This document provides an overview of map algebra, which is an analysis language for performing spatial analysis on raster data. It describes the main operators in map algebra, including arithmetic, boolean, combinatorial, logical, and relational operators. It also outlines different function types in map algebra, such as local functions that apply calculations independently to each cell, global functions that apply calculations based on all cell values, focal functions that apply calculations within a neighborhood focus, and zonal functions that apply calculations within zones.
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
Topics:
1. Introduction to GIS
2. Components of GIS
3. Types of Data
4. Spatial Data
5. Non-Spatial Data
6. GIS Operations
7. Coordinate Systems
8. Datum
9. Map Projections
10. Raster Data Compression Techniques
11. GIS Software
12. Free GIS Data Resources
Spatial analysis & interpolation in ARC GISKU Leuven
In ArcGIS, a data model describes the thematic layers used in the applications (for example, hamburger stands, roads, and counties); their spatial representation (for example, point, line, or polygon); their attributes; their integrity rules and relationships (for example, counties must nest within states).
Digital Elevation Model (DEM) is the digital representation of the land surface elevation with respect to any reference datum. DEM is frequently used to refer to any digital representation of a topographic surface. DEM is the simplest form of digital representation of topography. GIS applications depend mainly on DEMs, today.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
Gis Geographical Information System FundamentalsUroosa Samman
Gis, Geographical Information System Fundamentals. This presentation includes a complete detail of GIS and GIS Softwares. It will help students of GIS and Environmental Science.
A remote sensing system uses a detector to sense the reflected or emitted energy from the earth's surface, perhaps modified by the intervening atmosphere. The sensor can be on a satellite, aircraft, or drone. The sensor turns the energy into a voltage, which an analog to digital converter turns into a single integer value (called the Digital Number, or DN) for the energy. Alternatively a digital detector can store the DN directly. We can then display this value with an appropriate color to build up an image of the region sensed by the system. The DN represents the energy sensed by the sensor in a particular part of the electromagnetic spectrum, emitted or reflected from a particular region. The principles can also be applied to sonar imagery, especially useful in water where sound penetrates readily whereas electromagnetic energy attenuates rapidly.
Definitions,
Remote sensing systems can be active or passive: active systems put out their own source of energy (a large "flash bulb") whereas passive systems use solar energy reflected from the surface or thermal energy emitted by the surface. Active systems can achieve higher resolution.
Satellite resolution considers four things: spatial, spectral, radiometric, and temporal resolution.
Electromagnetic radiation and the atmosphere control many aspects of a remote sensing system.
Satellite orbits determine many characteristics of the imagery, what the satellite sees, and how often it revisits an area.
The signal to noise ratio is important for the design of remote sensing systems.
Satellite band tradeoffs.
Interpreting satellite reflectance patterns and images uses various statistical measures to assess surface properties in the image.
The colors used on the display are gray shading for single bands, and RGB for multi-band composites. We can also perform image merge and sharpening to combine the advantages of both panchromatic (higher spatial resolution) and color imagery (better differentiation of surface materials).
Keys for image analysis
Hyperspectral imagery
Spectral reflectance library--different materials reflect radiation differently
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
Radiometric corrections include correcting the data for sensor irregularities and unwanted sensor or atmospheric noise, and converting the data so they accurately represent the reflected or emitted radiation measured by the sensor.
The concept of GIS was first introduced in the early 1960s, and it was subsequently researched and developed as a new discipline. The GIS history views Roger Tomlinson as a pioneer of the concept, where the first iteration was designed to store, collate, and analyze data about land usage in Canada.
Topics:
1. Introduction to GIS
2. Components of GIS
3. Types of Data
4. Spatial Data
5. Non-Spatial Data
6. GIS Operations
7. Coordinate Systems
8. Datum
9. Map Projections
10. Raster Data Compression Techniques
11. GIS Software
12. Free GIS Data Resources
Spatial analysis & interpolation in ARC GISKU Leuven
In ArcGIS, a data model describes the thematic layers used in the applications (for example, hamburger stands, roads, and counties); their spatial representation (for example, point, line, or polygon); their attributes; their integrity rules and relationships (for example, counties must nest within states).
