Soil moisture is an essential metric to understand crop condition throughout the growing season. Collecting soil moisture data by field observation is time-consuming and labor-intensive, especially for a CONUS geographic coverage. NASA’s SMAP Mission has been providing global mapping of soil moisture and freeze/thaw state at high spatial and temporal resolutions since 2015. However, handling SMAP data could be difficult for users who do not have technical background. Creating a soil moisture map with SMAP data contains a series of steps, including data retrieval, reformatting, reprojection, mosaicking, and clipping. Moreover, users need to install special software and configure the system environment to further perform geospatial analysis for SMAP data. To facilitate using of SMAP data, this paper presents a cloud-based web geoprocessing service system for disseminating and analyzing SMAP data products. This web service system serves a variety of data products, including 9-km SMAP Level-4 data, 1-km SMAP Hybrid data, and MODIS-based vegetation index data. The development of the geoprocessing services is based on the three-layer system architecture composed of an infrastructure layer, a data layer, and a service layer. The infrastructure layer manages the fundamental computing resources and offers the Platform as a Service (PaaS) to the data layer and service layer. The data layer stores all raw raster and vector data offered by the web service. The service layer handles all geospatial web services including map services and geoprocessing services. Both the data layer and service layer are deployed as instances of virtual machines on the top of the infrastructure layer. The system offers a variety of geoprocessing operations in the OGC Web Processing Service (WPS) interface standard. These operations are grouped into get file processes, geospatial statistics processes, map production processes, time-series profile processes, image composite processes, and miscellaneous processes. The proposed geoprocessing services have been implemented as a part of the Crop Condition and Soil Moisture Analytics (Crop-CAMSA) web service system and are interoperable with other web applications. The experiment result shows the geoprocessing service can significantly simplify the procedures of dissemination and analysis of SMAP data.