Evaluating Spatial Heterogeneity of Land Surface Hydrothermal Conditions in the Heihe River Basin

2020 ◽  
Vol 30 (5) ◽  
pp. 855-875
Author(s):  
Yuan Zhang ◽  
Shaomin Liu ◽  
Xiao Hu ◽  
Jianghao Wang ◽  
Xiang Li ◽  
...  
2018 ◽  
Vol 10 (12) ◽  
pp. 2045 ◽  
Author(s):  
Xiaodan Wu ◽  
Jianguang Wen ◽  
Qing Xiao ◽  
Dongqin You ◽  
Baocheng Dou ◽  
...  

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.


2011 ◽  
Vol 26 (8) ◽  
pp. 1263-1269 ◽  
Author(s):  
Xinping Luo ◽  
Keli Wang ◽  
Hao Jiang ◽  
Jia Sun ◽  
Qingliang Zhu

2021 ◽  
Vol 13 (3) ◽  
pp. 362
Author(s):  
Xiuyi Wu ◽  
Wenping Yu ◽  
Jinan Shi ◽  
Mingguo Ma ◽  
Xiaolu Li ◽  
...  

Capturing the spatial heterogeneity and characteristic scale is the key to determining the spatial patterns of land surfaces. In this research, the core observation area of the middle reaches of the Heihe River Basin was selected as the study area, and the scale identification of several typical objects was carried out by implementing experiments on moderate- and high-resolution remotely sensed ASTER and CASI NDVI images. The aim was to evaluate the potential of the local variance and semivariance analysis to characterize the spatial heterogeneity of objects, track their changes with scale, and obtain their scales. Our results show that natural objects have multiscale structures. For a single object with a recognizable size, the results of the two methods are relatively consistent. For continuously distributed samples of indistinctive size, the scale obtained by the local variance is smaller than that obtained by the semivariance. As the image resolution becomes coarser and the research scopes expand, the scales of objects are also increasing. This article also indicates that with a small research area of uniform objects, the local variance and semivariance are easy to facilitate researchers to quickly select the appropriate spatial resolution of remote sensing data according to the research area.


2017 ◽  
Vol 9 (2) ◽  
pp. 152 ◽  
Author(s):  
Xiaoying Ouyang ◽  
Dongmei Chen ◽  
Si-Bo Duan ◽  
Yonghui Lei ◽  
Youjun Dou ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document