Resolution.pptx remote sensing resolution
Download as PPTX, PDF1 like1,682 views
Sensor resolution refers to a sensor's ability to detect fine detail and can be measured spatially, spectrally, or temporally. Spatial resolution is the smallest feature a sensor can detect, which depends on its instantaneous field of view and altitude. Spectral resolution is the narrowness of electromagnetic wavelength ranges detected. Radiometric resolution is the sensor's ability to detect slight differences in energy. India's remote sensing satellite program began in 1988 with the successful launch of IRS-1A, and has since grown to include multiple operational satellites providing data for applications like agriculture, resource management, and disaster response.
1 of 11
Download to read offline
Ad
Recommended
Remote sensing-presentaion
Remote sensing-presentaionMouna Guru This document discusses satellite remote sensing. It provides details on different types of remote sensing satellites including Landsat, MODIS, SPOT, IRS series, and IKONOS. It also describes various sensors used in remote sensing such as MSS, TM, HRV, LISS, PAN, and WiFS. The document discusses the basic principles, components, and applications of remote sensing from satellites for land resources survey, environmental monitoring, and other purposes.
Remote sensing
Remote sensingKaium Chowdhury This document provides an overview of key concepts in remote sensing including:
- The electromagnetic spectrum and how different wavelengths are used in remote sensing.
- How electromagnetic radiation interacts with the atmosphere, including scattering, absorption, and transmission.
- How radiation interacts with the Earth's surface through reflection, absorption, and transmission.
- Spectral reflectance curves and how the reflectance of materials like vegetation, soil, and water vary across the electromagnetic spectrum.
- The basic principles and elements of remote sensing systems, from the energy source and sensors to data analysis and applications.
Remote sensing & gis
Remote sensing & gisDilin Sathyanath Geographic information systems (GIS) are organized collections of computer hardware, software, and geographic data used to capture, store, update, manipulate, analyze, and display geographically referenced information. GIS provides spatial data depicted as points, lines, or polygons with attributes stored in tables, and can take data from various sources and integrate them into multiple layers for analysis. Common applications of GIS include agriculture, natural resource management, disaster management, and urban planning.
GIS Map Projection
GIS Map ProjectionMUHAMMAD BILAL SALEEM This document discusses map projections, which are methods for translating the three-dimensional surface of the Earth onto a two-dimensional map. It describes three types of developable projection surfaces - conic, cylindrical, and planar - that are used to create different map projections. Specific projections are then outlined, including what geometric properties they preserve or distort (shape, area, distance, direction) and their common uses. The document provides a detailed overview of different GIS map projection techniques.
Multispectral remote sensing
Multispectral remote sensingDharmendera Meena Multispectral remote sensing involves collecting reflected, emitted, and backscattered energy from objects in multiple bands of the electromagnetic spectrum simultaneously. There are three main types of multispectral sensor systems: line detectors that detect one object at a time; whiskbroom/cross-track sensors that use a rotating mirror to scan the surface; and pushbroom/along-track sensors that have no moving parts and sense energy directly using arrays of detectors. Multispectral remote sensing has applications in military intelligence gathering, medical imaging, land assessment, and studying seasonal variations.
GIS data analysis
GIS data analysisArindam Sarkar This document discusses GIS data analysis techniques including raster to vector conversion and spatial analysis through vector overlay. It provides information on various data types and models in GIS. Key analysis techniques covered are raster and vector data overlays, terrain mapping and analysis, and spatial interpolation methods. Specific vector and raster overlay methods like point-in-polygon, line-in-polygon and polygon-on-polygon are described. Spatial data editing techniques involving digitization errors and topological/non-topological editing are also summarized.
Sensors for remote sensing
Sensors for remote sensingMohsin Siddique This document discusses remote sensing and geographical information systems in civil engineering. It covers various topics related to remote sensing sensors including optical sensors, thermal scanners, multispectral sensors, passive and active sensors, scanning and non-scanning sensors, imaging and non-imaging sensors, and the different types of resolutions including spatial, spectral, radiometric, and temporal resolution. It provides examples and illustrations of these concepts.
Remote sensing - Scanners
Remote sensing - ScannersPRAMODA G The document discusses different types of remote sensing scanners. It describes multispectral scanners, thematic mappers, thermal scanners, and hyperspectral scanners. Multispectral scanners collect data in multiple wavelength bands using either across-track or along-track scanning. Thematic mappers were developed to improve upon multispectral scanners. Thermal scanners sense the thermal infrared wavelength range. Hyperspectral scanners record over 100 contiguous spectral bands to generate a continuous reflectance spectrum for each pixel.
Remote sensing - Sensors, Platforms and Satellite orbits
Remote sensing - Sensors, Platforms and Satellite orbitsAjay Singh Lodhi Remote sensing uses sensors on various platforms to detect electromagnetic radiation from the Earth. Sensors can be passive, detecting natural radiation, or active, emitting their own radiation. Platforms include ground-based, airborne, and space-based options at increasing heights. Space-based platforms include low Earth orbit satellites in polar or sun synchronous orbits for frequent coverage, and geostationary satellites for continuous coverage of fixed regions. Different sensors have varying spatial, spectral, radiometric, and temporal resolutions to detect features on Earth.
ppt spatial data
ppt spatial dataRahul Kumar This document discusses two types of spatial data used in GIS - vector data and raster data. Vector data represents geographic features as points, lines, and polygons using vertices with x, y, and z coordinates. It allows for accurate representation of shapes and storing of attribute data but requires more processing and storage. Raster data represents geographic information through a grid of cells (pixels), with each cell storing attribute values like elevation or temperature. It is better for continuously changing data but cannot represent linear features well and has increased storage needs at higher resolutions. Both data types have advantages and disadvantages depending on the use case.
Atmospheric windows
Atmospheric windowsSadia Rahat Certain wavelengths of light can penetrate the atmosphere better than others. These transparent regions are called "atmospheric windows". The figure shows that visible light and radio frequencies experience the least absorption as they travel through the atmosphere. These are the dominant windows. X-rays and UV light face strong absorption, while gamma rays and infrared see somewhat less absorption. Atmospheric windows may refer specifically to the radio, infrared, and visible portions of the electromagnetic spectrum.
