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 Googl...
This contribution was double-blind reviewed as extended abstract. Across the globe, accurate nationa...
In the present context of rapid change which is occurring either due to the natural or artificial ph...
Land cover information is the data neede in the management of watersheds. Identification to obtain l...
Diploma thesis deals with the land cover classification in Sidama region of Ethiopia and 2 kebeles, ...
Regions with high tourism density are very sensitive to human activities. Ensuring sustainability by...
This study examines the application of GIS and Remote Sensing in mapping Land Use and Land Cover cha...
Google Earth (GE) releases free images in high spatial resolution that may provide some potential fo...
In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferat...
Google Earth is a source of high spatial resolution images. The freely available Google Earth (GE) i...
This bachelor thesis is focused on the comparison of Random Forest (RF) and CART classifiers on the ...
Land use land cover (LULC) change analysis emerged as one of the most significant factors which assi...
Across the globe, accurate national spatial datasets on cropland extent are lacking. These are neces...
Across the globe, accurate national spatial datasets on cropland extent are lacking. These are neces...
The growing human population accelerates alterations in land use and land cover (LULC) over time, pu...
Land use planners require up-to-date and spatially accurate time series land resources information a...
This contribution was double-blind reviewed as extended abstract. Across the globe, accurate nationa...
In the present context of rapid change which is occurring either due to the natural or artificial ph...
Land cover information is the data neede in the management of watersheds. Identification to obtain l...
Diploma thesis deals with the land cover classification in Sidama region of Ethiopia and 2 kebeles, ...
Regions with high tourism density are very sensitive to human activities. Ensuring sustainability by...
This study examines the application of GIS and Remote Sensing in mapping Land Use and Land Cover cha...
Google Earth (GE) releases free images in high spatial resolution that may provide some potential fo...
In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferat...
Google Earth is a source of high spatial resolution images. The freely available Google Earth (GE) i...
This bachelor thesis is focused on the comparison of Random Forest (RF) and CART classifiers on the ...
Land use land cover (LULC) change analysis emerged as one of the most significant factors which assi...
Across the globe, accurate national spatial datasets on cropland extent are lacking. These are neces...
Across the globe, accurate national spatial datasets on cropland extent are lacking. These are neces...
The growing human population accelerates alterations in land use and land cover (LULC) over time, pu...
Land use planners require up-to-date and spatially accurate time series land resources information a...
This contribution was double-blind reviewed as extended abstract. Across the globe, accurate nationa...
In the present context of rapid change which is occurring either due to the natural or artificial ph...
Land cover information is the data neede in the management of watersheds. Identification to obtain l...