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Jianguang Wen
State key lab of remote sensing science, Institute of remote sensing an digital earth, beijing, beijing, China, 10011

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Journal article
Published: 18 August 2021 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Validation of satellite products is necessary to enable end-users to know the fitness and exploit their full potential in supporting the decision-making process. Representative in situ observations need to be obtained to make an independent, unified, standard, and traceable validation due to the spatial scale mismatch between satellite and in situ-based observations. Under the demand of validating various pixel scales of satellite products ranging from a few meters to kilometers, this paper proposed a multiscale nested sampling method (MNSM), which is able to provide representative ground observations at various pixel scales under a unified accuracy requirement. The basic idea is to extract the spatiotemporal variation information of surface variables using long time sequences of high-resolution images. And the sample locations were optimized with a random combination method using an index of spatiotemporal representativeness. The optimal sampling was carried out from a coarse pixel scale to a high pixel scale with the top-down nested approach. The final point in situ observations can represent surface variables at different pixel scales with a unified and predetermined accuracy. It was found that the representativeness error of a single in situ measurement and the minimum number of required filed plots under a unified sampling accuracy requirement are partly determined by spatial heterogeneity and partly determined by the spatial scale mismatch between the plot size and the pixel size to be matched. The sampling method is applicable to many other surface variables (e.g., soil moisture, biomass, albedo, GPP, and LAI) that exhibiting spatial heterogeneity.

ACS Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; Jingping Wang; Dujuan Ma; Xinwen Lin. A Multiscale Nested Sampling Method for representative albedo observations at various pixel scales. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, PP, 1 -1.

AMA Style

Xiaodan Wu, Jianguang Wen, Qing Xiao, Jingping Wang, Dujuan Ma, Xinwen Lin. A Multiscale Nested Sampling Method for representative albedo observations at various pixel scales. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; PP (99):1-1.

Chicago/Turabian Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; Jingping Wang; Dujuan Ma; Xinwen Lin. 2021. "A Multiscale Nested Sampling Method for representative albedo observations at various pixel scales." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing PP, no. 99: 1-1.

Journal article
Published: 07 April 2020 in Remote Sensing
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As an essential climate variable (ECV), land surface albedo plays an important role in the Earth surface radiation budget and regional or global climate change. The Tibetan Plateau (TP) is a sensitive environment to climate change, and understanding its albedo seasonal and inter-annual variations is thus important to help capture the climate change rules. In this paper, we analyzed the large-scale spatial patterns, temporal trends, and seasonal variability of land surface albedo overall the TP, based on the moderate resolution imaging spectroradiometer (MODIS) MCD43 albedo products from 2001 to 2019. Specifically, we assessed the correlations between the albedo anomaly and the anomalies of normalized difference vegetation index (NDVI), the fraction of snow cover (snow cover), and land surface temperature (LST). The results show that there are larger albedo variations distributed in the mountainous terrain of the TP. Approximately 10.06% of the land surface is identified to have been influenced by the significant albedo variation from the year 2001 to 2019. The yearly averaged albedo was decreased significantly at a rate of 0.0007 (Sen’s slope) over the TP. Additionally, the yearly average snow cover was decreased at a rate of 0.0756. However, the yearly average NDVI and LST were increased with slopes of 0.0004 and 0.0253 over the TP, respectively. The relative radiative forcing (RRF) caused by the land cover change (LCC) is larger than that caused by gradual albedo variation in steady land cover types. Overall, the RRF due to gradual albedo variation varied from 0.0005 to 0.0170 W/m2, and the RRF due to LCC variation varied from 0.0037 to 0.0243 W/m2 during the years 2001 to 2019. The positive RRF caused by gradual albedo variation or the LCC can strengthen the warming effects in the TP. The impact of the gradual albedo variations occurring in the steady land cover types was very low between 2001 and 2019 because the time series was short, and it therefore cannot be neglected when examining radiative forcing for a long time series regarding climate change.

ACS Style

Xingwen Lin; Jianguang Wen; Qinhuo Liu; DongQin You; Shengbiao Wu; Dalei Hao; Qing Xiao; Zhaoyang Zhang; Zhenzhen Zhang. Spatiotemporal Variability of Land Surface Albedo over the Tibet Plateau from 2001 to 2019. Remote Sensing 2020, 12, 1188 .

