Enviar búsqueda
Cargar
ERDAS IMAGINE
•
Descargar como PPTX, PDF
•
4 recomendaciones
•
1,724 vistas
Rahul Gawai
Seguir
Denunciar
Compartir
Denunciar
Compartir
1 de 67
Descargar ahora
Recomendados
Digital image classification By Aleemuddin Univ- Jamia MIllia Islamia Place- New Delhi- INDIA
Digital image classification
Digital image classification
Aleemuddin Abbasi
ERDAS IMAGINE
ERDAS IMAGINE
ERDAS IMAGINE
Eminent Planners
Image Classification in Remote Sensing
07 Image classification.pptx
07 Image classification.pptx
eshitaakter2
BASIC CONCEPTS OF PHOTOGRAMMETRY
BASIC CONCEPTS OF PHOTOGRAMMETRY
BASIC CONCEPTS OF PHOTOGRAMMETRY
Namitha M R
SPOT 7 Satellite
Spot 7 satellite
Spot 7 satellite
Nimra Butt
some basic information about digital image processing .
Digital image processing 1
Digital image processing 1
Dhaval Jalalpara
GIS
datum
datum
Riya Gupta
rs and gis
rs and gis
prem ranjan
Recomendados
Digital image classification By Aleemuddin Univ- Jamia MIllia Islamia Place- New Delhi- INDIA
Digital image classification
Digital image classification
Aleemuddin Abbasi
ERDAS IMAGINE
ERDAS IMAGINE
ERDAS IMAGINE
Eminent Planners
Image Classification in Remote Sensing
07 Image classification.pptx
07 Image classification.pptx
eshitaakter2
BASIC CONCEPTS OF PHOTOGRAMMETRY
BASIC CONCEPTS OF PHOTOGRAMMETRY
BASIC CONCEPTS OF PHOTOGRAMMETRY
Namitha M R
SPOT 7 Satellite
Spot 7 satellite
Spot 7 satellite
Nimra Butt
some basic information about digital image processing .
Digital image processing 1
Digital image processing 1
Dhaval Jalalpara
GIS
datum
datum
Riya Gupta
rs and gis
rs and gis
prem ranjan
for those interested in GIS field
Geographic coordinate system & map projection
Geographic coordinate system & map projection
vishalkedia119
Components of GIS
Components of GIS
Components of GIS
Calcutta University
Map Projections and Georeferencing
Gis georeference
Gis georeference
Shah Naseer
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
Introduction to GIS
Introduction to GIS
Uday kumar Devalla
An introduction to the basics of a GIS and remote sensing.
Intro to GIS and Remote Sensing
Intro to GIS and Remote Sensing
John Reiser
Thermal Infrared remote sensing
Thermal remote sensing
Thermal remote sensing
Sakthivel R
Distortion of an aerial photograph and different type of distortions.
Distortions and displacement on aerial photograph
Distortions and displacement on aerial photograph
chandan00781
SAR is a type of radar which works with antenna and receiver using radio waves which can create two dimension or three dimension of the objects . A synthetic-aperture radar is an imaging radar mounted on a moving platform. SAR gives high resolution data and works 24*7.
Synthetic aperture radar
Synthetic aperture radar
Cigi Cletus
Digital Elevation Model, Digital Terrain Model, Digital Surface Model.
DEM,DTM,DSM
DEM,DTM,DSM
BANKURA UNIVERSITY
photogrammetry
Digital photogrammetry
Digital photogrammetry
Juan José Machado Oviedo
This presentation can help you to quickly understand basics and concepts of Remote Sensing.
Basics of Remote Sensing
Basics of Remote Sensing
Akash Tikhe
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data. Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link. Finally, the georeferenced raster file can be exported for further usage. THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Remote Sensing: Georeferencing
Remote Sensing: Georeferencing
Kamlesh Kumar
Raster data model
Raster data model
Raster data model
Pramoda Raj
GIS
GIS - lecture-1.ppt
GIS - lecture-1.ppt
sapna kinattinkara
Remote Sensing Lec 10
Remote Sensing Lec 10
polylsgiedx
Essential for the primary learners of Geographical Information System (GIS)
Introduction to gis
Introduction to gis
Habibur Rahman
Aerial photography – Types of aerial cameras, Types of photographs, vertical, horizontal, oblique.
