Abstract
Abstract. Wheat is the most important food crop in Mongolia, most of the croplands are utilizing for wheat cultivating area in the central northern region of Mongolia. The Mongolian government has several policies on the agricultural sector with wheat production in the study region has been intensified to meet people’s food demands and economic development. Monitoring wheat-growing areas is thus important to developing strategies for food security in the region. In the present study, we aimed to develop an agricultural application method using remote sensing data. Sentinel-1 SAR and Sentinel-2 MSI analysis of time series data were carried out to monitor the wheat crop growth parameters. Time-series images were acquired during May 2019–September 2019 at different growth stages in Bornuur soum, Tuv province of Mongolia. The wheat crop parameters, i.e. normalized difference vegetation index, vegetation water content, backscatter value of VV, VH channels were estimated using remote sensing data with reference data as cadastre polygons of current cropland area. The results showed that provide timely and valuable information for agricultural production, management and policy-making. The agricultural application method will help to agriculture management and monitoring include crop identification and cropland mapping, crop growth monitoring, inversion of key biophysical, biochemical and environmental parameters, crop damage/disaster monitoring, precision agriculture, etc.
Highlights
Agricultural production is one of the most basic and important things in human life, which is the basic condition for human’s survival and development
The study paves a way for crop monitoring Tuv province in Mongolia
We used that there are two indices as Normalized difference water index (NDWI) and normalized difference vegetation index (NDVI) with backscatter values of VV/VH that are very relevant for wheat monitoring
Summary
Agricultural production is one of the most basic and important things in human life, which is the basic condition for human’s survival and development. Using the technology of remote sensing in the agricultural sector of people can monitor the comprehensive growing condition of crops, so as to timely acquire the information on crop yields (Xiong et al, 2014). These two indices derived from Sentinel satellite have so far not been used for crop yield prediction in Mongolia. In Mongolia, the monitoring of wheat yield at the regional and national levels are key issues for the agricultural policy and food management as well as for the economy as a whole. In other studies on wheat crop growth monitoring investigate the applicability of MODIS data to adjust the WOFOST model for wheat at the potential production level in North China and to improve the simulated performance of the crop model at the regional scale (Zhang et al, 2007)
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