REMOTE SENSING DATA PRODUCTS AND FORMATS

Transcription

1 UNIT 6 REMOTE SENSING DATA PRODUCTS AND FORMATS Data Types and Sources Structure 6.1 Introduction Objectives 6.2 What is a Data Product? 6.3 Index Numbers for Data Products 6.4 Types of Data Products Products Based on Level of Processing Products Based on Output Media/Scale Products Based on Area of Coverage 6.5 What is Data Format? Types of Data Formats Standards of Data Formats 6.6 Product Code 6.7 Placing an Order for a Data Product 6.8 Activity 6.9 Summary 6.10 Unit End Questions 6.11 References 6.12 Further/Suggested Reading 6.13 Answers 6.1 INTRODUCTION You have been introduced to the basic concepts of remote sensing, its principles and applications, in detail in Block 1 Introduction to Geoinformatics of MGY-001 Overview of Geoinformatics. You will find more details about remote sensing in Block 1 Introduction to Remote Sensing and Block 2 Sensors and Space Programmes of the course MGY-002 Remote Sensing and Image Interpretation, which will include electromagnetic radiation and its interactions with matter, remote sensing regions and bands, spectral signatures/response patterns of some common natural objects, sensors and platforms and image resolutions. The raw remote sensing data recorded through the medium of electromagnetic radiation contain many systematic distortions and errors. The data have to be processed to remove the distortions and errors. Finally, the data are converted into various products to be supplied to users for various applications. There is a remarkable difference between raw remote sensing data recorded and processed remote sensing data which is supplied to users. In this unit, you will be first introduced to remote sensing data products and formats. You will also get an idea about how and where to procure remote sensing data products from i.e. data centers/suppliers. 39

2 Concepts of Geospatial Data Remote sensing data is a product like a block of aluminium metal before it is shaped into a usable utensil/vessel. You will find that the whole process with raw satellite images is just like collecting a raw material and processing the same into a finished one, just as aluminium ore (i.e. bauxite) is processed into aluminium metal to be used to make utensils/vessels. Objectives After reading this unit you should be able to: define what is a data product; list out the types of data products; discuss about different types of data formats; and identify how and where to acquire remote sensing data. 6.2 WHAT IS A DATA PRODUCT? A pixel is the smallest cell of an image, representing a unit area of the Earth s surface. You will learn more about digital images in Unit 10 Characteristics of Digital Remote Sensing Images of MGY-002 Remote Sensing and Image Interpretation The first step while starting a geoinformatics related project is to place an order for the procurement of remote sensing data. There are two types of data used in geoinformatics. One is raster data and the other is vector data. When we talk of remote sensing data, we always mean raster data. In its simplest form, a raster data means data consisting of a matrix of cells or pixels (Fig. 6.1) organised into rows and columns (or a grid) where each cell contains a value representing information, such as reflected electromagnetic radiation (EMR), temperature, or height values (Fig. 6.1). Raster data products include digital aerial photographs, imagery from satellites, digital pictures, or even scanned maps. Fig. 6.1: Arrangement of grid cells or pixels in raster data (source: Arc GIS Guide Book by ESRI, 40 The data from various sensors are presented in a form and format with specified radiometric and geometric accuracy which can be readily used by various application scientists for specific themes of their interest. Remote