Photogrammetry-part 1
Photogrammetry-part 1
prasenjit bhowmick
photogrammetry
photogrammetry
photogrammetry
M L Harshavardhan
PPT discuss about GIS and its application in hydrology
Introduction and Application of GIS
Introduction and Application of GIS
Satish Taji
DTM
DTM
Abhiram Kanigolla
digitizing of a Raster using ERDAS software
Digitising using ERDAS software
Digitising using ERDAS software
Swetha A
Erdas Imagine 2011
Manual Erdas imagine 2011
Manual Erdas imagine 2011
Karina Jara
Más contenido relacionado
La actualidad más candente
for those interested in GIS field
Geographic coordinate system & map projection
Geographic coordinate system & map projection
vishalkedia119
Components of GIS
Components of GIS
Components of GIS
Calcutta University
Map Projections and Georeferencing
Gis georeference
Gis georeference
Shah Naseer
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
Introduction to GIS
Introduction to GIS
Uday kumar Devalla
An introduction to the basics of a GIS and remote sensing.
Intro to GIS and Remote Sensing
Intro to GIS and Remote Sensing
John Reiser
Thermal Infrared remote sensing
Thermal remote sensing
Thermal remote sensing
Sakthivel R
Distortion of an aerial photograph and different type of distortions.
Distortions and displacement on aerial photograph
Distortions and displacement on aerial photograph
chandan00781
SAR is a type of radar which works with antenna and receiver using radio waves which can create two dimension or three dimension of the objects . A synthetic-aperture radar is an imaging radar mounted on a moving platform. SAR gives high resolution data and works 24*7.
Synthetic aperture radar
Synthetic aperture radar
Cigi Cletus
Digital Elevation Model, Digital Terrain Model, Digital Surface Model.
DEM,DTM,DSM
DEM,DTM,DSM
BANKURA UNIVERSITY
photogrammetry
Digital photogrammetry
Digital photogrammetry
Juan José Machado Oviedo
This presentation can help you to quickly understand basics and concepts of Remote Sensing.
Basics of Remote Sensing
Basics of Remote Sensing
Akash Tikhe
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data. Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link. Finally, the georeferenced raster file can be exported for further usage. THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Remote Sensing: Georeferencing
Remote Sensing: Georeferencing
Kamlesh Kumar
Raster data model
Raster data model
Raster data model
Pramoda Raj
GIS
GIS - lecture-1.ppt
GIS - lecture-1.ppt
sapna kinattinkara
Remote Sensing Lec 10
Remote Sensing Lec 10
polylsgiedx
Essential for the primary learners of Geographical Information System (GIS)
Introduction to gis
Introduction to gis
Habibur Rahman
Aerial photography – Types of aerial cameras, Types of photographs, vertical, horizontal, oblique.
Photogrammetry-part 1
Photogrammetry-part 1
prasenjit bhowmick
photogrammetry
photogrammetry
photogrammetry
M L Harshavardhan
PPT discuss about GIS and its application in hydrology
Introduction and Application of GIS
Introduction and Application of GIS
Satish Taji
DTM
DTM
Abhiram Kanigolla
La actualidad más candente
(20)
Geographic coordinate system & map projection
Geographic coordinate system & map projection
Components of GIS
Components of GIS
Gis georeference
Gis georeference
Introduction to GIS
Introduction to GIS
Intro to GIS and Remote Sensing
Intro to GIS and Remote Sensing
Thermal remote sensing
Thermal remote sensing
Distortions and displacement on aerial photograph
Distortions and displacement on aerial photograph
Synthetic aperture radar
Synthetic aperture radar
DEM,DTM,DSM
DEM,DTM,DSM
Digital photogrammetry
Digital photogrammetry
Basics of Remote Sensing
Basics of Remote Sensing
Remote Sensing: Georeferencing
Remote Sensing: Georeferencing
Raster data model
Raster data model
GIS - lecture-1.ppt
GIS - lecture-1.ppt
Remote Sensing Lec 10
Remote Sensing Lec 10
Introduction to gis
Introduction to gis
Photogrammetry-part 1
Photogrammetry-part 1
photogrammetry
photogrammetry
Introduction and Application of GIS
Introduction and Application of GIS
DTM
DTM
Destacado
digitizing of a Raster using ERDAS software
Digitising using ERDAS software
Digitising using ERDAS software
Swetha A
Erdas Imagine 2011
Manual Erdas imagine 2011
Manual Erdas imagine 2011
Karina Jara
PCA
Steps for Principal Component Analysis (pca) using ERDAS software
Steps for Principal Component Analysis (pca) using ERDAS software
Swetha A
Georeferencing using ERDAS software
Map to Image Georeferencing using ERDAS software
Map to Image Georeferencing using ERDAS software
Swetha A
Manual de fotogrametria
Manual para realización un proyecto fotogramétrico con erdas imagine 2014.