Remote Sensing: Image Classification
Remote Sensing: Image ClassificationKamlesh Kumar The objective of image classification is to classify each pixel into only one class (crisp or hard classification) or to associate the pixel with many classes (fuzzy or soft classification). The classification techniques may be categorized either on the basis of training process (supervised and unsupervised) or on the basis of theoretical model (parametric and non-parametric).
Unsupervised classification is where the groupings of pixels with common characteristics are based on the software analysis of an image without the user providing sample classes. The computer uses techniques to determine which pixels are related and groups them into classes. The user can specify which algorism the software will use and the desired number of output classes but otherwise does not aid in the classification process. However, the user must have knowledge of the area being classified when the groupings of pixels with common characteristics produced by the computer have to be related to actual features on the ground (such as waterbodies, developed areas, forests, etc.).
Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these training sites as references for the classification of all other pixels in the image. Input classes are selected based on the knowledge of the user. The user also sets the bounds for how similar other pixels must be to group them together. These bounds are often set based on the spectral characteristics of the input classes (AOI), plus or minus a certain increment (often based on “brightness” or strength of reflection in specific spectral bands). The user also designates the number of classes that the image is classified into.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Thermal Remote Sensing
Thermal Remote SensingRohit Kumar This document provides an overview of thermal remote sensing. It begins with an introduction to remote sensing and defines thermal remote sensing as measuring electromagnetic radiation in the thermal infrared region. It describes the atmospheric windows and fundamental radiation laws governing thermal remote sensing. Applications discussed include surface temperature detection, fire detection, and volcano monitoring. The document concludes with the advantages of being able to detect true temperatures and limitations such as difficulty maintaining sensor temperatures.
Digital image processing
Digital image processingVandana Verma Digital image processing ,Techniques of Digital Image Processing
Image Enhancement ,Image Histogram,Spatial Filtering,Smoothing and Sharpening Examples,Image Classification,Supervised Classification,Unsupervised Classification
remote sensing applications.
IMAGE INTERPRETATION TECHNIQUES of survey
IMAGE INTERPRETATION TECHNIQUES of surveyKaran Patel Image interpretation is the process of examining an aerial photo or digital remote sensing image and manually identifying the features in that image. This method can be highly reliable and a wide variety of features can be identified, such as riparian vegetation type and condition, and anthropogenic features
Remote sensing
Remote sensingFidy Zegge The document discusses the four types of image resolution: spatial, spectral, radiometric, and temporal resolution. Spatial resolution refers to the ability of a sensor to identify the smallest details visible in an image. Spectral resolution is the sensor's ability to distinguish between narrow wavelength bands, while radiometric resolution refers to its ability to detect small differences in energy levels. Temporal resolution describes how frequently data is captured for a given location. Higher resolution in all four types provides more detailed, clear images for analysis.
SENSORS AND SCANNERS.pptx
SENSORS AND SCANNERS.pptxthanga2 Sensors and scanners can be categorized based on their energy source and detection method. The key types are active sensors that emit their own energy and passive sensors that detect existing energy sources like sunlight. Sensors have various resolutions that determine their capabilities. Imaging sensors like multispectral scanners use arrays of detectors to capture images across spectral bands either along or across their flight path. Thermal sensors detect infrared radiation, while hyperspectral sensors provide continuous spectral signatures through hundreds of contiguous bands.
Digital image processing 1
Digital image processing 1Dhaval Jalalpara This document discusses remote sensing raster data formats and image processing. It introduces three common raster data formats: band sequential (BSQ), band interleaved by pixel (BIP), and band interleaved by line (BIL). It then provides examples and explanations of how data is organized for each format. The document also discusses image quality issues like clouds, noise, and describes common image processing techniques like radiometric and geometric correction, enhancement, and classification. Univariate and multivariate image statistics are introduced for analyzing remote sensing images.
Basics of Remote Sensing
Basics of Remote SensingAkash Tikhe Remote sensing involves obtaining information about objects without physical contact. It works by sensing and recording electromagnetic radiation reflected or emitted from targets. The key components are an energy source, sensor, platforms, and data analysis to extract information. Sensors can be optical, thermal, or microwave. Platforms include satellites, aircraft, and ground bases. Applications of remote sensing include agriculture, forestry, geology, hydrology, urban planning, and national security.
VISUAL IMAGE INTERPRETATION.pptx
VISUAL IMAGE INTERPRETATION.pptxSamirsinh Parmar RS & GIS, Image Interpretation, Methods of Image interpretation, Types of interpretation, Factors governing image interpretation, Activities to interpret image, Sensors, Role of sensors in Image derivation, Aerial Photography, LISS-3, Image characteristics, Special characteristics, Shadow, Texture, Pattern, associated features in images
Remote Sensing Platforms and Its types
Remote Sensing Platforms and Its typesSenthamizhan M Types of Platforms
1. Airbrone Platforms
2. Spacebrone Platforms
Platforms are Vital Role in remote sensing data acquisition
Necessary to correct the position the remote sensors that collect data from the objects of interest
Aerial photographs and their interpretation
Aerial photographs and their interpretationSumant Diwakar Aerial photographs provide valuable information about the coastal and terrestrial environment when interpreted correctly. Vertical aerial photographs can be used to update existing maps and create new maps. Simple instruments can be used to correct horizontal distortion in aerial photographs and transfer information to line maps. More advanced photogrammetric equipment is required to correct for height displacement. Stereoscopic analysis of overlapping aerial photographs allows for three-dimensional interpretation of terrain and features.
Functions of GIS
Functions of GISFayaz Ahamed A P GIS is a computer system that can assemble, store, manipulate, and display geographic data. It efficiently captures, stores, updates, analyzes and displays geographically referenced information through hardware, software, data and personnel. GIS allows for data capture through various methods, storage of data in both physical and digital forms, manipulation through editing attributes, and analysis to aid in decision making. It has advantages like easily analyzing locations, general purpose problem solving, and mapping. The scope of GIS includes using its functions to find locations of hospitals, schools, businesses, government offices and transportation hubs.
Visual Image Interpretation in Remote Sensing
Visual Image Interpretation in Remote Sensingvishwanathabhat This document discusses keys for visual image interpretation including tone, texture, pattern, size, shape, shadow, association, and site. Tone refers to the brightness or color of objects. Texture is the frequency of tonal variations. Pattern is the spatial arrangement of objects. Size is important for assessing objects relative to the scene and resolution. Shape is the most important factor for recognition. Shadow can help with interpretation but also cause difficulties. Association refers to how features relate to each other. Site refers to topographic location which is important when other elements don't clearly identify objects.
