GIS for SUSTAINABLE DEVELOPMENT - PART 2

Part II GIS Research Perspectives for Sustainable Development Planning © 2006 by Taylor & Francis Group, LLC 7 Advanced Remote Sensing Techniques for Ecosystem Data Collection Alexandr A. Napryushkin and Eugenia V. Vertinskaya CONTENTS 7.1 Introduction..................................................................................................107 7.2 RS-Based Thematic Mapping Methodology...............................................109 7.2.1 General Concept...............................................................................109 7.2.2 Imagery Interpretation Approach.....................................................111 7.3 Thematic Mapping Methodology Implementation......................................114 7.3.1 The RS Imagery Processing and Interpretation System “LandMapper”..................................................................................114 7.3.2 Application of “LandMapper” for Anthropogenic Ecosystems Research.......................................................................116 7.3.2.1 Mapping Hydro Network and Urban Areas of Tomsk City...................................................................116 7.3.2.2 Landscape-Ecological Research of Pervomayskoe Oil Field............................................................................118 7.4 Conclusion....................................................................................................121 Acknowledgments..................................................................................................122 References..............................................................................................................122 7.1 INTRODUCTION The problems of monitoring and ecological control of ecosystems of different natures are becoming more and more urgent. Monitoring of the Earth’s surface has a mul-tidisciplinary character and allows a wide spectrum of issues to be solved. The ecosystem components involved in monitoring are manifold and include, among others, surface waters, soils, vegetation canopy, and anthropogenic landscape components. The latter represent the man-made and man-changed ecosystems and are of primary interest 107 © 2006 by Taylor & Francis Group, LLC 108 GIS for Sustainable Development in the context of monitoring and management problems due to degradation of recent ecological conditions [1]. One of the most important issues solved in the monitoring process is represen-tation of its results as a series of thematic maps indicating the spatial structure of complex ecosystem components [2]. The basic concern of thematic mapping is graphical modeling of ecosystems and providing the information on their conditions for efficient natural resources management. The geoinformation provided by the thematic maps is used for analysis and assessment of natural resource conditions, recording and accounting destructive natural phenomena, studying natural and man-made ecosystems interaction, revealing anthropogenic impact to environment, and assessing its consequences [1,3]. Initial information used for ecosystems thematic mapping is acquired by means of terrestrial and remote monitoring techniques. The former characterize only 1 to 5% of surface and are not efficient to provide sufficient information on large eco-systems. Moreover, when detailed research is conducted, personnel, equipment, and time costs increase dramatically. Remote monitoring techniques provide a number of advantages over the terrestrial techniques, allowing the limitations of the latter to be overcome. In the literature, the concept of remote monitoring or surveying is referred to as remote sensing (RS) [4]. The RS techniques involve detecting and measuring electromagnetic radiation or force fields associated with terrestrial objects located beyond the immediate vicinity of recording instruments, such as radiometers or radar systems mounted on an aircraft or satellite. Remote monitoring, unlike the terrestrial one, allows a large-scale ecosystem to be surveyed with a short repeat cycle. The latter in most cases is a crucial criterion for ecosystem-change research. Generally, RS data represent images much like photos of the sensed surfaces of the objects under surveillance, and in the literature, RS images are often referred to as aerospace imagery [5]. Recently, thematic mapping of ecosystems has been widely implemented through employing geographic information systems (GIS) characterized by advanced capabilities for spatial information storing, manipulating, and processing [6]. Modern GIS provide wide capabilities for both computer-aided thematic mapping and spatial analysis of mapped features and phenomena, allowing derivation of complex quan-titative characteristics indispensable for ecosystem conditions modeling and fore-casting. Commonly, GIS facilities are oriented mainly for vector data handling, while RS-based thematic mapping methodology requires supporting functions of raster image processing. This fact makes urgent the problem of developing efficient and highly integrated software means enabling GIS to implement aerospace imagery processing and facilitate the thematic mapping technologies with use of RS data. In this chapter, the methodology of RS-based thematic mapping is introduced. The implementation of the methodology is based on application of a vector GIS and original image processing and interpretation system “LandMapper” [7], developed at Tomsk Polytechnic University (TPU). The main distinction of the system from its counterparts is adaptive classification procedure (ACP), making the process of image interpretation more flexible and efficient in comparison with existing recog-nition techniques. The chapter considers the basic methodology of image processing and interpretation adopted in the “LandMapper” system and gives the results of its © 2006 by Taylor & Francis Group, LLC Advanced Remote Sensing Techniques for Ecosystem Data Collection 109 application for solving problems of mapping two anthropogenic ecosystems with the use of multispectral imagery acquired from the Russian satellite RESURS-O1. 