Manual para realización un proyecto fotogramétrico con erdas imagine 2014.
Julio Cesar Hernandez Cárdenas
Ocean GIS Initiative
Ocean GIS Initiative
Esri
Geospatial World Tour 2014: Energy Conference. Milano, 27 maggio 2014. Le soluzioni Geospaziali per il mondo energy Simone Colla, Hexagon Geospatial
GWT 2014: Energy Conference - 02 Le soluzioni Geospaziali per il mondo energy
GWT 2014: Energy Conference - 02 Le soluzioni Geospaziali per il mondo energy
Planetek Italia Srl
erdas
Manual erdas web
Manual erdas web
jhess gutierrez quenta
Presentation by David McChesney of ESRI CANADA on its Community Maps Program. Delivered at the Water and Environmental Hub track of the 2011 Cybera Summit.
ESRI Canada Community Maps Program
ESRI Canada Community Maps Program
Cybera Inc.
Pollmaps - 2011 Esri UC Presentation
Pollmaps - 2011 Esri UC Presentation
Alex Yule
Sample of rapid GEOINT update using Geospatial Enterprise Services from many vendors - Intergraph, ERDAS, CubeWerx
Rapid GEOINT Update
Rapid GEOINT Update
Carbon Project
NACIS 2012 presentation by Mamata Akella
Building a US National Park Service Online Basemap
Building a US National Park Service Online Basemap
akellam
"3D Printing - 3D Mapping". Lecture at Aristotelian University of Thessalonik...
"3D Printing - 3D Mapping". Lecture at Aristotelian University of Thessalonik...
Charalampos Paraschou
Presented at RSPSoc 2012 Annual Conference, University of Greenwich, London
An Academic SDI: Introducing the Enhanced Kaia Geoportal & Learning Zone
An Academic SDI: Introducing the Enhanced Kaia Geoportal & Learning Zone
Gail Millin-Chalabi
KLIP Digitaal is van start gegaan op 1 april 2015 en wordt verplicht vanaf 1 januari 2016. De GIM KLIP Oplossingen helpen u om tijdig uw data klaar te stomen en uw planafhandelingen te verzekeren.
Gim klip saas-avril2015
Gim klip saas-avril2015
GimKLIP
Algorithmic thinking and digital fabrication
Algorithmic thinking and digital fabrication
harshit2013
Il telerilevamento da droni aerei: normativa, elaborazione dei dati e casi applicativi. Seminario on-line: Martedì 27 gennaio 2015 Intervento Panoramica delle soluzioni Leica Geosystems e casi applicativi tramite l’uso della piattaforma AIBOTIX (Marco Labate, Leica Geosystems) Per dettagli sull'evento e per rivedere la registrazione video: http://www.planetek.it/formazione/webinar/webinar_il_telerilevamento_da_droni_aerei_normativa_elaborazione_dei_dati_e_casi_applicativi
[Webinar] Il telerilevamento da droni aerei: soluzioni Leica Geosystems e cas...
[Webinar] Il telerilevamento da droni aerei: soluzioni Leica Geosystems e cas...