AMA Style

Xingwen Lin, Jianguang Wen, Qinhuo Liu, DongQin You, Shengbiao Wu, Dalei Hao, Qing Xiao, Zhaoyang Zhang, Zhenzhen Zhang. Spatiotemporal Variability of Land Surface Albedo over the Tibet Plateau from 2001 to 2019. Remote Sensing. 2020; 12 (7):1188.

Chicago/Turabian Style

Xingwen Lin; Jianguang Wen; Qinhuo Liu; DongQin You; Shengbiao Wu; Dalei Hao; Qing Xiao; Zhaoyang Zhang; Zhenzhen Zhang. 2020. "Spatiotemporal Variability of Land Surface Albedo over the Tibet Plateau from 2001 to 2019." Remote Sensing 12, no. 7: 1188.

Journal article
Published: 28 November 2019 in Sensors
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The urban heat island effect has always been one of the hottest issues in urban development. In this study, Landsat images from the summers of 2001, 2004, 2009, 2014 and 2018 were used to identify land cover type in six districts of Chongqing’s main city. Land cover was categorized as water, vegetation or impervious surface with the object-oriented method. Land surface temperature (LST) data was calculated with the atmospheric radiation transfer equation method, and was then divided into different heat island intensity grades. Next, the spatial and temporal changes in land cover type and heat island effect were analyzed in the six districts. Center migration analysis and heat island coefficients were used to quantitatively reflect the spatiotemporal evolution relationship between land cover and heat island effect. All six districts exhibited a trend of expanding impervious surface, with a 419.38% increase from 2001 to 2018, and shrinking vegetation, with a 17.81% decrease from 2001 to 2018. Also from 2001 to 2018, Yuzhong District had the most significant heat island effect, with a heat island coefficient 0.35 higher than the mean value of the whole study area. The impervious surface center migrated in different directions in each district. Both the direction and the corresponding velocity of the impervious surface and heat island centers were tightly correlated, with a correlation coefficient of 0.53. Relative heat island coefficients (the difference from the mean) of water ranged from −2.08 to −1.17 in different districts. That of impervious surface ranged from 1.60 to 1.93, and that of vegetation ranged from −0.22 to 1.09. The internal heterogeneity of land cover and heat island effect in Chongqing’s main city was huge. This study quantitatively analyzed the evolution of the heat island effect in the study area to help provide each district with some targeted suggestions for future urban planning.

ACS Style

Qin Lang; Wenping Yu; Mingguo Ma; Jianguang Wen. Analysis of the Spatial and Temporal Evolution of Land Cover and Heat Island Effects in Six Districts of Chongqing’s Main City. Sensors 2019, 19, 5239 .

AMA Style

Qin Lang, Wenping Yu, Mingguo Ma, Jianguang Wen. Analysis of the Spatial and Temporal Evolution of Land Cover and Heat Island Effects in Six Districts of Chongqing’s Main City. Sensors. 2019; 19 (23):5239.

Chicago/Turabian Style

Qin Lang; Wenping Yu; Mingguo Ma; Jianguang Wen. 2019. "Analysis of the Spatial and Temporal Evolution of Land Cover and Heat Island Effects in Six Districts of Chongqing’s Main City." Sensors 19, no. 23: 5239.

Journal article
Published: 29 March 2019 in Remote Sensing of Environment
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The anisotropic scattering behavior of land surface is characterized by its bidirectional reflectance-distribution function (BRDF). However, a physically consistent BRDF definition is still lacking for heterogeneous and rugged terrain that accounts for approximately 24% of Earth's land surface. In this study, we revisited current BRDF definitions and updated them for rugged terrain with few dependent parameters: illumination and viewing geometries, terrain shadows, effective areas of illumination and observation, and anisotropic reflectance properties of subpixel-scale slopes. Furthermore, the bidirectional reflectance factor (BRF), hemispherical-directional reflectance factor (HDRF), directional-hemispheric reflectance (DHR), and bi-hemispherical reflectance (BHR) were proposed within the current physical framework of reflectance quantities. These reflectance quantities have been adopted by the 3-D Discrete Anisotropic Radiative Transfer (DART) model to provide the simulations of remote sensing images. To highlight the importance of a proper usage of such reflectance terms, we used DART simulations to present the topographic effects on these reflectance quantities. Finally, the other issues with respect to surface BRDF/BRF, such as spatial scale of rugged terrain, characterization of anisotropic reflectance of micro-scale surfaces, derivative reflectance quantities, topographic parameters, wavelength dependence and reciprocity, and future perspective were discussed.

