An Effective Method for Snow-Cover Mapping of Dense Coniferous Forests in the Upper Heihe River Basin Using Landsat Operational Land Imager Data

Xiao-Yan Wang, Jian Wang, Zhi-Yong Jiang, Hong-Yi Li, Xiao-Hua Hao
2015 Remote Sensing  
The Normalized Difference Snow Index (NDSI) is an effective index for snow-cover mapping at large scales, but in forested regions the identification accuracy for snow using the NDSI is low because of forest cover effects. In this study, typical evergreen coniferous forest zones on Qilian Mountain in the Upper Heihe River Basin (UHRB) were chosen as example regions. By analyzing the spectral signature of snow-covered and snow-free evergreen coniferous forests with Landsat Operational Land Imager
more » ... (OLI) data, a novel spectral band ratio using near-infrared (NIR) and shortwave infrared (SWIR) bands, defined as (ρ nir´ρswir )/(ρ nir + ρ swir ), is proposed. Our research shows that this band ratio, named the normalized difference forest snow index (NDFSI), can be used to effectively distinguish snow-covered evergreen coniferous forests from snow-free evergreen coniferous forests in UHRB. The Normalized Difference Snow Index (NDSI) is widely used for snow-cover mapping at large scales [18] . However, research has shown that when the underlying surface consists of vegetation, especially dense forest, applying the NDSI to identify snow leads to low accuracy [19] . In recent years, additional mapping methods for snow-covered forests have been developed. Vikhamar and Solberg in Norway used a linear spectral mixture model, which includes end members for snow, conifers, braches of leafless deciduous trees, and snow-free ground to calculate fractional snow cover [10] . However, this model needs in situ reflectance measurements, surface area proportions, and the individual tree species as input factors. Metsämäki et al. proposed the SCAmod algorithm for fractional snow-cover mapping of boreal forests [20] . This method is based on a semi-empirical reflectance model, and the model essentially depends on the apparent forest transmittance, which must be determined in advance for each unit area. Wang et al. presented a method to retrieve snow information for the coniferous forests of Tianshan Mountain using Multi-angle Imaging SpectroRadiometer (MISR) data [21] . Their results indicate that multi-angle remote sensing has the potential to address snow-mapping problems in forested areas, but lacks quantitative analysis. The Heihe River Basin (HRB; see Section 2) is a typical inland river basin in an arid area of western China. The Upper HRB (UHRB) is rich in water resources in the form of snow, which represents the majority of the water resources for the entire HRB [22] . A slight change in snow cover in the UHRB would greatly affect the water budget of the Heihe River, thus triggering a chain reaction that would affect agriculture and vegetation in the entire basin area [23] . So, the accuracy of snow-cover mapping is very important to the Heihe River hydrological process. The objective of this work is to improve the accuracy of snow-cover estimates for the forests of the UHRB. To this end, we present a simplified reflectance model suitable for snow-cover mapping in evergreen coniferous forests. The study area and the data are described in Section 2. The methodology is presented in Section 3. The experiment and verification are in Section 4. The discussion is in Section 5. Finally, the conclusion of this study is summarized in Section 6.
doi:10.3390/rs71215882 fatcat:2rllc5wck5fl5k46bcvjx3mffq