Open AccessSpatial-Temporal Analysis of Land Use and Land Cover Change Detection Using Remote Sensing and GIS Techniques
Author(s) -
Karar H. Fahad,
Samera Shams Hussein,
Hayder Dibs
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/671/1/012046
Subject(s) - wetland , urban sprawl , land use , land cover , remote sensing , vegetation (pathology) , change detection , geography , environmental science , physical geography , hydrology (agriculture) , ecology , geology , medicine , geotechnical engineering , pathology , biology
Remote sensing has become a central factor in approaches to managing natural resources and observing environmental fluctuations. Urban development has brought severe losses of farming land, vegetation land and water bodies. Urban sprawl is responsible for a variety of urban environmental issues including reduced air quality, increased local temperature and reduction in water quality. In this study, we have taken the city of Baghdad as a case study and explore the land use and land cover variation that took place over approximately 28 years from 1990 to 2018. Remote sensing practice was implemented to analyse the city of Baghdad’s land cover and land use changes throughout the study period. Landsat TM and OLI 8 images of Baghdad were collected from the USGS Earth Explorer website. Having pre-processed the image, we used supervised classification to categorize the images in different land cover classes. The study region was classified into five categories: urban area, water bodies, vegetative area, barren land and wetland. The accuracy assessment of classification we obtained was 85.11% and 88.14%. From these results, change detection analysis shows that urban area and soil land levels have gone up by 3% and 20%, respectively. In another area the vegetation has diminished, wetlands and water bodies have also decreased by 5%, 17%, and 1% respectively.