ACS Style

Shengbiao Wu; Jianguang Wen; Jean-Philippe Gastellu-Etchegorry; Qinhuo Liu; DongQin You; Qing Xiao; Dalei Hao; Xingwen Lin; Tiangang Yin. The definition of remotely sensed reflectance quantities suitable for rugged terrain. Remote Sensing of Environment 2019, 225, 403 -415.

AMA Style

Shengbiao Wu, Jianguang Wen, Jean-Philippe Gastellu-Etchegorry, Qinhuo Liu, DongQin You, Qing Xiao, Dalei Hao, Xingwen Lin, Tiangang Yin. The definition of remotely sensed reflectance quantities suitable for rugged terrain. Remote Sensing of Environment. 2019; 225 ():403-415.

Chicago/Turabian Style

Shengbiao Wu; Jianguang Wen; Jean-Philippe Gastellu-Etchegorry; Qinhuo Liu; DongQin You; Qing Xiao; Dalei Hao; Xingwen Lin; Tiangang Yin. 2019. "The definition of remotely sensed reflectance quantities suitable for rugged terrain." Remote Sensing of Environment 225, no. : 403-415.

Journal article
Published: 18 March 2019 in Remote Sensing
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Hydro-agricultural applications often require surface soil moisture (SM) information at high spatial resolutions. In this study, daily spatial patterns of SM at a spatial resolution of 1 km over the Babao River Basin in northwestern China were mapped using a Bayesian-based upscaling algorithm, which upscaled point-scale measurements to the grid-scale (1 km) by retrieving SM information using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and topography data (including aspect and elevation data) and in situ measurements from a wireless sensor network (WSN). First, the time series of pixel-scale (1 km) representative SM information was retrieved from in situ measurements of SM, topography data, and LST. Second, Bayesian linear regression was used to calibrate the relationship between the representative SM and the WSN measurements. Last, the calibrated relationship was used to upscale a network of in situ measured SM to map spatially continuous SM at a high resolution. The upscaled SM data were evaluated against ground-based SM measurements with satisfactory accuracy—the overall correlation coefficient (r), slope, and unbiased root mean square difference (ubRMSD) values were 0.82, 0.61, and 0.025 m3/m3, respectively. Moreover, when accounting for topography, the proposed upscaling algorithm outperformed the algorithm based only on SM derived from LST (r = 0.80, slope = 0.31, and ubRMSD = 0.033 m3/m3). Notably, the proposed upscaling algorithm was able to capture the dynamics of SM under extreme dry and wet conditions. In conclusion, the proposed upscaled method can provide accurate high-resolution SM estimates for hydro-agricultural applications.

ACS Style

Lei Fan; A. Al-Yaari; Frédéric Frappart; Jennifer J. Swenson; Qing Xiao; Jianguang Wen; Rui Jin; Jian Kang; Xiaojun Li; R. Fernandez-Moran; J.-P. Wigneron. Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures. Remote Sensing 2019, 11, 656 .

AMA Style

Lei Fan, A. Al-Yaari, Frédéric Frappart, Jennifer J. Swenson, Qing Xiao, Jianguang Wen, Rui Jin, Jian Kang, Xiaojun Li, R. Fernandez-Moran, J.-P. Wigneron. Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures. Remote Sensing. 2019; 11 (6):656.

Chicago/Turabian Style

Lei Fan; A. Al-Yaari; Frédéric Frappart; Jennifer J. Swenson; Qing Xiao; Jianguang Wen; Rui Jin; Jian Kang; Xiaojun Li; R. Fernandez-Moran; J.-P. Wigneron. 2019. "Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures." Remote Sensing 11, no. 6: 656.