3 sensing data can be procured by a number of users for various applications and information extraction, in the form of a data product. This may be in the form of photographic output for visual processing or in a digital format amenable for further computer processing. There are varieties of remote sensing data which are acquired by different sensors and satellites. Before reaching to users, the data undergo some processing steps. Requirements of users may vary depending upon their interests and project objectives, hence there are various remote sensing data providers/suppliers which prepare variety of data products in different formats. Remote Sensing Data Products and Formats Data Products are: data from various sensors in a suitable and standard form and format, which can be readily used by user. To order, a data the user should be aware of the types of data products available with the data agencies/suppliers. Once the data are received by the users, these need to be changed into a form required to perform image analysis task. To convert the data into required form, the users should have basic understanding of the characteristics of different data formats. It would be a time consuming and difficult task for users to understand all different data and their formats. Hence, there are some standards which are followed by data centers/suppliers with regard to the data products and formats for sharing with a variety of users. Remote sensing data products are generated in certain data formats about which the users must be aware of, for various practical reasons. Pre-processed remote sensing data are generated into a number of products, like hardcopy prints on various types of papers, digital data on various types of computer compatible media, like tapes, compact discs (CDs), DVDs, and various other computer compatible storage devices. If the data product is in hard copy print then it is impossible to carry out any further processing or conversion before use. But if the product is in digital form, it may be possible to convert the data into a processed digital image. It may be further required to carry out certain processing before any image analysis operation is performed. Types of data products may vary from country to country and/or from one data provider to another. Here, an account is given about the various data products made available in India to users by the National Data Center (NDC) of National Remote Sensing Centre (NRSC) of the Indian Space Research Organisation (ISRO), situated at Hyderabad. 6.3 INDEX NUMBERS FOR DATA PRODUCTS All remote sensing data products carry a specific index number. This index number is generated using the satellite path which runs from North Pole to South Pole of Earth. This pole to pole coverage on the Earth for each pass of the satellite is given a specific number, called path number or track number. In case of coverage of India, path numbers range from 88 to 116 from west to east for LISS sensor of IRS (Indian Remote Sensing) satellites. These paths are nothing but orbital tracks of a satellite which at a small angle from geographical north-south, and are somewhat parallel to each other. East-West lines (called row) cut across these lines giving a grid like structure. This is how a series of columns and rows are created. Just like each column is given a specific number, each row is also given a specific number. India is covered by rows 45 to 70 from north to south. In a similar way, the entire world is covered by paths and rows, and each grid (a scene) is identified by a specific 41

4 Concepts of Geospatial Data path and row number (Fig. 6.2). For example, Lucknow s scene of IRS image has an index number (Path-Row). As the path-row for different satellites are different, the index number of Lucknow image for other satellites will not be the same. Fig. 6.2: A sample piece from Index chart of IRS-1C. You can see in map that the Lucknow city is covered in the data having Path-100 and Row TYPES OF DATA PRODUCTS You will learn about radiometric and geometric distortions and corrections in Block 4 Processing and Classification of Remotely Sensed Images of MGY- 002 Remote Sensing and Image Interpretation. 42 The types of remote sensing data products depend on: level of processing output media/scale and area of coverage Products Based on Level of Processing Based on level of processing, the data products are classified into following three types: a) standard products b) value added products and c) derived products. Let us now discuss about each of these three classes of remote sensing products. You may note that the information presented here is sourced to the content in NRSC website ( You can log onto this website and get the information, as given here in the following pages. a) Standard Data Products These products are generated using information received directly from the satellites and by applying necessary radiometric and geometric corrections.

5 These products are of various types. You will read some important aspects of standard products; Remote Sensing Data Products and Formats Path-Row Based Standard Products: Actually, the data are recorded by the sensors along the track/path of the satellite covering a specific width (across the satellite track/path). The user specifies path and row of the scene, sensor, sub-scene (if any), number of scenes, date of pass of the satellite, band numbers/band combination (for photographic products) and the product code (specified by the data provider) as necessary information to procure the desired products from the provider, for example in India, the National Data Centre (NDC) of National Remote Sensing Centre (NRSC), Hyderabad. Shift Along Track (SAT) Products: In case a user s area of interest falls between two successive scenes of the same path (one below the other), the data can be supplied by sliding the scene in along-the-track direction. These products are called Shift-Along-Track Products. In this case, the percentage (10% to 90% in multiples of 10%) of shift has to be specified by the user in addition to the other necessary information about both the scenes. Quadrant Products: In IRS series of satellites, LISS III full scene (path/ row based products) data has been divided into 4 nominal quadrants designated by letter A, B, C & D. Each of these quadrants is one full scene of PAN data (B & W data), and is further divided into 9 quadrants. These are given numbers from 1 to 9 which are nothing but PAN subscenes. While placing a request for these products, users need to specify the quadrant number in addition to the details specified for path/row based products (Fig. 6.3). Fig. 6.3: Detailed Indexing Method of IRS-1C LISS III and PAN data products Georeferenced Products: Georeferencing is the process of transforming the remote sensing data or a map to a coordinate and projection system. This means, all the objects/elements in remote sensing data and the map get specific geographic location in terms of longitudes and latitudes. Thus, georeferenced products are north-east oriented products. Basic Stereo Products: A stereo-pair comprises two images of the same area, acquired on different dates or same day; from different angles. These products are used for generating digital elevation maps or 3D visualization of the study area. Cartosat-1 mission provides along track stereo images. 43

