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Wednesday, December 5, 2012


NDVI


What is NDVI?
The Normalized Difference Vegetation Index (NDVI) has been in use for many years to measure and monitor plant growth (vigor), vegetation cover, and biomass production from multispectral satellite data. The NDVI image maps shown here are prepared from 1-km AVHRR spectral data in the visible (Channel 1; 0.58-0.68 micrometers) and near infrared (Channel 2; 0.725-1.10 micrometers) regions of the electromagnetic spectrum. NDVI is calculated as follows:
NDVI = (Channel 2 – Channel 1) / (Channel 2 + Channel 1)
The principle behind NDVI is that Channel 1 is in the red-light region of the electromagnetic spectrum where chlorophyll causes considerable absorption of incoming sunlight, whereas Channel 2 is in the near-infrared region of the spectrum where a plant’s spongy mesophyll leaf structure creates considerable reflectance (Tucker 1979Jackson et al.1983Tucker et al. 1991). As a result, vigorously growing healthy vegetation has low red-light reflectance and high near-infrared reflectance, and hence, high NDVI values. This relatively simply algorithm produces output values in the range of -1.0 to 1.0. Increasing positive NDVI values, shown in increasing shades of green on the images, indicate increasing amounts of green vegetation. NDVI values near zero and decreasing negative values indicate non-vegetated features such as barren surfaces (rock and soil) and water, snow, ice, and clouds.
– Source : USGS (United States Geological Survey)

Tuesday, December 4, 2012


Image Processing
Pre-image Processing: Prior to data analysis, initial processing on the raw data is usually carried out to correct for any distortion due to the characteristics of the imaging system and imaging conditions. Its depend on the user's. These procedures include radiometric correction and field of view of the sensor.

Image Enhancement: It used to visual interpretation and understanding of imagery. Attempted after image is corrected for distortions. Linear contrast enhancement, also referred to as a contrast stretching, linearly expands the original digital values of the remotely sensed data into a new distribution. By expanding the original input values of the image, the total range of sensitivity of the display device can be utilized.

Type of enhancement
RADIOMETRIC ENHANCEMENT  - Modification of brightness values of each pixel in an image data set independently (Point operations).
SPATIAL ENHANCEMENT - Modification of pixel values based on the values of surrounding pixels. (Local operations)
SPECTRAL ENHANCEMENT- Enhancing images by transforming the values of each pixel on a multiband basis

Linear contrast enhancement: Linearly expands the original digital values of the remotely sensed data into a new distribution. These types of enhancements are best applied to remotely sensed images with all the brightness values. A DN is assigned extreme black(0) extreme white(255). There are three methods of linear contrast enhancement:
               Minimum-Maximum Linear Contrast Stretch
               Percentage Linear Contrast Stretch
               Piecewise Linear Contrast Stretch

Linear contrast stretch
 Input and Output Data Values follow a linear relationship
             • Min – Max Stretch
             • % stretch
             • Std. deviation Stretch
             • Piecewise Linear Stretch
             • Saw tooth Stretch

Non Linear contrast enhancement; Input and output data values do not follow a linear relationship. It included Square, Exponential, Logarithmic, log. Input and Output Data Values do not follow a linear relationship
            • Logarithmic
            • Inverse Log
            • Exponential
            • Square
            • Square root 

What is Spatial Filtering;
It is a process of dividing the image into its constituent spatial frequencies to emphasize some image features. This technique increases the analyst ability to discriminate detail. Main purpose of this technique is to: enhance certain features, remove the noise in the image, smoothness of image.

Low pass filter:
      It eliminate high frequency components, while leaving low frequencies untouched. It enhance the block high frequency, Smoothening effect on images, Removal of noise, Blurring of image especially at edges.
Low pass filter type,
        Mean – Smoothen the image and blurring the edge
        Median- Retain sharpness and smoothening of image
        Mode – Replace by most common neighbor in the window

High pass filter;
       Removes slowly varying components and preserves high frequencies, Emphasizes fine details, Use for edge detection and enhancement. Edges and locations where transition from one category to other occurs. Edge detection and enhancement. 

NDV I- Normalized different vegetation index-
       Monitor vegetation condition on continental and global scales using the advanced very high resolution Radiometric. The range of -1.0 to 1.0 increasing positive NDVI values. It calculated as
NDVI=B4-B3/B4+B3

Types of scattering are ;
      1. Rayleigh scattering
      2. Mie scattering
      3. Nonselective scattering Rayleigh

scattering : occurs when particles are very small compared to the wavelength of the radiation. These could be particles such as small specks of dust or nitrogen and oxygen molecules. 

Mie scattering : occurs when the particles are just about the same size as the wavelength of the
radiation. Dust, pollen, smoke and water  vapors  are common causes of Mie scattering which
tends to affect longer wavelengths than those affected by  Rayleigh scattering.

