Remote Sensing for Agriculture
Remote Sensing for Agriculture


With increasing population pressure throughout the world and the need for increased agricultural production there is a definite need for improved management of the world's agricultural resources. To make this happen it is first necessary to obtain reliable data on not only the types, but also the quality, quantity and location of these resources. Satellite or Aerial Remote Sensing (RS) technology has been and always will continue to be a very important factor in the improvement of the present systems of acquiring and generating agricultural and resources data.

Managed Canopy Assessment

Satellite Image - Sustainable Agriculture

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Agriculture surveys are presently conducted throughout the world in order to gather information and statistics on crops, rangeland, livestock and other related agricultural resources. This information of data is most important for the implementation of effective management decisions. Agricultural survey is needed for planning and allocation of the limited resources to different sectors of the economy.

Satellite Imaging Corporation provides satellite imagery data at different spatial, spectral and temporal resolutions for agriculture and crop assessment, crop health, change detection, environmental analysis, irrigated landscape mapping, yield determination and soils analysis. Scheduling and timing of image acquisition is very important and will hinge on the main goals and the type of information that the end user is hoping to gain. Images can show variations in organic matter and drainage patterns. Soils higher in organic matter can be differentiated from lighter sandier soil that has a lower organic matter content. This Geospatial information is valuable when used in conjunction with ancillary data to define management zones for a field. Once data has been collected it can be implemented into a mapping environment such as GIS (Geographic Information Systems) for management and control of agricultural resources.

Vegetation Analysis

Vegetation images — show crop growth from planting through to harvest, changes as the season progresses and abnormalities such as weed patches, soil compaction, watering problems etc. A georeferenced and orthorectified image can locate these problem areas as well as the size of the area affected can be easily determined. This information can help the farmer make informed decisions about the most feasible solution. In addition to highlighting problematic areas, images will also help monitor the effectiveness of any corrective actions which may be implemented. Images can act as an early indicator of crop yield. This early predictor of yield can aid the farmer in making marketing decisions as well as the allocation of resources.

To gain the benefits from remotely sensed data farmers, managers, consultants and technicians must understand and be able to interpret the image. There are a wide range of enhancement tools available which can help make an image more interpretable for specific applications. Enhancement and classification tools are often used to highlight features. The techniques employed will depend on the type of remote sensed data as well as the objectives of the end user. Techniques commonly used include:

Change detection — or studying vegetation changes by subtracting one image from another image acquired at an earlier date.

Satellite Images - Crop Change Detection

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Classifications — where the pixels of an image are sorted into classes and each class is given a unique color defined by the spectral "signatures". A supervised classification requires knowledge of the data as the analyst selects pixels that correspond to known features (such as differences in the land cover). Unsupervised classifications are more computer automated and cluster pixels which have similar spectral characteristics. Many companies use this approach to produce an image of a field with numerous color levels of 8-15 corresponding to leaf area or plant mass.

Satellite Image - Agriculture Classification

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Vegetation Indices — Using the distinct spectral signature of plants with low reflectance in the visible (0.4-0.7 um) and very high reflectance in the near infrared region (0.7-1.2 um) of the solar spectrum, the spectral contrast can be used for identifying the presence of green vegetation and evaluating some characteristics through various vegetation indices, such as the Normalized Difference Vegetation IndexNDVI.

Satellite Map - Wetlands Encroachment Satellite Image - Irrigation Pattern Agriculture Production Monitoring
Wetlands Encroachment Irrigation Pattern Production Monitoring
Satellite Image - Crop Health Variations Farming - Urban Forest and Turf Agriculture - Soils and Fertility Analysis
Crop Health Variations
Urban Forest and Turf Soils and Fertility Analysis

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Vegetation Response to Irrigation

Agriculture Satellite Image - Vegetation Response to Irrigation

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Satellite Imaging Corporation utilizes and provides advanced Remote Sensing techniques, Color and Panchromatic image data processing services including orthorectification, pan sharpening with image data fusion, enhancements, Georeferencing, mosaicing and color/grayscale balancing for GIS and other mapping applications.

Satellite Imaging Corporation offers satellite imaging acquisition from various commercial satellite sensors providing different resolutions including:

Satellite Sensor Resolution at Nadir

GeoEye-2, 0.41m/1.64m

Worldview-2, 0.46m

Worldview-1, 0.46m

QuickBird, 0.61m/2.4m

IKONOS, 0.82m/3.2m

SPOT-5, 2.5m/10m

LANDSAT 7 +ETM, 14.25m/28.5m

ASTER, 15m/30m

Rapid Acquisition

Rush tasking orders for satellite image data around the world are accepted in support of live events, natural disasters, global security, and various other applications in which FAST delivery of image data is critical. In most instances, we can provide image data within 24 hours after the initial data has been acquired and delivered via FTP and DVD media. A Spanish version is also available at