Digital Remote Sensing Data Processing Digital Remote Sensing Data Processing and Analysis: An Introduction and Analysis: An Introduction Content Remote sensing data Spatial, spectral, radiometric and temporal resolution Digital image processing tasks and scenarios Hardware and software Academic journals What is Remote Sensing? The non-contact recording of information from the ultraviolet, visible, infrared, and microwave regions of the electromagnetic spectrum by means of instruments such as camera, scanners, lasers, linear arrays, and/or area arrays located on platforms such as aircraft or spacecraft, and the analysis of acquired information by means of visual and digital image processing. Remote Sensing, GIS, Cartography, and Remote Sensing, GIS, Cartography, and Geography Interaction Model Depicting the Relationships of the Mapping Sciences as they relate to Mathematics and Logic, and the Physical, Biological, and Social Sciences Collects and/or processes spatial data derived from existing maps, remote sensors, field observation, interactive terminal, digitizers, text files, scanners, magnetic media etc. Characteristics and Components of A Remote Sensing System Measurements or observations are taken without making direct physical contact with the object in question Remote Sensing Data Acquisition A remote sensing instrument collects information about an object or phenomenon within the instantaneous field-of-view (IFOV) of the sensor system without being in direct physical contact with it. The sensor is located on a suborbital or satellite platform. 1
In Situ Data Collection In Situ Data Acquisition Problems Associated with In Situ Data Collection Scientists can collect data in the field using biased procedures often referred to as method-produced error. Such error can be introduced by: sampling design does not capture the spatial variability of the phenomena under investigation (i.e., some phenomena or geographic areas are oversampled while others are undersampled); improper operation of in situ measurement instruments; or uncalibrated in situ measurement instruments. In situ Measurement In Support of Remote Sensing Measurement In situ spectro-radiometer measurement of soybeans In situ ceptometer leaf-area-index (LAI) measurement Ground Reference Information It is a misnomer to refer to in situ data as ground truth data. Instead, we should refer to it simply as in situ ground reference data, and acknowledge that it also contains error. Characteristics and Components of A Remote Sensing System The electromagnetic spectrum is the energy that carries information through the atmosphere from the Earth's surface to the sensing device The remote sensing instrument used to record the EM signals are often to be referred to a sensor: camera, scanner, altimeters, and other photographic (analog) and digital remote sensing sensors; Remote: at a distance from the object or area of interest Remote sensing of the terrestrial Earth from platforms: aircraft, satellite, and space shuttles Science or Art or Both? Scientific aspects Image processing of remote sensing data involves developing algorithms or techniques that can be extract information from the detected EM energy exiting an object or area Art aspects Visual interpretation of images requires training and learned knowledge about the world, heuristic rules of thumb to extract valuable information from the imagery, widely traveling and seeing various landscapes and geographical areas 2
Advantages of Remote Sensing Advantages of Remote Sensing Observation of Earth s Surface Limitations of Remote Sensing Aerial vs. Space-borne Remote Sensing Airborne High-spatial, high-spectral resolution aerial photographs offer detailed view of the Earth s surface; Ground coverage is relatively small, and expensive to acquire; Severe geometric distortion may occur due to atmospheric turbulence and difficult to correct On less regular temporal basis Satellite-based Satellite photographs and images provide synoptic, less detailed view; Ground coverage is large, and relatively cheap; On regular and consistent temporal basis; Stable orbit, and better geometric integrity; Types of Remote Sensing Passive Remote Sensing Systems Active Remote Sensing Systems Visible & Infrared Remote Sensing Thermal remote sensing Radar remote sensing Lidar remote sensing Passive microwave remote sensing The Remote Sensing Process The remote sensing data-collection and analysis procedures used for Earth resource applications are often implemented in a systematic fashion referred to as the remote sensing process. In situ and collateral data necessary to calibrate the remote sensor data and/or judge its geometric, radiometric, and thematic characteristics are collected Remote sensor data are collected passively or actively using analog or digital remote sensing instruments, ideally at the same time as the in situ data In situ and remotely sensed data are processed using a) analog image processing, b) digital image processing, c) modeling, and d) n-dimensional visualization Remote Sensing Data Collection Resolution/Resolving Power/Scale of Remote Sensing Data Spatial resolution A measure of the smallest angular or linear separation between two objects that can be resolved by the sensor satellite sensors with fixed orbit and fixed optical 3
systems have a constant instantaneous-field-of-view (IFOV) Spectral Resolution The number and dimension of specific wavelength intervals in the EM spectrum to which a remote sensing instrument is sensitive Radiometric Resolution Temporal Resolution Angular Information Remote sensing systems record very specific angular characteristics associated with each exposed silver halide crystal or pixel There is always an angle of incidence associated with the incoming energy that illuminates the terrain and an angle of existence from the terrain to the sensor system. This bidirectional nature of remote sensing data collection is known to influence the spectral and polarization characteristics of the at-sensor radiance, L, recorded by the remote sensing system Remote Sensing Data Analysis The analysis of remotely sensed data is performed using a variety of image processing techniques, including: analog (visual) image processing, and digital image processing. Earth Resource Analysis Perspective Earth resource information is defined as any information concerning terrestrial vegetation, soils, minerals, rocks, water, certain atmospheric characteristics, and urban infrastructure Tasks and Scenario of Image Processing and Analysis Image Preprocessing-rectification and restoration Image Enhancement Image Transformation Image Classification Image Integration and Fusion Image Acquisition Imaging sensor & capability to digitize the signal collected by the sensor Video camera Digital camera Conventional camera & analog-to-digital converter Various sensors on the airborne or space-borne platforms Preprocessing To improve the image to ensure the success of further processes 4
Segmentation & Classification To partition the image into its constituent parts (objects) Representation & Description Feature selection (description) deals with extracting: features that result in quantitative information of interest or features that are important for differentiating one class of objects from another Knowledge Base Guides the operation of each processing module and controls the interaction between modules Recognition & Interpretation To assign a label to an object based on information provided by the descriptors To assign meaning to a group of recognized objects Comments Image enhancement for human visual interpretation usually stops at preprocessing Recognition and interpretation are associated with image analysis applications where the objective is automation (automated extraction of information from images) Nature of Digital Image A digital image is two-dimensional array of DN values Information from Remote Sensing Information about an Object or Area Such information may be useful for modeling Image Processing System Hardware /Software Considerations Interactive versus Batch Processing Non-interactive, batch processing is of value for time-consuming processes such as image rectification, mosaicking, orthophoto creation, filtering, etc Serial and Parallel Image Processing It is possible to obtain PCs, workstations, and mainframe computers that have multiple CPUs that operate concurrently. Specially written parallel processing software can parse (distribute) the remote sensor data to specific CPUs to perform digital image processing. Storage and Archiving Considerations Digital image processing of remote sensing and related GIS data requires substantial mass storage resources. 5
Commercial and Public Digital Image Processing Systems Major Commercial Software Major Public Digital Image Processing Systems ENVI Software ENVI is written in Interactive Data Language (IDL), a structured programming language Important Image System Functions Preprocessing (Radiometric and Geometric) Display and Enhancement Information Extraction Photogrammetric Information Extraction Metadata and Image/Map Lineage Documentation Image and Map Cartographic Composition Geographic Information Systems (GIS) Integrated Image Processing and GIS Utilities Sources of Digital Image Processing Systems Suggested Reading Chapter 1 and 3 in Jensen, J.R. 2005. Introductory digital image processing: a remote sensing perspective, 3rd Edition, Upper Saddle River, NJ, Prentice Hall. 526pp. Please see the class slides for the details. 6