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Qiang Liu
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China

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Communication
Published: 26 June 2021 in Remote Sensing
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With the development and improvement of modern surveying and remote-sensing technology, data in the fields of surveying and remote sensing have grown rapidly. Due to the characteristics of large-scale, heterogeneous and diverse surveys and the loose organization of surveying and remote-sensing data, effectively obtaining information and knowledge from data can be difficult. Therefore, this paper proposes a method of using ontology for heterogeneous data integration. Based on the heterogeneous, decentralized, and dynamic updates of large surveying and remote-sensing data, this paper constructs a knowledge graph for surveying and remote-sensing applications. First, data are extracted. Second, using the ontology editing tool Protégé, a knowledge graph mode level is constructed. Then, using a relational database, data are stored, and a D2RQ tool maps the data from the mode level’s ontology to the data layer. Then, using the D2RQ tool, a SPARQL protocol and resource description framework query language (SPARQL) endpoint service is used to describe functions such as query and reasoning of the knowledge graph. The graph database is then used to display the knowledge graph. Finally, the knowledge graph is used to describe the correlation between the fields of surveying and remote sensing.

ACS Style

Xuejie Hao; Zheng Ji; Xiuhong Li; Lizeyan Yin; Lu Liu; Meiying Sun; Qiang Liu; Rongjin Yang. Construction and Application of a Knowledge Graph. Remote Sensing 2021, 13, 2511 .

AMA Style

Xuejie Hao, Zheng Ji, Xiuhong Li, Lizeyan Yin, Lu Liu, Meiying Sun, Qiang Liu, Rongjin Yang. Construction and Application of a Knowledge Graph. Remote Sensing. 2021; 13 (13):2511.

Chicago/Turabian Style

Xuejie Hao; Zheng Ji; Xiuhong Li; Lizeyan Yin; Lu Liu; Meiying Sun; Qiang Liu; Rongjin Yang. 2021. "Construction and Application of a Knowledge Graph." Remote Sensing 13, no. 13: 2511.

Journal article
Published: 26 May 2021 in Water
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Watershed ecological compensation, as an important means to protect the environment and promote the sustainable and coordinated development of upstream and downstream has wide concern in China. At present, the compensation accounting method only assesses water quality. When applied to some northern rivers represented by the Yongding River, which are facing water shortage, the assessment of water quality indicators alone cannot effectively compensate the ecosystem service providers for their expenditure on the environment. This paper proposes a transboundary water quality and quantity ecological compensation standard model, which couples the water quality ecological compensation standard of pollutant reduction and the water quantity ecological compensation standard based on the restoration cost method. We set up two scenarios using the model to calculate the amount of compensation payable under the actual scenario in 2018, which is USD 68.2 million. The amount of compensation under the local environmental policy target scenario is USD 10.6–82.668–529 million. It was concluded that the funds obtained from this model can cover the rehabilitation cost and meet the benefits of the upstream and downstream, making compensation funds more reasonable. However, based on the cross-sectional assessment, there is still a lack of integrity and comprehensiveness for the river basin. The development of watershed ecological compensation should move from the game of upstream and downstream interests to a win–win situation.

ACS Style

Yizhuo Wang; Rongjin Yang; Xiuhong Li; Le Zhang; Weiguo Liu; Yi Zhang; Yunzhi Liu; Qiang Liu. Study on Trans-Boundary Water Quality and Quantity Ecological Compensation Standard: A Case of the Bahao Bridge Section in Yongding River, China. Water 2021, 13, 1488 .

AMA Style

Yizhuo Wang, Rongjin Yang, Xiuhong Li, Le Zhang, Weiguo Liu, Yi Zhang, Yunzhi Liu, Qiang Liu. Study on Trans-Boundary Water Quality and Quantity Ecological Compensation Standard: A Case of the Bahao Bridge Section in Yongding River, China. Water. 2021; 13 (11):1488.

Chicago/Turabian Style

Yizhuo Wang; Rongjin Yang; Xiuhong Li; Le Zhang; Weiguo Liu; Yi Zhang; Yunzhi Liu; Qiang Liu. 2021. "Study on Trans-Boundary Water Quality and Quantity Ecological Compensation Standard: A Case of the Bahao Bridge Section in Yongding River, China." Water 13, no. 11: 1488.

Journal article
Published: 19 April 2021 in Remote Sensing
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Land surface temperature (LST) is a vital physical parameter in geoscience research and plays a prominent role in surface and atmosphere interaction. Due to technical restrictions, the spatiotemporal resolution of satellite remote sensing LST data is relatively low, which limits the potential applications of these data. An LST downscaling algorithm can effectively alleviate this problem and endow the LST data with more spatial details. Considering the spatial nonstationarity, downscaling algorithms have been gradually developed from least square models to geographical models. The current geographical LST downscaling models only consider the linear relationship between LST and auxiliary parameters, whereas non-linear relationships are neglected. Our study addressed this issue by proposing an LST downscaling algorithm based on a non-linear geographically weighted regressive (NL-GWR) model and selected the optimal combination of parameters to downscale the spatial resolution of a moderate resolution imaging spectroradiometer (MODIS) LST from 1000 m to 100 m. We selected Jinan city in north China and Wuhan city in south China from different seasons as study areas and used Landsat 8 images as reference data to verify the downscaling LST. The results indicated that the NL-GWR model performed well in all the study areas with lower root mean square error (RMSE) and mean absolute error (MAE), rather than the linear model.

ACS Style

Shumin Wang; Youming Luo; Xia Li; Kaixiang Yang; Qiang Liu; Xiaobo Luo; Xiuhong Li. Downscaling Land Surface Temperature Based on Non-Linear Geographically Weighted Regressive Model over Urban Areas. Remote Sensing 2021, 13, 1580 .