Journal article
Published: 16 December 2018 in Remote Sensing
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This study assessed accuracies of MCD43A3, Global Land-Surface Satellite (GLASS) and forthcoming Multi-source Data Synergized Quantitative Remote Sensing Production system (MuSyQ) albedos using ground observations and Huan Jing (HJ) data over the Heihe River Basin. MCD43A3 and MuSyQ albedos show similar high accuracies with identical root mean square errors (RMSE). Nevertheless, MuSyQ albedo is better correlated with ground measurements when sufficient valid observations are available or snow-free. The opposite happens when less than seven valid observations are available. GLASS albedo presents a larger RMSE than MCD43A3 and MuSyQ albedos in comparison with ground measurements. Over surfaces with smaller seasonal variations, MCD43A3 and MuSyQ albedos show smaller RMSEs than GLASS albedo in comparison with HJ albedo. However, for surfaces with larger temporal variations, both RMSEs and R2 of GLASS albedo are comparable with MCD43A3 and MuSyQ. Generally, MCD43A3 and MuSyQ albedos featured the same RMSEs of 0.034 and similar R2 (0.920 and 0.903, respectively), which are better than GLASS albedo (RMSE = 0.043, R2 = 0.787). However, when it comes to comparison with aggregated HJ albedo, MuSyQ and GLASS albedos are with lower RMSEs of 0.027 and 0.032 and higher R2 of 0.900 and 0.898 respectively than MCD43A3 (RMSE = 0.038, R2 = 0.836). Despite the limited geographic region of the study area, they still provide an important insight into the accuracies of three albedo products.

ACS Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; DongQin You; Baocheng Dou; Xinwen Lin; Andreas Hueni. Accuracy Assessment on MODIS (V006), GLASS and MuSyQ Land-Surface Albedo Products: A Case Study in the Heihe River Basin, China. Remote Sensing 2018, 10, 2045 .

AMA Style

Xiaodan Wu, Jianguang Wen, Qing Xiao, DongQin You, Baocheng Dou, Xinwen Lin, Andreas Hueni. Accuracy Assessment on MODIS (V006), GLASS and MuSyQ Land-Surface Albedo Products: A Case Study in the Heihe River Basin, China. Remote Sensing. 2018; 10 (12):2045.

Chicago/Turabian Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; DongQin You; Baocheng Dou; Xinwen Lin; Andreas Hueni. 2018. "Accuracy Assessment on MODIS (V006), GLASS and MuSyQ Land-Surface Albedo Products: A Case Study in the Heihe River Basin, China." Remote Sensing 10, no. 12: 2045.

Journal article
Published: 08 November 2018 in Remote Sensing
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The academician Xiaowen Li devoted much of his life to pursuing fundamental research in remote sensing. A pioneer in the geometric-optical modeling of vegetation canopies, his work is held in high regard by the international remote sensing community. He codeveloped the Li–Strahler geometric-optic model, and this paper was selected by a member of the International Society for Optical Engineering (SPIE) milestone series. As a chief scientist, Xiaowen Li led a scientific team that made outstanding advances in bidirectional reflectance distribution modeling, directional thermal emission modeling, comprehensive experiments, and the understanding of spatial and temporal scale effects in remote sensing information, and of quantitative inversions utilizing remote sensing data. In addition to his broad research activities, he was noted for his humility and his dedication in making science more accessible for the general public. Here, the life and academic contributions of Xiaowen Li to the field of quantitative remote sensing science are briefly reviewed.

ACS Style

Qinhuo Liu; Guangjian Yan; Ziti Jiao; Qing Xiao; Jianguang Wen; Shunlin Liang; Jindi Wang; Crystal Schaaf; Alan Strahler. From Geometric-Optical Remote Sensing Modeling to Quantitative Remote Sensing Science—In Memory of Academician Xiaowen Li. Remote Sensing 2018, 10, 1764 .

AMA Style

Qinhuo Liu, Guangjian Yan, Ziti Jiao, Qing Xiao, Jianguang Wen, Shunlin Liang, Jindi Wang, Crystal Schaaf, Alan Strahler. From Geometric-Optical Remote Sensing Modeling to Quantitative Remote Sensing Science—In Memory of Academician Xiaowen Li. Remote Sensing. 2018; 10 (11):1764.

Chicago/Turabian Style

Qinhuo Liu; Guangjian Yan; Ziti Jiao; Qing Xiao; Jianguang Wen; Shunlin Liang; Jindi Wang; Crystal Schaaf; Alan Strahler. 2018. "From Geometric-Optical Remote Sensing Modeling to Quantitative Remote Sensing Science—In Memory of Academician Xiaowen Li." Remote Sensing 10, no. 11: 1764.