7.2 RS-BASED THEMATIC MAPPING METHODOLOGY 7.2.1 GENERAL CONCEPT Today, thematic mapping technologies making use of RS monitoring data and mod-ern GIS-based tools are of great value, especially when significant interest is taken in research of various aspects of anthropogenic ecosystems. The wide range of anthropogenic issues that can be solved by means of RS-based thematic mapping involve urban areas monitoring [2], land use mapping, anthropogenic load of petro-leum-production territories assessment, snow cover surveying, and flood forecasting. Recently joint use of GIS and thematic maps designed with aerospace imagery proved to be an efficient approach to creating and employing comprehensive models of anthropogenic ecosystems that were indispensable for decision-making. Designing thematic maps with the use of RS imagery consists of a number of steps, including complicated processing of initial imagery, and is, as a rule, a nontrivial task to accomplish. Figure 7.1 illustrates the general scheme of thematic mapping of landscape ecosystems with use of remotely sensed images. According to Figure 7.1, in the methodology of RS-based thematic mapping, the stages of preliminary and thematic processing of imagery may be distinguished. Orbital segment Radiometric and geometric corrections Radiochannel Imagery preliminary processing Rectification and georeferencing Receiving ground station (imagery archive) Imagery Rectified and georeferenced Sample data imagery Interpretation Imagery thematic processing Conversion of raster thematic classes into vector features Thematic maps Ancillary geoinformation Spatial analysis and quantitative estimation GIS analysis GIS modeling Forecasting and decision making FIGURE 7.1 Thematic mapping with use of remotely sensed imagery. © 2006 by Taylor & Francis Group, LLC 110 GIS for Sustainable Development Initially, imagery acquired from a satellite or aircraft is exposed to multilevel preliminary processing in order to make it usable for comprehensive analysis and facilitate transition from a simple raster image to a complex thematic map model. The preliminary processing involves solving the tasks of geometric and radiometric error correction. The tasks include compensation of radiometric distortion caused by atmospheric effect and instrumentation errors, correction of geometric distortion due to the earth curvature, rotation, and panoramic effect, noise reduction, image registration in a geographical coordinate system (georeferencing) through its recti-fication, and visual properties enhancement by histogram transformation [8]. The thematic and geometric information defining the application domain of the final thematic map is extracted at the stage of imagery thematic processing [5]. In thematic processing, very significant attention is paid to the image interpretation issue. Image interpretation provides revealing thematic knowledge about a studied ecosystem component and its spatial relationships by identifying image features and assigning them appropriate semantic information such as, for instance, landscape cover type. Commonly, two main approaches can be adopted for image interpretation. One is referred to as photointerpretation and involves a human analyst/interpreter extract-ing information by visual inspection of an RS image [5]. In practice, photointerpre-tation is a very laborious and time-consuming process, and its success depends mainly upon the analyst effectively exploiting the spatial and spectral elements present in the image product. Another approach involves the use of a computer to assign each pixel in the image semantic information (land cover type, vegetation, or soil class) based upon pixel attributes. This approach deals with the concept of automated image interpretation–classification. Commonly, the approach appears to be most efficient when applied to multispectral imagery [4] having several bands of data acquired in different not overlapped spectral ranges. In practice, classification is often carried out in so-called supervising mode, requiring the classification procedure to be trained beforehand. Training of the classification procedure relies upon selecting a set of representative elements (pixels) in the image for each informational class (land cover type) and forming training sets to be used further by the procedure as prototypes of extracted classes. Forming training data for supervised classification is one of the important issues in imagery thematic processing. This is carried out by gathering ancillary sample data that helps obtain a prior knowledge of the properties of ecosystem components present in RS imagery. Practically, sample data is acquired from different sources of information about the studied ecosystem — site visit data, topographic maps, air photographs, or even results of initial imagery photointerpretation. The final product of the thematic processing stage is a raster map, each pixel of which is labeled with an appropriate code (label) corresponding to a landscape thematic class. Thus, different groups of equally labeled pixels in a thematic map represent thematically uniform objects recognized in imagery by the classification procedure. Imagery thematic processing is followed by transferring the resultant thematic map into GIS, where it can be integrated with other data acquired from various informational sources, and comprehensive spatial analysis of the data can be con-ducted. Since many GIS software packages basically manipulate vector information, © 2006 by Taylor & Francis Group, LLC ... - tailieumienphi.vn