Principle of aerial photography and types.ppt
Principle of aerial photography and types.pptsrinivas2036 Principle of aerial photography and photogrammetry, types of aerial photographs, scale of aerial photograph.
Optical remote sensing
Optical remote sensingMohsin Siddique This document discusses different types of remote sensing systems used in civil engineering, including optical, photogrammetric, thermal, multispectral, hyperspectral, and panchromatic systems. It provides examples and specifications of various sensors, such as MODIS, AVIRIS, IKONOS, and WorldView. The document also covers digital image formats, photogrammetry, image distortions and displacements, reference ellipsoids, relief displacement, and methods of measuring heights from aerial photographs.
Introduction to GIS
Introduction to GISUday kumar Devalla 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 VECTOR Raster 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
Introduction to Landsat
Introduction to LandsatNizam GIS Landsat is a series of Earth observation satellite missions jointly managed by NASA and the U.S. Geological Survey. The first Landsat satellite was launched in 1972 and subsequent satellites were launched through 2013 to acquire global land data. Landsat satellites carry imaging sensors to collect medium-resolution multi-spectral images of the Earth's surface on a 16-day repeat cycle. The images are used to observe changes in land use, monitor deforestation, and detect water pollution among other applications. Six Landsat satellites have been launched to date, each carrying improved sensors from the Multi-Spectral Scanner to the Enhanced Thematic Mapper Plus. Landsat provides the longest continuous space-based record of Earth's surface.
Chapter 5: Remote sensing
Chapter 5: Remote sensingShankar Gangaju Analysis of remote sensing imagery involves identifying targets through their tone, shape, size, pattern, texture, and relationships to other objects. Targets may be environmental or artificial features appearing as points, lines, or areas. Interpretation relies on how radiation is reflected or emitted from targets and recorded by sensors to form images. The key to interpretation is recognizing targets based on these visual elements.
RADIOMETRIC RESOLUTION.pptx
RADIOMETRIC RESOLUTION.pptxKuki Boruah Radiometric resolution refers to a sensor's ability to distinguish slight differences in energy levels and is measured in bits. More bits allows an image to store more grayscale values, enabling better discrimination between classes. For example, Landsat-8 has 12-bit resolution, allowing it to distinguish over 4,000 grayscale levels and better characterize land cover compared to Landsat-7's 8-bit resolution of 256 levels. Higher radiometric resolution improves a sensor's sensitivity to capture subtle differences in surface reflectance.
Ad
More Related Content
What's hot (20)
Remote sensing - Sensors, Platforms and Satellite orbits
Remote sensing - Sensors, Platforms and Satellite orbitsAjay Singh Lodhi Remote sensing uses sensors on various platforms to detect electromagnetic radiation from the Earth. Sensors can be passive, detecting natural radiation, or active, emitting their own radiation. Platforms include ground-based, airborne, and space-based options at increasing heights. Space-based platforms include low Earth orbit satellites in polar or sun synchronous orbits for frequent coverage, and geostationary satellites for continuous coverage of fixed regions. Different sensors have varying spatial, spectral, radiometric, and temporal resolutions to detect features on Earth.
ppt spatial data
ppt spatial dataRahul Kumar This document discusses two types of spatial data used in GIS - vector data and raster data. Vector data represents geographic features as points, lines, and polygons using vertices with x, y, and z coordinates. It allows for accurate representation of shapes and storing of attribute data but requires more processing and storage. Raster data represents geographic information through a grid of cells (pixels), with each cell storing attribute values like elevation or temperature. It is better for continuously changing data but cannot represent linear features well and has increased storage needs at higher resolutions. Both data types have advantages and disadvantages depending on the use case.
Atmospheric windows
Atmospheric windowsSadia Rahat Certain wavelengths of light can penetrate the atmosphere better than others. These transparent regions are called "atmospheric windows". The figure shows that visible light and radio frequencies experience the least absorption as they travel through the atmosphere. These are the dominant windows. X-rays and UV light face strong absorption, while gamma rays and infrared see somewhat less absorption. Atmospheric windows may refer specifically to the radio, infrared, and visible portions of the electromagnetic spectrum.
Remote Sensing: Image Classification
Remote Sensing: Image ClassificationKamlesh Kumar The objective of image classification is to classify each pixel into only one class (crisp or hard classification) or to associate the pixel with many classes (fuzzy or soft classification). The classification techniques may be categorized either on the basis of training process (supervised and unsupervised) or on the basis of theoretical model (parametric and non-parametric).
Unsupervised classification is where the groupings of pixels with common characteristics are based on the software analysis of an image without the user providing sample classes. The computer uses techniques to determine which pixels are related and groups them into classes. The user can specify which algorism the software will use and the desired number of output classes but otherwise does not aid in the classification process. However, the user must have knowledge of the area being classified when the groupings of pixels with common characteristics produced by the computer have to be related to actual features on the ground (such as waterbodies, developed areas, forests, etc.).
Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these training sites as references for the classification of all other pixels in the image. Input classes are selected based on the knowledge of the user. The user also sets the bounds for how similar other pixels must be to group them together. These bounds are often set based on the spectral characteristics of the input classes (AOI), plus or minus a certain increment (often based on “brightness” or strength of reflection in specific spectral bands). The user also designates the number of classes that the image is classified into.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Thermal Remote Sensing
Thermal Remote SensingRohit Kumar This document provides an overview of thermal remote sensing. It begins with an introduction to remote sensing and defines thermal remote sensing as measuring electromagnetic radiation in the thermal infrared region. It describes the atmospheric windows and fundamental radiation laws governing thermal remote sensing. Applications discussed include surface temperature detection, fire detection, and volcano monitoring. The document concludes with the advantages of being able to detect true temperatures and limitations such as difficulty maintaining sensor temperatures.
Digital image processing
Digital image processingVandana Verma Digital image processing ,Techniques of Digital Image Processing
Image Enhancement ,Image Histogram,Spatial Filtering,Smoothing and Sharpening Examples,Image Classification,Supervised Classification,Unsupervised Classification
remote sensing applications.
