Remote Sensing Reversion of Water Depths and Water Management for the Stopover Site of Siberian Cranes at Momoge, China

Abstract

Traditional water depth survey of waterbird habitats takes huge amount of labor, time and money. The optical remote sensing image from passive multispectral scanner has been widely employed to estimate water depth. We developed a water depth model based on the characteristics of visible and near infrared spectra of Landsat ETM+ image at Etoupao shallow wetland. The wetland is the largest stopover habitat of the critically-endangered Siberian Crane, which mainly feed on the tubers of Scirpus planiculmis and S. nipponicus. Water control is critical for maintaining tubers production and food availability for the crane. Multi-band approach is employed in the model, which effectively simulates water depth for the shallow wetland. The parameters of NDVI and GREEN in the model indicated that the vegetation growth and coverage affecting reflectance from water column change were uneven. Combined with observed water level data in the same day of image acquisition, the digital elevation model (DEM) for underwater terrain was generated. The findings provide a good reference to manage water level and water demand, and create suitable foraging habitats for the crane. The methods can be adapted for underwater terrain simulation and water management in waterbirds habitats, especially in the shallow heterogeneous wetlands.