GEOG-588 – Remote Sensing for GIS

  1. Scope and Purpose

Geographic Information Systems (GIS) need information. More precisely, users of GIS need information which is relevant, accurate, timely, accessible, available in an appropriate format and cost-effective. Remote sensing is an established source of information which has met the needs of many users. Recent developments in Earth observation such as imaging radar, lidar and hyperspectral sensors are increasing the range of information which can be generated from remotely sensed data. Data are available more frequently due to sensors which can be maneuvered to point at locations of greatest interest and the launch of missions involving multiple satellites. Finally, users have seen significant improvements in data quality e.g. very high spatial resolution data, global data archives.

GIS is driving remote sensing forward due to demand for Earth observation data. At the same time remote sensing is changing applications of geographical information – andattitudes! Several new applications are dependent on remote sensing. Our management of natural resources at regional scales would be seriously impaired and our understanding of global processes very severely limited without satellite remote sensing. At a local scale users are relying on archives of Earth observation data to create a consistent record of land cover/land use change, a task which otherwise would be impossible in many areas of the world due to the historical lack of records.

This coursewill provide students with a broad insight into the sources, applications and future potential of remote sensing data for GIS applications. The course is organized into four components:

  • Principles of Remote Sensing – highlighting the principles of remote sensing including interactions between electromagnetic radiation, atmosphere and surface, but with particular emphasis on land surface characteristics.
  • Satellite Systems – describing of a range of satellite systems, their spectral, spatial and temporal characteristics and range of applications.
  • Quantitative Data – examining the extraction of quantitative data from remotely sensed images including the development and application of image-based data extraction techniques, spectral indices, and application of canopy reflectance models.
  • GIS Integration – highlighting the key issues in the integration of remotely sensed data in GIS, addressing issues of spatial scale, data availability and information content.
  1. Learning Outcomes

On completion of this course, students will be able to:

  • Explain the principles of remote sensing and the technical constraints on Earth observation missions.
  • Design, implement and critically evaluate methods of digital image processing.
  • Generate geographical information by processing digital remotely sensed data and critically evaluate its use forenvironmental applications.
  • Critically evaluate methods of integrating remote sensing and GIS.
  1. Teaching and Learning Strategies

The learning and teaching strategies are student centered. They aim to encourage a deep-learning approach by using reflection and self-evaluation. A written Course Reader will be provided on-line, which will provide the essential background, the framework for study and essential detail. It will include self assessment exercises. Each section of this Reader will be framed with a context setting introduction, clearly identified learning outcomes and additional reading within the academic and professional literature. Students will be required to reflect on their learning as part of the self assessment exercises and the summative assignments.

Numerous opportunities for students to discuss the course materials and accompanying issues with faculty and fellow students will be provided via e-mail, telephone, an online bulletin board, and at least two synchronous telephone or Webcam sessions in which students present or discuss one of the course readings and one of the items on which they are being evaluated. Students should anticipate spoken and/or written communication with the instructor and/or their fellow students on a weekly basis.

  1. Assessment Strategies

There will be two imagery analysis problems involving data extraction froma remotely sensed image data set provided by the instructor. These projects will be posted on the course’s online bulletin board for critique and evaluation by course participants. Each student will then select one of the posted projects, not their own, for critique of the imagery analysis. The students will then have to formulate their own project requiring data extraction from remote sensed imagery. The final written assignment will demonstrate the student’s mastery of this course’s learning objectives by critically evaluating the use of remotesensing and integration in GIS in a specific application area.

Two Image Analysis Problems (30%)

Students will be assessed on the manipulation of, and data extraction from,a remotely sensed image data set provided by the instructor, including ancillary data.

Two Image Analysis Critiques (10%)

For each of the Image Analysis Problems students will have to select one from each that is not their own for a critique.

Remote Sensing Project (20%)

Students will formulate an original project which will entail accessing remotely sensed imagery, then extracting and manipulating the data needed. The product map will be accompanied by a narrative elaborating on the imagery analysis and data extraction techniques employed in this project.

Analytic Paper (25%)

Students will be assessed on the critical evaluation of the use of remotesensing and integration in GIS in a specific application area.The outputs will include an oral presentation that is organized around a slide show and presented in a synchronous mode in a specially scheduled telephone or Webcam session as well as the written paper.

Fifteen Reading Assignments (15%; 1% per reading assignment)

Students will be required to write short discussions of a series of book chapters and journal articles that describe key programming applications, developments and challenges.Students will discuss at least one of these readings and their reports with the instructor via a synchronous telephone or Webcam session.

