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Land use land cover change detection thesis writing

Land use land cover change detection thesis writing of the data

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LANDSAT-1 was the first satellite (EOS), to be launched in the world. It was launched in 1972 in UnitedStates. Its excellent ability to observe the earth far from space made it important for use in different remote sensing applications. Following LANDSAT-1, LANDSAT-2, 3, 4, 5, and 7(currently operated as a primary satellite) were launched.

IMAGE PROCESSING. These involves those operations that are normally required before the main analysis and extraction of information from the image and are grouped into two classes namely the radiometric and geometric corrections. Radiometric corrections include correcting the data for sensor irregularities and atmospheric noise, so that the data represent accurately the reflected radiation measured by the sensor.

Land use land cover change detection thesis writing UK registered

In geometric corrections variations in geometric distortions due to sensor-Earth conversion of the data (measured by the remote sensor) into real world coordinates on the Earth’s surface is carried out. Image processing helps in image preprocessing, enhancement, transformation, classification and analysis.

Classification helps in categorizing and organizing the information deduced from the images. Before going into proper classifying, it is necessary to carry out image enhancement, false colour composition (in different band) and contrast stretching, which helps inmaking the different features appear clearly thereby help greatly in making visual interpretation easy and clear to seeS and distinguish the images in false colour (band 4:3:2).

Classification of landcover is done through digital image classification by using the spectral information represented by the digital numbers in one or more spectral bands, and classify each pixel based on its spectral property and assigning class to the image.

In this analysis two approaches to image classification was used. The per- pixel unsupervised classification and object-oriented supervised classification.

These classification creates a thematic raster layer from remotely sensed image by allowing the software identify statistical pattern in the data without using any real ground data. (Lillesand et al. 2008).

In supervised classification requires that the analyst is familiar with the geographical area and the different surface cover types in that area.

Land use land cover change detection thesis writing We have

Which means the analyst is supervising the classification by categorizing the correct landcover with the correct associated pixel value.

The objects within range were classified using 3 criteria, the segmentation performance to delineate urban object, the classification method performance on the fuzzy logical concepts and capability to create hierarchical link of landcover/landuse classes

In change detection, Images from earlier years are compared to recent images, to tangibly measure the differences in the sizes and extents of the loss or reduction or in some cases increase in any landcover class. Data from a variety of sources are used to provide complementary information. In this analysis, landsat image of 1987 and that of 2006 was compared to deduce the different changes that have taken place within that time frame between the years.

ANALYSIS AND DISCUSSION.

From what we can see from the images in fig 8 and table 7, the green colour shows increasing about 10% or more while the Red colour shows decreasing of about 10% or more. We can see that the there is an increase in change in most of the landcover class with very little decrease (waterbody) observed. A lot of change has taken place as can be seen from the various images Urbanisation has the highest increase due to developmental changes because Abuja is Fast growing and developing. The vegetation is decreasing too and some of the rocky soil has reduced and some of the bare and rocky ground had some increased urban development.

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LANDSAT-1 was the first satellite (EOS), to be launched in the world. It was launched in 1972 in UnitedStates. Its excellent ability to observe the earth far from space made it important for use in different remote sensing applications. Following LANDSAT-1, LANDSAT-2, 3, 4, 5, and 7(currently operated as a primary satellite) were launched.

IMAGE PROCESSING. These involves those operations that are normally required before the main analysis and extraction of information from the image and are grouped into two classes namely the radiometric and geometric corrections. Radiometric corrections include correcting the data for sensor irregularities and atmospheric noise, so that the data represent accurately the reflected radiation measured by the sensor. In geometric corrections variations in geometric distortions due to sensor-Earth conversion of the data (measured by the remote sensor) into real world coordinates on the Earth’s surface is carried out. Image processing helps in image preprocessing, enhancement, transformation, classification and analysis.

Classification helps in categorizing and organizing the information deduced from the images. Before going into proper classifying, it is necessary to carry out image enhancement, false colour composition (in different band) and contrast stretching, which helps inmaking the different features appear clearly thereby help greatly in making visual interpretation easy and clear to seeS and distinguish the images in false colour (band 4:3:2).

Classification of landcover is done through digital image classification by using the spectral information represented by the digital numbers in one or more spectral bands, and classify each pixel based on its spectral property and assigning class to the image.

In this analysis two approaches to image classification was used. The per- pixel unsupervised classification and object-oriented supervised classification.

These classification creates a thematic raster layer from remotely sensed image by allowing the software identify statistical pattern in the data without using any real ground data. (Lillesand et al. 2008).

In supervised classification requires that the analyst is familiar with the geographical area and the different surface cover types in that area. Which means the analyst is supervising the classification by categorizing the correct landcover with the correct associated pixel value.

The objects within range were classified using 3 criteria, the segmentation performance to delineate urban object, the classification method performance on the fuzzy logical concepts and capability to create hierarchical link of landcover/landuse classes

In change detection, Images from earlier years are compared to recent images, to tangibly measure the differences in the sizes and extents of the loss or reduction or in some cases increase in any landcover class. Data from a variety of sources are used to provide complementary information. In this analysis, landsat image of 1987 and that of 2006 was compared to deduce the different changes that have taken place within that time frame between the years.

ANALYSIS AND DISCUSSION.

From what we can see from the images in fig 8 and table 7, the green colour shows increasing about 10% or more while the Red colour shows decreasing of about 10% or more. We can see that the there is an increase in change in most of the landcover class with very little decrease (waterbody) observed. A lot of change has taken place as can be seen from the various images Urbanisation has the highest increase due to developmental changes because Abuja is Fast growing and developing. The vegetation is decreasing too and some of the rocky soil has reduced and some of the bare and rocky ground had some increased urban development.

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