In the agricultural field, optical remote sensing technology plays an important role in crop monitoring or production estimation. However, the widespread distribution of clouds and rain limits the application of optical remote sensing. Synthetic aperture radar (SAR) has been widely used for studies of oceans, atmosphere, land, and space exploration, as well as by the military due to its all-weather nature, penetration to surface and cloud layers, and diversity of information carriers. However, it is difficult to classify ground objects with high accuracy based on SAR data. Considering the features of these two datasets, we proposed a framework to improve crop classifications in cloudy and rainy areas based on the optical-SAR response mechanism. Specifically, this method is designed to train a parametric analytic model in the area using both kinds of datasets and applied in the area with only SAR data to obtain the optical time-series features. Then crops from the second area were classified by the long-short-term memory network. As an example, the parametric analytic model in Lixian County was studied and was applied to Xifeng County to classify the crops with the OA of 61%, which had proved the robustness of the method.
KEYWORDS: Data modeling, Statistical analysis, Data analysis, Error analysis, RGB color model, Spatial resolution, Composites, Remote sensing, Data centers, Vegetation
Spatialized Gross Domestic Product (GDP) data was essential for studying the relationship between human activities and environmental changes. Rapid and accurate acquisition of this data was always an important issue. The land use/cover data and the DMSP/OLS nighttime light (NTL) data both had been used to simulate GDP spatialization. By analyzing previous researches, the estimated method based on land use/cover data, estimated method based on radiance-calibrated NTL data and estimated method based on land use/cover data and radiance-calibrated NTL data were applied and compared in this study. The result showed the precision of agricultural production method based on land use/cover data and non-agricultural production method based on radiance-calibrated NTL data which did not include saturated pixels were both high. The accuracy of estimated GDP based on land use/cover data and radiance-calibrated NTL data was the best. The estimated method based on land use/cover data and radiance-calibrated NTL data was used to create a 1-km gridded GDP density map in 2010. In order to make the estimated result more accurate, the county-level statistical data was used to correct it. The corrected 1-km gridded GDP density map in 2010 reflected the Chinese economic development situation and spatial distribution characteristics of GDP density in 2010.
Regional synergy is seen as an advanced form of coordinating the social economy and maintaining competitiveness in today's global competition system. Since China's reform and development, under the background of rapid urbanization and regional coordinated development, cities with geographical proximity and close economic and social ties have gradually formed a new mode of urban development, which is called integrated city. As a new phenomenon in the process of China’s urbanization, the existing research mainly focuses on the typical case studies, and the research methods are mostly limited to literature review and theoretical analysis. Therefore, in this paper, the Guangfo city (the most representative case in China, resulting from the integration of Guangzhou and Foshan cities) was selected as research objective. Specifically, the work analyses the transitional zone of the integrated city, based on multi-spectral Landsat 8 and nighttime light NPP/VIIRS images, focusing on landuse conversion, block light fluctuation and light gravity center migration. In the analyzed period (2013-2017), results highlight significant spatial heterogeneity in the integration level of Guangfo city’s development. Moreover, the combined analysis of nighttime light and urban expansion in the boundary zone shows that the enhancement effect of construction land expansion on nighttime light is increasing with the development of integration, and the inhibition effect of vegetation cover on nighttime light intensity is weakening. The proposed approach applied to integrated city research and achieved results can potentially support decision-making and planning in the process of urban development.
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