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By Matteo Picchiani and Fabio Del Frate

Tor Vergata University, Italy

Plot of backscattering coefficients
City of Rome as imaged by ENVISAT-ASAR
Click for larger image and explanation

World population growth affects the environment through the swelling of the population in urban areas and by increasing the total consumption of natural resources. Monitoring these changes timely and accurately might be crucial for the implementation of effective decision-making processes.

The global view of urban areas makes satellite missions a valid instrument for updating urban maps and carrying out the analysis of settlement dynamics. While optical data can suffer from atmospheric limitations, especially where clouds are frequent, the long time series of SAR unages from ERS and Envisat provide a unique systematic means of periodically tracking the frequently dramatic changes undergone by the land cover of large cities in many parts of the world in the past 20 years.

IMPORTANT NOTE: This lesson requires Bilko 3.4 from February 2013 or later, as earlier versions of the software can not open and display all data as described in the lesson.


The ability of global coverage makes satellite missions an irreplaceable instrument to study the growth of the cities. In addition, the possibility of updating urban maps at regular interval, monitoring the green areas or the industrial parks can be of crucial interest to local administrations and planning. Although optical remote sensing techniques are well established data source for mapping land cover and monitoring changes, they suffer from cloud and atmospheric contamination.

To overcome these limitations, the use of synthetic aperture radar (SAR) data might become attractive especially when a continuously systematic survey of an urban area is required. Moreover, the near real time information provided by the SAR images, irrespective of sun illumination or cloud cover, makes this type of data very suitable for the management of emergencies over large areas. Several SAR instruments have been developed recently by different space agencies around the world and new missions are coming, like the ESA Sentinel mission which will provide continuity to the previous ERS-1, ERS-2 and Envisat ones. The ensemble of data from the last ESA missions provide a very large data archive suitable for the study of changes in large cities over the past 20 years.

Lesson Overview

In this lesson we will explore how multi-temporal acquisitions of SAR data from Rome, Italy, can be used to analyse the relationship between the variations of the backscattering coefficient and changes in land use. Before performing any specific analysis, some pre-processing steps such as coregistration and radiometric calibration should be performed. Following this, distinction between a built-up and a natural area will be covered. Finally, comparison between the results obtained from SAR and those derived from Landsat optical images will be provided

Aim and objectives

At the end of the lesson you should be able to

Lesson content

The lesson is divided into 6 sections:

  1. Radiometric calibration and co-registration of a SAR time series
  2. Speckle reduction
  3. Analysis of principal scattering mechanisms (in an urban context)
  4. Feature extraction for change detection
  5. Change detection on a pixel basis
  6. Comparison with optical images

Data and tools for this lesson

Files needed to complete the lesson activities

The following Level 1 precision image mode ASAR (Advanced Synthetic Aperture Radar) data from Rome are used in the lesson. Each has a spatial resolution of about 30m.

Data in their original format

These data files are in the format used by the data provider. Similar data sets are available from on-line archives, and may be displayed and processed in Bilko using tools and methodologies from this lesson.

Synthetic aperture radar (SAR) data from Envisat ASAR
Optical images from Landsat 7

Pre-processed data

coregistered_stack_Rome.set: Bilko set consisting of the following data, which must be kept in the same folder as the set:

LE71910312004048ASN01.set: Bilko set consisting of the following data files:

LT51910312010152MOR00.set:Bilko set consisting of the following data:

Bilko tools used in the lesson

Original SAR data used to create the pre-procesed sets

The following images have been pre-processed to minimise the time needed to complete the lesson. They are not needed in order to complete the lesson, but are available for download for the implementation of the complete processing chain, should you wish to do so.

Downloading the lesson

The lesson downloads contain everything you need to complete the lesson. This includes the data and tools listed above, and three PDF documents:

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