@article{oai:rakuno.repo.nii.ac.jp:00006774,
 author = {HOSHINO, Buho and 星野, 仏方 and Tian, Ying and Shima, Keita and Riga, Su and Enkhtuvshin, Zoljarga and McCarthy, Christopher and Purevtseren, Myagmartseren},
 issue = {1},
 journal = {IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium},
 month = {Oct},
 note = {Article, The Gobi Desert in Mongolia is characterized by sparse and patchy vegetation, interspersed with essentially bare areas. The vegetation pattern is typically formed by perennial shrubs, grasses or annually-herbaceous plant overlying a matrix composed of bare soil. Vegetation patterns, most broadly, refer to the spatial organization of vegetation in a landscape. However, since the plants in the Gobi Desert are sparsely distributed over a vast bare field, it is extremely difficult to accurately observe from satellite imagery. This is because reflectance of dry soil is very high and the reflectance of slightly distributed plants is eliminated by soil reflection. This study solves this problem by using field surveys and methods for combining different satellite sensor data and spectral un-mixing analysis. As a result, the pixel NDVI value of desert plants shows a smaller value than the ground measurement. It is shown that the fraction of the vegetation endmember after pixel un-mixing has a remarkably high correlation with the field measured values (where, R2=0.51 between NDVI of Landsat 8 imagery original pixels and un-mixed pixels and R2=0.79 between plants coverage of field measurement and un-mixed pixels percentage of vegetation endmembers).},
 pages = {1--4},
 title = {Remotely Sensed Method for Detection of Spatial Distribution Pattern of Dryland Plants in Water Limited Ecosystem},
 volume = {2020},
 year = {2020}
}