“… Fig. 15 Prediction graph for the approach by C. Mozumder et al [ 8 ]—with averaged SWIR1 and SWIR2 band data. Fig.…”
Section: Methodsmentioning
confidence: 99%
“…To further confirm the performance of our model, we conducted comparison experiments with other approaches similar to ours. Out of 12 works as mentioned in Table 15 , there are three approaches similar to what we are doing: 1) an approach by C. Mozumder et al [ 8 ], 2) another approach by W. Wang, et al [ 13 ], and 3) an approach by Q. Di, et al [ 9 ].…”
Section: Methodsmentioning
confidence: 99%
“…To compare the performance with an approach by Mozumder et al [ 8 ] : we used the suggested configurations and equations provided by the paper with our datasets in Thailand—although the original datasets applied in the paper was Landsat 7, which is not exactly the same as ours, which is Landsat 8 but still in the same series of landsat imagery. The suggested equation is as follows: …”
Section: Methodsmentioning
confidence: 99%
“…In 2012 Mozumder et al [ 8 ] proposed a method for air quality assessment using IRS and Landsat 7 data with VI, NDVI and TVI using Linear Regression techniques. In this work, there is no any other machine learning techniques proposed to predict AQI nor Landsat 8, which is newer, was utilized.…”
“… Fig. 15 Prediction graph for the approach by C. Mozumder et al [ 8 ]—with averaged SWIR1 and SWIR2 band data. Fig.…”
Section: Methodsmentioning
confidence: 99%
“…To further confirm the performance of our model, we conducted comparison experiments with other approaches similar to ours. Out of 12 works as mentioned in Table 15 , there are three approaches similar to what we are doing: 1) an approach by C. Mozumder et al [ 8 ], 2) another approach by W. Wang, et al [ 13 ], and 3) an approach by Q. Di, et al [ 9 ].…”
Section: Methodsmentioning
confidence: 99%
“…To compare the performance with an approach by Mozumder et al [ 8 ] : we used the suggested configurations and equations provided by the paper with our datasets in Thailand—although the original datasets applied in the paper was Landsat 7, which is not exactly the same as ours, which is Landsat 8 but still in the same series of landsat imagery. The suggested equation is as follows: …”
Section: Methodsmentioning
confidence: 99%
“…In 2012 Mozumder et al [ 8 ] proposed a method for air quality assessment using IRS and Landsat 7 data with VI, NDVI and TVI using Linear Regression techniques. In this work, there is no any other machine learning techniques proposed to predict AQI nor Landsat 8, which is newer, was utilized.…”
“…Failure of the scan line corrector (SLC) on the Landsat 7 ETM+ resulted in stripes in images acquired after June 2003, which affects the results of the TS analysis. The stripes were filled using the ENVI gap-fill plug-in [42][43][44][45].…”
Section: Preprocessing Of Remote Sensing Imagesmentioning
High-precision information regarding the location, time, and type of land use change is integral to understanding global changes. Time series (TS) analysis of remote sensing images is a powerful method for land use change detection. To address the complexity of sample selection and the salt-and-pepper noise of pixels, we propose a bidirectional segmented detection (BSD) method based on object-level, multivariate TS, that detects the type and time of land use change from Landsat images. In the proposed method, based on the multiresolution segmentation of objects, three dimensions of object-level TS are constructed using the median of the following indices: the normalized difference vegetation index (NDVI), the normalized difference built index (NDBI), and the modified normalized difference water index (MNDWI). Then, BSD with forward and backward detection is performed on the segmented objects to identify the types and times of land use change. Experimental results indicate that the proposed BSD method effectively detects the type and time of land use change with an overall accuracy of 90.49% and a Kappa coefficient of 0.86. It was also observed that the median value of a segmented object is more representative than the commonly used mean value. In addition, compared with traditional methods such as LandTrendr, the proposed method is competitive in terms of time efficiency and accuracy. Thus, the BSD method can promote efficient and accurate land use change detection.
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