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: 11 February 2018 in Remote Sensing
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Topography complicates the modeling and retrieval of land surface albedo due to shadow effects and the redistribution of incident radiation. Neglecting topographic effects may lead to a significant bias when estimating land surface albedo over a single slope. However, for rugged terrain, a comprehensive and systematic investigation of topographic effects on land surface albedo is currently ongoing. Accurately estimating topographic effects on land surface albedo over a rugged terrain presents a challenge in remote sensing modeling and applications. In this paper, we focused on the development of a simplified estimation method for snow-free albedo over a rugged terrain at a 1-km scale based on a 30-m fine-scale digital elevation model (DEM). The proposed method was compared with the radiosity approach based on simulated and real DEMs. The results of the comparison showed that the proposed method provided adequate computational efficiency and satisfactory accuracy simultaneously. Then, the topographic effects on snow-free albedo were quantitatively investigated and interpreted by considering the mean slope, subpixel aspect distribution, solar zenith angle, and solar azimuth angle. The results showed that the more rugged the terrain and the larger the solar illumination angle, the more intense the topographic effects were on black-sky albedo (BSA). The maximum absolute deviation (MAD) and the maximum relative deviation (MRD) of the BSA over a rugged terrain reached 0.28 and 85%, respectively, when the SZA was 60° for different terrains. Topographic effects varied with the mean slope, subpixel aspect distribution, SZA and SAA, which should not be neglected when modeling albedo.

ACS Style

Dalei Hao; Jianguang Wen; Qing Xiao; Shengbiao Wu; Xingwen Lin; Baocheng Dou; DongQin You; Yong Tang. Simulation and Analysis of the Topographic Effects on Snow-Free Albedo over Rugged Terrain. Remote Sensing 2018, 10, 278 .

AMA Style

Dalei Hao, Jianguang Wen, Qing Xiao, Shengbiao Wu, Xingwen Lin, Baocheng Dou, DongQin You, Yong Tang. Simulation and Analysis of the Topographic Effects on Snow-Free Albedo over Rugged Terrain. Remote Sensing. 2018; 10 (2):278.

Chicago/Turabian Style

Dalei Hao; Jianguang Wen; Qing Xiao; Shengbiao Wu; Xingwen Lin; Baocheng Dou; DongQin You; Yong Tang. 2018. "Simulation and Analysis of the Topographic Effects on Snow-Free Albedo over Rugged Terrain." Remote Sensing 10, no. 2: 278.

Journal article
Published: 24 January 2018 in Remote Sensing
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The issue for the validation of land surface remote sensing albedo products over rugged terrain is the scale effects between the reference albedo measurements and coarse scale albedo products, which is caused by the complex topography. This paper illustrates a multi-scale validation strategy specified for coarse scale albedo validation over rugged terrain. A Mountain-Radiation-Transfer-based (MRT-based) albedo upscaling model was proposed in the process of multi-scale validation strategy for aggregating fine scale albedo to coarse scale. The simulated data of both the reference coarse scale albedo and fine scale albedo were used to assess the performance and uncertainties of the MRT-based albedo upscaling model. The results showed that the MRT-based model could reflect the albedo scale effects over rugged terrain and provided a robust solution for albedo upscaling from fine scale to coarse scale with different mean slopes and different solar zenith angles. The upscaled coarse scale albedos had the great agreements with the simulated coarse scale albedo with a Root-Mean-Square-Error (RMSE) of 0.0029 and 0.0017 for black sky albedo (BSA) and white sky albedo (WSA), respectively. Then the MRT-based model was preliminarily applied for the assessment of daily MODerate Resolution Imaging Spectroradiometer (MODIS) Albedo Collection V006 products (MCD43A3 C6) over rugged terrain. Results showed that the MRT-based model was effective and suitable for conducting the validation of MODIS albedo products over rugged terrain. In this research area, it was shown that the MCD43A3 C6 products with full inversion algorithm, were generally in agreement with the aggregated coarse scale reference albedos over rugged terrain in the Heihe River Basin, with the BSA RMSE of 0.0305 and WSA RMSE of 0.0321, respectively, which were slightly higher than those over flat terrain.

ACS Style

Xingwen Lin; Jianguang Wen; Qinhuo Liu; Qing Xiao; DongQin You; Shengbiao Wu; Dalei Hao; Xiaodan Wu. A Multi-Scale Validation Strategy for Albedo Products over Rugged Terrain and Preliminary Application in Heihe River Basin, China. Remote Sensing 2018, 10, 156 .

