Urban bare land classification using NDbai index based on combination of sentinel 2 MSI and landsat 8 multiresolution images

This paper presents the method of combining of Sentinel 2 MSI and Landsat 8 multi-resolution satellite image data for urban bare land classification based on NDBaI index. Two images of Sentinel 2 and Landsat 8 acquired closely together, were used to calculate the NDBaI index, in which sortware infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) of Landsat 8 image were used to improve the spatial resolution of NDBaI index. | VNU Journal of Science Earth and Environmental Sciences Vol. 36 No. 2 2020 68-78 Original Article Urban Bare Land Classification Using NDBaI Index Based on Combination of Sentinel 2 MSI and Landsat 8 Multiresolution Images Trinh Le Hung Military Technical Academy 236 Hoang Quoc Viet Hanoi Vietnam Received 03 January 2020 Revised 08 February 2020 Accepted 11 February 2020 Abstract The classification of urban land cover land use is a difficult task due to the complexity in the structure of the urban surface. This paper presents the method of combining of Sentinel 2 MSI and Landsat 8 multi-resolution satellite image data for urban bare land classification based on NDBaI index. Two images of Sentinel 2 and Landsat 8 acquired closely together were used to calculate the NDBaI index in which sortware infrared band band 11 of Sentinel 2 MSI image and thermal infrared band band 10 of Landsat 8 image were used to improve the spatial resolution of NDBaI index. The results obtained from two experimental areas showed that the total accuracy of classifying bare land from the NDBaI index which calculated by the proposed method increased by about 6 compared to the method using the NDBaI index which is calculated using only Landsat 8 data. The results obtained in this study contribute to improving the efficiency of using free remote sensing data in urban land cover land use classification. Keywords bare land classification urban indices NDBaI Sentinel 2 MSI Landsat 8. ____ Corresponding author. E-mail address trinhlehung125@ https 2588-1094 68 . Hung VNU Journal of Science Earth and Environmental Sciences Vol. 36 No. 2 2020 68-78 69 Phân loại đất trống đô thị bằng chỉ số NDBaI trên cơ sở kết hợp ảnh vệ tinh đa độ phân giải Sentinel 2 MSI và Landsat 8 Trịnh Lê Hùng Học viện Kỹ thuật Quân sự 236 Hoàng Quốc Việt Hà Nội Việt Nam Nhận ngày 03 tháng 01 năm 2020 Chỉnh sửa ngày 08 tháng 02 năm 2020 Chấp nhận đăng .