Today, with massive flow of the spatial and non-spatial database, enormous field data collection with enhanced electronic protocols in agricultural research has led to assemblage of massive caches of digital information on agriculture that describe the context-options for technological as well as socio-economic interventions at multiple scales and scenarios.  However such tools and web services are often limited to certain geographical regions and do not exist for drylands in developing countries. In a bid to improve digital agricultural services in the dry areas, the International Center for Agricultural Research in Dry Areas (ICARDA) recognizes that Geoinformatics in agriculture is critical in obtaining adequate data for tackling food security and improving livelihoods, particularly in dry areas of the developing world that struggle with limited natural resources.  In order to make spatial information available at the finger tips in the era of smart phones and personal computations, the ICARDA developed number of geospatial tools and web portals for data access, visualization and sharing to help researcher and decision makers at various scales to influence agricultural research, programs, and policies. In this paper we discuss latest trends and advances in an integrated web based spatial data visualization tools and technology for agro-ecological research and application. The workflow uses the hybrid protocols for data storage/access (e.g., AWS, SAN), processing (e.g., numpy, rasterio and GDAL) and map server interface (e.g., ArcGIS online, OA APIs). An interactive end-user segment consists of Django, AngularJS, Open Layers and WDSL. System renders multiple spatial data to website and web services via Open Geospatial Consortium (OGC) standards, Web Mapping Service (WMS) for map images and Web Coverage Service (WCS) for raster data. Such user friendly map interface allows researchers to take into account of different factors such as land cover dynamics, cropping patterns and intensities, water use and availability, changing demographics, infrastructure, poverty, markets, climate change, and more.  Information generated can be used to assess vulnerable areas for possible pathways to increased resilience and mitigation of risks whether biophysical (land degradation and drought) or socioeconomic (price shocks or policy changes in land tenure).