6 Concepts of Geospatial Data Area of Interest (AOI) based Products: Users may define their area of interest according to the extent of study area. Scenes covering the user s AOI can be selected and ordered for procurement. The scenes covering the users AOI are provided as tiles and are not mosaicked. The minimum order/quantity for IRS P5 products is sq km and that for IRS-P6 data is sq km for LISS IV and maximum order/quantity is 10,000 sq km. AOI based products are provided as digital products (CD/DVD) only. Cartosat-1 products are supplied with different processing levels, viz. i) Radiometrically corrected products and ii) Orthokit - apart from radiometric corrections, these products are also provided with user defined projections. b) Value Added Products When standard products are processed according to specifications and requirements of users, these products get converted into value added products. These products are basically of four types viz. Geocoded products Merged products Ortho product and Template registered products. Let us now discuss in some detail about these four types of products. Geocoded Products: These products are also known as georeferenced products (mentioned in one of the preceding paragraphs). Geocoding can be performed with reference to both topographical maps and floating points. Thus, geocoded products are of two types viz. topographical map based products, and floating point (not based on topographical maps) based products. Merged Products: Remote sensing satellites record multiband/multispectral (MSS) data and single-band/panchromatic data. Panchromatic/ mono-band data contains higher spatial resolution and multi-band data have comparatively low in spatial resolution. When MSS data area is merged with panchromatic data, we get MSS data with spatial resolution of panchromatic data. Data can be merged only when both MSS and PAN data have been registered with the same georeferencing system. Ortho Products: Geometrically corrected products, with corrections for displacement caused by tilt and relief, are called Ortho Products. Therefore, ortho images show ground objects in their true planimetric positions, like the positions of objects in a map. The basic inputs required for ortho-image generation are: (i) Digital Elevation Model, (ii) Ground Control Points, (iii) Satellite ephemeris (orbit and altitude information), and (iv) Radiometrically corrected satellite data. 44 Template Registered Products: In specific cases, such as the study of crops and their monitoring, data of the same area having similar geometric fidelity and temporally registered are required. Such data sets are called template registered products. In India, data from AWiFS sensor

7 is envisaged for extensive use in crop monitoring. Such data sets are called templates in RESOURCESAT-1 context. These templates are used as reference images to register the AWiFS scene data. The template space is a fixed spatial reference grid over India. Full India space is overlaid with 1º 1º template grid, and each grid can be uniquely identified by a number. Remote Sensing Data Products and Formats c) Derived Products Information extracted from remote sensing data is also provided as useful products by data providers. For example, vegetation index map or sea surface temperature profiles extracted from various remote sensing data products are called derived products. These derived products are generated by further processing /analysing the data, and are readily usable by the user. Based on output media, data products are available on both photographic as well as digital media. Photographic products can be supplied as films or prints. Output products can vary from 1:1 million to 1:50000 or even to 1: The following table gives detailed information on the type of product available for various sensors of IRS series of satellites. The table is reproduced from the content of NRSC website ( Products Based on Output Media/Scale NRSC provides remote sensing products in two types of media: photographic media digital media. Photographic products are supplied on film or paper prints. The scale of these photographic products can range from 1:1M to 1: Products Based on Area of Coverage You will find main types of remote sensing data products based on area of coverage, as given in Table 6.1. Table 6.1: Main types of remote sensing data products based on area of coverage No Types of Remote Sensing Products Sensors/Satellites 1 Full Scenes-all bands PAN from LISS-III & LISS-IV; AWIFS; TM; MLA; PLA; WIFS; OCM; MSMR; MODIS 2 Full Scenes-specified bands LISS-III, LISS-II, LISS-I, TM, (3 bands for FCC products) 3 Full Scenes with Shift-Along Track PAN & WIFS from LISS-III; AWIFS from LISS-IV; OCM; 4 Quadrants LISS-III, TM, OCM 5 Geocoded Mapsheet based (15 x 15 ) LISS-III, LISS-II, TM, MLA, PLA 6 Geocoded Floating (15 x 15 ) LISS-III 7 Geocoded (7½ x7½ ) mapsheet/floating LISS-III, LISS-IV 8 Full pass/strip data of one array PAN, OCM, MODIS 45

