dr A R R Menon, Emeritus scientist, CED on Remote Sensing applications in agriculture and forestry was made at at the Kerala Environment Congress, Trivandrum organised by the Centre for Environment and Development
Working at heights training powerpoint
This document outlines requirements and safety procedures for working at heights. It discusses proper fall protection equipment like harnesses and lifelines, as well as safety protocols like hazard identification checklists and permits. Temporary anchor points must be approved and capable of withstanding significant loads. Proper PPE like hard hats is required, and workers must be trained before working alone or using fall arrest vs. restraint systems.
300.40 adverse operating conditions (weather)
This document outlines Orange County Animal Care's procedures for operating during periods of adverse weather conditions like smog alerts. It establishes two levels of smog alerts - Stage II, where mobile units return to the shelter and officers are dispatched to standby locations, and Stage III, where more aggressive measures are taken like sending employees home or implementing mandatory carpooling. The goal is to continue essential services while reducing vehicle use and outdoor activity to protect human and animal health during high pollution levels.
Work At Height
The document discusses the Work at Height Regulations in the UK. It notes that falls from height are a major cause of workplace fatalities and injuries. The regulations were introduced to improve safety by establishing a clear and consistent framework to manage risks associated with working at height. The regulations require hazards to be identified and risks to be properly assessed, controlled, and mitigated through measures such as proper planning, supervision, safe work equipment selection, inspection, and worker training.
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Developing Image Processing System for Classification of Indian Multispectral...
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APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
Effective response to adverse weather conditions using SolarPulse
Effective response to adverse weather conditions using SolarPulse
Use of remote sensing for land cover monitoring servir science applications
Use of remote sensing for land cover monitoring servir science applications
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
Similar to Automatic Classification Satellite images for weather Monitoring
A Review on Haze Removal Techniques
1. The document discusses techniques for removing haze from digital images. It begins with an introduction to how haze forms and degrades image quality.
2. It then describes several categories of haze removal techniques, including multiple image dehazing methods that use multiple images and single image dehazing methods that rely on statistical assumptions. Specific techniques discussed include dark channel prior, guided image filtering, and bilateral filtering.
3. The document focuses on comparing different haze removal approaches and evaluating which methods produce higher quality results for single image dehazing.
A STUDY AND ANALYSIS OF DIFFERENT EDGE DETECTION TECHNIQUES
In the first study [1], a combination of K-means, watershed segmentation method, and Difference In Strength (DIS) map were used to perform image segmentation and edge detection
tasks. We obtained an initial segmentation based on K-means clustering technique. Starting from this, we used two techniques; the first is watershed technique with new merging
procedures based on mean intensity value to segment the image regions and to detect their boundaries. The second is edge strength technique to obtain accurate edge maps of our images without using watershed method. In this technique: We solved the problem of undesirable over segmentation results produced by the watershed algorithm, when used directly with raw data images. Also, the edge maps we obtained have no broken lines on entire image. In the 2nd study level set methods are used for the implementation of curve/interface evolution under various forces. In the third study the main idea is to detect regions (objects) boundaries, to isolate and extract individual components from a medical image. This is done using an active contours to detect regions in a given image, based on techniques of curve evolution, Mumford–Shah functional for segmentation and level sets. Once we classified our images into different intensity regions based on Markov Random Field. Then we detect regions whose boundaries are not necessarily defined by gradient by minimize an energy of Mumford–Shah functional forsegmentation, where in the level set formulation, the problem becomes a mean-curvature which will stop on the desired boundary. The stopping term does not depend on the gradient of the image as in the classical active contour. The initial curve of level set can be anywhere in the image, and interior contours are automatically detected. The final image segmentation is one
closed boundary per actual region in the image.
05397385
This document proposes an object detection technique for aerial videos based on motion vector compensation and statistical analysis. It begins with an introduction to the importance of object detection in aerial surveillance. It then describes the characteristics of aerial video images and a preprocessing method using Bayesian wavelet denoising. A compensation of motion vectors is performed using camera motion estimation. Statistical analysis and clustering of compensated motion vectors is used to detect objects and eliminate isolated vectors. The method is tested on a road surveillance video, showing it can effectively detect objects after noise removal and motion vector processing.