AMA Style

Shumin Wang, Youming Luo, Xia Li, Kaixiang Yang, Qiang Liu, Xiaobo Luo, Xiuhong Li. Downscaling Land Surface Temperature Based on Non-Linear Geographically Weighted Regressive Model over Urban Areas. Remote Sensing. 2021; 13 (8):1580.

Chicago/Turabian Style

Shumin Wang; Youming Luo; Xia Li; Kaixiang Yang; Qiang Liu; Xiaobo Luo; Xiuhong Li. 2021. "Downscaling Land Surface Temperature Based on Non-Linear Geographically Weighted Regressive Model over Urban Areas." Remote Sensing 13, no. 8: 1580.

Journal article
Published: 14 January 2021 in IEEE Transactions on Geoscience and Remote Sensing
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The retrieval of aerosol properties over land from satellite sensors has always been a challenge. At present, several different algorithms for retrieving aerosol optical depth (AOD) have been developed from different satellite sensors. While each algorithm has its own advantages, the accuracy of AOD retrieval still needs to be further improved. To improve the retrieval accuracy of aerosol algorithms, it is necessary to provide a better method to describe the surface properties. In the current study, a new aerosol retrieval algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) images at a high spatial resolution of 500 m is proposed based on a priori bidirectional reflectance distribution function (BRDF) shape parameters database, which is reconstructed via the 3-D discrete cosine transform (DCT-PLS) method. Then, the surface reflectances are calculated from BRDF model (i.e., RossThick-LiSparse), and a non-Lambertian forward model used to describe the surface anisotropy. The new algorithm is used for processing the MODIS over the Beijing-Tianjin-Hebei of China, and Southeastern United States of America regions, and results are validated against AERONET AOD measurements as well as compared with the MODIS AOD products. The comparison showed that the estimation scheme of surface reflectance in this new algorithm significantly improved the AOD retrievals accuracy, with average correlation coefficient ~0.965 and root-mean-square error ~0.125; the number of AOD retrievals falling within expected error has increased to ~80.1%, and the overestimation uncertainty has been reduced compared with MODIS products. Due to the high spatial resolution and continuous spatial distributions of the AOD retrievals by the new algorithm, therefore, it can well-captured aerosol details over mixed surfaces and better useful for air pollution studies than the MODIS products at local and urban scales.

ACS Style

Xinpeng Tian; Qiang Liu; Zhiqiang Gao; Yueqi Wang; Xiuhong Li; Jing Wei. Improving MODIS Aerosol Estimates Over Land With the Surface BRDF Reflectances Using the 3-D Discrete Cosine Transform and RossThick-LiSparse Models. IEEE Transactions on Geoscience and Remote Sensing 2021, PP, 1 -10.

AMA Style

Xinpeng Tian, Qiang Liu, Zhiqiang Gao, Yueqi Wang, Xiuhong Li, Jing Wei. Improving MODIS Aerosol Estimates Over Land With the Surface BRDF Reflectances Using the 3-D Discrete Cosine Transform and RossThick-LiSparse Models. IEEE Transactions on Geoscience and Remote Sensing. 2021; PP (99):1-10.

Chicago/Turabian Style

Xinpeng Tian; Qiang Liu; Zhiqiang Gao; Yueqi Wang; Xiuhong Li; Jing Wei. 2021. "Improving MODIS Aerosol Estimates Over Land With the Surface BRDF Reflectances Using the 3-D Discrete Cosine Transform and RossThick-LiSparse Models." IEEE Transactions on Geoscience and Remote Sensing PP, no. 99: 1-10.

Journal article
Published: 17 December 2020 in Remote Sensing
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Land surface albedo is an important variable for Earth’s radiation and energy budget. Over the past decades, many surface albedo products have been derived from a variety of remote sensing data. However, the estimation accuracy, temporal resolution, and temporal continuity of these datasets still need to be improved. We developed a multi-sensor strategy (MSS) based on the direct-estimation algorithm (DEA) and Statistical-Based Temporal Filter (STF) to improve the quality of land surface albedo datasets. The moderate-resolution imaging spectroradiometer (MODIS) data onboard Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi-National Polar-orbiting Partnership (NPP) were used as multi-sensor data. The MCD43A3 product and in situ measurements from the Surface Radiation Budget Network (SURFRAD) and FLUXNET sites were employed for validation and comparison. The results showed that the proposed MSS method significantly improved the temporal continuity and estimation accuracy during the snow-covered period, which was more consistent with the measurements of SURFRAD (R = 0.9498, root mean square error (RMSE) = 0.0387, and bias = −0.0017) and FLUXNET (R = 0.9421, RMSE = 0.0330, and bias = 0.0002) sites. Moreover, this is a promising method to generate long-term, spatiotemporal continuous land surface albedo datasets with high temporal resolution.

ACS Style

Mengsi Wang; Xianlei Fan; Xijia Li; Qiang Liu; Ying Qu. Estimation of Land Surface Albedo from MODIS and VIIRS Data: A Multi-Sensor Strategy Based on the Direct Estimation Algorithm and Statistical-Based Temporal Filter. Remote Sensing 2020, 12, 4131 .

AMA Style

Mengsi Wang, Xianlei Fan, Xijia Li, Qiang Liu, Ying Qu. Estimation of Land Surface Albedo from MODIS and VIIRS Data: A Multi-Sensor Strategy Based on the Direct Estimation Algorithm and Statistical-Based Temporal Filter. Remote Sensing. 2020; 12 (24):4131.

