Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization

Beijing, China

Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization

Beijing, China

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Li Y.,Beijing Normal University | Li Y.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Li Y.,Monash University | Sun R.,Beijing Normal University | And 3 more authors.
Science China Earth Sciences | Year: 2015

Land surface process modeling of high and cold area with vegetation cover has not yielded satisfactory results in previous applications. In this study, land surface energy budget is simulated using a land surface model for the A’rou meadow in the upper-reach area of the Heihe River Basin in the eastern Tibetan Plateau. The model performance is evaluated using the in-situ observations and remotely sensed data. Sensible and soil heat fluxes are overestimated while latent heat flux is underestimated when the default parameter setting is used. By analyzing physical and physiological processes and the sensitivities of key parameters, the inappropriate default setting of optimum growth and inhibition temperatures is identified as an important reason for the bias. The average daytime temperature during the period of fastest vegetation growth (June and July) is adopted as the optimum growth temperature, and the inhibition temperatures were adjusted using the same increment as the optimum temperature based on the temperature acclimation. These adjustments significantly reduced the biases in sensible, latent, and soil heat fluxes. © 2014, Science China Press and Springer-Verlag Berlin Heidelberg.


Qiao C.,Beijing Normal University | Qiao C.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 5 more authors.
IEEE Geoscience and Remote Sensing Letters | Year: 2015

The transpiration from shelterbelts and the evapotranspiration (ET) from cropland (maize and vegetables) and orchards (apple) in an irrigated area in the middle reaches of the Heihe River, China, were estimated using a modified Penman-Monteith (P-M) formula and airborne remote sensing data. The results were compared to the shelter transpiration results obtained from measurements of sup flow in tree trunks made with thermal dissipation probes and the latent heat fluxes observed by the eddy covariance technique at flux towers in croplands. The modified P-M formula was found to be an effective means to estimate not only the cropland and orchard ET but also the shelter transpiration. The seasonal variation of shelterbelt transpiration was smaller than those of cropland and orchard ET. Estimates of ET made using the P-M formula along with the remote sensing data showed that 9.9%, 3.1%, and 87.0% of the total ET were allotted to shelterbelts, apple orchards, and cropland, respectively. © 2004-2012 IEEE.


Hongwei X.,University of Chinese Academy of Sciences | Hongwei X.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Hongwei X.,Beijing Normal University | Rui S.,University of Chinese Academy of Sciences | And 5 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

ET plays an important role in the energy exchange mass transfer between the hydrosphere, atmosphere and biosphere. ET is a critical variable in hydrological modeling and provides important boundary conditions for weather prediction. Environment and Disasters Monitoring Microsatellite Constellation of A and B star (HJ-1A/B), which was developed by China, has high space and temporary resolution and is widely used. In this paper, SEBS model and Priestley-Taylor Equation combined with Ts-NDVI feature space are used to estimate ET of Heihe River basin. The remote sensing data including visible and infrared data are acquired by HJ-1A/B satellites. We use GLDAS ET product as validation data. By comparison, the results show that HJ-1A/B data can be effectively used to estimate ET. © 2012 IEEE.


Zhang R.,Beijing Normal University | Zhang R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 3 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

In this study, land use data in the Mianzhu city, China are extracted from remote sensing data of 1970s, 1980s, 1995, 2000 and 2005 and land use atlas are established and analyzed using geo-information atlas theory. The results indicate that from the temporal series, farmland and unused land decrease and other lands increase during 1970s to 2005 except farmland increases and forest land reduces in sub-period of 1995 to 2000. From the spatial series, farmland convert to construction land in the nearby of town and unused land converting to forest land and grassland are in the northwest of Qingping. In arising/declining atlas, the largest expanding atlas is construction land, increasing by 11.11km2, accounting for 65.66% in expanding atlas, mainly from farmland. And the largest shrinking atlas is farmland, reducing by 11.54km2, accounting for 68.20% in shrinking atlas, mainly transforming to construction land and forest land. © 2012 IEEE.


