Mobile Version ╗ | About Company ╗ | Contact Us ╗ | Company Websites ╗ | Registration ╗ |
Site Map ╗ | Print Version ╗

Application of satellite images in agriculture

Application of satellite images in agriculture

Historically, agriculture has been playing a great role in Russia. After certain recession in the past few years, an increase of the interest to this segment of the Russian economy is nowadays observed. Mostly due to the changes in the land policy: new landowners appear, who are interested in an efficient land use.

Vast territories of arable lands are difficult to control due to the lack of precise maps, primitive network of the near real-time monitoring and ground stations, meteorological included; the lack of air support because of its high costs, etc. Besides, different natural processes cause continuous changes in the crop area boundaries, soil properties and vegetation conditions on different fields. All these factors prevent from receiving unbiased real-time data, required to confirm the current condition, make its assessment and forecasting. Without this it is almost impossible to increase the output of agricultural products, to optimize land use, to forecast productivity, to decrease costs and to improve efficiency. Similar problems are being successfully resolved abroad using aerial and satellite-based survey, as well as wide GPS systems during crop monitoring and harvesting to assess the canopy condition and make crop productivity predictions. In our country the use of remote sensing data in agriculture is a quickly developing and promising trend. Satellite imagery data may help to resolve both major and specific agricultural management tasks.

Typical objectives in this industry are: arable land acreage determination, crop condition monitoring, land erosion, salinity, swamping and desertification assessment, soil composition determination, quality and timely execution monitoring of agricultural measures. Repeated satellite imagery allows for a dynamic crop development monitoring and yield forecasting. For example, knowing how the vegetation spectral brightness is changing throughout the vegetation period, it is possible to assess the crop condition by the image color of the fields. Winter crops condition after winter season is assessed by the difference in color between strong and lost plants; the condition of winter and spring crops before harvesting ľ based on the grass canopy condition and its uniformity.

©2005-2014 R&D Center ScanEx. All Rights Reserved.
mailto: webmaster@scanex.ru
Alice - SCÖ
UniScanÖ
ScanEx Ground Stations (SGS) Network
Mosaics
IRS-1C/1D
Cartosat-1 (IRS-P5)
CARTOSAT-2
Resourcesat-1 (IRS-P6)
SPOT 2/4
SPOT 5
SPOT 6&7
COSMO-SkyMed
FORMOSAT-2
LANDSAT 5/7
Landsat 8 (LDCM)
EROS
IKONOS
GeoEye-1
QuickBird
WorldView-1
WorldView-2
KOMPSAT-2
KOMPSAT-3
RADARSAT-1
RADARSAT-2
ENVISAT-1
TerraSAR-X
ALOS
MODIS
ASTER
UK-DMC2
Pleiades-1
Suomi NPP
đň˝ˇ­˝-╬1, ╠ň˛ňţ­-3╠
Satellite Image Processing
ScanEx Image Processor«
ScanMagic«
ScanEx Web Catalog«
MeteoGamma«
ScanEx Satellite Orbit Kit«
ScanEx RADARSAT Processor«
ScanEx ENVISAT Processor«
ScanEx SPOT Processor«
ScanEx Task Flow«
ScanEx ADPS
Preprocessing Tools
Resellers
Downloads
Agriculture
Forestry
Cartography
Emergencies
Nature Protection
Cadastre & Land Management
Weather Forecast
Ice Situation
Courses
Curriculum
Online-requests
Contacts
Personal ground stations
Software