Chicago/Turabian Style

Mengsi Wang; Xianlei Fan; Xijia Li; Qiang Liu; Ying Qu. 2020. "Estimation of Land Surface Albedo from MODIS and VIIRS Data: A Multi-Sensor Strategy Based on the Direct Estimation Algorithm and Statistical-Based Temporal Filter." Remote Sensing 12, no. 24: 4131.

Journal article
Published: 11 July 2020 in Journal of Cleaner Production
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Global ecological degradation and rapid economic growth has increased the focus on the sustainable relationship between ecological security and economic development. This paper evaluated and partitioned Guizhou Province's ecological security and economic development, and discussed the population, industrial structure and land use of each zone in 2010 and 2015. An ecological security assessment was performed based on land use. Principal component analysis (PCA) was used to evaluate the level of economic development. Spatially, the ecological security level was high in the south and low in the north of the province, while economic development in central regions was higher than in surrounding areas. The ecological security and wealth gaps were widening. In this study, Guizhou Province was partitioned into the Coordinated Development Zone (CDZ), the Ecological Risk Zone (ERZ), the Economic Poverty Zone (EPZ), and the Dual Pressure Zone (DPZ) based on the ecological security index and economic development index. The characteristics of the population, industrial structure, and land use in the zones showed that generally: (1) Populations became more aggregated in prosperous regions, while ecological security was higher in regions with sparse populations. (2) Regions with a high proportion of primary industry (over 25% in 2010 and over 23% in 2015) lagged economically, while regions with a high proportion of secondary industry (over 35% in 2010 and over 33% in 2015) were prosperous. In poor regions, tertiary industry had less ability to drive economic growth than secondary industry. (3) Nearly half of the communities with below-median values in the ecological security index had a grassland proportion between 20% and 32%, but most of the communities with above-median values in the ecological security index had a grassland proportion of less than 20%. Most communities with better ecological security had a high proportion of forestlands (over 52% in 2010 and over 53% in 2015), and a low proportion of croplands (below 30% in 2010 and below 27% in 2015). The communities with low ecological security showed the opposite pattern. The expansion of mining fields, transportation lands, and settlements on built-up lands was conducive to economic development, but they threatened regional ecological security. Different strategies are proposed for the four zones, based on the analysis. In the CDZ, priority should be given to developing tertiary industry that will improve ecological security. In the ERZ, controls over resource-based industry should be strengthened to implement sustainable industrial development and the focus on ecological restoration and environmental governance should be increased. In the EPZ, the development of the primary, secondary and tertiary industries should be integrated based on tourism, and ecological, environmental and biological resources. In the DPZ, the way of transforming lucid waters and lush mountain into invaluable assets should be explored. The Grain for Green Project should be taken seriously and ecological restoration should be combined with poverty alleviation.

ACS Style

Meiying Sun; Xiuhong Li; Rongjin Yang; Yi Zhang; Le Zhang; Zhenwei Song; Qiang Liu; Dan Zhao. Comprehensive partitions and different strategies based on ecological security and economic development in Guizhou Province, China. Journal of Cleaner Production 2020, 274, 122794 .

AMA Style

Meiying Sun, Xiuhong Li, Rongjin Yang, Yi Zhang, Le Zhang, Zhenwei Song, Qiang Liu, Dan Zhao. Comprehensive partitions and different strategies based on ecological security and economic development in Guizhou Province, China. Journal of Cleaner Production. 2020; 274 ():122794.

Chicago/Turabian Style

Meiying Sun; Xiuhong Li; Rongjin Yang; Yi Zhang; Le Zhang; Zhenwei Song; Qiang Liu; Dan Zhao. 2020. "Comprehensive partitions and different strategies based on ecological security and economic development in Guizhou Province, China." Journal of Cleaner Production 274, no. : 122794.

Journal article
Published: 11 June 2020 in Remote Sensing
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Surface albedo is an important parameter in climate models. The main way to obtain continuous surface albedo for large areas is satellite remote sensing. However, the existing albedo products rarely meet daily-scale requirements, which has a large impact on climate change research and rapid dynamic changes of surface analysis. The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) platform, which was launched into the Sun–Earth’s first Lagrange Point (L1) orbit, can provide spectral images of the entire sunlit face of Earth with 10 narrow channels (from 317 to 780 nm). As EPIC can provide high-temporal resolution data, it is beneficial to explore the feasibility of EPIC to estimate high-temporal resolution surface albedo. In this study, hourly surface albedo was calculated based on EPIC observation data. Then, the estimated albedo results were validated by ground-based observations of different land cover types. The results show that the EPIC albedo is basically consistent with the trend of the ground-based observations in the whole time series variation. The diurnal variation of the surface albedo from the hourly EPIC albedo exhibits a “U” shape curve, which has the same trend as the ground-based observations. Therefore, EPIC is helpful to enhance the temporal resolution of surface albedo to diurnal. Surfaces with a three-dimensional structure that casts shadows display the hotspot effect, producing a reflectance peak in the retro-solar direction and lower reflectance at viewing angles away from the solar direction. DSCOVR observes the entire sunlit face of the Earth, which is helpful to make up for the deficiency in the observations of traditional satellites in the hotspot direction in bidirectional reflectance distribution function (BRDF) research, and can help to improve the underestimation of albedo in the direction of hotspot observation.

ACS Style

Qiuyue Tian; Qiang Liu; Jie Guang; Leiku Yang; Hanwei Zhang; Cheng Fan; Yahui Che; Zhengqiang Li. The Estimation of Surface Albedo from DSCOVR EPIC. Remote Sensing 2020, 12, 1897 .

