Application of Remote Sensing in the Monitoring of Marine pollution By Atif Shahzad Institute of Environmental Studies University of Karachi
Remote Sensing "Remote sensing is the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. This is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information. The term, remote sensing, was coined by Evelyn L. Pruitt (U.S. Office of Naval Research) in 1960. Evelyn Pruitt
Energy Source The first requirement for remote sensing is to have an energy source which illuminates or provides electromagnetic energy to the target of interest. The Sun
Electromagnetic Radiations Long wave Radio wave, Micro wave, IR Visible Red-Violet Short wave UV, X-ray From Lillesand & Kiefer, 2001
The Electromagnetic Spectrum Long wave Visible Short wave
Atmospheric interaction As the energy travels from its source to the target, it will come in contact with the atmosphere it passes through. This interaction may take place a second time as the energy travels back from the target to the sensor. There are three types of interactions. Reflection Absorption Scattering
Atmospheric interaction
Platform Platform is the place where sensors are mounted on. 1. Balloon 2. Kite 3. Pigeon 4. Airplane 5. Satellite
Platforms Balloon photography, 1858 The first known aerial photograph is obtained by aeronaut Gaspard Felix Tournachon, also known as Nadar, was a famous French photographer and balloonist whose goal was to make land surveys from aerial photographs. NADAR Nadar s 1868 photo of Paris
Kite Photography, 1890 Platforms Arthur Batut pioneered the development of kite aerial photography and took a photograph of Labruguiere, France in 1890. Arthur Batut Labruguiere, France
Platforms In 1906, George R. Lawrence took oblique aerial pictures of San Francisco after the earthquake and fires One of Lawrence's 1906 photographs of San Francisco.
Platforms Pigeons Photography, 1903 In 1903, Julius Neubranner, photography enthusiast, designed and patented a breastmounted aerial camera for carrier pigeons
Aerial Photography, 1909 Platforms The first photographs from an aircraft were taken by L. P. Bonvillain, a passenger of Wilbur Wright, during a demonstration flight in France. Aerial photographer during World War I, and a French air field
Platforms Satellite Imagery, 1972 1972 - Launch of ERTS-1, the first Earth Resources Technology Satellite (later renamed Landsat 1). Carried return beam vidicon (RBV) and multispectral scanner (MSS). Landsat 1 Brazil Deforestation Landsat mss June, 19 1975 vs Landsat TM August 19, 1986
Sensor After the energy has been reflected by, or emitted from the target, we require a sensor (remote - not in contact with the target) to collect and record the electromagnetic radiation. The sensor acquires several images (bands) at once, each recording a specific color or range of colors. When viewed, each individual band looks like a black and white photograph
Types of Sensors There are two types of sensors with respect to illumination source. Passive sensors measure natural radiation emitted by the target material or/and radiation energy from other sources reflected from the target. Active sensors transmit their own signal and measure the energy that is reflected (or scattered back) from the target material. Today, we will be focusing on passive remote sensing!
Passive Sensor (Landsat TM) A satellite view of Karachi from Landsat a passive remote sensing satellite Karachi
Active Sensor (Radarsat) Karachi
Interaction with the feature When electro-magnetic energy is incident on any given earth surface feature, three fundamental energy interactions with the feature are possible depending on the properties of both the target and the radiation. Transmission Reflection Absorption
Interaction with the feature The incident energy on an earth surface feature is a function of reflected, transmitted and absorbed energy. Basic interactions between electromagnetic energy and an earth surface feature
Reflectance from a leaf An earth surface feature behaves differently against different spectral bands. As we can see that a leaf absorbs incident energy in blue and red bands while it reflect energy in green and near infra red bands. From Avery & Berlin, 1977
Spectral Reflectance Curve Spectral reflectance curve reveals that vegetation (leaves) has maximum reflectance in NIR than green band.
Reflectance in different bands
Applications On the basis of spectral reflectance and field measurements we can find parameters that are important in the monitoring of plant diversity 1. Chlorophyll (a & b) 2. Vegetation density (NDVI) 3. Species Richness (No. of Species)
Chlorophyll-a This paper focused on developing and applying remote sensing algorithms to determine the chlorophyll-a content of mesotrophic to highly eutrophic lake waters, using Lake Taihu, China as a case study. Statistical techniques have been the most commonly used approach to derive a correlation between spectral data and chlorophyll concentration values (Zhou yi et al., 2004). Such techniques were also adopted in this study. 1. Weiqi Zhou, Shixin Wang, Yi Zhou. Determination of Chlorophyll a Content of the Lake Taihu, China using Landsat-5 TM data. Institute of Remote Sensing Applications, Chinese Academy of Sciences P O Box, 9718, Beijing 100101, P R. China. 2. Zhou yi, Zhou Weiqi, Wang shixin et al. Applications of Remote Sensing Techniques to Inland Water Quality Monitoring. Advances in Water Science, 2004, 15(3), 312-317. (In Chinese)
Field measurement Water was sampled at 0.5m depths using a bottle and was later filtered and stored in liquid nitrogen to break the algae cells. Chlorophyll concentrations were retrieved from filtered water using the hot ethanol method, which use 90% hot ethanol as the chlorophyll-a extraction agent (Chen and Gao, 2000). 25 chl-a concentration measurements were collected on October 27th and 28th, 2003, which were used as the dependent variable in the regression analysis with corresponding satellite-derived water surface reflectance. The values of chl-a concentration varied from 2.2 mgm -3 to 230.59 mgm -3. Chen yuwei, Gao xiyun. Comparison of Two Methods for Phytoplankton Chlorophyll-a Concentration Measurement. Journal of Lake Sciences, 2000, 12(2): 186-188. (In Chinese)
Numerical model Based on the correlation analysis between chl-a and various bands and bands combinations, the multiple regressions were performed using the 22 chl-a concentration values and selected bands combinations. Closeness of fit (r 2 values) and mean Std. Error of the Estimate (SEE) were used to assess the regression models. A four-coefficient regression model using TM4/TM3 ratio and TM1, TM2 was a reliable predicator of chl-a (r 2 = 0.837). The equation of this model is: Where R 1, R 2 were the reflectance of TM 1 and TM 2 ; R 43 was the reflectance ratio of TM4 to TM3.
Remote Sensing Analysis Map of chl-a concentrations (in mgm-3), by applying numerical model to Landsat TM reflectance data from October 28th, 2003.