Land cover mapping based on time‐series MODIS‐NDVI using dynamic time warping approach a case‐study of the agricultural pastoral ecotone of northern China

To curb land degradation, a series of ecological restoration projects have been carried out since 1999, leading to dramatic land cover change (LCC) in the agricultural pastoral ecotone of northern China (APENC). To date, there is still lack of timely and accurate land cover (LC) information for management and assessment actions. This paper presents a LC mapping scheme to map annual LC information based on dynamic time warping (DTW) approach and time-series MODIS-NDVI product for the APENC. The DTW approach was optimized firstly based on the change of vegetation phenology phase. Next, typical reference time-series curves set of different LC types were established and pixel-wise similarity was examined to identify the LC type. Before that, the reconstruction of time-series MODIS-NDVI was performed using harmonic analysis of time-series and reconstruction accuracy was evaluated quantitatively at a regional scale. Results showed that the gap error was relatively large for the high vegetation cover areas while it might be ignored for the moderate and low vegetation cover areas. The overall accuracy of LC mapping in year 2010 (LC-2010) was 77.89% and kappa coefficient reached 0.71, which suggested that LC mapping scheme could extract LC information with high accuracy. The producer's accuracy ranged between 69.83% (grasslands) and 100% (water body), while the user's accuracy changed from 58% (built-up) to 86% (forest). The overall spatial agreement between LC-2010 and GlobaLand30-2010 was about 64.44%. The total area of forests, croplands, water body and built-up exhibited an increasing trend while the contrary trend were found for the grasslands and bare land during the 2001-2017. These LC maps are valuable for research the land degradation investigation and monitoring, benefit evaluation of ecological restoration projects and effect of LCC on surface hydrothermal process in APENC.