AMA Style

Qiuyue Tian, Qiang Liu, Jie Guang, Leiku Yang, Hanwei Zhang, Cheng Fan, Yahui Che, Zhengqiang Li. The Estimation of Surface Albedo from DSCOVR EPIC. Remote Sensing. 2020; 12 (11):1897.

Chicago/Turabian Style

Qiuyue Tian; Qiang Liu; Jie Guang; Leiku Yang; Hanwei Zhang; Cheng Fan; Yahui Che; Zhengqiang Li. 2020. "The Estimation of Surface Albedo from DSCOVR EPIC." Remote Sensing 12, no. 11: 1897.

Journal article
Published: 07 May 2020 in IEEE Transactions on Geoscience and Remote Sensing
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The angular and spectral kernel-driven (ASK) model distinguishes soil and vegetation spectral features by the component spectra and is a promising model which combines multisensor data for inversion. However, its global application is limited by the component spectra. This article proposes parameterization of the ASK component spectra of soil and leaf from global spectra libraries as ANGERS, GOSPEL, LOPEX, and USGS. A statistical ratio (ɣ ) of various leaf to soil spectra is used to capture their spectral differences and variations, with mean (m) +u (0, ± 0.5,,,±1) standard deviations (σ ) [i.e., ɣ (m+uσ )]. Optimization inversion is applied to determine the ratio candidates ɣ (m+uσ ), allowing more tolerance for spectral uncertainty, which releases the semiempirical nature of the kernel-driven model. Simulation data analysis proves its feasibility and good capture of vegetation-soil spectral differences. The model's bidirectional reflectance factor (BRF) fitting error [root-mean-square error (RMSE)] of 0.0245 is slightly larger than the true component spectra of 0.0178, and albedo RMSE is 0.0116 in Black Sky Albedo and 0.0182 in White Sky Albedo. The result also shows its good robustness to the noises, where the level up to 20% noise conducts a 0.0277 error in BRF fitting and an ignorable influence in albedo. The synergistic-retrieved albedo from multisensor satellite data consists of in situ measurements with an RMSE of 0.0171, compared to 0.0131 from true component spectra retrievals. The new parameterization sacrifices some accuracy, but it is simple and operational for global retrieval with a satisfactory precision.

ACS Style

DongQin You; Jianguang Wen; Qiang Liu; Yingtong Zhang; Yong Tang; Qinhuo Liu; Hongjie Xie. The Component-Spectra-Parameterized Angular and Spectral Kernel-Driven Model: A Potential Solution for Global BRDF/Albedo Retrieval From Multisensor Satellite Data. IEEE Transactions on Geoscience and Remote Sensing 2020, 58, 8674 -8688.

AMA Style

DongQin You, Jianguang Wen, Qiang Liu, Yingtong Zhang, Yong Tang, Qinhuo Liu, Hongjie Xie. The Component-Spectra-Parameterized Angular and Spectral Kernel-Driven Model: A Potential Solution for Global BRDF/Albedo Retrieval From Multisensor Satellite Data. IEEE Transactions on Geoscience and Remote Sensing. 2020; 58 (12):8674-8688.

Chicago/Turabian Style

DongQin You; Jianguang Wen; Qiang Liu; Yingtong Zhang; Yong Tang; Qinhuo Liu; Hongjie Xie. 2020. "The Component-Spectra-Parameterized Angular and Spectral Kernel-Driven Model: A Potential Solution for Global BRDF/Albedo Retrieval From Multisensor Satellite Data." IEEE Transactions on Geoscience and Remote Sensing 58, no. 12: 8674-8688.

Journal article
Published: 20 December 2019 in ISPRS Journal of Photogrammetry and Remote Sensing
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Measurements of the surface thermal infrared (TIR) radiance provides an estimate of the land surface temperature (LST). However, any TIR measurement must be acquired under a certain geometry observation, which may refer to strong directional anisotropies. Although physical radiative transfer models can provide high precision directional brightness temperature simulation, they are too complex for processing large volumes of satellite data. With the objective to compare TIR measures acquired under different viewing angles, the topic of angular normalization issue for retrieved LSTs could be treated based on semi-empirical modelling. In this paper, we consider such category of models to simulate the directional anisotropy of surface brightness temperatures in combination with visible and near-infrared (VNIR) data. In these models, the vegetation fraction and the hot spot effect are depicted by a vegetation index and a brightness factor, respectively. An evaluation of the method is performed with both synthetic and measured datasets. The directional anisotropies that are fitted by this semi-empirical model demonstrate good agreement with an extensive synthetic dataset that is generated with the Soil Canopy Observation, Photochemistry and Energy Fluxes (SCOPE) soil-vegetation-atmosphere transfer model. An evaluation using airborne multi-angle TIR data also reveals that this model performs well when predicting BT directional anisotropies, with root mean square errors (RMSEs) of less than 0.31 °C over a maize-planted area. Relative to Roujean-Lagouarde (RL) and Vinnikov models using only TIR data, the proposed model offers better performances. In addition, for future use with satellite data, the proposed model using observations at different times and the combination with VNIR BRDF model are also evaluated, and good results are obtained. It yields a promising approach for the angular normalization of LST and mosaics of fine-scale images.

ACS Style

Zunjian Bian; Jean-Louis Roujean; J.-P. Lagouarde; Biao Cao; Hua Li; Yongming Du; Qiang Liu; Qing Xiao; Qinhuo Liu. A semi-empirical approach for modeling the vegetation thermal infrared directional anisotropy of canopies based on using vegetation indices. ISPRS Journal of Photogrammetry and Remote Sensing 2019, 160, 136 -148.

