A Review of Hyperspectral Remote Sensing and its Application for Water

Pollution

Introduction

Water, the hydrosphere, covers approximately 71% percent of the earth. It consists

of ocean, river, lake, marsh, glacier, snow, groundwater, air moisture, and so on.

Water environment, closely linked with human being’s life, is facing serious problems

of pollution and eutrophication. Water is one of the most valuable and essential

resources that form the basis of all life.

Over the last decade, the increased spectral and spatial resolution of remote sensing

equipment has promoted the development of new methods for water bodies

monitoring. The advantages of the new physical approaches, with respect to

empirical methods, include the capability of fully deploy hyperspectral data, the

reduction of the amount of laboratory and in-situ measurement. This new methods

require very rigorous data processing. The measured signal, in fact, has to be as

similar as possible to the real signal to be interpreted on the bases of a physical

model.

Hyperspectral systems have made it possible for the collection of several hundred

spectral bands in a single acquisition, thus producing many more detailed spectral

data. However, with the advances in hyperspectral technologies practical issues

related to increased sensor or imager costs, data volumes and data-processing costs

and times would need to be considered especially for operational modes.

Water pollution is one of the major threats to public health in the world. Water

pollution refers to harmful substances released into surface or ground water, either

directly or indirectly. water pollutants can originate, for example from waste water

stabilization ponds, sludge lagoons, barnyard runoff, septic tank leaching fields or

seepage pits, pit privies and the deep well disposal of certain industrial wastes or

treatment plant effluents

This article is structured as follows. Section 2 presents the overall overview of the

hyperspectral technology. Section 3 presents the application of hyperspectral on the

water pollution types. Section 4 includes current problems of the hyperspectral and

recommendations for the future improvements. Section 5 closes the paper with

conclusions.

Overview of the hyperspectral technology

The trend in the of development of remote sensing has been, with the increase of the

spectral resolution, to move from the panchromatic multispectral to the hyperspectral,

and then to the ultraspectral. Sensor developments include a new generation of high-

resolution commercial satellites that will provide unique levels of accuracy in spatial,

spectral and temporal attributes.

In the airborne remote sensing system, the hyperspectral sensor is already in place

as one of the basic systems. Two new kinds of hyperspectral sensors, PHI and

OMIS, were designed specifically for hyperspectral applications. In addition, a small

hyperspectral digital camera system (HDCS) with limited number but narrow band

was also implemented for environmental and agricultural monitoring.

With the development and perfection of the hyperspectral remote sensing

technologies, hyperspectral remote sensing has been the major technique applied in

many studies. Now with commercial airborne hyperspectral imagers such as CASI

and Hymap and the launch of satellite-based sensors such as Hyperion,

hyperspectral imaging is fast moving into the mainstream of remote sensing and

applied remote sensing research studies Hyperspectral images have found many

applications in water resource management, agriculture and environmental

monitoring (Smith, 2001a). For hyperspectral sensors have become available to

provide both high spatial and high spectral resolution with high signal/noise ratio. Due

to the sufficient spectral features such as spectral reflectance with wavelength it

provides, hyperspectral data plays an important role in the different fields.

To obtain data of a higher spectral resolution compared to multispectral data,

hyperspectral sensors on board satellites or airborne hyperspectral imagers are used

(Smith, 2001b).

Hyperspectral remote sensing imagers acquire many, very narrow, contiguous

spectral bands throughout the visible, nearinfrared, mid-infrared, and thermal infrared

portions of the electromagnetic spectrum. Hyperspectral sensors typically collect 200

or more bands enabling the construction of an almost continuous reflectance

spectrum for every pixel in the scene

Brownfields, refineries, tank farms, pipeline corridors, oil fields, and other industrial

sites can have surface deposits of hydrocarbon-based materials. Sophisticated

VNIR-SWIR hyper-spectral sensor is ideal for detecting soils and surfaces that have

been impacted by oil-based materials. Some researchers have found that the

detection of oil spills in soil is related with the concentration of light hydrocarbons in

the soil and in the air. Light hydrocarbons tend to evaporate fairly quickly, therefore is

a time constrain with this way of detection. On the other side, the more hydrocarbons

get evaporated from soil or the water the less environmental damage in can cause.

Tests have shown that hydrocarbons in soil and plastics are characterized by

absorption maxima at wavelengths of 1730 and 2310nm.

Hyperspectral Analysis

The sensor used for the study of the Patuxent River oil spill is the Airborne Imaging

Spectroradiometer for Applications (AISA) sensor system. AISA hyper-spectral

imaging sensor can measure up to 55 spectral bands of information; has an airborne

DGPS (Differential Global Positioning System - to measure aircraft position); and an

INS (Integrated Navigation System - to combine the DGPS and an IMU (Inertial

Measurement Unit) - to measure aircraft attitude. AISA is a solid-state, push-broom

instrument of small size, which makes it perfect for use in aircrafts. The instrument

can be mounted on a plate that is compatible with a standard aerial camera mount,

and has the flexibility of selecting the sensor's spatial and spectral resolution

characteristics. AISA is capable of collecting data within a spectral range of 430 to

900 nm, and up to 286 spectral channels within this range. Current operational

collection configurations for the AISA hyperspectral sensor covers a range from 10

to 70 spectral bands, this will depend on the aircraft speed, altitude, and the 1212

specific mission goals.

Hyperspectral systems have made it possible for the collection of several hundred

spectral bands in a single acquisition, thus producing many more detailed spectral

data. However, with the advances in hyperspectral technologies practical issues

related to increased sensor or imager costs, data volumes and data-processing costs

and times would need to be considered especially for operational modes.

Problems of the hyperspectral and recommendations for the future

improvements

. In this specific study (oil in water) since the signature can be easily misidentify as

water, hyper-spectral imagery can help to obtain a more detail spectrum to be able to

separate between pure water and oil-water

Conclusions

The use of hyper-spectral imagery to detect oil spills in water has a lot of advantages

in the field. It can be use to monitor oil facilities and therefore prevent worst scenarios

when a leak in the facility is found. Also can be use to help planning the cleanup of

the area, by quickly identifying the affected areas and possible path of the spill to be

one step ahead.