Feng L.,Beijing Normal University | Feng L.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 5 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2011

Carbon cycle of terrestrial ecosystem is one of the hot issues in global change science. And there are more difficult during study with agroecosystem because of the strong affect caused by human activities such as sowing, fertilizing and irrigation. In this study, a measurement is carried out in Guantao, Hebei Province, China, which is a typical argoecosystem station. In this paper, carbon dioxide fluxes in Guantao, were simulated by BIOME-BGC model as well, and the result was compared with the eddy covariance (EC) data. The result shows that the trend curves of simulated data and observation data were well matched in growing season of winter wheat in 2009. © 2011 IEEE.


Zhu Z.,Beijing Normal University | Zhu Z.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Tan L.,Beijing Normal University | Tan L.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 4 more authors.
IEEE Geoscience and Remote Sensing Letters | Year: 2014

The newly developed cosmic-ray probe (CRP) method for measuring area-average soil moisture at the hectometer horizontal scale was tested in the 2012 observation campaign of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in the irrigated cropland area of Zhangye Oasis. As compared with the traditional point observation, data analysis shows that the CRP could measure the real areal soil moisture, except when the water is frozen and during thaw. During the irrigation period, the presence of surface water can lead to an overestimation of the soil moisture. During non-irrigated periods, the CRP has a very strong correlation with the averaged soil moisture of 19 SoilNET probes in its footprint, whose R2is 0.73 and root-mean-square error is 0.0275 m3/m3. In comparison with the Polarimetric L-band Multi-beam Radiometer (PLMR) retrieved soil moisture, which has a pixel resolution of 700 m, the CRP provides much better results, with a coefficient of determination of 0.96 and 0.64, respectively. The results show that the CRP is a robust area-averaged soil moisture observation method, which can be used to obtain 'true' values of field-scale soil moisture for remote sensing validation. © 2014 IEEE.


Zhang R.-H.,Beijing Normal University | Zhang R.-H.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 12 more authors.
Journal of Mountain Science | Year: 2013

Net primary productivity (NPP) and evapotranspiration (ET) are two key variables in the carbon and water cycles of terrestrial ecosystems. In this study, to test a newly developed NPP algorithm designed for HJ-1 A/B data and to evaluate the usage of HJ-1 A/B data in the quantitative assessment of environments, NPP and ET in Jinggangshan city, Jiangxi province, are calculated using HJ-1 A/B data. The results illustrate the following: (1) The NPP and ET in Jinggangshan city in 2010 both show obvious seasonal variation, with the highest values in summer and the lowest values in winter, and relatively higher values were observed in autumn than in spring. (2) The spatial pattern indicates that the annual NPP is high in the southern area in Jinggangshan city and low in the northern area. Additionally, high NPP is distributed in forests located in areas with high elevation, and low NPP is found in croplands at low elevations. ET has no significant north-south difference, with high values in the southeast and northwest and low values in the southwest, and high ET is distributed in forests at low elevations in contrast to low ET in forests in high-elevation areas and in cropland and shrub grassland in low-elevation areas. (3) Compared to the MODIS product, the range of HJ-1 NPP is larger, and the spatial pattern is more coincident with the topography. The range of HJ-1 ET is smaller than that of the MODIS product, and ET is underestimated to some extent but can reflect the effect of topography. This study suggests that the algorithm can be used to estimate NPP and ET in a subtropical monsoon climate if remotely sensed images with high spatial resolution are available. © 2013 Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg.


Tang Y.,Beijing Normal University | Tang Y.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 4 more authors.
2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012 - Proceedings | Year: 2012

The existence of mixed pixels in satellite images, especially those with coarse resolution, is still a challenge for crop planting area extraction with traditional classification methods. In this study, taking Henan Province as the pilot area, N-FINDR algorithm was used for automatic determination of spectral endmembers, and then Linear Mixing Model was utilized for mixed pixels decomposition to derive the planting area of winter wheat with multi-temporal MODIS data. Moreover, validation was carried out with statistical data. The results show that the phenological characteristic of winter wheat can be identified by the endmembers in general, which indicates that N-FINDR is an applicable algorithm for endmember determination. The extracted planting area of winter wheat in Henan Province is 4939.174 thousand hectares in 2008, with a total accuracy reaching up to 93.9%. The accuracies are various for different region; however, they can be improved with higher dimensions data and the mask data such as DEM or actual classification data. © 2012 IEEE.

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