AMA Style

Zunjian Bian, Jean-Louis Roujean, J.-P. Lagouarde, Biao Cao, Hua Li, Yongming Du, Qiang Liu, Qing Xiao, Qinhuo Liu. A semi-empirical approach for modeling the vegetation thermal infrared directional anisotropy of canopies based on using vegetation indices. ISPRS Journal of Photogrammetry and Remote Sensing. 2019; 160 ():136-148.

Chicago/Turabian Style

Zunjian Bian; Jean-Louis Roujean; J.-P. Lagouarde; Biao Cao; Hua Li; Yongming Du; Qiang Liu; Qing Xiao; Qinhuo Liu. 2019. "A semi-empirical approach for modeling the vegetation thermal infrared directional anisotropy of canopies based on using vegetation indices." ISPRS Journal of Photogrammetry and Remote Sensing 160, no. : 136-148.

Journal article
Published: 12 December 2018 in Remote Sensing
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The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Products (APs) have provided long-term and wide-spatial-coverage aerosol optical properties across the globe, such as aerosol optical depth (AOD). However, the performance of the latest Collection 6.1 (C6.1) of MODIS APs is still unclear over urban areas that feature complex surface characteristics and aerosol models. The aim of this study was to validate and compare the performance of the MODIS C6.1 and C6 APs (MxD04, x = O for Terra, x = Y for Aqua) over Beijing, China. The results of the Dark Target (DT) and Deep Blue (DB) algorithms were validated against Aerosol Robotic Network (AERONET) ground-based observations at local sites. The retrieval uncertainties and accuracies were evaluated using the expected error (EE: ±0.05 + 15%) and the root-mean-square error (RMSE). It was found that the MODIS C6.1 DT products performed better than the C6 DT products, with a greater percentage (by about 13%–14%) of the retrievals falling within the EE. However, the DT retrievals collected from two collections were significantly overestimated in the Beijing region, with more than 64% and 48% of the samples falling above the EE for the Terra and Aqua satellites, respectively. The MODIS C6.1 DB products performed similarly to the C6 DB products, with 70%–73% of the retrievals matching within the EE and estimation uncertainties. Moreover, the DB algorithm performed much better than DT algorithm over urban areas, especially in winter where abundant missing pixels were found in DT products. To investigate the effects of factors on AOD retrievals, the variability in the assumed surface reflectance and the main optical properties applied in DT and DB algorithms are also analyzed.

ACS Style

Xinpeng Tian; Qiang Liu; Xiuhong Li; Jing Wei. Validation and Comparison of MODIS C6.1 and C6 Aerosol Products over Beijing, China. Remote Sensing 2018, 10, 2021 .

AMA Style

Xinpeng Tian, Qiang Liu, Xiuhong Li, Jing Wei. Validation and Comparison of MODIS C6.1 and C6 Aerosol Products over Beijing, China. Remote Sensing. 2018; 10 (12):2021.

Chicago/Turabian Style

Xinpeng Tian; Qiang Liu; Xiuhong Li; Jing Wei. 2018. "Validation and Comparison of MODIS C6.1 and C6 Aerosol Products over Beijing, China." Remote Sensing 10, no. 12: 2021.

Journal article
Published: 16 May 2018 in IEEE Geoscience and Remote Sensing Letters
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This letter presents a new algorithm that allows the retrieval of the aerosol optical depth (AOD) at a high (500 m) spatial resolution from Landsat 8 Operational Land Imager (OLI) data over urban areas. Because of the complex structure over urban surfaces, the bidirectional reflectance characteristic is obvious; however, most of the current aerosol retrieval algorithms over land do not account for the anisotropic effect of the surface. This letter improves the quality of AOD retrieval by providing the surface reflectance based on the multiyear MODIS bidirectional reflectance distribution function (BRDF)/Albedo model parameters product (MCD43A1) and the RossThick-LiSparse reciprocal kernel-driven BRDF model. The ground-based Aerosol Robotic Network (AERONET) AOD measurements from five sites located in urban and suburban areas are used to validate the AOD retrievals, and the MODIS Terra Collection 6 (C6) dark target/deep blue AOD products (MOD04) at 10-km spatial resolution are obtained for comparison. The validation results show that the AOD retrievals from the OLI images are well correlated with the AERONET AOD measurements (R = 0.987), with a low root-mean-square error of 0.07, a mean absolute error of 0.036, and a relative mean bias of 1.029; approximately 95.3% of the collocations fall within the expected error. The analysis indicates that the BRDF is essential in ensuring the accuracy of AOD retrieval. Compared with the MOD04 AOD retrievals, the OLI AOD retrievals have better spatial continuity and higher accuracy. The new algorithm can provide continuous and detailed spatial distributions of the AOD over complex urban surfaces.

ACS Style

Xinpeng Tian; Qiang Liu; Zhenwei Song; Baocheng Dou; Xiuhong Li. Aerosol Optical Depth Retrieval From Landsat 8 OLI Images Over Urban Areas Supported by MODIS BRDF/Albedo Data. IEEE Geoscience and Remote Sensing Letters 2018, 15, 976 -980.

AMA Style

Xinpeng Tian, Qiang Liu, Zhenwei Song, Baocheng Dou, Xiuhong Li. Aerosol Optical Depth Retrieval From Landsat 8 OLI Images Over Urban Areas Supported by MODIS BRDF/Albedo Data. IEEE Geoscience and Remote Sensing Letters. 2018; 15 (7):976-980.

Chicago/Turabian Style

Xinpeng Tian; Qiang Liu; Zhenwei Song; Baocheng Dou; Xiuhong Li. 2018. "Aerosol Optical Depth Retrieval From Landsat 8 OLI Images Over Urban Areas Supported by MODIS BRDF/Albedo Data." IEEE Geoscience and Remote Sensing Letters 15, no. 7: 976-980.