8 Concepts of Geospatial Data Spend Check Your Progress I 5 mins 1) Define data products. 2) From where will you procure the desire remote sensing data? 3) On which factors do the types of remote sensing data products depend? 4) Name the types of value added remote sensing data products. 6.5 WHAT IS DATA FORMAT? Remote sensing data or image data is a digital picture or representation of various objects on the Earth s surface. The picture is a systematic arrangement of raster cells. Each of the raster cells, depending on the intensity of radiation received, contains a digital number between a certain range, for example, (7 bit image) or (8 bit image) and so on, depending upon radiometric processing capacity of the detector system of the sensor. Each number (of each cell) in an image file is a data file value, sometimes also called pixel (abbreviation of picture element), and data file value is the measured brightness value of the pixel at a specific wavelength. Raster image data are laid out in a grid format similar to squares on a checkerboard. These raster cells are assigned gray shades from darkest shade for zero digital number to the brightest white shade for digital number 127 or 255 or 511 and so on, and comparative grades of dark and white shades are assigned in between from digital numbers or or and so on. Image data format can be defined as the sequential arrangement of pixels, representing a digital image in a computer compatible storage medium, such as a compact disk (CDs/DVDs). 46 Superposition of any three bands of data, each of which is developed in blue, green and red shades gives a color composite image of the area. That means, remote sensing image data, stored in data files/image files on magnetic tapes, compact disks (CDs/DVDs) or other media, consist only of digital numbers.

9 These representations of numbers form the B & W or color images when they are displayed on a screen or output on a hard copy. Thus, the image has to be retained in its digital form in order to carry computer processing/ classification. The digital output is supplied on a suitable computer compatible storage media, such as DVDs, CD-ROMs, DAT, etc., depending on user requests. The data may be arranged in band sequential (BSQ), band interleaved by line (BIL) or band interleaved pixel (BIP) formats. Remote Sensing Data Products and Formats Similarly, the concept of image data format comes in, with the question of how to arrange these pixels to achieve optimum level of desired processing and display. Let us look at the following example, a data file in jpg format is a compressed file in a small size, say 10MB; whereas, the same file in tiff format is uncompressed and its size can go up to 100MB. What happens in these two cases of files is the data transfer is easier with small size file, like a jpg file than in tiff format Types of Data Formats Basically, there are three types of data formats: Band Interleaved by Pixel (BIP), Band Interleaved by Line (BIL), and Band Sequential (BSQ) Band Interleaved by Pixel (BIP) Data storage sequence in BIP format is shown in Fig. 6.4, for an image of size 3 3 (i.e. 3 rows and 3 columns) having three bands. Band, row and column (pixel) are generally represented as B, R and P, respectively. B1, R1 and P1, respectively represent band 1, row 1 and column (pixel)1. In this format, first pixel of row 1 of band 1 is stored first then the first pixel of row 1 of band 2 and then the first pixel of row 1 of band 3. These are followed by the second pixel of row 1 of band 1, and then second pixel of row 1 of band 2 and then second pixel of row 1 of band 3 and likewise. Fig. 6.4: The data storage sequence in BIP format 47