AMA Style

Xingwen Lin, Jianguang Wen, Qinhuo Liu, Qing Xiao, DongQin You, Shengbiao Wu, Dalei Hao, Xiaodan Wu. A Multi-Scale Validation Strategy for Albedo Products over Rugged Terrain and Preliminary Application in Heihe River Basin, China. Remote Sensing. 2018; 10 (2):156.

Chicago/Turabian Style

Xingwen Lin; Jianguang Wen; Qinhuo Liu; Qing Xiao; DongQin You; Shengbiao Wu; Dalei Hao; Xiaodan Wu. 2018. "A Multi-Scale Validation Strategy for Albedo Products over Rugged Terrain and Preliminary Application in Heihe River Basin, China." Remote Sensing 10, no. 2: 156.

Articles
Published: 04 May 2017 in International Journal of Digital Earth
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Upscaling ground albedo is challenged by the serious discrepancy between the heterogeneity of land surfaces and the small number of ground-based measurements. Conventional ground-based measurements cannot provide sufficient information on the characteristics of surface albedo at the scale of coarse pixels over heterogeneous land surfaces. One method of overcoming this problem is to introduce high-resolution albedo imagery as ancillary information for upscaling. However, due to the low frequency of updating of high-resolution albedo maps, upscaling time series of ground-based albedo measurements is difficult. This paper proposes a method that is based on the idea of conceptual universal scaling methodology for establishing a spatiotemporal trend surface using very few high-resolution images and time series of ground-based measurements for spatial-temporal upscaling of albedo. The construction of the spatiotemporal trend surface incorporates the spatial information provided by auxiliary remote sensing images and the temporal information provided by long time series of ground observations. This approach was illustrated by upscaling ground-based fine-scale albedo measurements to a coarse scale over the core study area in HiWATER. The results indicate that this method can characterize the spatiotemporal variations in surface albedo well, and the overall correlation coefficient was 0.702 during the study period.

ACS Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; DongQin You; Qiang Liu; Xingwen Lin. Forward a spatio-temporal trend surface for long-term ground-measured albedo upscaling over heterogeneous land surface. International Journal of Digital Earth 2017, 11, 470 -484.

AMA Style

Xiaodan Wu, Jianguang Wen, Qing Xiao, DongQin You, Qiang Liu, Xingwen Lin. Forward a spatio-temporal trend surface for long-term ground-measured albedo upscaling over heterogeneous land surface. International Journal of Digital Earth. 2017; 11 (5):470-484.

Chicago/Turabian Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; DongQin You; Qiang Liu; Xingwen Lin. 2017. "Forward a spatio-temporal trend surface for long-term ground-measured albedo upscaling over heterogeneous land surface." International Journal of Digital Earth 11, no. 5: 470-484.

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: 26 November 2016 in Remote Sensing
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Validation is mandatory to quantify the reliability of remote sensing products (RSPs). However, this process is not straightforward and usually presents formidable challenges in terms of both theory and real-world operations. In this context, a dedicated validation initiative was launched in China, and we identified a validation strategy (VS). This overall VS focuses on validating regional-scale RSPs with a systematic site-to-network concept, consisting of four main components: (1) general guidelines and technical specifications to guide users in validating various land RSPs, particularly aiming to further develop in situ sampling schemes and scaling approaches to acquire ground truth at the pixel scale over heterogeneous surfaces; (2) sound site-based validation activities, conducted through multi-scale, multi-platform, and multi-source observations to experimentally examine and improve the first component; (3) a national validation network to allow for comprehensive assessment of RSPs from site or regional scales to the national scale across various zones; and (4) an operational RSP evaluation system to implement operational validation applications. Research progress on the development of these four components is described in this paper. Some representative research results, with respect to the development of sampling methods and site-based validation activities, are also highlighted. The development of this VS improves our understanding of validation issues, especially to facilitate validating RSPs over heterogeneous land surfaces both at the pixel scale level and the product level.

ACS Style

Shuguo Wang; Xin Li; Yong Ge; Rui Jin; Mingguo Ma; Qinhuo Liu; Jianguang Wen; Shaomin Liu. Validation of Regional-Scale Remote Sensing Products in China: From Site to Network. Remote Sensing 2016, 8, 980 .