Review
Published: 27 February 2018 in Remote Sensing
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Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF) has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

ACS Style

Jianguang Wen; Qiang Liu; Qing Xiao; Qinhuo Liu; DongQin You; Dalei Hao; Shengbiao Wu; Xingwen Lin. Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments. Remote Sensing 2018, 10, 370 .

AMA Style

Jianguang Wen, Qiang Liu, Qing Xiao, Qinhuo Liu, DongQin You, Dalei Hao, Shengbiao Wu, Xingwen Lin. Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments. Remote Sensing. 2018; 10 (3):370.

Chicago/Turabian Style

Jianguang Wen; Qiang Liu; Qing Xiao; Qinhuo Liu; DongQin You; Dalei Hao; Shengbiao Wu; Xingwen Lin. 2018. "Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments." Remote Sensing 10, no. 3: 370.

Journal article
Published: 29 January 2018 in Remote Sensing
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Satellite remote sensing has been widely used to retrieve aerosol optical depth (AOD), which is an indicator of air quality as well as radiative forcing. The dark target (DT) algorithm is applied to low reflectance areas, such as dense vegetation, and the deep blue (DB) algorithm is adopted for bright-reflecting regions. However, both DT and DB algorithms ignore the effect of surface bidirectional reflectance. This paper provides a method for AOD retrieval in arid or semiarid areas, in which the key points are the accurate estimation of surface reflectance and reasonable assumptions of the aerosol model. To reduce the uncertainty in surface reflectance, a minimum land surface reflectance database at the spatial resolution of 500 m for each month was constructed based on the moderate-resolution imaging spectroradiometer (MODIS) surface reflectance product. Furthermore, a bidirectional reflectance distribution function (BRDF) correction model was adopted to compensate for the effect of surface reflectance anisotropy. The aerosol parameters, including AOD, single scattering albedo, asymmetric factor, Ångström exponent and complex refractive index, are determined based on the observation of two sunphotometers installed in northern Xinjiang from July to August 2014. The AOD retrieved from the MODIS images was validated with ground-based measurements and the Terra-MODIS aerosol product (MOD04). The 500 m AOD retrieved from the MODIS showed high consistency with ground-based AOD measurements, with an average correlation coefficient of ~0.928, root mean square error (RMSE) of ~0.042, mean absolute error (MAE) of ~0.032, and the percentage falling within the expected error (EE) of the collocations is higher than that for the MOD04 DB product. The results demonstrate that the new AOD algorithm is more suitable to represent aerosol conditions over Xinjiang than the DB standard product.

ACS Style

Xinpeng Tian; Sihai Liu; Lin Sun; Qiang Liu. Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China. Remote Sensing 2018, 10, 197 .

AMA Style

Xinpeng Tian, Sihai Liu, Lin Sun, Qiang Liu. Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China. Remote Sensing. 2018; 10 (2):197.

Chicago/Turabian Style

Xinpeng Tian; Sihai Liu; Lin Sun; Qiang Liu. 2018. "Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China." Remote Sensing 10, no. 2: 197.

Journal article
Published: 15 June 2017 in Sensors
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In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory results because of the heterogeneity of soil moisture and its low correlation with the auxiliary variables. This study developed an Extended Kriging method to interpolate with the aid of remote sensing images. The underlying idea is to extend the traditional Kriging by introducing spectral variables, and operating on spatial and spectral combined space. The algorithm has been applied to WSN-measured soil moisture data in HiWATER campaign to generate daily maps from 10 June to 15 July 2012. For comparison, three traditional Kriging methods are applied: Ordinary Kriging (OK), which used WSN data only, Co-kriging and KED, both of which integrated remote sensing data as covariate. Visual inspections indicate that the result from Extended Kriging shows more spatial details than that of OK, Co-kriging, and KED. The Root Mean Square Error (RMSE) of Extended Kriging was found to be the smallest among the four interpolation results. This indicates that the proposed method has advantages in combining remote sensing information and ground measurements in soil moisture interpolation.

ACS Style

Jialin Zhang; Xiuhong Li; Rongjin Yang; Qiang Liu; Long Zhao; Baocheng Dou. An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks. Sensors 2017, 17, 1390 .

AMA Style

Jialin Zhang, Xiuhong Li, Rongjin Yang, Qiang Liu, Long Zhao, Baocheng Dou. An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks. Sensors. 2017; 17 (6):1390.

Chicago/Turabian Style

Jialin Zhang; Xiuhong Li; Rongjin Yang; Qiang Liu; Long Zhao; Baocheng Dou. 2017. "An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks." Sensors 17, no. 6: 1390.

Journal article
Published: 06 March 2017 in Remote Sensing
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Sea surface hemispherical broadband emissivity (BBE, 8–13.5 μm) is a vital parameter for calculating surface radiation budgets. Such data are currently unavailable. This paper proposes a lookup table-based method for retrieving sea surface hemispherical BBE values. The physicallybased sea surface emissivity model of Wu and Smith, together with the optimal refractive index, were used to generate hemispherical BBE values under wind speeds ranging from zero to 50 m/s. A lookup table of hemispherical BBE values as a function of wind speed was established and used to retrieve sea surface hemispherical BBE values under foam-free conditions. The accuracy of the estimates of hemispherical BBE was 0.003, given a wind speed of zero. The foam effect was explicitly considered. After incorporating the foam effect, hemispherical BBE was expressed as a linear function of the hemispherical BBE values of sea water and foam, weighted by the fraction of foam coverage. With this method, we have produced an hourly sea surface hemispherical BBE product with a resolution of 10 km and global coverage that covers the period from 2003 to 2005, using wind speed data from Modern-Era Retrospective analysis for Research and Applications (MERRA)-2.