10 Concepts of Geospatial Data Band Interleaved by Line (BIL) Data storage sequence in BIL format is shown here in Fig. 6.5 for a three band image of size 3x3 (i.e. 3 rows and 3 columns). B and R represent band and row. B1 and R1 represent band 1 and row 1. In this format, all the pixels of row 1 of band 1 are stored in sequence first, then all the pixels of row 1 of band 2 and then the pixels of row 1 of band 3. These are followed by the all the pixels of row 2 of band 1, and then all the pixels of row 1 of band 2 and then all the pixels of row 1 of band 3 and likewise. You should note that both the BIP and BIL format store data/pixels in a line (row) at a time. Fig. 6.5: Data storage sequence in BIL format Band Sequential (BSQ) BSQ format stores each band of data as a separate file. Arrangement sequence of data in each file is shown in Fig. 6.6 for a three band image of size 3 3 (i.e. 3 rows and 3 columns). B and R, respectively represent band and row. B1 and R1 represent band 1 and row 1, respectively. In this format, all the pixels of band 1 are stored in sequence first, followed by all the pixels of band 2 and then the pixels of band Fig. 6.6: Data storage sequence in BSQ format

11 For color image output, BSQ format is considered as convenient because three bands are assigned to R (red), G (green) and B (blue). However, BIP format is considered better for classification because multi-band data are required pixel by pixel for processing. BIL is considered as a compromise between BSQ and BIP. Keeping to these three basic data formats, a number of other formats, like tiff, geotiff, png, adrg, super structured, jfif, jpeg, etc., are developed by different organisations. Most of the image processing software for remote sensing data processing support these file formats. You can see the list of data file formats supported by the image processing software in the software s documentation manual. If a software does not have a certain data format in its list then that file cannot be opened and used in that particular software. Remote Sensing Data Products and Formats You will read about concept of generation of false color and true color images in Unit 10 Characteristics of Digitally Remotely Sensed Images of MGY-002 Remote Sensing and Image Interpretation Standards of Data Formats There are certain standards when the data are supplied as softcopy in digital form. Digital products are commonly supplied in the following formats: LGSOWG (Landsat Ground Station Operators Working Group) or Super Structured Format Fast Format GeoTIFF (Geographic Tagged Image File Format) HDF (Hierarchical Data Format) LGSOWG or Superstructure Format This format has been developed by Landsat Ground Station Operators Working Group, and is considered as standard. This extensive format is suitable for Level-0 (raw data with no correction applied) and Level-2 (GEO i.e., both radiometric and geometric corrections applied) products. This format is also known as Super Structured Format or World Standard Format, or LTWG format (as specified by Landsat Technical Working Group). It is a consistent collection of one or more files recorded consecutively. All logical volumes have a volume directory as the first file and null volume directory as the last file. The layout of the superstructure format both in BSQ and BIL is shown in Fig. 6.7, respectively. When the digital data are provided in this format in a CD-ROM or DVD, the data contain following five files: a) volume directory file b) leader file c) image file d) trailer file e) null volume directory file a) Volume directory file is the first file of the media containing the data product. It contains information on file format record length, number of records, etc. This gives information about all subsequent files present in the medium, viz. number of bands, arrangement of bands, total number of files, information about processing station, software version used to process, etc. 49

12 Concepts of Geospatial Data b) Leader file is composed of a file descriptor record and three types of data record types i.e., header, ancillary and annotation. Header contains information (such as about mission, sensor, processing parameters, etc. Ancillary information consists about information related to ephemeris, attitude, calibration, histogram, map projection and ground control points (GCP s), for image geometric correction, radiometric calibration data, etc. Volume directory file Volume directory file File descriptor record Leader file File descriptor record Leader file File descriptor record Image data file B2 File descriptor record Image data file B3 File descriptor record Image data file B4 File descriptor record Trailer record File descriptor record Image data file Line of B2 Line of B3 Line of B Line M of B2 Line M of B3 Line M of B4 File descriptor record Trailer record Null volume directory file (a) Null volume directory file (b) Fig. 6.7: Physical layout of three band image data (e.g. IRS-1C/1D LISS-3 B2, B3, B4) in (a) super structure BSQ; (b) Super structure in BIL format. File desc rec refers to File descriptor record (source: Joseph, 2005) c) Image file contains the actual raw or processed data as requested by the user. It consists of file descriptor records giving information regarding band number, bite per pixel, etc. and image data records. Image data record contains the video data in band interleaved by line (BIL) format or band sequential format (BSQ). d) Trailer file provides information about the mode of reading the file and contains information about cloud coverage, etc. This file follows the image data file. e) Null volume directory file marks the end of logical volume. It is referred to as null because it defines a non-existent (empty) logical volume. File contains a volume descriptor record. The data procurer obtains the necessary information from the different files as required by the remote sensing data processing software to read the data and to convert it into an image. 50 Fast Format Fast format is a comprehensive digital data format that is suitable for Level-2 data products. The physical layout of fast format is shown in Fig In this