05397385
This document proposes an object detection technique for aerial videos based on motion vector compensation and statistical analysis. It begins with an introduction to the importance of object detection in aerial surveillance. It then describes the characteristics of aerial videos and discusses how motion vectors can be used for detection. The technique involves preprocessing the video via wavelet denoising, compensating motion vectors estimated from frame differences using a global motion vector, and performing statistical analysis and clustering on the compensated motion vectors to detect and segment objects. Experimental results demonstrate that the technique can successfully detect objects in aerial videos by distinguishing object motion from background motion.
Stereo Correspondence Algorithms for Robotic Applications Under Ideal And Non...
The use of visual information in real time applications such as in robotic pick, navigation, obstacle avoidance etc. has been widely used in many sectors for enabling them to interact with its environment. Robotics require computationally simpler and easy to implement stereo vision algorithms that will provide reliable and accurate results under real time constraint. Stereo vision is a less expensive, passive sensing technique, for inferring the three dimensional position of objects from two or more simultaneous views of a scene and there is no interference with other sensing devices if multiple robots are present in the same environment. Stereo correspondence aims at finding matching points in the stereo image pair based on Lambertian criteria to obtain disparity. The correspondence algorithm will provide high resolution disparity maps of the scene by comparing two views of the scene under the study. By using the principle of triangulation and with the help of camera parameters, depth information can be extracted from this disparity .Since the focus is on real-time application, only the local stereo correspondence algorithms are considered. A comparative study based on error and computational costs are done between two area based algorithms. Evaluation of Sum of absolute Difference algorithm, which is less computationally expensive, suitable for ideal lightening condition and a more accurate adaptive binary support window algorithm that can handle of non-ideal lighting conditions are taken for this study. To simplify the correspondence search, rectified stereo image pairs are used as inputs.
D04432528
This document describes a laser distance measurement system using a webcam. It consists of a laser transmitter and webcam receiver. The laser pulse is reflected off an object and received by the webcam. Software calculates the distance based on the time of flight. The system achieves high accuracy of ±3cm. It calibrates the system using test measurements to determine the relationship between pixel location of the laser dot and actual distance. This allows accurate distance measurements within a few percent of error out to over 2 meters. Potential improvements discussed are using a laser line instead of dot for more data points and a green laser for better visibility.
Adaptive lifting based image compression scheme using interactive artificial ...
This paper presents image compression method using Interactive Artificial Bee Colony (IABC) optimization algorithm. The proposed method reduces storage and facilitates data transmission by reducing transmission costs. To get the finest quality of compressed image, utilizing local search, IABC determines different update coefficient, and the best update coefficient is chosen
optimally. By using local search in the update step, we alter the center pixels with the coefficient in 8-different directions with a considerable window size, to produce the compressed image, expressed in terms of both PSNR and compression ratio. The IABC brings in the idea of
universal gravitation into the consideration of the affection between onlooker bees and the employed bees. By passing on different values of the control parameter, the universal gravitation involved in the IABC has various quantities of the single onlooker bee and employed bees. As a result when compared to existing methods, the proposed work gives better PSNR.
E0333021025
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Paper id 35201575
This document summarizes a research paper on using a hybrid dark channel prior method for visibility restoration in images degraded by haze or fog. It begins by introducing the problem of image degradation in poor weather conditions like fog. Then it describes existing techniques for image restoration, including the dark channel prior method, which estimates atmospheric light and transmission maps to recover the original scene. The document proposes a hybrid dark channel prior method that uses both small and large patch sizes to better estimate the haze density. Simulation results demonstrate that the hybrid method more effectively removes haze than traditional techniques. The paper concludes that the hybrid approach works well for fog and noise removal in single images under different weather conditions.
Digital image processing
Digital images can be manipulated mathematically by treating pixel brightness values as numbers. This document discusses various digital image processing techniques including:
1. Image rectification to correct geometric distortions and calibrate radiometric data. This involves techniques like geometric corrections to adjust for sensor distortions and radiometric corrections to standardize brightness values.
2. Image enhancement techniques like contrast stretching to increase image contrast and improve feature detection. Methods include linear stretches, histogram equalization, and logarithmic transforms.
3. Local operations called spatial filtering that modify pixel values based on neighboring pixels. This can emphasize or de-emphasize certain image features or spatial frequencies to enhance details or reduce noise.