ACS Style

Jie Cheng; Xiaolong Cheng; Shunlin Liang; Raquel Niclòs; Aixiu Nie; Qiang Liu. A Lookup Table-Based Method for Estimating Sea Surface Hemispherical Broadband Emissivity Values (8–13.5 μm). Remote Sensing 2017, 9, 245 .

AMA Style

Jie Cheng, Xiaolong Cheng, Shunlin Liang, Raquel Niclòs, Aixiu Nie, Qiang Liu. A Lookup Table-Based Method for Estimating Sea Surface Hemispherical Broadband Emissivity Values (8–13.5 μm). Remote Sensing. 2017; 9 (3):245.

Chicago/Turabian Style

Jie Cheng; Xiaolong Cheng; Shunlin Liang; Raquel Niclòs; Aixiu Nie; Qiang Liu. 2017. "A Lookup Table-Based Method for Estimating Sea Surface Hemispherical Broadband Emissivity Values (8–13.5 μm)." Remote Sensing 9, no. 3: 245.

Journal article
Published: 20 January 2017 in Remote Sensing
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Narrowband-to-broadband conversion is a critical procedure for mapping land-surface broadband albedo using multi-spectral narrowband remote-sensing observations. Due to the significant difference in optical characteristics between soil and vegetation, NTB conversion is influenced by the variation in vegetation coverage on different surface types. To reduce this influence, this paper applies an approach that couples NTB coefficient with the NDVI. Multi-staged NDVI dependent NTB coefficient look-up tables (LUT) for Moderate Resolution Imaging Spectroradiometer (MODIS), Polarization and Directionality of Earth’s Reflectance (POLDER) and Advanced Very High Resolution Radiometer (AVHRR) were calculated using 6000 spectra samples collected from two typical spectral databases. Sensitivity analysis shows that NTB conversion is affected more by the NDVI for sensors with fewer band numbers, such as POLDER and AVHRR. Analysis of the validation results based on simulations, in situ measurements and global albedo products indicates that by using the multi-staged NDVI dependent NTB method, the conversion accuracies of these two sensors could be improved by 2%–13% on different NDVI classes compared with the general method. This improvement could be as high as 15%, on average, and 35% on dense vegetative surface compared with the global broadband albedo product of POLDER. This paper shows that it is necessary to consider surface reflectance characteristics associated with the NDVI on albedo-NTB conversion for remote sensors with fewer than five bands.

ACS Style

Shi Peng; Jianguang Wen; Qing Xiao; DongQin You; Baocheng Dou; Qiang Liu; Yong Tang. Multi-Staged NDVI Dependent Snow-Free Land-Surface Shortwave Albedo Narrowband-to-Broadband (NTB) Coefficients and Their Sensitivity Analysis. Remote Sensing 2017, 9, 93 .

AMA Style

Shi Peng, Jianguang Wen, Qing Xiao, DongQin You, Baocheng Dou, Qiang Liu, Yong Tang. Multi-Staged NDVI Dependent Snow-Free Land-Surface Shortwave Albedo Narrowband-to-Broadband (NTB) Coefficients and Their Sensitivity Analysis. Remote Sensing. 2017; 9 (1):93.

Chicago/Turabian Style

Shi Peng; Jianguang Wen; Qing Xiao; DongQin You; Baocheng Dou; Qiang Liu; Yong Tang. 2017. "Multi-Staged NDVI Dependent Snow-Free Land-Surface Shortwave Albedo Narrowband-to-Broadband (NTB) Coefficients and Their Sensitivity Analysis." Remote Sensing 9, no. 1: 93.

Journal article
Published: 17 November 2016 in Sensors
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Of the modern technologies in polar-region monitoring, the remote sensing technology that can instantaneously form large-scale images has become much more important in helping acquire parameters such as the freezing and melting of ice as well as the surface temperature, which can be used in the research of global climate change, Antarctic ice sheet responses, and cap formation and evolution. However, the acquirement of those parameters is impacted remarkably by the climate and satellite transit time which makes it almost impossible to have timely and continuous observation data. In this research, a wireless sensor-based online monitoring platform (WSOOP) for the extreme polar environment is applied to obtain a long-term series of data which is site-specific and continuous in time. Those data are compared and validated with the data from a weather station at Zhongshan Station Antarctica and the result shows an obvious correlation. Then those data are used to validate the remote sensing products of the freezing and melting of ice and the surface temperature and the result also indicated a similar correlation. The experiment in Antarctica has proven that WSOOP is an effective system to validate remotely sensed data in the polar region.

ACS Style

Xiuhong Li; Xiao Cheng; Rongjin Yang; Qiang Liu; Yubao Qiu; Jialin Zhang; Erli Cai; Long Zhao. Validation of Remote Sensing Retrieval Products using Data from a Wireless Sensor-Based Online Monitoring in Antarctica. Sensors 2016, 16, 1938 .

AMA Style

Xiuhong Li, Xiao Cheng, Rongjin Yang, Qiang Liu, Yubao Qiu, Jialin Zhang, Erli Cai, Long Zhao. Validation of Remote Sensing Retrieval Products using Data from a Wireless Sensor-Based Online Monitoring in Antarctica. Sensors. 2016; 16 (11):1938.

Chicago/Turabian Style

Xiuhong Li; Xiao Cheng; Rongjin Yang; Qiang Liu; Yubao Qiu; Jialin Zhang; Erli Cai; Long Zhao. 2016. "Validation of Remote Sensing Retrieval Products using Data from a Wireless Sensor-Based Online Monitoring in Antarctica." Sensors 16, no. 11: 1938.

