A rapid model (Cov_psdi) for winter wheat mapping in fallow rotation area using modis ndvi time-series satellite observations: The case of the heilonggang region

Zhang，Xiaoyuan1,2; Liu，Kai2; Wang，Shudong2; Long，Xin3; Li，Xueke4

2021-12-01

10.3390/rs13234870

Remote Sensing   影响因子和分区

2072-4292

Rapid and accurate monitoring of spatial distribution patterns of winter wheat over a long period is of great significance for crop yield prediction and farmland water consumption estimation. However, weather conditions and relatively long revisit cycles often result in an insufficient number of continuous medium-high resolution images over large areas for many years. In addition, the cropland pattern changes frequently in the fallow rotation area. A novel rapid mapping model for winter wheat based on the normalized difference vegetation index (NDVI) time-series coefficient of variation (NDVI_COV) and peak-slope difference index (PSDI) is proposed in this study. NDVI_COV uses the time-series index volatility to distinguish cultivated land from background land-cover types. PSDI combines the key growth stages of winter wheat phenology and special bimodal characteristics, substantially reducing the impact of abandoned land and other crops. Taking the Heilonggang as an example, this study carried out a rapid mapping of winter wheat for four consecutive years (2014–2017), and compared the proposed COV_PSDI with two state-of-the-art methods and traditional methods (the Spectral Angle Mapping (SAM) and the Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA)). The verification results revealed that the COV_PSDI model improved the overall accuracy (94.10%) by 4% compared with the two state-of-art methods (90.80%, 89.00%) and two traditional methods (90.70%, 87.70%). User accuracy was the highest, which was 93.74%. Compared with the other four methods, the percentage error (PE) of COV_PSDI for four years was the lowest in the same year, with the minimum variation range of PE being 1.6–3.6%. The other methods resulted in serious overestimation. This demonstrated the effectiveness and stability of the method proposed in the rapid and accurate extraction of winter wheat in a large area of fallow crop rotation region. Our study provides insight for remote sensing monitoring of spatiotemporal patterns of winter wheat and evaluation of “fallow rotation” policy implementation.

Coefficient of variation Fallow rotation MODIS NDVI Time-series Winter wheat mapping

SCI ; EI

英语

其他

National Natural Science Foundation of China[41907191,41671362] ; Shenzhen Science and Technology Innovation Committee[JCYJ20190809144601730] ; Special Fund for Transformation of Scientific and Technological Achievements in Inner Mongolia Autonomous Region[2021CG0045]

Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology

Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology

WOS:000734601300001

MDPI

20215011300645

Crops ; Iterative methods ; Land use ; Photomapping ; Radiometers ; Remote sensing ; Rotation ; Water supply

Urban and Regional Planning and Development:403 ; Surveying:405.3 ; Water Supply Systems:446.1 ; Photography:742.1 ; Agricultural Products:821.4 ; Numerical Methods:921.6 ; Mathematical Statistics:922.2 ; Mechanics:931.1 ; Radiation Measuring Instruments:944.7

2-s2.0-85120707209

Scopus

1.School of Earth Sciences and Resources,China University of Geosciences,Beijing,100083,China
2.Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing,100094,China
3.Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
4.Institute at Brown for Environment and Society,Brown University,Providence,02912,United States

Zhang，Xiaoyuan,Liu，Kai,Wang，Shudong,et al. A rapid model (Cov_psdi) for winter wheat mapping in fallow rotation area using modis ndvi time-series satellite observations: The case of the heilonggang region[J]. Remote Sensing,2021,13(23).

Zhang，Xiaoyuan,Liu，Kai,Wang，Shudong,Long，Xin,&Li，Xueke.(2021).A rapid model (Cov_psdi) for winter wheat mapping in fallow rotation area using modis ndvi time-series satellite observations: The case of the heilonggang region.Remote Sensing,13(23).

Zhang，Xiaoyuan,et al."A rapid model (Cov_psdi) for winter wheat mapping in fallow rotation area using modis ndvi time-series satellite observations: The case of the heilonggang region".Remote Sensing 13.23(2021).