| Title | UNVI-Based Time Series for Vegetation Discrimination Using Separability Analysis and Random Forest Classification |
| Authors | Liu, Hualiang Zhang, Feizhou Zhang, Lifu Lin, Yukun Wang, Siheng Xie, Yefeng |
| Affiliation | Peking Univ, Sch Earth & Space Sci, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China Shihezi Univ, Key Lab Oasis Ecoagr, Xinjiang Prod & Construct Grp, Shihezi 832003, Peoples R China Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China Univ Chinese Acad Sci, Beijing 100049, Peoples R China China Acad Space Technol, Beijing Inst Spacecraft Syst Engn, Beijing 100094, Peoples R China Peking Univ, Coll Urban & Environm Sci, Beijing 100871, Peoples R China |
| Keywords | LAND-COVER CLASSIFICATION CROP CLASSIFICATION FEATURE-SELECTION MODIS DATA SATELLITE INDEX ACCURACY TM STABILITY NDVI |
| Issue Date | 1-Feb-2020 |
| Publisher | REMOTE SENSING |
| Abstract | Land cover data is crucial for earth system modelling, natural resources management, and conservation planning. Remotely sensed time-series data capture dynamic behavior of vegetation, and have been widely used for land cover mapping. Temporal profiles of vegetation index (VI), especially normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), are the most used features derived from time-series spectral data. Whether NDVI or EVI is optimal to generate temporal profiles has not been evaluated. The universal normalized vegetation index (UNVI), a relatively new index with all spectral bands incorporated, has been proved to be more effective than several commonly used satellite-derived VIs in some application scenarios. In this study, we explored the ability of UNVI time series for discriminating different vegetation types in Chaoyang prefecture, northeast China, in comparison with normalized NDVI, EVI, triangle vegetation index (TVI), and tasseled cap transformation greenness (TCG). These five indices were calculated using Landsat 8 surface reflectance data, and two comparative experiments were conducted. The first experiment analyzed class separabilities using pairwise JM (Jeffries-Matusita) distance as indicator, and the results showed that UNVI was superior to EVI, TVI, and TCG, and almost equivalent to NDVI, especially during the peak of vegetation growing season and for the most indistinguishable vegetation pair broadleaf and shrubs. The second experiment compared the vegetation classification accuracies using the features of these VI temporal profiles and the corresponding phenological parameters, and the results showed that UNVI can better classify the five major vegetation in Chaoyang prefecture than other four indices. Therefore, we conclude that UNVI time series has considerable potential for regional land cover mapping, and we recommend that the use of the UNVI is considered in the future time series related studies. |
| URI | http://hdl.handle.net/20.500.11897/586394 |
| DOI | 10.3390/rs12030529 |
| Indexed | SCI(E) Scopus EI |
| Appears in Collections: | 地球与空间科学学院 城市与环境学院 |
