A Two-Step Filtering approach for detecting maize and soybean phenology with time-series MODIS data

By Toshihiro Sakamoto, Brian D. Wardlow, Anatoly A. Gitelson, Shashi B. Verma, A. Suyker, Timothy J. Arkebauer. 2010

322 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/34b387a6671daf4e6d2a19100c3e7a50fd462089

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. J. Ivan Ortiz-Monasterio
2. David B. Lobell
3. V. Sohu
4. A. Sibley

In Environmental Engineering

1. J. Ivan Ortiz-Monasterio
2. David B. Lobell
3. V. Sohu
4. A. Sibley

Citations in the corpus

• Satellite detection of earlier wheat sowing in India and implications for yield trends (2013, background): “Sakamoto et al. (2010) provide good evidence of the agreement between MODIS derived phenology estimates and metrics of crop development given at the level of agricultural statistical districts by the National Agricultural Statistics Service.”
• Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources (2020, background): “First, we defined the inflection and maximum points of the LAI time series as the specific timing of key phenological stages for different crops (Sakamoto et al 2005, 2010, Sakamoto 2018).”