Radiometric Correction- It included correcting the data for unwanted sensor or atmospheric noise and converting the data.

Geometric correction: Include correcting for geometric distortions due to sensor-Earth geometry variations, and conversion of the data to real world coordinates  on the Earth's surface.

Why Geometric correction;
•To allow an image to overlay a map.
•To warp an image to eliminate distortion. caused by terrain, instrument wobble, earth curvature, etc.
•To change the spatial resolution of an image.
•To change the map projection.
• Sources of distortions are-
• Variation in the altitude
• Altitude & Velocity of the sensor platform
• Earth curvature• Atmospheric refraction
• Relief displacement and
• Nonlinearities in the sweep of a sensor’s IFOV

Georeferencing; Conversion of the data to real world coordinates are carried by analyzing well distributed Ground Control Points (GCPs). This is done in two steps Georeferencing and Geocoding

Georeferencing : This involves the calculation of the appropriate transformation from image to terrain coordinates.

Geocoding :This step involves resembling the image to obtain a new image in which all pixels are correctly positioned within the terrain coordinate system. Georeferencing with additional resampling the image so that the pixels are exactly positioned within the map system. When Geocording images it involves resembling the image to obtain a new image in which all pixels are correctly positioned within the terrain coordinate system.

Coordinate system: File coordinate- Refer to the location of the pixels within the image file. This pixel value starting in upper left corner of the image 0,0

Map coordinates : Expressed in one of a number of map coordinate or projection system.

Color Composit; Singalband images are normally display from black(0) to white (255). Colour images display combination of 3 bands, red, green and blue.

R<G<B – colour

R      255       0       255
G          0    255         0
B      255       0       255
          R        G         B
In general three techniques are used :
– Natural color composite
– Pseudo natural color composite
– False color composite

Natural Color Composite
• For a Natural Color Composite one should use the spectral bands Blue, Green and Red and display them in Blue, Green and Red on a graphical screen.

R     G     B
3      2      1
R      G    B

Actually to get a true natural scene the spectral signature of the screen should be equal to the pectral signature of the satellite.
Red Green Blue
Red Green Blue

Pseudo natural color composite For a Pseudol Color Composite one should use the spectral bands Red,
NIR and Green and display them in Red, Green and Blue on a graphical screen.

R     NIR     G
3      4/5      2
R      G       B

False color composite  For a False Color Composite one should use the spectral bands NIR, Red and Green and display them in Red, Green and Blue on a graphical screen.

NIR   R      G
4       3       2
R      G       B

Band 1  -Blue
Band 2  -Green
Band 3 – Red
Band4- Near IR
Band 5 – Near IR
Band 6 – Thermai IR
Band 7 – Mid IR

NCC – 3,2,1
FCC – 4,3,2
PNCC – 3,4,2

Remote Sensing 

            Is the science of acquiring, processing and interpreting images that record the interaction between Electromagnetic energy & matter or RS is the science of acquiring information about the Earth's surface without actually being in contact with it.  Observed object size, shape and character without direct contact with them.

Process of Remote Sensing
Energy Source or Illumination - Illuminates or provides electromagnetic energy to the target of interest.
Radiation and the Atmosphere – The energy travels to target and it will come in contact with target to the sensor.
Interaction with the Target – Energy makes its way to the target through the atmosphere, it interacts with the target depending on the properties of both the target and the radiation.
Recording of Energy by the Sensor - after the energy emitted from the target, sensor to collect and record the EM radiation.
Transmission, Reception, and Processing – The energy transmitted from electronic form, to a receiving and processing station where the data are processed into an image.
Interpretation and Analysis – The processed image is interpreted, to extract information about the target which was illuminated.
Application – Apply the information we have been able to extract from the imagery about the target in order to better understand it.

Fields of Application
Meteorology    - Weather forecast,Climate Studies,Global Change
Hydrology       -Water balance,Energy balance,Agrohydrology
Soil Science    - Land evaluation,Soil Mapping
Biology/Nature Conservation-Vegetation mapping/monitoring,Vegetation condition assessment
Forestry         -Forest mapping,de-/re-forestation,forest fire detection
Environmental studies     -pollution,(Ground) water quality,Climate Change
Agriculture Engineering   -Landuse development,Erosion assessment,Water management
Physical Planning            -Physical Planning,Scenario studies
Land Surveying              -Topography (DTM),Spatial Data Models,GIS

Advantages of remote sensing
• Enables to observe a broad area at a time.
• Enables to observe the area for a long period.
• Enables us to know the condition without visiting the area.
• Enables us to know invisible information.

