Shuguo Wang, Chunfeng Ma, Zebin Zhao, Long Wei
Remote Sensing Technology and Application, 2020 35 (1): 22
Soil moisture is a key variable in land surface system. Using active microwave remote sensing observations, especially Synthetic Aperture Radar (SAR), has been proven a promising way on the estimation of spatial-temporal distribution of surface soil moisture by a lot of studies. However, there is still challenging in this field, because of the impacts caused by surface roughness and vegetation cover. In this context, this paper proposes an optimal estimation approach combined using SAR and optical remote sensing imagery, in order to retrieve vegetation water content, roughness and soil moisture simultaneously. First, water-cloud model is used to correct vegetation effect on microwave scatter. . .
Guo Jian, Liu Liangyun, Liu Xinjie, Hu Jiaochan, Jing Xia
Remote Sensing Technology and Application, 2019 34 (3): 475
Tower-based spectral observation is an important connecting bridge between flux sites and satellite remote sensing data，and the effect of atmospheric absorption and scattering between horizontal surface and tower-based platform on the atmospheric absorption band such as O2-A is difficult to ignore.Firstly，the influence of atmospheric radiation transfer on the up-welling radiance and down-welling irradiance of the tower-based platform is analyzed，and the atmospheric correction method of based on upward and downward transmittance is established，that is，the influence of the upwelling radiance and down-welling irradiance is corrected by the direct transmittance and the total transmittance.Secon. . .
Ding Haining, Chen Yu, Chen Yunzhi
Remote Sensing Technology and Application, 2019 34 (2): 283
The information of soil composition and its spatial distribution could be obtained quickly and efficiently by using spectral technology.In order to accurately estimate the content and distribution characteristics of soil Fe elements in the loess plateau，the typical loess in the eastern part of Yulin was collected in the field.Laboratory physical and chemical analysis，spectral determination and pretreatment，analysis of the correlation between soil iron content and reflection spectrum，screening sensitive bands，using partial least squares modeling to determine the best estimation model.The spectral reflectivity and the selected sensitive bands are mainly distributed at 500 nm，870 nm，1 700 nm an. . .
Gu Xiaotian, Gao Xiaohong, Ma Huijuan, Shi Feifei, Liu Xuemei, Cao Xiaomin
Remote Sensing Technology and Application, 2019 34 (1): 67
Aiming at the characteristics of varied and complex geomorphic types，crisscross network of ravines and broken terrain in high altitude complicated terrain regions，it is very important to study and find the rapid and effective land use/land cover classification method for obtaining and timely updating of land use information.Taking the Huangshui river basin located in the transitional zone between the Loess Plateau and the Qinghai-Tibet Plateau as acasestudy area，the objective of this study is to explore a kind of effective information extraction method from comparison of four kinds machine learning methods for complicated terrain regions.based on Landsat 8 OLI satellite data，DEM and co. . .
Wang Juanle, Cheng Kai, Bian Lingling, Han Xuehua, Wang Mingming
Remote Sensing Technology and Application, 2018 33 (5): 783
Construction of UN Sustainable Development Goals(SDGs) and Beautiful Chinashare the same meaning.Both of them endeavor to achieve national and regional social，environment and economy sustainable development.Accurate，reliable，timely and well classified data is the key for accurate evaluation of sustainable development.In order to address issues such as single data source，poor timeliness，lack of high accuracy and evaluation results unreliable，we puts forward the integration framework and standardization of the bigearth data which includes big network data，big remote sensing data，and big socioeconomic data facing to the evaluation of SDGs and Beautiful China.Then，the key technologies of network. . .