Remote sensing (RS) and geographic information system (GIS) technologies have been of great use to planners in planning for efficient use of natural resources at national, sub region and rural levels.

RS can be used for precision farming in a number of ways for providing input supplies and variability management through decision support system.

GIS is the principal technology used to integrate spatial data coming from various sources in a computer. GIS techniques deal with the management of spatial information of soil properties, cropping systems, pest infestations, land use land cover, environment and weather conditions. GIS technology will help the farmers and scientists in decision making, as precise information on field will be readily available. GIS coupled with GPS, computers, RS and sensors is used for soil mapping, crop stress, yield mapping, estimation of soil organic matter and available nutrients.

The objective of this study to develop farming land information system and monitor in the agricultural land cover changes in the Selenge aimag as there is important agricultural producing area in Mongolia. 

In this study, maximum likelihood supervised classification methodology was applied to Landsat TM and ETM images acquired in 1989 and 2000, respectively supplemented by topographic maps, fieldwork and use of other existing data. A supervised classification was carried out on the six reflective bands (bands 1-5 and band 7). From this, land cover and farmland maps at 1:10,000 with attribute data were prepared in the area.