Map of winter crops of the season 2017 placed on the service VEGA: Results of selective quality control

Winter crop masks, based on MODIS satellite data, are regularly laid out from the Internet service VEGA as one of the operational products. The information of the quality of such masks is important for practical use, however this information is not available on the VEGA service. The article presents some results of the field verification of the quality of the winter crop mask laid out on the site on May 12, 2017 in Moscow and Tula regions of Russia. It is found out that MODIS pixels identified on the mask as 'winter crop' cannot cover the entire arable plot, but can also 'grab' adjacent fields. There are many cases where within the plot there are only few pixels identified as 'winter crops'. Most likely this is due to the status of winter crops on the field and it indicates that the used algorithm detects only crops in good condition. Many pixels are expected to be mistakenly classified on the boundaries between plots. Errors in the detection of individual plots with winter crops are also quite numerable. This is due to the size and shape of the plots, fairly small spatial resolution of the MODIS data, as well as due to peculiarities of the algorithm used. VEGA masks may well be used as a first approximation of geographic location of the winter crops, but the assessment of winter crop sowing areas (and, consequently, the assessment of their condition and the forecast of yields) for the territory of the Moscow and Tula regions can hardly be successful.

Авторы
Savin I.Y. 1, 2 , Zhang X.3 , Shishkonakova E.A.1 , Zhogolev A.V.1 , Gabdullin B.S.1
Издательство
Space Research Institute of the Russian Academy of Sciences
Номер выпуска
4
Язык
Русский
Страницы
125-131
Статус
Опубликовано
Том
14
Год
2017
Организации
  • 1 V. V. Dokuchaev Soil Science Institute, Moscow, 119017, Russian Federation
  • 2 Agrarian-Technological Institute of RUDN, Moscow, 117198, Russian Federation
  • 3 Institute of Remote Sensing and Digital Earth, Beijing, 100094, China
Ключевые слова
Crop recognition; MODIS; Quality check; Satellite monitoring; Winter crops
Дата создания
19.10.2018
Дата изменения
19.10.2018
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/6159/
Поделиться

Другие записи