IMAGE INTERPRETATION TECHNIQUES of survey
IMAGE INTERPRETATION TECHNIQUES of surveyKaran Patel Image interpretation is the process of examining an aerial photo or digital remote sensing image and manually identifying the features in that image. This method can be highly reliable and a wide variety of features can be identified, such as riparian vegetation type and condition, and anthropogenic features
Remote sensing
Remote sensingFidy Zegge The document discusses the four types of image resolution: spatial, spectral, radiometric, and temporal resolution. Spatial resolution refers to the ability of a sensor to identify the smallest details visible in an image. Spectral resolution is the sensor's ability to distinguish between narrow wavelength bands, while radiometric resolution refers to its ability to detect small differences in energy levels. Temporal resolution describes how frequently data is captured for a given location. Higher resolution in all four types provides more detailed, clear images for analysis.
SENSORS AND SCANNERS.pptx
SENSORS AND SCANNERS.pptxthanga2 Sensors and scanners can be categorized based on their energy source and detection method. The key types are active sensors that emit their own energy and passive sensors that detect existing energy sources like sunlight. Sensors have various resolutions that determine their capabilities. Imaging sensors like multispectral scanners use arrays of detectors to capture images across spectral bands either along or across their flight path. Thermal sensors detect infrared radiation, while hyperspectral sensors provide continuous spectral signatures through hundreds of contiguous bands.
Digital image processing 1
Digital image processing 1Dhaval Jalalpara This document discusses remote sensing raster data formats and image processing. It introduces three common raster data formats: band sequential (BSQ), band interleaved by pixel (BIP), and band interleaved by line (BIL). It then provides examples and explanations of how data is organized for each format. The document also discusses image quality issues like clouds, noise, and describes common image processing techniques like radiometric and geometric correction, enhancement, and classification. Univariate and multivariate image statistics are introduced for analyzing remote sensing images.
Basics of Remote Sensing
Basics of Remote SensingAkash Tikhe Remote sensing involves obtaining information about objects without physical contact. It works by sensing and recording electromagnetic radiation reflected or emitted from targets. The key components are an energy source, sensor, platforms, and data analysis to extract information. Sensors can be optical, thermal, or microwave. Platforms include satellites, aircraft, and ground bases. Applications of remote sensing include agriculture, forestry, geology, hydrology, urban planning, and national security.
VISUAL IMAGE INTERPRETATION.pptx
VISUAL IMAGE INTERPRETATION.pptxSamirsinh Parmar RS & GIS, Image Interpretation, Methods of Image interpretation, Types of interpretation, Factors governing image interpretation, Activities to interpret image, Sensors, Role of sensors in Image derivation, Aerial Photography, LISS-3, Image characteristics, Special characteristics, Shadow, Texture, Pattern, associated features in images
Remote Sensing Platforms and Its types
Remote Sensing Platforms and Its typesSenthamizhan M Types of Platforms
1. Airbrone Platforms
2. Spacebrone Platforms
Platforms are Vital Role in remote sensing data acquisition
Necessary to correct the position the remote sensors that collect data from the objects of interest
Aerial photographs and their interpretation
Aerial photographs and their interpretationSumant Diwakar Aerial photographs provide valuable information about the coastal and terrestrial environment when interpreted correctly. Vertical aerial photographs can be used to update existing maps and create new maps. Simple instruments can be used to correct horizontal distortion in aerial photographs and transfer information to line maps. More advanced photogrammetric equipment is required to correct for height displacement. Stereoscopic analysis of overlapping aerial photographs allows for three-dimensional interpretation of terrain and features.
Functions of GIS
Functions of GISFayaz Ahamed A P GIS is a computer system that can assemble, store, manipulate, and display geographic data. It efficiently captures, stores, updates, analyzes and displays geographically referenced information through hardware, software, data and personnel. GIS allows for data capture through various methods, storage of data in both physical and digital forms, manipulation through editing attributes, and analysis to aid in decision making. It has advantages like easily analyzing locations, general purpose problem solving, and mapping. The scope of GIS includes using its functions to find locations of hospitals, schools, businesses, government offices and transportation hubs.
Visual Image Interpretation in Remote Sensing
Visual Image Interpretation in Remote Sensingvishwanathabhat This document discusses keys for visual image interpretation including tone, texture, pattern, size, shape, shadow, association, and site. Tone refers to the brightness or color of objects. Texture is the frequency of tonal variations. Pattern is the spatial arrangement of objects. Size is important for assessing objects relative to the scene and resolution. Shape is the most important factor for recognition. Shadow can help with interpretation but also cause difficulties. Association refers to how features relate to each other. Site refers to topographic location which is important when other elements don't clearly identify objects.
Principle of aerial photography and types.ppt
Principle of aerial photography and types.pptsrinivas2036 Principle of aerial photography and photogrammetry, types of aerial photographs, scale of aerial photograph.
Optical remote sensing
Optical remote sensingMohsin Siddique This document discusses different types of remote sensing systems used in civil engineering, including optical, photogrammetric, thermal, multispectral, hyperspectral, and panchromatic systems. It provides examples and specifications of various sensors, such as MODIS, AVIRIS, IKONOS, and WorldView. The document also covers digital image formats, photogrammetry, image distortions and displacements, reference ellipsoids, relief displacement, and methods of measuring heights from aerial photographs.
Introduction to GIS
Introduction to GISUday kumar Devalla 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 VECTOR Raster 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
Introduction to Landsat
Introduction to LandsatNizam GIS Landsat is a series of Earth observation satellite missions jointly managed by NASA and the U.S. Geological Survey. The first Landsat satellite was launched in 1972 and subsequent satellites were launched through 2013 to acquire global land data. Landsat satellites carry imaging sensors to collect medium-resolution multi-spectral images of the Earth's surface on a 16-day repeat cycle. The images are used to observe changes in land use, monitor deforestation, and detect water pollution among other applications. Six Landsat satellites have been launched to date, each carrying improved sensors from the Multi-Spectral Scanner to the Enhanced Thematic Mapper Plus. Landsat provides the longest continuous space-based record of Earth's surface.
Similar to Resolution.pptx remote sensing resolution (20)
Chapter 5: Remote sensing
Chapter 5: Remote sensingShankar Gangaju Analysis of remote sensing imagery involves identifying targets through their tone, shape, size, pattern, texture, and relationships to other objects. Targets may be environmental or artificial features appearing as points, lines, or areas. Interpretation relies on how radiation is reflected or emitted from targets and recorded by sensors to form images. The key to interpretation is recognizing targets based on these visual elements.