Digital Elevation Model (DEM) is the digital representation of the land surface elevation with respect to any reference datum. DEM is frequently used to refer to any digital representation of a topographic surface. DEM is the simplest form of digital representation of topography. GIS applications depend mainly on DEMs, today.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
Gis Geographical Information System FundamentalsUroosa Samman
Gis, Geographical Information System Fundamentals. This presentation includes a complete detail of GIS and GIS Softwares. It will help students of GIS and Environmental Science.
A remote sensing system uses a detector to sense the reflected or emitted energy from the earth's surface, perhaps modified by the intervening atmosphere. The sensor can be on a satellite, aircraft, or drone. The sensor turns the energy into a voltage, which an analog to digital converter turns into a single integer value (called the Digital Number, or DN) for the energy. Alternatively a digital detector can store the DN directly. We can then display this value with an appropriate color to build up an image of the region sensed by the system. The DN represents the energy sensed by the sensor in a particular part of the electromagnetic spectrum, emitted or reflected from a particular region. The principles can also be applied to sonar imagery, especially useful in water where sound penetrates readily whereas electromagnetic energy attenuates rapidly.
Definitions,
Remote sensing systems can be active or passive: active systems put out their own source of energy (a large "flash bulb") whereas passive systems use solar energy reflected from the surface or thermal energy emitted by the surface. Active systems can achieve higher resolution.
Satellite resolution considers four things: spatial, spectral, radiometric, and temporal resolution.
Electromagnetic radiation and the atmosphere control many aspects of a remote sensing system.
Satellite orbits determine many characteristics of the imagery, what the satellite sees, and how often it revisits an area.
The signal to noise ratio is important for the design of remote sensing systems.
Satellite band tradeoffs.
Interpreting satellite reflectance patterns and images uses various statistical measures to assess surface properties in the image.
The colors used on the display are gray shading for single bands, and RGB for multi-band composites. We can also perform image merge and sharpening to combine the advantages of both panchromatic (higher spatial resolution) and color imagery (better differentiation of surface materials).
Keys for image analysis
Hyperspectral imagery
Spectral reflectance library--different materials reflect radiation differently
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
Radiometric corrections include correcting the data for sensor irregularities and unwanted sensor or atmospheric noise, and converting the data so they accurately represent the reflected or emitted radiation measured by the sensor.
The concept of GIS was first introduced in the early 1960s, and it was subsequently researched and developed as a new discipline. The GIS history views Roger Tomlinson as a pioneer of the concept, where the first iteration was designed to store, collate, and analyze data about land usage in Canada.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
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Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
2. INTRODUCTION
Map Algebra is an analysis language based loosely on the map algebra concepts
presented by Dr. Dana Tomlin in his book entitled Geographic Information
Systems and Cartographic Modeling(Tomlin, 1990)
Map Algebra is a high-level computational language used for performing
cartographic spatial analysis using raster data.
4. ARITHMETIC OPERATORS
Arithmetic operators allow addition, subtraction, multiplication, and division.
Arithmetic operators can also be used to convert values from one measurement
to another (Example: feet x 0.3048 = meters).
5. RELATIONAL OPERATORS
Relational operators allow you to build logical tests returning values of true (1)
and false (0).
You can ether use the Relational Operator (=,<,>)
of the Abbreviation (EQ,LT, GT)
6. BOOLEAN OPERATORS
Boolean operators such as "and", "or", and "not" allow you to chain logical tests.
Like relational operators, Boolean operators return values of true and false.
Example: slopes that are "greater-than" 45 degrees "and" that have an elevation that is
"greater-than" 5000 meters
7. LOGICAL OPERATORS
The logical operators DIFF, IN, and OVER, also allow you to build logical tests on
a cell-by-cell basis, but are implemented with specific rules.
A DIFF B: If a cell value in raster A and raster B are different, the cell value in raster A is
returned. If the cell values are the same, the value zero is returned.
A IN {value list}: If a cell value in raster A is in the value list, the cell value in raster A is
returned. Otherwise, No Data is returned.
8. COMBINATORIAL OPERATORS
Combinatorial operators combine the attributes of multiple input rasters.
These operators find all unique combinations of values and assign a unique ID to
each, which is then returned to the output grid.