The ERDAS IMAGINE Tour Guides manual is part of a whole suite of printed and on- ERDAS Spatial Modeler Language Reference Manual (only as ronaldweinland.info). Preface. About This Manual The ERDAS IMAGINE Essentials Tour Guides™ manual is a documents, digital hardcopy documents which are delivered as PDF. Three modules presented in this tutorial will guide users through the process of .. for an ERDAS IMAGINE file,.jpg for JPEG,.jp2 for JPEG ,.png for PNG.
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ERDAS Imagine is a frequently used software package within the Remote .. All three of these can be automatic or manual, in practice the manual option. Crop mapping using remote sensing data of Landsat 8: A Training Manual. . ERDAS Imagine is a powerful software package that is used (by remote sensing. 3 | ERDAS IMAGINE The world's most widely-used remote sensing software package. ERDAS IMAGINE. Geographic imaging professionals need to process.
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Ephemeris Data downloading instructions. Quick Plan: GPS Workshop Files: Download tutorial files for and from the GPS Workshops. Data Flow Diagrams. Obtaining Census Data from the Census web site. See also Notes on Bellingham and Whatcom Census numbering.
MrSID files: Converting to jpeg files downloadable program. Large-Format Printing at Huxley: Transferring Files on or off campus. Windows Explorer: Notes on using Windows Explorer to create, copy and move files and folders.
Working with Office GIS Tutorial Books online. GIS Links misc. Converting addresses to point locations GeoReferencing Raster Data notes: Both models are able to handle horizontally varying optical depths and contain a statistical haze removal algorithm.
The database covers terrain elevations from 0 to 2. The following parameters were explicitly taken into account: A database has been compiled for a wide range of typical atmospheric conditions.
The next section summarizes the scope of the database followed by a presentation of the correction algorithm. They account for the influence of atmospheric absorption and scattering. Both models utilize the small angle approximation. The main variable atmospheric parameters that affect the radiative transfer in the atmospheric window regions are water vapor content as well as the type of aerosol and the optical depth.
Different view and azimuth angles for tilt sensors. Interpolated atmospheric functions are provided for intermediate values of zenith angle. Aerosol types: The haze removal algorithm runs fully automatic.
ATCOR3 E dir. Based on the selected atmosphere water vapor content. The final equation has to be extended slightly to account for the directional dependence of the direct and diffuse solar radiation in a rugged terrain. The radiation components are written in a quasi-monochromatic form to stress the main physical contents.
E dif are ground-to-sensor transmittance. Details concerning the actual implementation with the weighting of the channel response function are given in Appendix B. The measured at-sensor radiance Lsat can be obtained from the recorded digital number DN and the calibration coefficients c0. Vsky and Vterrain are related by: Vsky x.
Hill et al.
It is preceded by a binary factor b. To assess the influence of the anisotropic diffuse sky radiance there is an option to calculate the isotropic case as well. Vterrain x. The horizon algorithm provides a more accurate value of the sky view factor by considering the terrain neighborhood of each pixel Dozier et al.
L p z elevation dependent path radiance. Sandmeier and Itten Factor b is also set to zero if shadow is cast from surrounding topography. Equation 3. It is a linear combination of the contribution of the circumsolar diffuse irradiance from the solid angle near the sun and an isotropic contribution for the remaining sky dome. For the simple trigonometric case one obtains Vsky x. This applies for the case of self-shadowing. E d z is the isotropic diffuse solar flux on a horizontal plane at elevation z.
The values for elevations beyond 2. Sky and terrain view factors. In case of horizontally constant atmospheric conditions a visibility in the 5. They are weighted with the corresponding spectral response function for each band. In case of horizontally varying atmospheric conditions.
These radiance and transmittance functions are stored in the database for the elevations 0. The diffuse solar flux E dif of equation 3. This equation has been extended to include the range-dependent exponential decrease of the adjacency effect: The exact relationship for the reflected radiance of equation 3. Kaufman and Sendra R is approximately 0. Richter a depending on the strength of the atmospheric scattering effect. As an example: The shaded region indicates a typical range of reflectance values.