RADIOMETRIC RESOLUTION.pptx
RADIOMETRIC RESOLUTION.pptxKuki Boruah Radiometric resolution refers to a sensor's ability to distinguish slight differences in energy levels and is measured in bits. More bits allows an image to store more grayscale values, enabling better discrimination between classes. For example, Landsat-8 has 12-bit resolution, allowing it to distinguish over 4,000 grayscale levels and better characterize land cover compared to Landsat-7's 8-bit resolution of 256 levels. Higher radiometric resolution improves a sensor's sensitivity to capture subtle differences in surface reflectance.
Resolution and scanning system
Resolution and scanning systemAglaia Connect Resolution and scanning system
high resolution scanning
scanning resolution for photos
high resolution scanning service
best resolution for scanning photos
best scanning resolution for documents
scanning resolution dpi
high resolution scanning near me
Remotely sensed satellite data comes in two basic types.docx
Remotely sensed satellite data comes in two basic types.docxFemiShittu1 Data types and sources in GIS
spatial resolutionin remote sensing
spatial resolutionin remote sensingGhassan Hadi Spatial resolution refers to the size of the smallest detectable feature in an image. Sensors on platforms farther from their targets can image larger areas but with less detail, while closer platforms provide higher resolution images over smaller areas. Spatial resolution depends on the sensor's instantaneous field of view and pixel size, which determines the area on the ground represented by each pixel. Images with larger pixels or that can only detect larger features are considered low resolution, while high resolution images can detect smaller objects.
MAPPING REMOTE PLANTS THROUGH REMOTE SENSING TECHNOLOGY AND GIS
MAPPING REMOTE PLANTS THROUGH REMOTE SENSING TECHNOLOGY AND GISInternational Journal of Technical Research & Application Remote sensing implies to the collection of data
about an object from a distance. With the use of LiDAR
remote sensing technology, the three dimensional
distribution of plant canopies and vegetation structural
attributes can be accurately estimated. The measure of
difference in reflectance from leaves of plants, due to the
presence of chlorophyll pigments in different ratios, can be
helpful to locate and characterize the plant remote
location through remote sensing technology and
Geographic Information System (GIS). The present study
highlights the importance of remote sensing technology and
GIS in detection of herbs located distantly.
Remote sensing
Remote sensingMohamed Salah The document provides an overview of remote sensing concepts through three lectures presented by Dr. Safaa Mohamed Hasan. The lectures cover definitions of remote sensing, sensor types, image characteristics, and resolutions including spatial, spectral, radiometric, and temporal resolutions. Geometric distortions and corrections through registration and resampling techniques are also discussed.
Remote Sensing: Meaning, Concept and Components | Geography
Remote Sensing: Meaning, Concept and Components | GeographySrimantaKarak This document provides an overview of remote sensing, including its definition, key concepts, components, and applications. In 3 sentences:
Remote sensing is defined as obtaining information about an object through analysis of data from a device not in contact with the object. It has major components including an energy source, sensors, platforms, and processing systems. Satellite remote sensing provides multispectral images that are utilized across various applications including land management, global change research, mapping, and more.
Remote sensing
Remote sensingNishant Chaturvedi The document discusses various topics related to satellite remote sensing including:
1. Types of sensors used in satellite remote sensing such as multispectral scanners, thematic mappers, high resolution visible imagers, linear imaging self-scanning cameras, panchromatic cameras, and wide field sensors.
2. Examples of sensors on specific satellite missions including MSS and TM on Landsat, HRV on SPOT, and LISS and PAN on IRS satellites.
3. Characteristics of different satellite data types and formats including imagery, digital data, and film and printed products.
The document provides an overview of the key components and technologies involved in satellite remote sensing.
Hyperspectral & Remote Sensing on Remote Sensing and GIS.pptx
Hyperspectral & Remote Sensing on Remote Sensing and GIS.pptxKabaliVasudevasu This document provides an overview of a presentation on hyperspectral analysis. It discusses hyperspectral imaging techniques, sensors, applications, and includes references. The presentation was given by 4 students - Nilotpal Lahkar, Navya Bharathi, Sai Bharathi, and Vamshi Palaparthi - at the National Institute of Technology in Warangal, India in 2024-2025. The document covers the working principles of hyperspectral imaging, advantages, differences between hyperspectral, multispectral and optical sensors, examples of hyperspectral sensors including airborne and spaceborne sensors, and applications of hyperspectral analysis.
Unit 1 introduction to remote sensing 
Unit 1 introduction to remote sensing Dhanalakshmi Dasari Remote sensing is the science of obtaining information about objects through analysis of sensor data without physical contact. Electromagnetic radiation is used for remote sensing and propagates as waves through the electromagnetic spectrum. Platforms for remote sensing include ground, aerial, and space-based sensors. Spaceborne sensors on satellites provide large area coverage at regular intervals. Common satellite sensors discussed are Cartosat, RISAT, MODIS, and ASTER.
rsbasics-150227022648-conversion-gate01.pptx
rsbasics-150227022648-conversion-gate01.pptxBSuresh26 Natural sensing uses electromagnetic radiation to obtain information about objects without physical contact. It involves sensing, analysis, and extracting knowledge. Remote sensing uses various sensors on different platforms to collect data across the electromagnetic spectrum. The key components are the target area, sensor, interpretation/analysis, energy source, atmosphere, and receivers. Sensors can be passive (depending on external energy) or active (with their own energy source) and operate on different platforms like ground, airborne, or spaceborne. The data has applications in agriculture, forestry, geology, hydrology, urban planning, and more.
Continuing chapter rs.pptx
Continuing chapter rs.pptxThomasHundasa1 This document discusses remote sensing platforms and sensors. It describes the three main categories of remote sensing platforms: ground-based, airborne, and satellite (space-borne). It provides details on each type of platform, including examples. The document also discusses remote sensing systems and their characteristics, focusing on spatial, spectral, temporal, and radiometric resolution. It provides information on imaging systems and scanning systems, such as whiskbroom and pushbroom scanning. Finally, it discusses Landsat satellites as an example of resource satellites.
1Resolutions of Remote Sensing1. Spatial (what area an.docx
1Resolutions of Remote Sensing1. Spatial (what area an.docxaulasnilda 1
Resolutions of Remote Sensing
1. Spatial (what area and how detailed)
2. Spectral (what colors – bands)
3. Temporal (time of day/season/year)
4. Radiometric (color depth)
Spatial Resolution describes how much
detail in a photographic image is visible to
the human eye.