AMA Style

Shuguo Wang, Xin Li, Yong Ge, Rui Jin, Mingguo Ma, Qinhuo Liu, Jianguang Wen, Shaomin Liu. Validation of Regional-Scale Remote Sensing Products in China: From Site to Network. Remote Sensing. 2016; 8 (12):980.

Chicago/Turabian Style

Shuguo Wang; Xin Li; Yong Ge; Rui Jin; Mingguo Ma; Qinhuo Liu; Jianguang Wen; Shaomin Liu. 2016. "Validation of Regional-Scale Remote Sensing Products in China: From Site to Network." Remote Sensing 8, no. 12: 980.

Journal article
Published: 14 June 2016 in Remote Sensing of Environment
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To evaluate and improve the quality of coarse-pixel land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. The performance of albedo validation depends on the quality of ground-based albedo measurements at a corresponding coarse-pixel scale, which can be conceptualized as the “truth” value of albedo at coarse-pixel scale. In this paper, a sampling strategy based on multiple nodes using wireless sensor network (WSN) technology, WSN-based albedo observation, is proposed. The WSN nodes are distributed in an optimal layout determined by a sequential selection method based on the representativeness of each sensor. The WSN dataset in this study includes 6 nodes. A method of weighting is used to upscale WSN node albedo to a coarse-pixel scale. The weights for each node are calculated with the ordinary least squares (OLS) linear regression method. Compared with the multiple scale validation strategy, the dataset of WSN albedo “truth” at the coarse-pixel scale reveals a good quality both in stability and continuity. Application of this strategy is exemplified by validation of the MODIS 1 km albedo product.

ACS Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; Qiang Liu; Jingjing Peng; Baocheng Dou; Xiuhong Li; DongQin You; Yong Tang; Qinhuo Liu. Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: A case of MODIS albedo products preliminary validation over northern China. Remote Sensing of Environment 2016, 184, 25 -39.

AMA Style

Xiaodan Wu, Jianguang Wen, Qing Xiao, Qiang Liu, Jingjing Peng, Baocheng Dou, Xiuhong Li, DongQin You, Yong Tang, Qinhuo Liu. Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: A case of MODIS albedo products preliminary validation over northern China. Remote Sensing of Environment. 2016; 184 ():25-39.

Chicago/Turabian Style

Xiaodan Wu; Jianguang Wen; Qing Xiao; Qiang Liu; Jingjing Peng; Baocheng Dou; Xiuhong Li; DongQin You; Yong Tang; Qinhuo Liu. 2016. "Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: A case of MODIS albedo products preliminary validation over northern China." Remote Sensing of Environment 184, no. : 25-39.

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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The adjacency effect and non-uniform responses complicate the precise delimitation of the surface support of remote sensing data and their derived products. Thus, modeling spatial response characteristics (SRCs) prior to using remote sensing information has become important. A point spread function (PSF) is typically used to describe the SRCs of the observation cells from remote sensors and is always estimated in a laboratory before the sensor is launched. However, research on the SRCs of high-order remote sensing products derived from the observations remains insufficient, which is an obstacle to converting between multi-scale remote sensing products and validating coarse-resolution products. This study proposed a method that combines simulation and validation to establish SRC models of coarse-resolution albedo products. Two series of commonly used 500-m/1-km resolution albedo products, which are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data, were investigated using 30-m albedo products that provide the required sub-pixel information. The analysis proves that the size of the surface support of each albedo pixel is larger than the nominal resolution of the pixel and that the response weight is non-uniformly distributed, with an elliptical Gaussian shape. The proposed methodology is generic and applicable for analyzing the SRCs of other advanced remote sensing products.

ACS Style

Jingjing Peng; Qiang Liu; Lizhao Wang; Qinhuo Liu; Wenjie Fan; Meng Lu; Jianguang Wen. Characterizing the Pixel Footprint of Satellite Albedo Products Derived from MODIS Reflectance in the Heihe River Basin, China. Remote Sensing 2015, 7, 6886 -6907.

AMA Style

Jingjing Peng, Qiang Liu, Lizhao Wang, Qinhuo Liu, Wenjie Fan, Meng Lu, Jianguang Wen. Characterizing the Pixel Footprint of Satellite Albedo Products Derived from MODIS Reflectance in the Heihe River Basin, China. Remote Sensing. 2015; 7 (6):6886-6907.

