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Gully erosion is widespread in central China's ecologically fragile loess plateau. However, research on the monitoring and evaluation of large-scale fine erosion is scarce. Here, we use the sentinel-1A imagery during a rainy season, using the small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) technology to calculate gully erosion for the largest loess plateau in China, the Dongzhiyuan tableland. The results showed that the average and cumulative subsidence rates of the whole study area are 9 mm/year and 6 mm/year respectively, while the subsidence within the gullies reached 160 mm/year and 70 mm/year, which was mainly caused by rainfall and landslides formed by groundwater softening slopes. In addition, erosion was more severe at the bottom of the gully closer to the lower reaches of the watershed, which may be related to the concentrated runoff downstream during rainfall. Interestingly, the erosion deformation was more intense on slopes 20m above the gully bottom caused by groundwater seepage. The results demonstrated the reliable capability of the SBAS-InSAR method in accurately assessing large-scale erosion deformation.

NDVI (Normalized Difference Vegetation Index) time series usually contain a lot of loud noise, which limits its further application. However, the existing filtering and reconstruction methods cannot effectively remove continuous loud noise, which is particularly obvious in cloudy areas. This paper proposes a Spatial-temporal Kriging improved Savitzky Golay filtering algorithm (TSK-SG) based on Spatial-temporal Kriging. By combining the quality factors in MODIS VI products to generate reference data, a Spatial-temporal Kriging variogram model is established and interpolated using the adjacent Spatial-temporal information. Finally, the fitting result is obtained by iterating Savitzky Golay (S-G) filtering based on the quality weight. The NDVI time series curve reconstructed by this method can effectively suppress noise and has a better spatial reconstruction effect, which can better reflect the phenological characteristics of different types of crops.

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Gully erosion is widespread in central China's ecologically fragile loess plateau. However, research on the monitoring and evaluation of large-scale ne erosion is scarce. Here, we use the sentinel-1A imagery during a rainy season, using the small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) technology to calculate gully erosion for the largest loess plateau in China, the Dongzhiyuan tableland. The results showed that the average and cumulative subsidence rates of the whole study area are 9 mm/year and 6 mm/year respectively, while the subsidence within the gullies reached 160 mm/year and 70 mm/year, which was mainly caused by rainfall and landslides formed by groundwater softening slopes. In addition, erosion was more severe at the bottom of the gully closer to the lower reaches of the watershed, which may be related to the concentrated runoff downstream during rainfall. Interestingly, the erosion deformation was more intense on slopes 20m above the gully bottom caused by groundwater seepage. The results demonstrated the reliable capability of the SBAS-InSAR method in accurately assessing large-scale erosion deformation. IntroductionGully erosion is the low subsidence or sudden sinking of land around a gully due to natural processes (Valentin et al. 2005). It is one of the most dangerous geological hazards (Di Stefano and Ferro 2011) and has signi cant environmental adverse effects (Jin et al. 2021). Furthermore, it increases the likelihood of other geological phenomena like debris ows, and landslides, which can lead to casualties and economic loss, particularly amongst the most vulnerable (Guan et al. 2021;Guo et al. 2021;Jiang et al. 2021b).Interest in gully erosion has increased recently (Garcia-Ruiz 2010) as new tools have been developed for their assessment, such as Global Positioning System (GPS), Unmanned Aerial Vehicle (UAV), and Automated-ground-surveying (Conforti et al. 2011;d'Oleire-Oltmanns et al. 2012;Wu and Cheng 2005). However, these tools allow for only discrete, and relatively sparse measurements in small areas, obtained at high costs that compound with time. Another option is considering Light Detection and Ranging (LIDAR) (Castillo et al. 2012), which is more accurate and can be done quickly, but usually, it is done on a small scale. It places the sensor at a distance that spans usually less than a kilometer from the target resulting in limiting the scale of the assessment. This is a critical shortcoming as gully erosion can be conditioned by processes at the mesoscale (Haregeweyn et al. 2017) making studies at local instances of limited impact. Rather it is critical to monitor deformation in the vicinities of gullies in wide areas (960km 2 ). Synthetic Aperture Radar (SAR) Satellite Images are better suited for area-wide gully erosion assessments. They can be sourced free of charge; there is no need to deploy sensors on the eld; they are available at a relatively high spatial resolution (pixel values ranging between 40 and 80m for the Sentinel Constellation deployed by...