This study examines the accuracy assessment of land use land cover classification using Google Earth in the case of Kilite Awulalo, Tigray State, Ethiopia for the year 2014. For this study, Landsat-8 OLI_TIRS image of 2014 was used and analyzed using Arc GIS 10.1. Supervised classification scheme was used to classify the images. Under land use and land cover categories Agriculture land, Settlement land, Grazing land, Forest land, Bush land, Water bodies and Bare/stony land were studied. After classification of land use land cover types, 100 Random Points were generated in Arc GIS and converting random points to KML in order to open in Google Earth. Each random point’s value verified from Google Earth for accuracy assessment. Google Earth model was used to measure of how many ground truth pixels are correctly classified. For this study, Free Google Earth which was Build in Date 10/7/2013 was used. The result shows that total (overall) accuracy of land use and land cover for 2014 is 82.00% and Kappa (K) is 77.02% which is acceptable in both accuracy total (overall) and Kappa accuracy.
Published in | American Journal of Environmental Protection (Volume 4, Issue 4) |
DOI | 10.11648/j.ajep.20150404.14 |
Page(s) | 193-198 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Accuracy Assessment, Google Earth, Kappa, Land Use Land Cover
[1] | Abineh Tilahun and I. Zubairul .2015. Use of Google Earth for Land Use mapping in the Case of Gish Abbay Sekela, West Gojjam, Amhara State, Ethiopia. International Journal of Society and Humanities (ISSN-2319-2070/VOL 6:1-6. |
[2] | Abubaker, H. M, Elhag A.M.H. and Salih, A.M. (2013). Accuracy Assessment of Land Use and Land Cover Classification (LU/LC) Case study of Shomadi area-Renk County-Upper Nile State, South Sudan. International Journal of Scientific and Research Publications, Volume 3, Issue 5. |
[3] | Canute Hyandye, Christina Geoffrey Mandara, John Safari. GIS and Logit Regression Model Applications in Land Use/Land Cover Change and Distribution in Usangu Catchment. American Journal of Remote Sensing.Vol. 3, No. 1, 2015, pp. 6-16. doi: 10.11648/j.ajrs.20150301.12. |
[4] | Congalton, R. G. 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment 37:35-46. |
[5] | Dash, P. (2005). Land Surface Temperature and Emissivity Retrieval from Satellite Measurements, Institut fur Meteorologie und Klimaforshung. |
[6] | David, P. (2008). Horizontal Positional Accuracy of Google Earth’s High Resolution Imagery Archive. Sensors 2008, 8, 7973-7981; DOI: 10.3390/s8127973. |
[7] | Fakeye, Attah Motunrayo, Aitsebaomo, Francis Omokekhai, Osadebe, Charles Chuka, Lamidi, Risikat Bukola, Okonufua, Endurance Omamoke. Digital Modeling of Land Use Changes in Some Parts of Eastern Nigeria. American Journal of Remote Sensing. Vol. 3, No. 3, 2015, pp. 37-42. doi: 10.11648/j.ajrs.20150303.11 |
[8] | Jensen, J. R. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective (Second edition). Prentice Hall, Inc., Upper Saddle River, New Jersey, USA. |
[9] | Nagi, Z. M, Ahmed G. and Hussam E. (2013). Positional Accuracy Testing of Google Earth. International Journal Of Multidisciplinary Sciences And Engineering, VOL. 4, NO. 6, JULY 2013. |
[10] | Roy, P.S. and Giriraj, A. 2008. Land Use and Land Cover Analysis in Indian Context. Journal of applied science, Vol. 8(8): 1346-1353. |
[11] | Shirkou, J. and Aliakbar, N. (2013). Comparison between Land Use/Land Cover Mapping Through Landsat and Google Earth Imagery. American-Eurasian J. Agric. & Environ. Sci., 13 (6): 763-768. |
[12] | Yadav, P., Kapoor, M. and Sarma, K. 2010. Land Use Land Cover Mapping, Change detection and conflict Analysis of Nagzira-Navegaon Corridor, Central India Using Geospatial Technology. International Journal of Remote Sensing and GIS, Vol. 1(2): 90-98. |
