Abstract
Change detection is a technology ascertaining the changes ofspecific features within a certain time Interval. The use of remotelysensed image to detect changes in land use and land cover is widelypreferred over other conventional survey techniques because thismethod is very efficient for assessing the change or degrading trendsof a region. In this research two remotely sensed image of Baghdadcity gathered by landsat -7and landsat -8 ETM+ for two time period2000 and 2014 have been used to detect the most important changes.Registration and rectification the two original images are the firstpreprocessing steps was applied in this paper. Change detection usingNDVI subtractive has been computed, subtractive between the bandsof the two images and the ratio of the red to blue bands was alsocomputed. Change detection mask using minimum distanceclassification or detection after classification have be also used tocompute the changes between the resultant classes, many statisticalproperties of the original and process image have been illustrated inthis research
Highlights
The term of remote sensing can be defined as the science of deriving information about an object from measurements made at a distance from the object, i.e., without coming in contact with it [1]
There are many techniques have been used to detect the change in the land use and land cover such as building, vegetation, water, soil, roads
The increasing of vegetation areas between time 2000 and 2014 is not much because convert most of farms of Baghdad city to buildings, small increase in agricultural areas accompanied by a slight increase in expansion of water regions. image subtraction method such as bands subtraction and red to blue ratio subtraction reduces the probability of errors
Summary
The term of remote sensing can be defined as the science of deriving information about an object from measurements made at a distance from the object, i.e., without coming in contact with it [1]. Temporal mapping from satellite data has successfully demonstrated the utility of integrating existing historic maps with remotely sensed data and related geographic information to dynamically map land characteristics for large metropolitan areas These regional databases provide a strong visual portrayal of recognized growth patterns, and dramatically convey how the progress of modern development results in profound changes to the landscape [3]. Three to five seed points have been provide manually [5] This co-registration is very important process must be applied on the original images before starting change detection subtractive methods. The NDVI was used in numerous studies estimate vegetation biomass, primary production, dominant species [6] It is a method with the most extensive application that can be applied to a wide variety of types of images and geographical environments.
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