Journal article
Published: 05 November 2015 in Remote Sensing
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To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN) to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS) and then to identify the most representative combination (MRC). On this basis, an upscaling transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS) linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a) The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b) When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c) The most representative combination (MRC) combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a preliminary validation of the MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product was performed as the tentative application for upscaling predictions.

ACS Style

Xiaodan Wu; Qing Xiao; Jianguang Wen; Qiang Liu; DongQin You; Baocheng Dou; Yong Tang; Xiaowen Li. Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe. Remote Sensing 2015, 7, 14757 -14780.

AMA Style

Xiaodan Wu, Qing Xiao, Jianguang Wen, Qiang Liu, DongQin You, Baocheng Dou, Yong Tang, Xiaowen Li. Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe. Remote Sensing. 2015; 7 (11):14757-14780.

Chicago/Turabian Style

Xiaodan Wu; Qing Xiao; Jianguang Wen; Qiang Liu; DongQin You; Baocheng Dou; Yong Tang; Xiaowen Li. 2015. "Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe." Remote Sensing 7, no. 11: 14757-14780.

Journal article
Published: 09 October 2015 in Remote Sensing
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High spatial resolution soil moisture (SM) data are crucial in agricultural applications, river-basin management, and understanding hydrological processes. Merging multi-resource observations is one of the ways to improve the accuracy of high spatial resolution SM data in the heterogeneous cropland. In this paper, the Bayesian Maximum Entropy (BME) methodology is implemented to merge the following four types of observed data to obtain the spatial distribution of SM at 100 m scale: soil moisture observed by wireless sensor network (WSN), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-derived soil evaporative efficiency (SEE), irrigation statistics, and Polarimetric L-band Multi-beam Radiometer (PLMR)-derived SM products (~700 m). From the poor BME predictions obtained by merging only WSN and SEE data, we observed that the SM heterogeneity caused by irrigation and the attenuating sensitivity of the SEE data to SM caused by the canopies result in BME prediction errors. By adding irrigation statistics to the merged datasets, the overall RMSD of the BME predictions during the low-vegetated periods can be successively reduced from 0.052 m3·m−3to 0.033 m3·m−3. The coefficient of determination (R2) and slope between the predicted and in situ measured SM data increased from 0.32 to 0.64 and from 0.38 to 0.82, respectively, but large estimation errors occurred during the moderately vegetated periods (RMSD = 0.041 m3·m−3, R = 0.43 and the slope = 0.41). Further adding the downscaled SM information from PLMR SM products to the merged datasets, the predictions were satisfactorily accurate with an RMSD of 0.034 m3·m−3, R2 of 0.4 and a slope of 0.69 during moderately vegetated periods. Overall, the results demonstrated that merging multi-resource observations into SM estimations can yield improved accuracy in heterogeneous cropland.

ACS Style

Lei Fan; Qing Xiao; Jianguang Wen; Qiang Liu; Rui Jin; Dongqing You; Xiaowen Li. Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations. Remote Sensing 2015, 7, 13273 -13297.

AMA Style

Lei Fan, Qing Xiao, Jianguang Wen, Qiang Liu, Rui Jin, Dongqing You, Xiaowen Li. Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations. Remote Sensing. 2015; 7 (10):13273-13297.

Chicago/Turabian Style

Lei Fan; Qing Xiao; Jianguang Wen; Qiang Liu; Rui Jin; Dongqing You; Xiaowen Li. 2015. "Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations." Remote Sensing 7, no. 10: 13273-13297.

Journal article
Published: 28 May 2015 in Remote Sensing
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A land-cover-based linear BRDF (bi-directional reflectance distribution function) unmixing (LLBU) algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI) reflectance with the moderate resolution imaging spectroradiometer (MODIS) daily reflectance product to derive the BRDF/albedo of the two sensors simultaneously in the foci experimental area (FEA) of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER), which was carried out in the Heihe River basin, China. For each land cover type, an archetypal BRDF, which characterizes the shape of its anisotropic reflectance, is extracted by linearly unmixing from the MODIS reflectance with the assistance of a high-resolution classification map. The isotropic coefficients accounting for the differences within a class are derived from the CASI reflectance. The BRDF is finally determined by the archetypal BRDF and the corresponding isotropic coefficients. Direct comparisons of the cropland archetypal BRDF and CASI albedo with in situ measurements show good agreement. An indirect validation which compares retrieved BRDF/albedo with that of the MCD43A1 standard product issued by NASA and aggregated CASI albedo also suggests reasonable reliability. LLBU has potential to retrieve the high spatial resolution BRDF/albedo product for airborne and spaceborne sensors which have inadequate angular samplings. In addition, it can shorten the timescale for coarse spatial resolution product like MODIS.

ACS Style

DongQin You; Jianguang Wen; Qing Xiao; Qiang Liu; Qinhuo Liu; Yong Tang; Baocheng Dou; Jingjing Peng. Development of a High Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance with MODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China. Remote Sensing 2015, 7, 6784 -6807.

AMA Style

DongQin You, Jianguang Wen, Qing Xiao, Qiang Liu, Qinhuo Liu, Yong Tang, Baocheng Dou, Jingjing Peng. Development of a High Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance with MODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China. Remote Sensing. 2015; 7 (6):6784-6807.

Chicago/Turabian Style

DongQin You; Jianguang Wen; Qing Xiao; Qiang Liu; Qinhuo Liu; Yong Tang; Baocheng Dou; Jingjing Peng. 2015. "Development of a High Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance with MODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China." Remote Sensing 7, no. 6: 6784-6807.