  1. Course Outline

Week 1 –Introduction

An introduction to the nature of the course, including assignments, materials, resources, as well as support services and fellow students.

Readings – Jensen (2000), Estes and Loveland (1999)

Weeks 2, 3 –Earth Observation

The need to effectively monitor our resources and measure the impact of events on our environment is becoming increasingly important. For some years now remote sensing has been recognized as an especially valuable tool for monitoring the Earth's natural resources.

Remote sensing can be defined as the means of sensing or measuring things (objects, areas or phenomena) without coming into direct contact with the phenomenon. What is measured is the emitted, scattered and reflected electromagnetic energy from the phenomena under investigation. From these measurements, useful information is then extracted through visual or computer-assisted interpretation. Satellite data, in particular, can provide relatively inexpensive, repetitive datasets that can either augment or replace expensive and often time consuming ground based monitoring programs. They provide an instantaneous view of surface phenomena over large areas that are often inaccessible to ground personnel due to physical or political reasons.

Remotely-sensed data are a natural input to GIS because it provides spatially consistent information over large areas. Remote sensing and GIS are among many tools available to resource management professionals today. These tools vary widely in their sophistication, cost, effectiveness, availability, and familiarity. These factors add to the potential risks associated with successful implementation. Planning must be systematic and realistic and must focus on problem solving rather than a technology push. With proper planning, remote sensing can be a powerful tool.

Readings – Jensen (2000), Lange and Gilbert (1999), Lees (2006), Mesev (2003)

Weeks 4, 5, 6 –Principles of Remote Sensing

The science of remote sensing concerns the pathways which regulate the flow of electromagnetic energy through the remote sensing system. As such, remote sensing requires a source of energy. The most convenient, abundant and inexpensive source of energy is the sun.

What does this mean for remote sensing? Knowing the amount of solar energy available tells us if there is enough energy available for a passive sensor to function or if an active sensor (one which provides its own energy source) is required. For example, sensors operating in the visible, near-infrared and thermal infrared regions of the electromagnetic spectrum can usually function effectively by using the available solar energy to illuminate the Earth's surface. Active sensors such as radar, which operates in the microwave portion of the spectrum, create their own energy source and are, therefore, not dependent on solar energy from the sun.

Readings – Jensen (2000)

Weeks 7, 8, 9 –Properties of Earth Surfaces and their Interactions withElectromagnetic Radiation at Visible and Near Infrared Wavelength

Energy reaching the Earth's surface may be reflected at the interface, transmitted through the surface material or absorbed and stored within the material. The division of energy dependson the specific wavelengths involved and the physical properties of the material receiving the radiation. In reality, the response of asurface is usually a complex combination of these forms of interaction: reflection, transmission, and absorption.

Our objectives when applying remote sensing are to detect objects of interest, commonly known as targets, or infer the nature of a surface from its spectral response. Detection largely depends on the contrast between the target and its surroundings and is most easily achieved if a target has unique spectral characteristics.

Surfaces can often be characterized in terms of their spectral response, or how they appear at a particular wavelength. For example, in the near-infrared part of the spectrum, an area commonly used in remote sensing to assess the health of vegetation, healthy vegetation is highly reflective. Active radar sensors are sensitive to surface roughness, topography, and moisture conditions. These properties arethe subject of this section of the unit.

Readings – Jensen (2000), Lucieer and Kraak (2004), Petit and Lambin (2001)

Weeks 10, 11, 12 –Earth Observation Missions

Remotely-sensed data can contribute in a variety of ways to Earth observation activities. This potential derives from the inherent characteristics of remotely-sensed data which are spatial continuity,uniform accuracy and precision,multitemporal coverage, andcomplete coverage regardless of site location.This section examines the variety of Earth observation data acquired by satellite missions.

The spatial, spectral and temporal characteristics and format of the data vary with the platform and sensor combination. However, with the many data format options (print, film, digital, geometrically corrected, orthorectified, etc.), how does one then decide which type of data is best suited for the needs of the project at hand? The answer lies in careful examination of data application and by answering some basic questions, which will help determine data requirements:

In the use of remote sensing technologies effective project planning is critical. Planning your data requirements makes all the difference, due in part to the relative newness of operational uses. This section reviews the application of data acquired by several missions. A summary of the technical specifications of a wider range of EO missions is available through the link in the Course Reader.