The ability to "resolve," or separate, small
details is one way of describing what we
call spatial resolution.
2
Spatial resolution of images acquired by satellite sensor
systems is usually expressed in meters.
For example, we often speak of Landsat as having “30-
meter" resolution, which means that two objects, thirty
meters long or wide, sitting side by side, can be
separated (resolved) on a Landsat image.
Other sensors have lower or higher spatial resolutions.
Comparison of Landsat Sensors
Thematic Mapper
(TM) Landsat 4 and 5
Enhanced Thematic
Mapper Plus (ETM+)
Landsat 7
Multispectral
Scanner (MSS)
Landsat 1-5
Spectral
Resolution
(µm)
1. 0.45-0.52 (B)
2. 0.52-0.60 (G)
3. 0.63-0.69 (R)
4. 0.76-0.90 (NIR)
5. 1.55-1.75 (MIR)
6. 2.08-2.35 (MIR)
7. 10.4-12.5 (TIR)
1. 0.45-0.52
2. 0.53-0.61
3. 0.63-0.69
4. 0.78-0.90
5. 1.55-1.75
6. 2.09-2.35
7. 10.4-12.5
8. 0.52-0.90 (Pan)
0.5-0.6 (green)
0.6-0.7 (red)
0.7-0.8 (NIR)
0.8-1.1 (NIR)
Spatial
Resolution
(meter)
30 x 30
120 x 120 (TIR)
15 x 15 (Pan)
30 x 30
60 x 60 (TIR)
79 x 79
Temporal
Resolution
(revisit in days)
16 16 18
Spatial
coverage (km)
185 x 185 183 x 170 185 x 185
Altitude (km) 705 705 915 (Landsat 1,2,3)
3
Planimetric data – roads, buildings, driveways
Spatial Resolution
80 meter MSS w/ planimetric overlay
Spatial Resolution
4
30 meter TM w/ planimetric overlay
Spatial Resolution
10 meter SPOT w/ planimetric overlay
Spatial Resolution
5
1 meter DOQ w/ planimetric overlay
Spatial Resolution
Sub-meter data w/ planimetric overlay
Spatial Resolution
6
Looking More Closely at Resolution
Looking More Closely at Resolution
7
Landsat MSS
Satellite
80 Meter
Resolution Grid
Cell
Looking More Closely at Resolution
Landsat TM
Satellite
30 Meter
Resolution Grid
Cell
Looking More Closely at Resolution
8
SPOT Satellite 10 Meter
Resolution Grid Cell
Looking More Closely at Resolution
IKONOS Satellite
4 Meter Resolution
Grid Cell
Looking More Closely at Resolution
9
IKONOS Satellite
1 Meter Resolution
Grid Cell
Looking More Closely at Resolution
Landsat 7
185 by 170 km
30-m multispectral
Indian Remote
Sensing
145 by 145 km
25-m multispectral
SPOT
60 by 60 km
20-m multispectral
QuickBird 2
16 by 16 km
2.5-m multispectral
IKONOS
11 by 11 km
4-m multispectral
Selected Satellite Footprints
OrbView 3
8 by 8 km
4-m multispectral
1-m panchromatic10
10 100
10 100
10
Resolutions of Remote Sensing
1. Spatial (what area and how detailed)
2. Spectral (what colors – bands)
3. Temporal (time of day/season/year)
4. Radiometric (color depth)
The best spatial resolution?
11
1. ...
Remote Sensin
Remote Sensinguest7b3693 This document discusses remote sensing sensors and their characteristics. It describes how sensors are designed to record electromagnetic radiation and generate signals corresponding to energy variations of earth surface features. Imaging sensors convert EM radiation into numerical or image data. The document discusses different types of scanning sensors, including whisk broom and push broom, and covers various airborne sensors used by CIMSS including passive imagers and sounders, as well as active sensors like LIDAR.
REMOTE SENSING BASIC .......................................
REMOTE SENSING BASIC .......................................Dr. B. Sarkar, Dinhata College Remote Sensing
IRS Sattellite
IRS SattelliteParthaMandalbadraBis IRS-1A was the first Indian remote sensing satellite successfully launched on March 17, 1988. It carried two cameras, LISS-I and LISS-II, with spatial resolutions of 73m and 36.25m respectively. IRS-1B, the second satellite, was launched on August 29, 1991 with the same sensor characteristics as IRS-1A. Both satellites orbited at an altitude of 904km with sensors that operated in the visible and near-infrared bands. The key characteristics of the IRS satellite sensors that determine data quality are spatial, spectral, radiometric, and temporal resolution.
Surveying ii ajith sir class4
Surveying ii ajith sir class4SHAMJITH KM Remote sensing systems have four main types of resolution:
1. Spatial resolution determines the ability to detect fine spatial details like small objects. Higher resolution means smaller detectable objects.
2. Spectral resolution refers to the number and width of electromagnetic wavelength bands detected. Higher spectral resolution allows finer distinction between targets.
3. Radiometric resolution affects the ability to distinguish slight differences in radiation.
4. Temporal resolution is the frequency of data collection, usually days for satellites but can be more frequent depending on factors like swath overlap and latitude. Multi-temporal data is useful for observing changes over time.
High resolution data
High resolution dataPrem Chandra This document discusses remote sensing satellite imagery. It defines four types of resolution for satellite images: spatial, spectral, temporal, and radiometric. It provides examples of high resolution commercial satellites like GeoEye-1, WorldView-2, WorldView-3 and QuickBird. It describes how weather satellite images are received via HRPT transmissions. Applications of satellite imagery include meteorology, oceanography, agriculture and more. However, processing large satellite databases and obtaining images in cloudy conditions are challenges.
MAPPING REMOTE PLANTS THROUGH REMOTE SENSING TECHNOLOGY AND GIS
MAPPING REMOTE PLANTS THROUGH REMOTE SENSING TECHNOLOGY AND GISInternational Journal of Technical Research & Application
Ad
Recently uploaded (20)
Michelle Rumley & Mairéad Mooney, Boole Library, University College Cork. Tra...
Michelle Rumley & Mairéad Mooney, Boole Library, University College Cork. Tra...Library Association of Ireland
How to track Cost and Revenue using Analytic Accounts in odoo Accounting, App...
