# Mapping Rice Fields in Urban Shanghai, Southeast China, Using Sentinel-1A and Landsat 8 Datasets
## 5 Conclusions  
Globally, little research effort has been directed towards urban agricultural mapping, where land dedicated to rice cultivation in particular, is increasingly becoming smaller and fragmented by other land-uses. With rice production forming an integral part in meeting global food demands, it is important to not only monitor rice cultivation at large scales, but also those at relatively smaller scales such as in urban areas. Furthermore, rice cultivation is at the center stage of global environmental debates involving greenhouse gas emissions and water resource allocation. However, the contribution of urban rice agriculture to the above environmental issues is largely ignored due to limited urban agricultural information. In an attempt to fill some of the knowledge gaps in agricultural mapping in urban landscapes, this study is conducted to test the potential of integrating the new Sentinel-1A SAR data with Landsat 8 optical data for urban rice mapping. In this study, we have noted the VH polarization of Sentinel-1A to be the optimal polarization for rice field mapping as it exhibited the most sustained increase in the temporal backscatter of rice, relative to the nearly uniform temporal backscatter profiles of the other land-cover classes. Using a two-class separability measure, the VH polarization showed better inter-class discrimination ability, and was thus combined with NDVI and MNDWI images in our proposed rice mapping algorithm. With the introduction of NDVI and MNDWI, overall classification accuracy increased from 79.7% to 85.0%, and the Kappa statistic from 0.73 to 0.81. The slight increase in overall classification accuracy (5.3%) has demonstrated the added value of limited optical data to the more available radar data in cloud-prone tropics and subtropics for land-cover mapping. We strongly suppose that with more temporal optical data, the potential of SAR data in paddy rice mapping will be fully realized. The increase in Rice user's accuracy (reduction in commission errors) with the addition of these two optical indices confirms the operational applicability of integrating the new Sentinel-1A data with optical data for rice mapping in subtropical and highly heterogeneous landscapes. It can be observed in Figure 7 that the rice parcels are located in the peripheral areas of the study site. This indicates the gradual shift of rice cultivation to the urban fringe and peri-urban as a consequence of urban expansion and industrialization. Additionally, the intensification of urban agricultural land-uses such as vegetable gardening, fruit farming and aquaculture has reduced the amount of land allocated to rice cultivation. Apart from providing better rents than rice, perishable goods such as vegetables, fruits and fish require closer proximity to urban markets and consumers. Hence, rice fields are increasingly becoming smaller and fragmented by other agricultural land-uses in urban areas such as Shanghai. However, rice being a major staple food means its cultivation is still central in the attainment of global food security and in urban areas could not only meet food demands at household levels but also provide an alternative employment for unskilled or urban surplus labor. Even though our study has only mapped rice fields at a single time point (2015), our results could be instrumental in updating previous records while providing a basis for revealing the spatio-temporal dynamics of rice cultivation in urban Shanghai and its potential impacts on food availability, greenhouse gas emissions, water resource utilization and land-use management. This study could be regarded as one of, if not the first, to test the operational applicability of integrating the new Sentinel-1A data with Landsat 8 data for mapping smallholder rice fields in an urban landscape at a district scale, providing details of individual rice field boundaries.