top of page


Images are captured via drones, once it reaches our cloud we do all the pre-processing required in order to produce optimal analysis on your data.

Once pre-processing is completed, our specialist get straight onto analysing your data using tools and techniques specific to your needs.


After the analysis is completed, we compose a detailed report, explaining what we have found from the data, this giving you the power to make the best decisions when it comes to managing your farm.



Before we analyse your data, we do initial processing on the raw data. This is generally done to correct any distortion due to the characteristics of the imaging system and imaging conditions.



We use analysis techniques to aid the interpretation of remote sensing images and to extract as much information as possible from the images. The choice of specific techniques or algorithms to use depends on the goals of each individual project. In this section, we will examine some procedures commonly used in analysing/interpret remote sensing images.

Image Enhancement
In order to aid visual interpretation, visual appearance of the objects in the image can be improved by image enhancement techniques such as grey level stretching to improve the contrast and spatial filtering for enhancing the edges.

Image Classification
 Land cover types in an image can be differentiated using some image classification algorithm, for example, by using spectral features such as brightness and "colour" information contained in each pixel.

Vegetative Indices (VI)
Enable the acquisition of ecological information from satellite and drone data through the analysis of multi- or hyper-spectral imagery bands. The reflectance of light changes with chlorophyll content, plant type, sugar content, water content within tissues and other factors. A wide range of plant characteristics can be inferred through various indices. These indices are also used to improve the accuracy of classification algorithms.

Some of the indices we use :
CIG = Green Chlorophyll Index 
G-NDVI = Green Normalised Vegetation Index
NDVI = Normalised Difference Vegetation Index
SR = Simple Ratio index


Statistical Analysis

 Is the scientific method of collecting, exploring and presenting large amounts of data which allows one to discover underlying patterns and trends. It involves scrutinizing every data sample in a set of items from which samples can be drawn. 


The goal of statistical analysis is to identify trends, describe the nature of the data to be analyzed and explore the relations/correlations of the data to chosen factors.




At AGRI-SENSE INTERNATIONAL we perform a systematic examination and evaluation of data and information, by breaking it into its component parts. This is done to uncover their interrelationships and understand the cause-effect association, thus providing a basis for problem-solving and decision making.




We produce:


High-Resolution Geo-rectified Maps

•UAV, Satellite

•Processing and analysis



Vegetation & Crop Assessment Maps

•Calibrated NIR,

•Standardised NDVI

bottom of page