Observing giant panda habitat and forage abundance from space

Giant pandas are obligate bamboo grazers. The bamboos favoured by giant
pandas are typical forest understorey plants. Therefore, the availability and
abundance of understorey bamboo is a key factor in determining the quantity
and quality of giant panda food resources. However, there is little or no
information about the spatial distribution or abundance of bamboo underneath
the forest canopy, due to the limitations of traditional ground survey and
remote sensing classification techniques. In this regard, the development of
methods that can predict the understorey bamboo spatial distribution and cover
abundance is critical for an improved understanding of the habitat, foraging
behaviour and distribution of giant pandas, as well as facilitating an optimal
conservation strategy for this endangered species.
The objectives of this study were to develop innovative methods in remote
sensing and GIS for estimating the giant panda habitat and forage abundance,
and to explain the altitudinal migration and the spatial distribution of giant
pandas in the fragmented forest landscape.
It was concluded that 1) the vegetation indices derived from winter (leaf-off)
satellite images can be successfully used to predict the distribution of evergreen
understorey bamboo in a deciduous-dominated forest, 2) winter is the optimal
season for quantifying the coverage of evergreen understorey bamboo in a
mixed temperate forest, regardless of the classification methods used, 3) a
higher mapping accuracy for understorey bamboo in a coniferous-dominated
forest can be achieved by using an integrated neural network and expert system
algorithm, 4) the altitudinal migration patterns of sympatric giant pandas and
golden takins are related to satellite-derived plant phenology (a surrogate of
food quality) and bamboo abundance (a surrogate of food quantity), 5) the
driving force behind the seasonal vertical migration of giant pandas is the
occurrence of bamboo shoots and the temperature variation along an altitudinal
gradient, 6) the satellite-derived forest patches occupied by giant pandas were
significantly larger and more contiguous than patches where giant pandas were
not recorded, indicating that giant pandas appear sensitive to patch size and
isolation effects associated with forest fragmentation.
Overall, the study has been shown the potential of satellite remote sensing to
map giant panda habitat and forage (i.e., understorey bamboo) abundance. The
results are important for understanding the foraging behaviour and the spatial
distribution of giant pandas, as well as the evaluation and modelling of giant
panda habitat in order to guide decision-making on giant panda conservation.