# Near Real-Time Irrigation Detection at Plot Scale Using Sentinel-1 Data
## 3 Methodology
### Optical Normalized Differential Vegetation Index (NDVI) Filter  
During the sowing or harvesting periods, the cropland plots usually encounter an increase in the surface roughness due to soil work. In fact, the backscattered radar signal strongly depends on the geometric characteristics such as the surface roughness that is usually expressed by the height root mean square (_Hrms_). The _Hrms_ is the standard deviation of surface height (root mean square) which specifies the vertical scale of surface roughness. Several studies have discussed the sensitivity of the radar backscattering signal to the surface roughness ([PERSON] et al., 2018; [PERSON] et al., 2018; [PERSON] et al., 2018). [PERSON] et al. (2018) reported that a difference of 4 dB could be observed between backscattering signal from smooth surface (_Hrms_ = 0.5 cm) and rough surfaces (_Hrms_ = 3 cm). Therefore, between two near-date SAR acquisitions, an increase in the surface roughness could cause an increase in the backscattering coefficient. This increase is related to the change of the geometrical characteristics of the soil and not to the change of the water content (irrigation or rainfall). To overcome this limitation, an additional optical filter is suggested in order to better distinguish irrigation peaks from soil works such as sowing or harvesting.  
Generally, irrigation activities must occur during a crop-growing cycle. This means that irrigation must be followed by a development of the vegetation cycle. When croplands receive water, high soil moisture causes better photosynthesis resulting in an increase in the leaf area index (LAI) valuesand therefore an increase in the NDVI values [6]. Therefore, we consider that an irrigation event should be followed by the development of NDVI values. For this reason, a post processing filter is proposed to eliminate some false detected irrigation events due to soil work. At each plot and for each detected irrigation event (at a given SAR date), we first obtain the difference between the NDVI value at the detected irrigation event and the next NDVI value of the next optical image (after 20 to 30 days according to cloud limitation):  
\[\Delta NDVI=NDVI_{li}-NDVI_{li+(20\text{ {to 30 days}})} \tag{4}\]  
where \(NDVI_{li}\) is the NDVI value at the current SAR date and \(NDVI_{li+(20\text{ {to 30 days}})}\) is the NDVI value one month later.  
The \(\Delta NDVI\) value is considered as a vegetation indicator which helps in detecting whether an increase of the NDVI values is observed or not (growing cycle) after the probable detected irrigation event. The filter suggests that if the \(NDVI_{li}\) value is less than 0.4 (bare soil conditions with small vegetation cover) and \(\Delta NDVI\leq 0.1\), then the point is a falsely detected irrigation point and is eliminated. For \(NDVI_{li}\) greater than 0.4, the filter is discarded because in the presence of vegetation the existence of irrigation event is more probable. This filter ensures that if the bare soil condition is permanent and a vegetation growth cycle does not exist (or was in a decreasing stage), then the detected event is most likely to be a soil work point and not an irrigation point. However, this filter is a post-processing filter that can be applied after obtaining another NDVI image after 20 to 30 days.