The increasing frequency and severity of extreme climatic events and their impacts are
being realized in many regions of the world, particularly in smallholder crop and livestock …

Geospatial big data plays a major role in the era of big data, as most data today are
inherently spatial, collected with ubiquitous location-aware sensors such as mobile apps …

Soil moisture is an essential parameter to understand crop conditions throughout the
growing season. Collecting soil moisture data by field observation is labor-intensive …

Abstract Google Earth Engine (GEE) is an ideal platform for large-scale geospatial
agricultural and environmental modeling based on its diverse geospatial datasets, easy-to …

The remote-sensing based Flood Crop Loss Assessment Service System (RF-CLASS) is a
web service based system developed and managed by the Center for Spatial Information …

AI (artificial intelligence)-based analysis of geospatial data has gained a lot of attention.
Geospatial datasets are multi-dimensional; have spatiotemporal context; exist in disparate …

As an important tool for air quality simulation, the Community Multiscale Air Quality (CMAQ)
model is widely used in the environmental modeling community. However, setting up and …

Abstract In recent decades, Earth Observation (EO) systems have seen remarkable
technological advancements, leading to a surge in Earth-orbiting satellites capturing EO …

Cloud technology and services provide a convenient platform for managing large scale
watershed modeling studies, such as probabilistic studies or modeling campaigns requiring …

Scientific irrigation scheduling aims to solve the on-farm allocation of water, deciding
whether or not to irrigate, when, and determining the amount. Studies conducted in various …