How to track Cost and Revenue using Analytic Accounts in odoo Accounting, App...Celine George Analytic accounts are used to track and manage financial transactions related to specific projects, departments, or business units. They provide detailed insights into costs and revenues at a granular level, independent of the main accounting system. This helps to better understand profitability, performance, and resource allocation, making it easier to make informed financial decisions and strategic planning.
Quality Contril Analysis of Containers.pdf
Quality Contril Analysis of Containers.pdfDr. Bindiya Chauhan Quality control test for containers, rubber closures and secondary packing materials.
To study the nervous system of insect.pptx
To study the nervous system of insect.pptxArshad Shaikh The *nervous system of insects* is a complex network of nerve cells (neurons) and supporting cells that process and transmit information. Here's an overview:
Structure
1. *Brain*: The insect brain is a complex structure that processes sensory information, controls behavior, and integrates information.
2. *Ventral nerve cord*: A chain of ganglia (nerve clusters) that runs along the insect's body, controlling movement and sensory processing.
3. *Peripheral nervous system*: Nerves that connect the central nervous system to sensory organs and muscles.
Functions
1. *Sensory processing*: Insects can detect and respond to various stimuli, such as light, sound, touch, taste, and smell.
2. *Motor control*: The nervous system controls movement, including walking, flying, and feeding.
3. *Behavioral responThe *nervous system of insects* is a complex network of nerve cells (neurons) and supporting cells that process and transmit information. Here's an overview:
Structure
1. *Brain*: The insect brain is a complex structure that processes sensory information, controls behavior, and integrates information.
2. *Ventral nerve cord*: A chain of ganglia (nerve clusters) that runs along the insect's body, controlling movement and sensory processing.
3. *Peripheral nervous system*: Nerves that connect the central nervous system to sensory organs and muscles.
Functions
1. *Sensory processing*: Insects can detect and respond to various stimuli, such as light, sound, touch, taste, and smell.
2. *Motor control*: The nervous system controls movement, including walking, flying, and feeding.
3. *Behavioral responses*: Insects can exhibit complex behaviors, such as mating, foraging, and social interactions.
Characteristics
1. *Decentralized*: Insect nervous systems have some autonomy in different body parts.
2. *Specialized*: Different parts of the nervous system are specialized for specific functions.
3. *Efficient*: Insect nervous systems are highly efficient, allowing for rapid processing and response to stimuli.
The insect nervous system is a remarkable example of evolutionary adaptation, enabling insects to thrive in diverse environments.
The insect nervous system is a remarkable example of evolutionary adaptation, enabling insects to thrive
Phoenix – A Collaborative Renewal of Children’s and Young People’s Services C...
Phoenix – A Collaborative Renewal of Children’s and Young People’s Services C...Library Association of Ireland
The ever evoilving world of science /7th class science curiosity /samyans aca...
The ever evoilving world of science /7th class science curiosity /samyans aca...Sandeep Swamy The Ever-Evolving World of
Science
Welcome to Grade 7 Science4not just a textbook with facts, but an invitation to
question, experiment, and explore the beautiful world we live in. From tiny cells
inside a leaf to the movement of celestial bodies, from household materials to
underground water flows, this journey will challenge your thinking and expand
your knowledge.
Notice something special about this book? The page numbers follow the playful
flight of a butterfly and a soaring paper plane! Just as these objects take flight,
learning soars when curiosity leads the way. Simple observations, like paper
planes, have inspired scientific explorations throughout history.
World war-1(Causes & impacts at a glance) PPT by Simanchala Sarab(BABed,sem-4...
World war-1(Causes & impacts at a glance) PPT by Simanchala Sarab(BABed,sem-4...larencebapu132 This is short and accurate description of World war-1 (1914-18)
It can give you the perfect factual conceptual clarity on the great war
Regards Simanchala Sarab
Student of BABed(ITEP, Secondary stage)in History at Guru Nanak Dev University Amritsar Punjab 🙏🙏
YSPH VMOC Special Report - Measles Outbreak Southwest US 4-30-2025.pptx
YSPH VMOC Special Report - Measles Outbreak Southwest US 4-30-2025.pptxYale School of Public Health - The Virtual Medical Operations Center (VMOC) A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 795 from Texas, New Mexico, Oklahoma, and Kansas. 95 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
How to Set warnings for invoicing specific customers in odoo
How to Set warnings for invoicing specific customers in odooCeline George Odoo 16 offers a powerful platform for managing sales documents and invoicing efficiently. One of its standout features is the ability to set warnings and block messages for specific customers during the invoicing process.
How to manage Multiple Warehouses for multiple floors in odoo point of sale
How to manage Multiple Warehouses for multiple floors in odoo point of saleCeline George The need for multiple warehouses and effective inventory management is crucial for companies aiming to optimize their operations, enhance customer satisfaction, and maintain a competitive edge.
YSPH VMOC Special Report - Measles Outbreak Southwest US 5-3-2025.pptx
YSPH VMOC Special Report - Measles Outbreak Southwest US 5-3-2025.pptxYale School of Public Health - The Virtual Medical Operations Center (VMOC) A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 817 from Texas, New Mexico, Oklahoma, and Kansas. 97 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
CURRENT CASE COUNT: 817 (As of 05/3/2025)
• Texas: 688 (+20)(62% of these cases are in Gaines County).
• New Mexico: 67 (+1 )(92.4% of the cases are from Eddy County)
• Oklahoma: 16 (+1)
• Kansas: 46 (32% of the cases are from Gray County)
HOSPITALIZATIONS: 97 (+2)
• Texas: 89 (+2) - This is 13.02% of all TX cases.
• New Mexico: 7 - This is 10.6% of all NM cases.
• Kansas: 1 - This is 2.7% of all KS cases.
DEATHS: 3
• Texas: 2 – This is 0.31% of all cases
• New Mexico: 1 – This is 1.54% of all cases
US NATIONAL CASE COUNT: 967 (Confirmed and suspected):
INTERNATIONAL SPREAD (As of 4/2/2025)
• Mexico – 865 (+58)
‒Chihuahua, Mexico: 844 (+58) cases, 3 hospitalizations, 1 fatality
• Canada: 1531 (+270) (This reflects Ontario's Outbreak, which began 11/24)
‒Ontario, Canada – 1243 (+223) cases, 84 hospitalizations.
• Europe: 6,814
How to Customize Your Financial Reports & Tax Reports With Odoo 17 Accounting
How to Customize Your Financial Reports & Tax Reports With Odoo 17 AccountingCeline George The Accounting module in Odoo 17 is a complete tool designed to manage all financial aspects of a business. Odoo offers a comprehensive set of tools for generating financial and tax reports, which are crucial for managing a company's finances and ensuring compliance with tax regulations.
