Meeting Earth Observation Requirements for Global Agricultural Monitoring: An Evaluation of the Revisit Capabilities of Current and Planned Moderate Resolution Optical Earth Observing Missions

Abstract

Agriculture is a highly dynamic process in space and time, with many applications requiring data with both a relatively high temporal resolution (at least every 8 days) and fine-to-moderate (FTM < 100 m) spatial resolution. The relatively infrequent revisit of FTM optical satellite observatories coupled with the impacts of cloud occultation have translated into a barrier for the derivation of agricultural information at the regional-to-global scale. Drawing upon the Group on Earth Observations Global Agricultural Monitoring (GEOGLAM) Initiative's general satellite Earth observation (EO) requirements for monitoring of major production areas, Whitcraft et al. (this issue) have described where, when, and how frequently satellite data acquisitions are required throughout the agricultural growing season at 0.05°, globally. The majority of areas and times of year require multiple revisits to probabilistically yield a view at least 70%, 80%, 90%, or 95% clear within eight days, something that no present single FTM optical observatory is capable of delivering. As such, OPEN ACCESSRemote Sens. 2015, 7 1483there is a great potential to meet these moderate spatial resolution optical data requirements through a multi-space agency/multi-mission constellation approach. This research models the combined revisit capabilities of seven hypothetical constellations made from five satellite sensors-Landsat 7 Enhanced Thematic Mapper (Landsat 7 ETM+), Landsat 8 Operational Land Imager and Thermal Infrared Sensor (Landsat 8 OLI/TIRS), Resourcesat-2 Advanced Wide Field Sensor (Resourcesat-2 AWiFS), Sentinel-2A Multi-Spectral Instrument (MSI), and Sentinel-2B MSI-and compares these capabilities with the revisit frequency requirements for a reasonably cloud-free clear view within eight days throughout the agricultural growing season. Supplementing Landsat 7 and 8 with missions from different space agencies leads to an improved capacity to meet requirements, with Resourcesat-2 providing the largest incremental improvement in requirements met. The best performing constellation can meet 71%-91% of the requirements for a view at least 70% clear, and 45%-68% of requirements for a view at least 95% clear, varying by month. Still, gaps exist in persistently cloudy regions/periods, highlighting the need for data coordination and for consideration of active EO for agricultural monitoring. This research highlights opportunities, but not actual acquisition rates or data availability/access; systematic acquisitions over actively cropped agricultural areas as well as a policy which guarantees continuous access to high quality, interoperable data are essential in the effort to meet EO requirements for agricultural monitoring.

A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring

“…Recently, the COVE tool was used by Whitcraft et al [14] to simulate the number of observations provided by different combinations of medium resolution satellites (Landsat-7, Landsat-8, Sentinel-2A, Sentinel-2B, and Resourcesat-2) with respect to agricultural applications, from 60 • N to 60 • S, and for periods up to 180 days. The COVE tool models the orbits and coincident overpasses of multiple satellite missions using orbit and sensor models and satellite ephemeras information.…”

“…When remote sensing satellite orbits are designed, the satellite coverage may be considered in several ways including the number of observations in a given period and the revisit interval [7][8][9]. Previously, researchers have examined the number of observations in different periods for Landsat [10][11][12][13] and Sentinel-2 [14]. However, the revisit interval, i.e., the time period between consecutive observations of a surface location, has not been studied but is of considerable interest for terrestrial applications.…”

Self-Guided Segmentation and Classification of Multi-Temporal Landsat 8 Images for Crop Type Mapping in Southeastern Brazil

“…The disadvantage of Landsat relates to its low revisit frequency of 16 days (eight days if Landsat-7 and 8 are combined) [28]. Together with cloudiness, this may drastically reduce the number of high quality observations [29].…”

A Workflow for Automated Satellite Image Processing: from Raw VHSR Data to Object-Based Spectral Information for Smallholder Agriculture

“…Single satellite platforms cannot trivially satisfy such needs, especially where cloud presence is a limiting factor. For instance, [11] describes the observation requirements for a global agricultural monitoring activity and claims that no current satellite platform with fine-to-moderate spatial resolution can accommodate it. However, a synergistic use of data from multiple agencies and missions may meet the requirements; this leads to the idea of a virtual satellite constellation, which forces significant development in image analytics, especially in the harmonized use of Earth Observation information and the on-time availability of ready-to-use products.…”