Chicago/Turabian Style

Jingjing Peng; Qiang Liu; Lizhao Wang; Qinhuo Liu; Wenjie Fan; Meng Lu; Jianguang Wen. 2015. "Characterizing the Pixel Footprint of Satellite Albedo Products Derived from MODIS Reflectance in the Heihe River Basin, China." Remote Sensing 7, no. 6: 6886-6907.

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.

Journal article
Published: 26 May 2015 in Remote Sensing
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In rugged terrain, the accuracy of surface reflectance estimations is compromised by atmospheric and topographic effects. We propose a new method to simultaneously eliminate atmospheric and terrain effects in Landsat Thematic Mapper (TM) images based on a 30 m digital elevation model (DEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric products. Moreover, we define a normalized factor of a Bidirectional Reflectance Distribution Function (BRDF) to convert the sloping pixel reflectance into a flat pixel reflectance by using the Ross Thick-Li Sparse BRDF model (Ambrals algorithm) and MODIS BRDF/albedo kernel coefficient products. Sole atmospheric correction and topographic normalization were performed for TM images in the upper stream of the Heihe River Basin. The results show that using MODIS atmospheric products can effectively remove atmospheric effects compared with the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) model and the Landsat Climate Data Record (CDR). Moreover, superior topographic effect removal can be achieved by considering the surface BRDF when compared with the surface Lambertian assumption of topographic normalization.

ACS Style

Yanli Zhang; Xin Li; Jianguang Wen; Qinhuo Liu; Guangjian Yan. Improved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF. Remote Sensing 2015, 7, 6558 -6575.

AMA Style

Yanli Zhang, Xin Li, Jianguang Wen, Qinhuo Liu, Guangjian Yan. Improved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF. Remote Sensing. 2015; 7 (6):6558-6575.

Chicago/Turabian Style

Yanli Zhang; Xin Li; Jianguang Wen; Qinhuo Liu; Guangjian Yan. 2015. "Improved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF." Remote Sensing 7, no. 6: 6558-6575.

Journal article
Published: 21 May 2015 in Remote Sensing
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It remains a challenging issue to accurately estimate the fraction of absorbed photosynthetically-active radiation (FPAR) using remote sensing data, as the direct and diffuse radiation reaching the vegetation canopy have different effects for FPAR. In this research, a FPAR inversion model was developed that may distinguish direct and diffuse radiation (the DnD model) based on the energy budget balance principle. Taking different solar zenith angles and diffuse PAR proportions as inputs, the instantaneous FPAR could be calculated. As the leaf area index (LAI) and surface albedo do not vary in a short periods, the FPAR not only on a clear day, but also on a cloudy day may be calculated. This new method was used to produce the FPAR products in the Heihe River Basin with the Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI and surface albedo products as the input data source. The instantaneous FPAR was validated by using field-measured data (RMSE is 0.03, R2 is 0.85). The daily average FPAR was compared with the MODIS FPAR product. The inversion results and the MODIS FPAR product are highly correlated, but the MODIS FPAR product is slightly high in forest areas, which is in agreement with other studies for MODIS FPAR products.

ACS Style

Li Li; Yongming Du; Yong Tang; Xiaozhou Xin; Hailong Zhang; Jianguang Wen; Qinhuo Liu. A New Algorithm of the FPAR Product in the Heihe River Basin Considering the Contributions of Direct and Diffuse Solar Radiation Separately. Remote Sensing 2015, 7, 6414 -6432.

AMA Style

Li Li, Yongming Du, Yong Tang, Xiaozhou Xin, Hailong Zhang, Jianguang Wen, Qinhuo Liu. A New Algorithm of the FPAR Product in the Heihe River Basin Considering the Contributions of Direct and Diffuse Solar Radiation Separately. Remote Sensing. 2015; 7 (5):6414-6432.

Chicago/Turabian Style

Li Li; Yongming Du; Yong Tang; Xiaozhou Xin; Hailong Zhang; Jianguang Wen; Qinhuo Liu. 2015. "A New Algorithm of the FPAR Product in the Heihe River Basin Considering the Contributions of Direct and Diffuse Solar Radiation Separately." Remote Sensing 7, no. 5: 6414-6432.