Kimes There is a further difficulty: Figure 4 shows the bi-directional reflectance of coniferous forest in the near infrared nm. BRDF effects Many surface types exhibit anisotropic reflectance behavior. BRF measurements of tilted natural land surfaces are not available. For this extreme range.
The relationship is described by the bi-directional reflectance distribution function BRDF. There is a clear trend of increasing reflectance with rising angle of incidence. Kimes et al. These options are included for tilt sensors SPOT. The following set of empirical functions G serves to reduce the high reflectance values in regions of extreme geometry to get reflectance values closer to those of adjacent areas with moderate incident angles.
G ranges between a specified lower boundary g and 1. QuickBird etc. Figure 5 shows the course of G for options a and b. As an example. Bi-directional reflectance of coniferous forest. The second option provides more realistic terrain view factors. Geometric functions for empirical BRDF correction. Self-shadowing can be determined immediately from the solar geometry and the DEM. Figure 5. Radiance contributions from surrounding terrain such as reflected radiation from opposite slopes and valleys can be included term Vterrain in equation 3.
The shaded region indicates the range of incident angles encountered for the selected sample geometry nadir view. TM band 4 nm: Although the scattering efficiency strongly decreases with wavelength. The range-dependence of the adjacency effect usually is not a critical point as shown in the following examples. Long street running through a large vegetated field. Because of short path lengths of less than 0. For a midlatitude summer atmosphere with a rural aerosol and a visibility range of km the difference in retrieved lake reflectance for both cases including adjacency correction equation 12 with one region.
After adjacency correction the difference in reflectance between both cases 1 region versus 5 regions is also less than 0. Inland lake surrounded by vegetation. After adjacency correction the difference in reflectance between both cases 1 region versus 5 regions is less than 0. Thomas The range of the adjacency effect is also assumed to be 1 km. Coastal region. This option also reduces execution time and memory requirements.
Figure 6. Influence of the number of iterations on the average terrain reflectance. The graph presents the direct and diffuse solar flux for the sensor Landsat TM band 2 as a function of elevation. The top line represents the direct solar flux. To obtain a fast image processing algorithm. The extrapolation and interpolation errors are tolerable. Because of the linear behavior of these functions.
The database contains calculations for the elevation range 0 — 2. Mid-latitude summer atmosphere with a rural aerosol. The fluxes are displayed for two visibilities 10 km and 23 km assuming a rural aerosol.
A simple way to reduce overcorrected high reflectance values is to fix the terrain reflectance for each spectral band at a high level. Even though data may exist for some areas or will be generated in the future there will always be a trade-off with high costs of these data.
It would be desirable to have a spatial resolution of 0. Sometimes a cubic convolution resampling of the DEM to the pixel size of the image might be useful to minimize these effects. The last item is to some degree coupled to the DEM accuracy. The terrain contribution varies with the terrain view factor. If the DEM is coarser as the resolution of the imaging satellite sensor. For most areas of the world such high spatial resolution data are not available.
This method is computationally fast. Solid and dashed lines indicate required and optional processing steps. Instead a position-sensitive quick help for most of the fields is displayed in the usual IMAGINE-fashion in the bottom line of the window. This of course also depends on the height variation within the image or how steep ridges or prominent other topographic features are.
Several tests have proven that even with a bilinear resampling the spectral consistency is still maintained and valid reflectance images can be obtained.
The resolution of the used DEM plays an important role in the topographic and atmospheric correction. The satellite image to be topographically and atmospherically corrected in ATCOR3 should be orthorectified and georeferenced. The DEM needs to be georeferenced and does have to have at least some overlap for the area which is supposed to be corrected.
For a detailed discussion please refer to chapter 3. This option lets you calculate the Solar zenith degrees and the Solar azimuth degrees for your image. Time of Day must be entered in UTC. If there is a misalignment between the DEM and the image. Note that a resampling is necessary as well. The latter two can be extracted via the Sun Position Calculator by clicking on Calculate. Enter the input Elevation File and type in the Elevation Unit.
Pixel Size. See chapter 4. L Usually the ephemeris data of satellite images list the sun elevation. The result can automatically be pasted into the menu by clicking on Apply.