Wavelet-Based Warping Technique for Mobile Devices
The document proposes a wavelet-based warping technique to render novel views of compressed images on mobile devices. It uses Haar wavelet transform to compress large reference and depth images, reducing their size. The technique decomposes the images into approximation and detail parts, but only uses the approximation parts for warping. This improves rendering speed on mobile devices. The framework is implemented using Android tools and experiments show it provides faster rendering times for large images compared to direct warping without compression.
Final
This document describes a project that uses photometric stereo to reconstruct 3D surfaces from images taken under different lighting conditions on a computer screen. Photometric stereo uses variations in pixel intensities across images to estimate surface normals and reconstruct the 3D shape. The project creates a MATLAB program that performs photometric stereo in real-time by flashing different light patterns on a screen and capturing images with a webcam. By using singular value decomposition, the program can reconstruct surfaces without knowing the exact positions of the light sources, overcoming a limitation of traditional photometric stereo. The reconstruction contains noise but demonstrates photometric stereo in a less controlled environment. Further work could explore tradeoffs of the method and improve efficiency.
VISUAL MODEL BASED SINGLE IMAGE DEHAZING USING ARTIFICIAL BEE COLONY OPTIMIZA...
Images are often degraded by atmospheric haze , a phenomenon due to the particles in the air that scatter light. Haze induces a loss of contrast,its visual effect is blurring of distant objects. This paper presents a novel algorithm for improving the visibility of an image degraded by haze. The proposed method uses a cost function based on human visual model to estimate airlight map. It employs Artificial Bee Colony optimization (ABC) as the optimization technique for estimating air light map. Image is dehazed by removing the estimatedairlight from the degraded image. The performance of the algorithm is tested and compared with various other dehazing methods and the proposed algorithm dehazes the image effectively outperforming other methods.
chAPTER1CV.pptx is abouter computer vision in artificial intelligence
This document provides an overview of digital image processing and computer vision. It discusses:
1. Low-level image processing techniques like pre-processing, segmentation, and object description that use little domain knowledge.
2. High-level image understanding techniques based on knowledge, goals, and plans that aim to imitate human cognition.
3. Fundamental concepts in digital image processing including image functions, sampling, quantization, and properties. Mathematical tools from linear systems theory, transforms, and statistics are used.
computervision1.pptx its about computer vision
This document provides an overview of digital image processing and computer vision. It discusses:
1. Low-level image processing techniques like pre-processing, segmentation, and object description that use limited domain knowledge.
2. High-level image understanding techniques based on knowledge, goals, and plans that aim to imitate human cognition through artificial intelligence methods.
3. Fundamental concepts in digital image processing including image functions, sampling, quantization, and properties like histograms and noise that are introduced and will be used throughout the course.
mini prjt
This document discusses single object tracking and velocity determination. It begins with an introduction and objectives of the project which is to develop an algorithm for tracking a single object and determining its velocity in a sequence of video frames. It then provides details on preprocessing techniques like mean filtering, Gaussian smoothing and median filtering to reduce noise. It describes segmentation methods including histogram-based, single Gaussian background and frame difference approaches. Feature extraction methods like edges, bounding boxes and color are explained. Object detection using optical flow and block matching is covered. Finally, it discusses tracking and calculating velocity of the moving object. MATLAB is introduced as a technical computing language for solving these types of problems.
G0443640
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Visual Environment by Semantic Segmentation Using Deep Learning: A Prototype ...
This document describes a proposed method for estimating sky view factor (SVF) using semantic segmentation with deep learning networks. Specifically:
- It develops a system using SegNet and U-Net deep learning models to perform pixel-wise semantic segmentation of sky and non-sky areas from images to calculate SVF ratios.
- The system was trained on 300 manually segmented images and tested on 100 fisheye photographs, achieving 98% accuracy in estimating SVF under different sky conditions.
- Future work is needed to apply the system to live video streams rather than static images. The method provides an efficient, high-precision way to estimate important urban environmental metrics like SVF.