Presentation on Tourism Product Development By Md Shaifullar Rabbi
Presentation on Tourism Product Development By Md Shaifullar RabbiMd Shaifullar Rabbi Presentation on Tourism Product Development By Md Shaifullar Rabbi, Assistant Manager- SABRE Bangladesh.
Marie Boran Special Collections Librarian Hardiman Library, University of Gal...
Marie Boran Special Collections Librarian Hardiman Library, University of Gal...Library Association of Ireland Phoenix – A Collaborative Renewal of Children’s and Young People’s Services Clare Doyle - Cork City Libraries
Geography Sem II Unit 1C Correlation of Geography with other school subjects
Geography Sem II Unit 1C Correlation of Geography with other school subjectsProfDrShaikhImran The correlation of school subjects refers to the interconnectedness and mutual reinforcement between different academic disciplines. This concept highlights how knowledge and skills in one subject can support, enhance, or overlap with learning in another. Recognizing these correlations helps in creating a more holistic and meaningful educational experience.
SCI BIZ TECH QUIZ (OPEN) PRELIMS XTASY 2025.pptx
SCI BIZ TECH QUIZ (OPEN) PRELIMS XTASY 2025.pptxRonisha Das SCI BIZ TECH QUIZ (OPEN) PRELIMS - XTASY 2025
Michelle Rumley & Mairéad Mooney, Boole Library, University College Cork. Tra...
Michelle Rumley & Mairéad Mooney, Boole Library, University College Cork. Tra...Library Association of Ireland
Phoenix – A Collaborative Renewal of Children’s and Young People’s Services C...
Phoenix – A Collaborative Renewal of Children’s and Young People’s Services C...Library Association of Ireland
YSPH VMOC Special Report - Measles Outbreak Southwest US 4-30-2025.pptx
YSPH VMOC Special Report - Measles Outbreak Southwest US 4-30-2025.pptxYale School of Public Health - The Virtual Medical Operations Center (VMOC)
YSPH VMOC Special Report - Measles Outbreak Southwest US 5-3-2025.pptx
YSPH VMOC Special Report - Measles Outbreak Southwest US 5-3-2025.pptxYale School of Public Health - The Virtual Medical Operations Center (VMOC)
Marie Boran Special Collections Librarian Hardiman Library, University of Gal...
Marie Boran Special Collections Librarian Hardiman Library, University of Gal...Library Association of Ireland
Ad
Resolution.pptx remote sensing resolution
- 1. Sensor Resolution Definition: Ability of a sensor to record and display fine details 4 types of sensor resolutions: 1. Spatial Resolution A measure of the smallest angular or linear separation between two objects that can be resolved by the sensor. It is the ability of the sensor to measure the size of the smallest possible feature that can be detected It is dependant of the IFOV of the sensor. IFOV is the angular cone of the sensor. Size of the area viewed is determined by multiplying the IFOV by flying height. Area seen on the ground is called resolution cell which is the maximum spatial resolution of the sensor For a feature to be detected, its size should be equal or larger than the resolution cell Finer the resolution, lesser the total ground area can be seen Finer the resolution, smaller the objects can be detected Military sensors have finer resolution as compared to commercial sensors
- 2. 2. Spectral Resolution Number and size of the specific wavelength intervals (bands) of the electromagnetic spectrum to which the sensor is sensitive Ability of a sensor to define the fine wavelengths intervals (bands) Finer the spectral resolution, narrower the wavelength ranges of a particular band Black and white films record only visible bands of the EM spectrum while color film also does same but can detect the colors of RGB so have higher spectral resolution compared to former one Multispectral and Hyperspectral sensors High spectral resolution helps in discrimination between different targets based on their spectral response in each of the narrow bands
- 3. 3. Radiometric Resolution Actual information content in an image. Radiometric resolution of an imaging system describes its ability to discriminate very slight differences in energy. Finer the radiometric resolution, more the sensitivity to detect small differences in reflected or emitted energy. imagery data are represented in positive digital numbers which depends on the number of bits used for coding numbers in binary format e.g. 2 bits, 4 bits, 32 bits, 64 bits. Each bit records an exponent of power 2. For example 8 bits mean 2 to the power 8 means 2x2x2x2x2x2x2x2=256 where 0 (Black) means low reflection, 255 (White) means high reflection) CartoSat 2 uses 10 bits coding
- 4. Temporal Resolution frequency of obtaining data over a given area It is related with the revisit period which is often in days (e.g. CartoSat 2 has 4 days revisit time and 14 with 14 orbits per day while CartoSat 3 has
- 5. The Saga of Indian Remote Sensing Satellite System • IRS-1A, the first of the series of indigenous state-of-art operating remote sensing satellites, was successfully launched into a polar sun-synchronous orbit on March 17, 1988 from the Soviet Cosmodrome at Baikonur. • The successful launch of IRS-1A was one of the proudest moments for the entire country, which depicted the maturity of satellite to address the various requirements for managing natural resources of the nation. Its LISS-I had a spatial resolution of 72.5 meters with a swath of 148 km on ground sensors, LISS-II A and LISS-II B, with spatial resolution of 36.25 meters each and mounted on the spacecraft in such a way to provide a composite swath of 146.98 km on ground. LISS-II had two separate imaging sensors • The IRS-1A satellite, with its LISS-I and LISS-II sensors quickly enabled India to map, monitor and manage its natural resources at coarse and medium spatial resolutions. The operational availability of data products to the user organisations further strengthened the operationalisation of remote sensing applications and management in the country.
- 6. • Starting with IRS-1A in 1988, ISRO has launched many operational remote sensing satellites. Today, India has one of the largest constellations of remote sensing satellites in operation. Currently, *thirteen* operational satellites are in Sun- synchronous orbit – RESOURCESAT-1, 2, 2A CARTOSAT-1, 2, 2A, 2B, RISAT-1 and 2, OCEANSAT-2, Megha-Tropiques, SARAL and SCATSAT-1, and *four* in Geostationary orbit- INSAT-3D, Kalpana & INSAT 3A, INSAT -3DR. • The data from these satellites are used for several applications covering agriculture, water resources, urban planning, rural development, mineral prospecting, environment, forestry, ocean resources and disaster management.