Zenith and Azimuth value.
Calculations will not work if angular units x. They are named automatically in the following convention: Value is flat no aspect. Data type is U1. For a detailed discussion on the resolution of the DEM refer to chapter 3. Data type is U L DEM prerequisites: The DEM needs to be georeferenced and does have to have at least overlap for the area which is supposed to be corrected.
On the following page examples of the original DEM and the 4 derivatives are shown. Data type is U8. Create a new ATCOR3 project will open a file chooser menu and let you define your new project file name. Open an existing ATCOR3 project will open a file chooser menu and let you select your existing project file.
Solar Zenith and Azimuth. Note that a resampling is necessary: First the Input Raster File must be specified. Several tests have proven that even with a bilinear resampling the spectral behavior is still maintained and valid reflectance images can be obtained. Acquisition Date: L Some sensors require specific entries: The same principle is used to encode the ground brightness temperature degree Celsius.
Terrain File Specifications: Further information on calibration files is available from this site. Sensor Tilt and Satellite Azimuth. Satellite Azimuth: For sensors with a tilting capability. With the option Calculate… the Sun-position Calculator is opened. All others are filled in automatically. The Visibility Estimate… function provides a visibility value for the selected aerosol type by checking dark scene pixels in the red band vegetation.
Practically speaking. L Visibility: The ability to distinguish a black object against a white background ground meteorological range. Also a visibility of ca 30km is usually a good starter. L When initially displayed To do this the Target Box Size has first to be set to 1 pixels. Range of Adjacency Effect m The adjacency effect is taken into account in the computation of the reflectance for the spectral graphs.
If the adjacency effect should be switched off the value has to be set to 0. To view these spectra the user selects "OK". Since these data are tailored to each sensor they can be displayed as reference plots in the ATCOR3 reflectance charts.
Spruces are large trees. The needles. L The Resampled Spectra option is the preferred option at the start of a project. The users are advised to build their own spectral libraries. Define Signature Select 3. The actual digital number DN or gray level imagery delivered by satellite data providers. In principle. Identify Target Pick 2. Confirm Calibration Accept With this selection the target can be selected. The band specific radiometric calibration values c0. As a starter the ATCOR calibration files contain values which are either pre-flight values or values which have been provided by the satellite data vendors.
Solve Calibration Solve 4. This can then be used during the following processing steps: Define Signature: The examples spectra are located in. Identify Target: Identified reference target e. Solve Calibration 4. Confirm Calibration If Yes is selected. Start identifying atmospheric conditions: Please refer for details to chapter 3.
Many surface types exhibit anisotropic reflectance behavior. Options 1 and 2: Most of the high spatial resolution sensors have view angles close to nadir. The correction report gives all information concerning the atmospheric correction.
The following data can be displayed with the Select Overlay: Also all the Options of Tab-1 and -2 within the ATCOR3 Main Menu which deal with setting the atmospheric condition at the time of the data take do not need to be elaborated in detail.
A Haze Removal is not possible as no bands for an estimation of the haze are available.
The effect of an atmospheric correction is -as no haze removal is done- some times not very much recognizable. This example is also available after installation on your PC where it is installed if chosen during installation in the this directory: It already contains all the necessary parameters. File name: Time of Acquisition: Atmosphere solar and thermal: Calibration file: B Subset.
L Negative reflectance values in the measured Spectra: If a sensor has selectable gain settings. On the other hand. Make sure not to use images which have been generated with Dynamic Range Adjustment DRA [automatic stretch to use the whole dynamic range] to enhance image interpretability.
This is an option when ordering an image from Space Imaging.
According to Eq The offset c0 values are set to 0. In some cases we have found that the above procedure does not lead to correct spectra. A reason for this is still unknown.
Currently the only alternative is to built your own individual calibration file. A procedure can be found in the paper on CalibrationFiles on the www. As 11bit data do not 'exist' they will be already in bit U16 , just the dynamic range is still the bit 2, levels while bit actually can provide 32, levels.
