Lectures Remote Sensing Presented by Dr. Safaa Mohamed Hasan National Authority for Remote Sensing and Space Sciences (NARSS) E-mail; firstname.lastname@example.org
Who am I? Dr. Safaa Mohamed Hasan Ph.D of Remote sensing and GIS Head of image processing department Data Reception, Analysis and Receiving Station Affairs Division. National Authority for Remote Sensing and Space Sciences (NARSS)
Remote Sensing – A primer (three lectures)
conceptual framework for the course
What exactly is geographic information, and why is it important? What is special about it?
What is information generally, and how does it relate to data, evidence, knowledge and understanding?
What kinds of decisions make use of geographic information?
What is a geographic information system, and how would I know one if I saw one?
What is geographic information science, and how does it relate to the use of geographic information systems for scientific purposes?
How do scientists use GIS, and why do they find it helpful?
Using ARCGIS software to apply a practical project
In the broadest sense, remote sensing is the small or large-scale acquisition of information of an object or phenomenon, by the use of either recording or real-time sensing device's) that is not in physical or intimate contact with the object (such as by way of aircraft, spacecraft, satellite, or ship).
What is remote sensing?
A remote sensing instrument collects information about an object or phenomenon within the instantaneous-field-of-view (IFOV) of the sensor system without being in direct physical contact with it. The sensor is located on a suborbital or satellite platform.
Interaction Model Depicting the Relationships of the Mapping Sciences as they relate to Mathematics and Logic, and the Physical, Biological, and Social Sciences
RS as Source of information
Variety of sensors, techniques, image processing algorithms.
Up to date information.
More that human knowledge.
Capability of monitoring with time series of data (earth, environment).
The invisible becomes visible (inaccessible areas).
Person in photo is holding a sensor similar to the ones used on satellites. By recording a highly accurate spectral signature for this crop type using this hand-held spectrometer, scientists can then search for and extract this signature from satellite imagery and develop detailed maps of this crop type over very large areas.
AVHRR OLS MODIS MERIES SSM/I Seawinds SAR ASAR reflective Emissive Radiative Thermal Sensor Types The Electromagnetic Spectrum
Visible region (0.4-0.7 m)
Blue (0.4-0.5 m)
Green (0.5-0.6 m
Red (0.6-0.7 m)
Near-infrared region (0.7-1.3 m)
Middle-infrared (MIR, 1.3-3 m) or shortwave infrared (SWIR, 1.3-8 m) region
Thermal infrared region (8-14 m)
Microwave region (>1mm)
Wavelength,µm 0.4 0.5 0.6 0.7
Electromagnetic Wave Interaction/ Propagation through the Atmosphere
What happens to solar radiation as it passes through the atmosphere?
What happens to radiation as it reaches the earth?
Incident (I) Absorption (A) Transmission (T) Reflection (R) Specular or mirror reflection. where all (or almost all) of the energy is directed away from the surface in a single direction Diffuse reflection . the surface is rough and the energy is reflected almost uniformly in all directions Radiation - Target Interactions
1.5 Radiation - Target Interactions Leaves Interactions: A chemical compound in leaves called chlorophyll strongly absorbs radiation in the red and blue wavelengths but reflects green wavelengths Water Interactions: Longer wavelength visible and near infrared radiation is absorbed more by water than shorter visible wavelengths
Characteristics of Images An image refers to any pictorial representation, regardless of what wavelengths or remote sensing device has been used to detect and record the electromagnetic energy
Remote sensing is unobtrusive if the sensor passively records the EMR reflected or emitted by the object of interest. Passive remote sensing does not disturb the object or area of interest.
Remote sensing devices may be programmed to collect data systematically, such as within a 9 9 in. frame of vertical aerial photography. This systematic data collection can remove the sampling bias introduced in some in situ investigations.
Under controlled conditions, remote sensing can provide fundamental biophysical information, including x,y location, z elevation or depth, biomass, temperature, and moisture content.
Advantages of Remote Sensing
Remote sensing–derived information is now critical to the successful modeling of numerous natural (e.g., water-supply estimation; eutrophication studies; nonpoint source pollution) and cultural (e.g., land-use conversion at the urban fringe; water-demand estimation; population estimation) processes (Walsh et al., 1999; Stow et al., 2003).
Advantages of Remote Sensing
Active Sensor Passive Sensor Active and Passive ATMOSPHERE SURFACE Reflectance Emission Radiance
Spatial Resolution, Pixel Size, and Scale spatial resolution of the sensor and refers to the size of the smallest possible feature that can be detected. Instantaneous Field of View (IFOV). The IFOV is the angular cone of visibility of the sensor (A) and determines the area on the Earth's surface which is "seen" from a given altitude at one particular moment in time (B). Pixels which are the smallest units of an image. Scale = The distance on an image or map / actual ground distance.
Low spatial resolution High spatial resolution
Spectral Resolution Spectral resolution: the ability of a sensor to define fine wavelength intervals. Finer the spectral resolution narrower wavelength range for a particular band. Black and White film Coarse spectral resolution Color film fine spectral resolution Some material may not be easily distinguishable using broad wavelength. They would require comparison at much finer spectral resolution (hyperspectral sensors)
Advanced Very High Resolution Radiometer (AVHRR) Bandwidths
Spectral Bandwidths of SPOT and Landsat Sensor Systems
One byte = 8bit Byte: is the smallest stored units for users Bit: is the smallest stored units for computers If we have 11 bits digital values, should be stored on………byte on our computer If we have 6 bits digital values, What ranges on the gray level put in our computer
The sensor sensitivity to the magnitude of the electromagnetic energy
The finer the radiometric resolution of a sensor, the more sensitive it is to detecting small differences in reflected or emitted energy.
6 bits recorded data, 2 6 =64 digital values, ranging from 0 to 63. 8 bits recorded data, 2 8 =256 digital values available, ranging from 0 to 255 . (High Radiometric Resolution) 4 bits were used, then only 2 4 =16 values ranging from 0 to 15 would be available (low Radiometric Resolution)
High Radiometric Resolution Low Radiometric Resolution
The geometric distortions may be due to several factors, including:
Perspective of the sensor optics.
Motion of the scanning system.
Motion of the platform.
Platform altitude, attitude, and velocity.
curvature and rotation of the Earth.
The geometric registration process involves identifying the image coordinates (i.e. row, column) of several clearly discernible points, called ground control points (or GCPs), in the distorted image (A - A1 to A4), and matching them to their true positions in ground coordinates (e.g. latitude, longitude). 1- Image-to-map registration 2- Image-to-image registration
Geometric Registration Process G.R. process involves identifying the image coordinates (i.e. row, column) of several clearly discernible points, called ground control points (or GCPs), in the distorted image (A - A1 to A4), and matching them to their true positions in ground coordinates (e.g. latitude, longitude). The true ground coordinates are typically measured from a map (B - B1 to B4), either in paper or digital format.
Resampling is used to determine the digital values to place in the new pixel locations of the corrected output image. Resampling methods
Nearest neighbour resampling uses the digital value from the pixel in the original image which is nearest to the new pixel location in the corrected image
Bilinear interpolation resampling takes a weighted average of four pixels in the original image nearest to the new pixel location.
Cubic convolution resampling goes even further to calculate a distance weighted average of a block of sixteen pixels from the original image which surround the new output pixel location