10 results match your criteria: "Institute of Remote Sensing and Digital Earth (RADI)[Affiliation]"
Sensors (Basel)
March 2019
State Key Lab of Remote Sensing Sciences, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Beijing 100101, China.
This paper presents a novel approach for semantic segmentation of building roofs in dense urban environments with a Deep Convolution Neural Network (DCNN) using Chinese Very High Resolution (VHR) satellite (i.e., GF2) imagery.
View Article and Find Full Text PDFSensors (Basel)
January 2019
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Beijing 100094, China.
Spectral unmixing is a vital procedure in hyperspectral remote sensing image exploitation. The linear mixture model has been widely utilized to unmix hyperspectral images by extracting a set of pure spectral signatures, called endmembers in hyperspectral jargon, and estimating their respective fractional abundances in each pixel of the scene. Many algorithms have been proposed to extract endmembers automatically, which is a critical step in the spectral unmixing chain.
View Article and Find Full Text PDFSensors (Basel)
July 2018
College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China.
Timely and accurate estimation of rice parameters plays a significant role in rice monitoring and yield forecasting for ensuring food security. Compact-polarimetric (CP) synthetic aperture radar (SAR), a good compromise between the dual- and quad-polarized SARs, is an important part of the new generation of Earth observation systems. In this paper, the ability of CP SAR data to retrieve rice biophysical parameters was explored using a modified water cloud model.
View Article and Find Full Text PDFCarbon Balance Manag
December 2017
REDD Implementation Center, Babarmahal, Kathmandu, Nepal.
Background: The reliable monitoring, reporting and verification (MRV) of carbon emissions and removals from the forest sector is an important part of the efforts on reducing emissions from deforestation and forest degradation (REDD+). Forest-dependent local communities are engaged to contribute to MRV through community-based monitoring systems. The efficiency of such monitoring systems could be improved through the rational integration of the studies at permanent plots with the geospatial technologies.
View Article and Find Full Text PDFSensors (Basel)
January 2017
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China.
Net radiation plays an essential role in determining the thermal conditions of the Earth's surface and is an important parameter for the study of land-surface processes and global climate change. In this paper, an improved satellite-based approach to estimate the daily net radiation is presented, in which sunshine duration were derived from the geostationary meteorological satellite (FY-2D) cloud classification product, the monthly empirical and Angstrom coefficients for net shortwave radiation were calibrated by spatial fitting of the ground data from 1997 to 2006, and the daily net longwave radiation was calibrated with ground data from 2007 to 2010 over the Heihe River Basin in China. The estimated daily net radiation values were validated against ground data for 12 months in 2008 at four stations with different underlying surface types.
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November 2016
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China.
Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements.
View Article and Find Full Text PDFSensors (Basel)
May 2015
School of GeoSciences and Info-Physics, Central South University, Changsha 410083, China.
Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs).
View Article and Find Full Text PDFPLoS One
January 2016
State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, P. R. China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Beijing 100094, P. R. China.
Water quality assessment at the watershed scale requires not only an investigation of water pollution and the recognition of main pollution factors, but also the identification of polluted risky regions resulted in polluted surrounding river sections. To realize this objective, we collected water samplings from 67 sampling sites in the Honghe River watershed of China with Grid GIS method to analyze six parameters including dissolved oxygen (DO), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N), nitrite nitrogen (NO2-N), total nitrogen (TN) and total phosphorus (TP). Single factor pollution index and comprehensive pollution index were adopted to explore main water pollutants and evaluate water quality pollution level.
View Article and Find Full Text PDFScientificWorldJournal
April 2015
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, China.
A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001-2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R (2)), and the relative error (RE).
View Article and Find Full Text PDFGuang Pu Xue Yu Guang Pu Fen Xi
October 2013
Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China.
Domestic satellites BJ-1, HJ and the most widely used satellite Landsat were selected to systematically compare their abilities and differences on the estimation of the biophysical parameters of grassland in sandstorm source region in Beijing and Tianjin, with the combination of field-measured fractional coverage, leaf area index and aboveground biomass data. The result shows: (1) In terms of the surface reflectance, HJ-1B and Landsat have a higher correlation with biophysical parameters in red band, compared with BJ-1, while BJ-1's near infra-red band was obviously superior to HJ-1B and Landsat, (2) with respect to the vegetation indices, Landsat performed best, HJ-1B was the second, and BJ-1 was the worst, (3) compared with vegetation indices, multiple regression model can raise the estimation accuracy, BJ-1 based model improved significantly, while Landsat and HJ-1B based models were less obvious. Among them, the highest accuracy was acquired for leaf area index estimation through the BJ-1 based model (R2 = 0.
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