This value actually signifies the following: This value can be found within the Metadata as: Nominal Collection Azimuth. The line connecting the target point and the satellite's projection on the target point's horizon tangent plane and, 2. The e. This value can be found within the Metadata as "Nominal Collection Azimuth": The Nominal Collection Elevation is the angle between 1st the target point's horizon tangent plane and, 2nd the line connecting the target point with the satellite.
Nominal Collection Elevation Tilt Angle. The calibration values for the QuickBird Sensor: Value taken from Table 2. IMD File. L 86 Note: Water Resources Research. In Digital Airborne Spectrometer Experiment Air Force Research Laboratory. Remote Sensing.. Remote Sensing of Environment Geophysical Research. Solar Energy.. Digital Globe. Applied Optics Applied Meteorology. Geoscience Remote Sensing.. ReSe and RSL User Guide.. Canadian J.. It can be a useful complement to local detailed field campaign measurements.
The justification for the simple approach is that these heat fluxes depend on a number of micrometeorological parameters thermal properties of soil. The second group comprises quantities relevant for surface energy balance such as absorbed solar radiation flux. A simple model based on the SAVI vegetation index is employed to calculate the leaf area index and the heat flux into the ground. The first group of products include a vegetation index SAVI.
Ground Albedo Leaf Area Index The combination of this information with point-like local measurements of meteorological data is indispensable for applications in climatology. They are coded with 2 bytes per pixel bit: Leaf Area Index. The file containing the above mentioned layers is scaled with the following factors: This report describes some products that can be derived from atmospherically corrected imagery of optical sensors.
Layers 6 — 10 are included only if surface temperature data from a thermal band are available. This application is mainly intended to get the correct trends in multi-temporal studies. Baret and Guyot The range of SAVI is 0 — Choudhury Multitemporal comparisons: The employed LAI equation is an empirical 3-parameter approximation based on a vegetation index.
Since it is difficult to take into account the parameters for different agricultural fields and different seasons it is suggested to use a fixed 8 ATCOR VAP. A quantitative agreement with field measurements of different crop types in different seasons cannot be expected. The absorbed photosynthetically active radiation is called APAR. Wiegand et al. Then the absolute values of the derived LAI may not be correct. Concerning e. These terms are associated with the green phytomass and crop productivity.
Then use this set of parameters for all scenes. Equations 3.
The contribution of the 2. It is calculated as 2. Wavelength gap regions are supplemented with interpolation. The extrapolation to longer wavelengths is computed as: At least four bands in the blue. Extrapolation for the 0. In the current version of ATCOR a blue band is required and the described options without a blue band are not implemented.
The energy available to evaporate water from the surface LE is usually obtained as the residual to balance the net radiation with the dissipation terms. It may warm or cool the surface depending on whether the air is warmer or cooler than the surface. If the satellite imagery contains no thermal band s from which ground temperature can be derived. The numerical calculation of equation 4. The terms on the right hand side of equation 3. Convection to the atmosphere is called sensible heat flux H.
The amount of energy employed in photosynthesis in case of vegetated surfaces is usually small compared to the other terms. The net energy is dissipated by conduction into the ground G. With thermal bands a ground temperature or at least a ground brightness temperature image can be derived. For sensors with a single thermal band such as Landsat TM or ASTER an assumption has to be made about the surface emissivity to obtain the surface temperature.
For cloud-free conditions. Wolfe and Zissis The pressure is calculated as: T is the air temperature in Kelvin. Emissivities of various surfaces are documented in Buettner and Kern Water vapour partial pressure as a function of air temperature and humidity. Air emissivity as a function of water vapor partial pressure and air temperature.
Equation 4. If surface temperature data are not available. Carlson et al. See also chapter 4. The factor in equation 4. For applications where daily 24 h LE values are required the following equation can be used for the unit conversion: The bottom left graph contains the latent heat flux according to equations 4.
The top left graph shows the ground heat flux as a function of the SAVI computed with equation 4. In this case the latent heat LE calculated with equations 3. G and H are set to zero here. There is a problem in applying equations 3. For water surfaces the distribution of net radiation into G.
