A review on change detection method and accuracy assessment for land use land cover
Küçük Resim Yok
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The assessment of land use land cover change is extremely important for understanding the relationship between humans and nature. The enormous changes at a regional scale and advancements in technology have encouraged researchers to gather more information. The remote sensing technology and GIS tools cooperatively have made it easier to monitor the changes in land use land cover (LULC) from past to present. This technology has unraveled the changes at the regional and global level and has also contributed tremendous benefits to the scientific community. A variety of change detection algorithms have been used in the history of remote sensing to detect changes at earth's surface and newer techniques are still in process. The data from remote sensing satellites are the primary sources that provide an opportunity to acquire information about LULC change in recent decades, which extensively use different algorithms according to the research needs. The selection of appropriate change detection method is highly recommended in every remote sensing project. This review paper begins with the traditional pre and post-classification change detection techniques related to LULC information at the regional level. Therefore, this paper evaluated the mostly used change detection method among all others to find remarkable results. Thus the review concludes the post-classification change detection method using maximum likelihood classifier (MLC) supervised classification is applicable in all cases. The comparative analysis was also performed in a selected region having multiple land features during review in which MLC results best in comparison to others. MLC is the most commonly used technique from the past till present that has achieved high accuracy in all regions comparatively to other techniques.
Açıklama
Anahtar Kelimeler
Remote sensing, Change detection, LULC change, Supervised classification, Unsupervised classification, Post-classification
Kaynak
Remote Sensing Applications-Society and Environment
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
22