Type of RS: -
Visible and reflective IR RS- The sun reflectance: Optical energy Visible Reflectance, Near Infrared Reflectance, Thermal Infrared Thermal Radiation
(Drown the diagram- source – sensor)
Thermal RS – Object thermal radiation emissivity, temp: Optical energy Visible Reflectance, Near Infrared Reflectance, Thermal Infrared Thermal Radiation
(Drown the diagram – sensor)
Microwave RS – Microwave radiation/ radar backscatter coefficient: Object Microwave - Microwave Radiation.

Spatial Data Acquisition
Collection
Processing
Analysis

Need for spatial data
Urban planer
Engineer
Landuse planner

Data acquisition
- Ground based method (Surveying & mapping, Photogrammetric)
- Remote sensing methods (Field observation by performing land surveying)

Classification of Sensors
A sensor that measures and records electromagnetic energy. Sensors can be divided into two groups
– Passive Sensors: Depend on an external source like Sun, For all reflected energy, this can only take place during the time when the sun is illuminating the earth.
– Active Sensors: Active sensors have their own source of energy. Active sensors include the laser altimeter and radar.

Advantages for active sensors:
– The ability to obtain measurement anytime. Regardless of the time of the day, season or weather.
– Examine wavelengths that are not sufficiently provided by the Sun.
– To better control the way that a target is illuminated.

Platforms:
There are three types of flatforms in RS. These sensing is from 1m to 36,000km height.
- Ground based- Surveying & mapping, Photogrammetry, ground observation
– Airborne : Observations are carried out using aircraft with special modification to carry sensors. It is above 100m  to 40 km height. This system can collect information any time from the earth surface.
– Spaceborne : This is base on satellites system, Satellites are positioned in orbits between 150 – 36,000 km altitude. Due to repetitive coverage of the Earth surface on a continuing basis. 

Remote Sensing Platforms
Platform Altitude(km)
• Geostationary Sat. 36,000
• Earth Observation sat. 400 – 1000
• Space shuttle 240 – 350
• Airplane 0.3 – 7.5

Scanner
It is a one line, or row, in a raster scanning pattern, such as a line of video on a CRT display of a television. Raster data may need to be analyzed at the level of scan lines in order to convert between formats. This radiation level called digital numbers mulitispectral scanners(MSS), have range of 0.3 to 14um. Two type of scanners, pushbroom scanners- Along track scanners, Wishbroom scanners – Across track scanner.
pushbroom scanners- Linear array CCD,Each pixel has its own detector, recording one entire line at the time
Wishbroom scanners- Combination of singal detectors and rotating mirror across track scanner
Benefits med resolution sat in urban area
Scope :  Vass area maps can be prepared. Specially vegetation, soil map land use map, forestry maps etc.
Benefits: As this is law resolution images, the primary cost will be less. As there is not much data, we can reduce processing coast.

Swath-
When the satallte move around the earth in obrbit, it sees the portion of earth surface. This image referred as swath

Electromagnetic Radiation
Electromgnetic radiation consist with electrical field(E) and magnetic field(M). RS required energy source to illuminate the target. The two characteristics of EM radiation is wavelength and frequency. By measuring the energy that is reflected by targets on earth’s surface in different wavelengths. The pattern can be identify the pattern of different fatures. It is 10-11 to 108 wavelength. Microwave 10-2 ,Infrared 10-5, Visible 0.5 – 10-6,Ultraviolet 10-8

The visible spectrum
• The light which our eyes our "remote sensors“can detect.
• Note how small the visible portion is relative to the rest of the spectrum.
• The visible wavelengths cover a range from approximately 0.4 to 0.7µm.
Violet: 0.400 - 0.446 µm
Blue: 0.446 - 0.500 µm
Green: 0.500 - 0.578 µm
Yellow: 0.578 - 0.592 µm
Orange: 0.592 - 0.620 µm
Red: 0.620 - 0.700 µm

Infra red and Thermal IR:
Infra red portion; Covers the wavelength range from approximately 0.7 µm to 100 µm.Reflected IR region (0.7 µm to 3.0 µm) is used for remote sensing purposes in ways very similar to radiation in the visible portion.
Thermal IR; region (3.0 µm to 100 µm) is quite different than the visible and reflected IR portions, as this energy is essentially the radiation that is emitted from the Earth„s surface in the form of heat. From 1µm - 6µm mid range. From 6µm - 100µm far range. The mid range is reflective and the far range is emissive radiative thermal. From 1µm - 5µm covered short wave.

Visible(reflected) IR range : It is easy to separate vegetation and water boundaries as vegetation are reflected energy and the water is absorbing the energy. Not only vegetation and water but also dry soil, wet soil, clear water and turbid water, etc.

Thermal IR range : It is possible to take images (collect data or reflect energy) with sun or without sun. We can take visible or invisible images. This process is time irrespective.