Phenology–Gross Primary Productivity (GPP) Method for Crop Information Extraction in Areas Sensitive to Non-Point Source Pollution and Its Influence on Pollution Intensity

The excessive use of pesticides and fertilizers during agricultural production causes water pollution, which is an important type non-point source pollution (NSP). Large amounts harmful substances, such as nitrogen phosphorus, flow into surface along with farmland runoff, leading to eutrophication other problems. However, the pollutant discharge capacity different types cultivated land varies greatly. Areas sensitive NSP are areas rich crop types, large spatial differences in growth, complex planting patterns. These factors can cause fertilizer used absorbed by crops influence emission intensity pollutants. mapping reflect distribution lands’ it provide a basis for control. when estimating intensity, existing methods generally treat category ignore how conditions impact intensity. Remote sensing technology enables classification monitoring ground objects, geographical data mapping. In this study, we phenology–GPP (gross primary productivity) method extract Yuecheng reservoir catchment area from Sentinel-2 remote images overall accuracy reached 85%. Moderate resolution imaging spectroradiometer (MODIS) GPP were simulate growth. Finally, new model that more suitable was obtained combining amount models. findings study highlight distributions between total phosphorous; they also means improve estimations.