Publications

Bartalev, SA; Plotnikov, DE; Loupian, EA (2016). Mapping of arable land in Russia using multi-year time series of MODIS data and the LAGMA classification technique. REMOTE SENSING LETTERS, 7(3), 269-278.

Abstract
The sustainable agriculture requires a regular country-wide update of information on the status and extension of arable land in Russia. The arable land mapping method is developed based on multi-year time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data. The method exploits differences between the intra- and inter-annual changes in the spectral reflectance of arable land and the corresponding changes for other land cover types. It involves a set of satellite data-derived phenological metrics generated using a 6years long time series of the perpendicular vegetation index (PVI). The approach utilizes the Locally Adaptive Global Mapping Algorithm (LAGMA), which is a supervised classification technique accounting for the spatial variability of intra-classes spectral properties. The method has been applied to produce a uniform time series of comparable annual arable land maps for Russia at 250m spatial resolution for the years 2005-2013. Countrywide arable land area trends over the above time series were found to be consistent with official statistics (ROSSTAT).The mapping result has been evaluated using reference data providing F-score exceeding 80% for the most productive regions.

DOI:
10.1080/2150704X.2015.1130874

ISSN:
2150-704X