尽管在融合网络中用作输入的三幅Sentinel-2图像中存在明显的LULC变化,但2017年7月1日30米处的最终融合图像仍然没有纳入这些LULC变化(图8(i))。这些发现表明,融合网络可以识别经历LULC变化的区域,然后删除与目标图像不一致的光谱变化相关的特征。 4.3. 具有灵活数量的辅助Sentinel-2图像的图像融合 在上一节中,Landsa...
Level-2A 主要包含经过大气校正的大气底层反射率数据（Bottom-of-Atmosphere corrected reflectance），但这...
其次，使用select()函数选择特定的波段。在这里，我是选择了影像中的B2、B3、B4、B5、B6、B7、B8和B8...
Land use/land cover (LULC)image processingsupervised classificationmanual vectorizationorthophotomapThe study was performed for the part of the administrative district Milicz. The authors analysed the parcels where the changes in land use, compared to the cadastral data, were found. The areas of ...
Best accuracy land use/land cover (LULC) classification to derive crop types using multitemporal, multisensor, and multi-polarization SAR satellite images Remote Sens. (2016), 10.3390/rs8080684 Google Scholar Inglada et al., 2016 J. Inglada, A. Vincent, M. Arias, C. Marais-Sicre Improved ...
In this sense, we aimed to select the best Land Use and Land Cover (LULC) classification approach for tropical regions using Sentinel family products. We choose the city of Belém, Brazil, as the study area. Images of close dates from Sentinel-1 (S-1) and Sentinel-2 (S-2) were ...
BigEarthNet是一个新的大规模Sentinel-2基准档案,由590,326个Sentinel-2图像斑块组成。为了构建BigEarthNet,最初选择了2017年6月至2018年5月期间在欧洲10个国家(奥地利、比利时、芬兰、爱尔兰、科索沃、立陶宛、卢森堡、葡萄牙、塞尔维亚、瑞士)获得的125张Sentinel-2瓦片。所有的瓦片都通过Sentinel-2 2A级产品生成和...
land use land cover analysisThis study proposes the development of a multi-sensor, multi-spectral composite from Landsat-8 and Sentinel-2A imagery referred to as 'LSC' for land use land cover (LULC) characterisation and compared with respect to the hyperspectral imagery of the EO1: Hyperion ...
This study proposes the development of a multi-sensor, multi-spectral composite from Landsat-8 and Sentinel-2A imagery referred to as 'LSC' for land use land cover (LULC) characterisation and compared with respect to the hyperspectral imagery of the EO1: Hyperion sensor. A three-stage ...
LULCSentinel MissionSAREhlers FusionLand use land cover mapping from satellite imagery is of great important since it allows to analyze terrain features and is also useful for monitor temporal changes (change detection) like dynamics of water resource, forest cover or urban environment economically. ...