Planetek Italia Srl
It’s surprisingly straightforward to migrate feature code from the CPU to the DSP – and determine the resulting benefits to the end application. In this session we’ll demonstrate Qualcomm® Hexagon™ SDK installation, code generation, profiling and execution of dynamic code modules on a Qualcomm® Snapdragon™ hardware target, and you’ll learn how to analyze the resulting performance benefits. Qualcomm Snapdragon and Qualcomm Hexagon are products of Qualcomm Technologies, Inc. Learn more about Hexagon SDK: https://developer.qualcomm.com/hexagon Watch this presentation on YouTube: https://www.youtube.com/watch?v=x6mKEWLzJM0
Qualcomm Hexagon SDK: Optimize Your Multimedia Solutions
Qualcomm Hexagon SDK: Optimize Your Multimedia Solutions
Qualcomm Developer Network
World’s Fastest Image Serving Technology
World’s Fastest Image Serving Technology
Siyathokoza Ngcobo
Introduction of GAMS Software
Introduction of GAMS Software
Saeid Abbasi Parizi
Destacado
(20)
Digitising using ERDAS software
Digitising using ERDAS software
Manual Erdas imagine 2011
Manual Erdas imagine 2011
Steps for Principal Component Analysis (pca) using ERDAS software
Steps for Principal Component Analysis (pca) using ERDAS software
Map to Image Georeferencing using ERDAS software
Map to Image Georeferencing using ERDAS software
Manual para realización un proyecto fotogramétrico con erdas imagine 2014.
Manual para realización un proyecto fotogramétrico con erdas imagine 2014.
Ocean GIS Initiative
Ocean GIS Initiative
GWT 2014: Energy Conference - 02 Le soluzioni Geospaziali per il mondo energy
GWT 2014: Energy Conference - 02 Le soluzioni Geospaziali per il mondo energy
Manual erdas web
Manual erdas web
ESRI Canada Community Maps Program
ESRI Canada Community Maps Program
Pollmaps - 2011 Esri UC Presentation
Pollmaps - 2011 Esri UC Presentation
Rapid GEOINT Update
Rapid GEOINT Update
Building a US National Park Service Online Basemap
Building a US National Park Service Online Basemap
"3D Printing - 3D Mapping". Lecture at Aristotelian University of Thessalonik...
"3D Printing - 3D Mapping". Lecture at Aristotelian University of Thessalonik...
An Academic SDI: Introducing the Enhanced Kaia Geoportal & Learning Zone
An Academic SDI: Introducing the Enhanced Kaia Geoportal & Learning Zone
Gim klip saas-avril2015
Gim klip saas-avril2015
Algorithmic thinking and digital fabrication
Algorithmic thinking and digital fabrication
[Webinar] Il telerilevamento da droni aerei: soluzioni Leica Geosystems e cas...
[Webinar] Il telerilevamento da droni aerei: soluzioni Leica Geosystems e cas...
Qualcomm Hexagon SDK: Optimize Your Multimedia Solutions
Qualcomm Hexagon SDK: Optimize Your Multimedia Solutions
World’s Fastest Image Serving Technology
World’s Fastest Image Serving Technology
Introduction of GAMS Software
Introduction of GAMS Software
ERDAS IMAGINE
1.
ERDAS IMAGINE Presented by Nahid
Alavi PRESENTATION -ON Guide By Prof.Ramesh Nanaware & Prof.Nitin Jadhav
2.
Contents 1] Layer stack 2]
Model Maker 3] Georeferencing 4] Reproject Image 5] Image Enhancement
3.
Contents 1] Layer stack 2]
Model Maker 3] Georeferencing 4] Reproject Image
4.
Layer stacking in
ERDAS
5.
Add First Band
6.
Add 4 Band
one by one
7.
8.
9.
After Layer stacking Image
10.
Layer Stack Using
Model Maker
11.
12.
Input
13.
Add Band 1
14.
15.
Add +1
16.
Temporary Raster Only
17.
Data Generation
18.
Output
19.
Georeferencing In ERDAS
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
RMS Error <1OUTPUT
30.
31.
32.
OUTPUT TOPOSHEET
33.
ReProject Image
34.
35.
36.
37.
38.
Spatial Enhancement
39.
Convolution-3*3 Low Pass
Filter
40.
41.
Before After
42.
Before After
43.
3*3 High Pass
Filter
44.
Before After
45.
AfterBefore
46.
Before After
47.
5*5 Vertical Kernel
48.
Before After
49.
AfterBefore
50.
5*5 Horizontal Kernel
51.
52.
Before After
53.
AfterBefore
54.
Before After
55.
AfterBefore
56.
Radiometric Enhancement
57.
Histogram Equalization
58.
59.
Before After
60.
AfterBefore
61.
Brightness Inversion
62.
Before After
63.
Haze Reduction
64.
Before After
65.
AfterBefore
66.
Before After
67.
AfterBefore
Descargar ahora