Infrared, Hyperspectral and Thermal Remote Sensing Applications

Color Infrared (CIR) Imagery

Aerial imagery, whether it is panchromatic (gray scale), color, or color infrared (CIR) imagery, is based on the fact that each type of land cover, depending of its current condition, absorbs a particular portion of the electromagnetic spectrum, transmits another portion, and reflects the remaining portion, which can be recorded with a passive imaging system. In particular, most objects exhibit a negligible NIR reflectance, but actively growing plants exhibit a high NIR reflectance and stressed plants (either from disease or drought) exhibit a reduction in their NIR reflectance. In addition, there are subtle NIR reflectance differences between vegetation types and species that can aid in plant identification.

AeroPhoto Co Ltd takes advantage of the Near Infrared (NIR) band except from the typical RGB, offering a unique tool to assist with the assessment of the health, density, classification, state of vegetation (e.g. healthy, non-vegetated), and also to map submerged vegetation. CIR imagery is an incredibly valuable tool and when it is used in synergy with other geospatial data it can assist in the making of informed decision in the following applications:

Crop inventory and analysis (e.g. NDVI, LAI index, tree canopy, deforestation studies, foliage health)
Environmental monitoring
Soil and surface mapping
Coastal management

As our society needs to be able to do more and more with decreasing resources and funds, the information derived from high accuracy CIR imagery will become even more valuable.

Airborne Hyperspectral and Thermal Remote Sensing

AeroPhoto Co Ltd uses hyperspectral (CASI) and thermal (TABI) cameras in cooperation with National Technical University of Athens. Those remote sensing data are processed using worldwide standards and utilized to various scientific projects.

Thermographic spatial information makes it possible to visualize the invisible heat radiation to the human eye and to measure the surface temperature of objects without contact, being used in numerous field applications such as creation of infrastructure heat-loss maps. Thermal mapping can also be used for pollution monitoring, in forestry studies to identify diseased or infested trees, for detection of power cable and pipeline leakage, or as a comprehensive inventory of the thermal insulation of all buildings in urban environments. The results of thermal imaging can also be presented in the form of a three-dimensional model.

Hyperspectral scanners (spectrometers) are instruments which receive multi-spectral images in many consecutive spectral channels, at every point of visible, near infrared, and mid-infrared spectral region. They collect data from over 200 channels, something that allows for each pixel in the viewing landscape, the construction of an effective continuous spectrum of reflectivity. Hyperspectral scanners’ aim is to allow the distinction between earth’s characteristics. They exhibit diagnostic characteristics of absorption and reflection in very narrow wavelengths that have been degraded due to the non-so accurate wavelength ranges of a conventional multi-spectral scanner’s channels.

Υπέρυθρη / Υπερφασματική / Θερμική

Below we present some of the applications AeroPhoto Co Ltd is able to offer, categorized by type of market, by executing hyperspectral survey missions:


Classification of crop type
Provide structure information about the health of the vegetation
Detection and follow-up of the effects of farming of natural, chemical and anthropogenic factors like salinity of soil, nitrates, organic materials, nutrients deficiency, dryness, pollution of soil, weeds, etc.
Extent of infestation and stress damage. Assessment of crop damage due to natural hazards (storms, drought).
Evaluation of the agricultural production
Evaluation of the quality of soil (content of organic material), monitoring its corrosion and mapping its characteristics. Potential yield and soil conditions.
Measurement of natural and biological parameters of the farming such as Leaf Area Index (LAI), humidity content etc.
Investigation, census and monitoring of the health of farming. Compliance monitoring (farming practices). Planning of farming (precision farming)


Mapping of forests and their characteristics like phytomass density, structure, stem counts, canopy closure, volume inventories etc.
Monitoring of the natural state of forests (disease & stress detection)
Planning and monitoring of reforestation. Environmental impact assessment

Geology / Edaphology

Detection of available extractives
Mapping of surface appearances of minerals
Lithology mapping
Stratigraphic mapping
Geo-botanical mapping
Analysis of geological structures

Water resources (rivers, lakes, underground and coastal water, snow, ice)

Census of phytoplankton biomass in marine regions, lakes and rivers
Estimation of chlorophyll, suspended solids (organic and inorganic), of the diluted organic material (CDOM), of Posidonia and of the aquatic vegetation in coastal regions, lakes and rivers
Mapping and monitoring of the coastlines and the coastal bottom of the sea
Mapping of the wetlands
Measurement of the optical properties of the water, its opacity and quality
Investigation of the natural and biological processes that affect the fish farming
Detection of coastal and submarine sources of water
Mapping and monitoring of snow-covered regions. Estimation of equivalent quantity of water

Environment / Land use planning

Mapping and monitoring changes of uses/covers of land
Census of environmental burdens by natural disasters
Census of the effects caused by human actions (industrial pollutants, dust exhaust fumes) and natural parameters (dryness, increase of humidity, etc.) in the environment
Mapping of mine acid waste (copper, etc.)
Restoration of quarries and mines
Detection and monitoring of blighted areas due to pollution
Monitoring of the environmental changes in active and abandoned industrial areas
Locating a place for a landfill of waste, factories, plants etc.
Detection of ground saturated with diesel which comes from underground conductors and refineries leakages

Detection of illegal substance & oil sources

Detection of cannabis cultivation
Detection of counterfeit money
Use of four indexes based on hyperspectral data indicative for detection of possible sources of oil:
A- Detection of transformed ores,

B- Detection of geo-botanical abnormalities (farming illness due to large collection of hydrocarbons)

C- Detection of asphalt minerals in the soil, and

D- Detection of soils contaminated by oil leaks.