Readings – Jensen (2000)

Weeks 13, 14 –Integrating Remote Sensing and GIS

Remote sensing and GIS are among many tools available to resource management professionals today. These tools vary widely in their sophistication, cost, effectiveness, availability, and familiarity. These factors add to the potential risks associated with successful implementation. Planning must be systematic and realistic and must focus on problem solving rather than a technology push. Remotely-sensed data are a natural input to GIS because images provide spatially consistent information over large areas, and with proper planning, remote sensing can be a powerful tool. In this section students will investigate specific techniques for integrating remote sensing and GIS technologies to solve environmental problems

Readings – Barnsley (1999), Dietzel et al. (2005), Lees (2006), Mesev (2003)

Week 15 - Conclusions

Remote sensing has been, and still is, driven by the needs of geoinformation users. It is different from GIS, however, because national governments have had much greater involvement historically due to military applications and more recently their concern with environmental issues. In both cases government agencies are the principle end-user. The only market sector dominated by private companies has been geological applications, and in particular mineral exploration. The emergence of commercial remote sensing and the availability of sub-metre resolution imagery from satellites (largely as a spin-off from military activity) are likely to result in a shift in the balance of applications from the natural to the built environment. Nevertheless, new applications are emerging because of the improved availability and accessibility of these data, e.g. frequent and scheduled data acquisition, consistent data quality, digital format, ease-of-import to image processing/GIS software. Yet, these are but operational issues.

The more important question and the key element to any Earth observation strategy using remote sensing is will it meet all (or some or none) of your information needs? To make this determination, you need to understand the principles of the remote sensing system –of electromagnetic radiation, of energy interactions with targets, of platforms and sensors. You need to understand how a signal detected by a sensor is calibrated and formatted into multispectral images and how to extract meaningful Earth surface information from them. By completing this course you will better-placed to design and implement a successful strategy for applied remote sensing. In this final section we will postulate on future directions for remote sensing and consider how remote sensing and GIS are likely to develop.

  1. Student Learning Resources

The primary resource will be the Course Reader supplemented by a mixture of academic books, academic journal articles, and professional references.

The Course Reader walks the student through the key issues for each of the topics and offers two sets of tasks that revolve around reflection and self-reflection on the part of the students. The first set of tasks is a series of approximately 15-20 weekly exercises that students can complete in 1-4 hours. The answers for five of these exercises are shared with the other students in the course and submitted to the instructor for grading. The second set of tasks is a series of two or three paper assignments that students prepare and submit for grading. These papers rely on individual research and are more substantial in terms of scope and purpose than the exercises.

The academic book, academic journal and professional references serve slightly different roles. The two books specified below are mainly for reference and/or to help with the preparation of papers. The academic journal and professional references, on the other hand, are an integral part of the course and help to facilitate reflection and self-reflection on the part of the students, who must prepare short reports summarizing the content of each book chapter or journal article and how it relates to the material provided in the Course Reader.

Books:

Jensen J R (2000) Remote Sensing of Environment: An Earth Resource Perspective.Upper Saddle Creek, NJ, Prentice Hall

Mesev V (ed) (2003) Remotely Sensed Cities.London, Taylor and Francis

Academic Journal Articles:

Barnsley M (1999) Digital remotely-sensed data and their characteristics. In Longley P A, Goodchild M F, Maguire D J, and Rhind D W (eds) Geographical Information Systems: 1, Principles and Technical Issues.New York, John Wiley and Sons: 451-66

Dietzel C, Herold M, Hemphill J J, and Clarke K C (2005) Spatio-temporal dynamics in California’s Central Valley: Empirical links to urban theory. International Journal of Geographical Information Science 19: 175-95

Estes J E and Loveland T R (1999) Characteristics, sources, and management of remotely-sensed data. In Longley P A, Goodchild M F, Maguire D J, and Rhind D W (eds) Geographical Information Systems: 2, Management Issues and Applications.New York, John Wiley and Sons: 667-75

Lange A and Gilbert C (1999) Using GPS for GIS data capture. In Longley P A, Goodchild M F, Maguire D J, and Rhind D W (eds) Geographical Information Systems: 1, Principles and Technical Issues.New York, John Wiley and Sons: 467-76

Lees B (2006) Remote sensing and GIS. In Wilson J P and Fotheringham A S (eds) The Handbook of Geographical Information Science.Oxford, Blackwell: in press

Lucieer A and Kraak M-J (2004) Interactive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty. International Journal of Geographical Information Science 18: 491-512

Petit C C and Lambin E F (2001) Integration of multi-source remote sensing data for land cover change detection. International Journal of Geographical Information Science 15: 785-804

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