They represent instantaneous flux values. In case of mountainous terrain the air temperature Ta z 0 and water vapour partial pressure p wv z 0 at a reference elevation z 0 have to be specified. Spatial maps of air temperature equation 4.
These have to be interpolated to generate a spatial map co-registered to the image prior to applying the ATCOR model. The water vapor pressure is extrapolated exponentially according to: For PAN imagery. The button becomes active after the complete processing of the ATCOR atmospheric correction procedure.
For an discussion of the parameters refer to the theory section of this manual. The defaults usually can be used as a starter.
The respective examples of the two sections have been used: DLR Wessling.. Correction of satellite imagery over mountainous terrain. Correction of atmospheric and topographic effects for high spatial resolution satellite imagery..
A new look at the simplified method for remote sensing of daily evapotranspiration. A soil adjusted vegetation index SAVI. A spatially adaptive fast atmospheric correction algorithm..
Synergism of multispectral satellite observations for estimating regional land surface evaporation. On the computation of saturation vapor pressure.
The determination of infrared emissivities of terrestrial surfaces International Journal of Remote Sensing.. Multisite analyses of spectral-biophysical data for corn. DG XII. Theory and applications of optical remote sensing. DLR Wessling On a derivable formula for long-wave radiation from clear skies. Estimating absorbed photosynthetically active radiation and leaf area index from spectral reflectance in wheat.
International Journal of Remote Sensing. Relations between evaporation coefficients and vegetation indices studied by model simulations.. The Infrared Handbook. Vegetation indices in crop assessments. Resampling of Radiance Terms C. Satellite Sensors supported by ATCOR Presently the following sensors are supported or will be supported as soon as they are successfully launched and operated: The unit of bandpass-normalized radiances is the same as the unit of a spectral radiance..
In the same manner. The transmitted diffuse flux contribution is: Each user is encouraged to set these preferences for his operating environment. DTED files support a set of fixed resolutions i.
DTED levels which are defined as aligning on particular boundaries. The dialog consists of a DTED Options panel which allows the user to set up the DTED level and other options, a Gridding panel, and an Export Bounds panel which allows the user to set up the portion of the loaded data they wish to export. The dialog consists of a General options panel which allows the user to set up the grid spacing and vertical units, a Gridding panel, and an Export Bounds panel which allows the user to set up the portion of the loaded data they wish to export.
This option may be useful when used with other software packages that do not specify the DXF mesh format. ECW files are highly compressed and great for storing things like satellite imagery. There is no size restriction on exported ECW files, so you can store many terabytes worth of imagery within a single highly compressed ECW file. When selected, the command displays the ECW Export Options dialog which allows the user to setup the export.
The dialog consists of a General options panel which allows the user to set up the pixel spacing and target compression ration, a Gridding panel, and an Export Bounds panel which allows the user to set up the portion of the loaded data they wish to export. Export Erdas Imagine Command The Export Erdas Imagine command allows the user to export any loaded raster, vector,and elevation grid data sets to an Erdas Imagine file.
When selected, the command displays the Erdas Imagine Export Options dialog which allows the user to setup the export. The dialog consists of a General options panel which allows the user to set up the pixel spacing and format, a Gridding panel, and an Export Bounds panel which allows the user to set up the portion of the loaded data they wish to export.
In addition to the elevation data file, an ESRI-format. There is also an option to allow exporting slope values in degrees rather than elevation values at each sample location. When selected, the command displays the Geosoft Grid Export Options dialog which allows the user to setup the export. The dialog consists of a GeoTIFF Options panel, a Gridding panel, and an Export Bounds panel which allows the user to set up the portion of the loaded vector data they wish to export.
The Palette options described below will apply in this case. This option will generate a relatively small output file, at the expense of some color fidelity depending on the palette that you choose. The image data will be compressed using the PackBits compression algorithm. GeoTIFF images generated with this option will be at least 3 times the size of those generated with the 8-bit Palette option, but the colors in the image will exactly match what you see on the screen.
GeoTIFF images generated with this option will maintain good color fidelity and often be highly compressed, although they will lose some information as compared to the uncompressed bit RGB option. This will generate by far the smallest image, but if you source image had more than two colors the resulting image will be very poor.