I0343065072
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Automatic Detection of Window Regions in Indoor Point Clouds Using R-CNN
The document describes a method to automatically detect window regions in 3D point cloud data of indoor environments collected using a backpack sensor system. The method is based on R-CNN and uses MCG to generate region proposals, extracts features from proposals using a CNN, and classifies proposals as windows or non-windows using a random forest. Experiments on a dataset of 400 images achieved an F1 score of 89.79% and mAP of 96.64% for window detection, outperforming an existing method. Adding a small amount of manually labeled data further improved results.
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Wavelet-Based Warping Technique for Mobile Devices
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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Automatic Classification Satellite images for weather Monitoring
- 1. WELCOME TO NEW WORLD OF IMAGINATION The Knowledge where imagination comes true
- 2. "Automatic classification of Satellite Images for Weather Monitoring"
- 3. Abstract In this paper we discuss on a system where in automatically the images collected from the satellite are classified into either normal weather patterns or adverse weather patterns developed. An alarm used to rise as early warning if a tendency of adverse weather system is about to be formed. This requires the domain knowledge about the cloud formation, movement of clouds, and image processing techniques. We discuss here regarding the displaying and analyzing the satellite image data, image segmentation which subdivides an image into its constituent regions/objects, and attempting to achieve the goals of early warning system.
- 5. Diagram of Object Recognition Relations between PR and IP Diagram of Object Recognition Image Processing Images Data Analysis Pattern Recognition Pattern Recognition Object Classes Image Processing (IP) Pattern Recognition (PR) Object Classes Images
- 9. Segmentation
- 10. Processing the whole image is computationally expensive. So for our further processing we considered only 100X100 pixel. We give a search area by giving X and Y coordinates and increases the X and Y coordinate vale respectively. The region of interest is on the specific area so our interest will be more on that area so we segment that regions for our further process.
- 11. New image is pointed on the old image to enable the user to instantaneously compare the subsequent images. Algorithm: Segmentation Step 1 : Using image display algorithm displays the image. Step 2 : Initialize two seeding point. Step 3 : Select first seeding point and grow the region, similarly do same for second seeding point . Step 4 : Display those segment using Display Algorithm.
- 12. Image considered for processing of size 255 X 255 pixels
- 13. Region B (100X100) Region A (100X100) Segmented Image After Segmentation twice for the region of interest (Region A and region B)
- 14. Identification of Movement of Clouds Dealing with indefinite shapes
- 16. Message & Value of pixels Calculations Centroid Distance Alarm Image Segment Proximity Image matching FLOW OF PROCESS FOR IDENTIFICATION OF MOVEMENTS OF CLOUDS MODEL
- 18. Experimental results: Reference Image of order 255 X 255
- 19. Centroid C=(51.92,58.8) Centroid of region A No of rows=100, No of columns=200 No of pixels= 52 Centroid C=(Xstartpoint+X, Ystartpoint+Y) (50+1.92,55+3.8) Showing the centroid of the region A
- 20. Centroid of region B Centroid = (55.75,80) Similarly we calculate Centroid for Region B Showing the centroid of the region B
- 22. The Next successive Image of order 255 X 255 Experimental results:
- 23. Centroid of region B1 Centroid = (70.77,80) Showing the centroid of the region B1
- 24. Distance between reference image and the next successive region B1 Region B1 Region A Distan ce D1 Showing the distance between reference image and the next cloud region
- 26. ALGORITHM : Image matching Input : File B- reference image of cloud region. File B1- cloud region of new image. Or Two 2D arrays to retrieve values of files, (X2,Y2)- Centroid of reference Cloud region. (X1,Y1)- Centroid of reference Earth region Output : Output- 2D array to store the difference of two images. Method : Subtract the two images and store the resultant in Output. Find the centroid of resultant image. Find the shift(X2out=X2+X211,Y2out=Y2+Y211). Find the distance between the new Cloud region and reference Earth region using distance algorithm.
- 31. The Ultimate goal of the project is to give warning message about the status of clouds. The Algorithm for Alarm follows MESSAGE
- 33. Ist condition
- 34. 2 nd Condition 1 st part
- 35. 2 nd condition 2 nd part
- 36. 2 nd condition 3 rd part
- 37. We took the following Spacecraft images for the project and the output we have seen in previous slides. The last two images show that we have taken images every 1-hour of time.
- 38. The image took after 1-hour of the previous image
- 42. ? Questions