Combined Use of Landsat-8 and Sentinel-2 Data for Agricultural Monitoring
Abstract
Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). Here, we explore the combined use of Landsat-8 and Sentinel-2 data for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2 data improves both winter crop mapping and winter wheat yield assessment.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMEP22C..07S
- Keywords:
-
- 0416 Biogeophysics;
- BIOGEOSCIENCES;
- 0480 Remote sensing;
- BIOGEOSCIENCES