APA Style
Abineh Tilahun, Bogale Teferie. (2015). Accuracy Assessment of Land Use Land Cover Classification using Google Earth. American Journal of Environmental Protection, 4(4), 193-198. https://doi.org/10.11648/j.ajep.20150404.14
ACS Style
Abineh Tilahun; Bogale Teferie. Accuracy Assessment of Land Use Land Cover Classification using Google Earth. Am. J. Environ. Prot. 2015, 4(4), 193-198. doi: 10.11648/j.ajep.20150404.14
AMA Style
Abineh Tilahun, Bogale Teferie. Accuracy Assessment of Land Use Land Cover Classification using Google Earth. Am J Environ Prot. 2015;4(4):193-198. doi: 10.11648/j.ajep.20150404.14
@article{10.11648/j.ajep.20150404.14, author = {Abineh Tilahun and Bogale Teferie}, title = {Accuracy Assessment of Land Use Land Cover Classification using Google Earth}, journal = {American Journal of Environmental Protection}, volume = {4}, number = {4}, pages = {193-198}, doi = {10.11648/j.ajep.20150404.14}, url = {https://doi.org/10.11648/j.ajep.20150404.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajep.20150404.14}, abstract = {This study examines the accuracy assessment of land use land cover classification using Google Earth in the case of Kilite Awulalo, Tigray State, Ethiopia for the year 2014. For this study, Landsat-8 OLI_TIRS image of 2014 was used and analyzed using Arc GIS 10.1. Supervised classification scheme was used to classify the images. Under land use and land cover categories Agriculture land, Settlement land, Grazing land, Forest land, Bush land, Water bodies and Bare/stony land were studied. After classification of land use land cover types, 100 Random Points were generated in Arc GIS and converting random points to KML in order to open in Google Earth. Each random point’s value verified from Google Earth for accuracy assessment. Google Earth model was used to measure of how many ground truth pixels are correctly classified. For this study, Free Google Earth which was Build in Date 10/7/2013 was used. The result shows that total (overall) accuracy of land use and land cover for 2014 is 82.00% and Kappa (K) is 77.02% which is acceptable in both accuracy total (overall) and Kappa accuracy.}, year = {2015} }
TY - JOUR T1 - Accuracy Assessment of Land Use Land Cover Classification using Google Earth AU - Abineh Tilahun AU - Bogale Teferie Y1 - 2015/07/25 PY - 2015 N1 - https://doi.org/10.11648/j.ajep.20150404.14 DO - 10.11648/j.ajep.20150404.14 T2 - American Journal of Environmental Protection JF - American Journal of Environmental Protection JO - American Journal of Environmental Protection SP - 193 EP - 198 PB - Science Publishing Group SN - 2328-5699 UR - https://doi.org/10.11648/j.ajep.20150404.14 AB - This study examines the accuracy assessment of land use land cover classification using Google Earth in the case of Kilite Awulalo, Tigray State, Ethiopia for the year 2014. For this study, Landsat-8 OLI_TIRS image of 2014 was used and analyzed using Arc GIS 10.1. Supervised classification scheme was used to classify the images. Under land use and land cover categories Agriculture land, Settlement land, Grazing land, Forest land, Bush land, Water bodies and Bare/stony land were studied. After classification of land use land cover types, 100 Random Points were generated in Arc GIS and converting random points to KML in order to open in Google Earth. Each random point’s value verified from Google Earth for accuracy assessment. Google Earth model was used to measure of how many ground truth pixels are correctly classified. For this study, Free Google Earth which was Build in Date 10/7/2013 was used. The result shows that total (overall) accuracy of land use and land cover for 2014 is 82.00% and Kappa (K) is 77.02% which is acceptable in both accuracy total (overall) and Kappa accuracy. VL - 4 IS - 4 ER -