13 format, instead of many numbers of files as in the LSGOWG or super structured format, only two files are provided in CD-ROM or DVD. The files provided in this format are as follows: a) Header file b) Image file(s) a) Header file is the first file on each volume, a Read-Me-First file, contains header data. It is in American Standard Code for Information Interchange (ASCII) format. The first record is the Administrative Record which contains information that identifies the product. The second record is the Radiometric Record, which contains the coefficients needed to convert the scene digital values. The third record is the Geometric Record which contains the scene geographic location (e.g., latitude, longitude, etc) information. Remote Sensing Data Products and Formats b) Image files are written into CDROM, DAT or DISK in Band Sequential (BSQ) order i.e., each image file contains one band of image file. As in the LSGOWG or super structured format, this format also requires the user to instruct the remote sensing data processing software to read the data and to convert it into an image. Fig. 6.8: Fast format physical layout (source: Joseph, 2005) GeoTiff Format Presently, there are various data formats (e.g. PGM, GIF, BMP, and TIFF, etc.) used for storage of raster image data, but they have limitations in cartographic applications. GeoTIFF is based on the original TIFF (Tagged Image File Format) format, with additional geographic information. This format does not require the user to convert the contents of the CD-ROM or DVD into an image data. In this format remote sensing data is provided in the form of an image itself. The digital image data has the *.tiff extension. Users can directly start their image processing and analysis steps. IRS-1C/1D data products are supplied in GeoTIFF format in CDROM. The details of GeoTIFF format can be obtained from Hierarchical Data Format (HDF) HDF is a data file format designed by the National Center for Supercomputing Applications (NCSA) of USA to assist users in the storage and manipulation of scientific data across diverse operating systems and machines. HDF supports a variety of data types i.e. scientific data arrays, tables, and text annotations, as well as several types of raster images and their associated color palettes. There are two distinct varieties of HDF, known as HDF (version 4 51

14 Concepts of Geospatial Data Spend 5 mins and earlier) and the newer HDF5. HDF files are also self-describing. The selfdescribing capability of HDF files has important implications for processing scientific data. A program that has been written to interpret certain tag types can scan a file containing those tag types and process the corresponding data. Self-description also means that many types of data can be bundled in an HDF file. For example, it is possible to accommodate symbolic, numerical, and graphical data in one HDF file. Check Your Progress II 1) Define data format. 2) What are the three basic formats for remote sensing data? 3) What is null volume directory? 6.6 PRODUCT CODE In view of the large number of remote sensing data products, NRSC has prepared a unique product code in short form that fully describes and takes care of all the specifications of a desired product. If this code is mentioned in the order/indent form, it is easy for NRSC to supply the correct/desired data. The product code has nine characters. Table 6.2 shows details about the product types and codes. 52

15 Table 6.2: The product types and product codes Product Type (First two characters) ST Standard Product QU Quadrant Product Remote Sensing Data Products and Formats G3 G4 SR TR J1 J3 J4 MO Geocoded product (15 x15 of SOI map sheet) Geocoded product(7 ½ x7 ½ of SOI mapsheet) Stereo pair product Shift-Along Track product Geocoded product (1 deg.x1deg. without SOI reference) Geocoded product (15 x15 without SOI reference) Geocoded product (7 ½ x7 ½ without SOI reference) Full strip/full path Projection Applied (Third character) Data supported include EV Everest W4 WGS -84 Resampling used (Fourth character) 0 No sampling done C Cubic convolution N Nearest neighbour Enhancement (Fifth and sixth character) 00 Enhancement (mostly applicable for digital) 01 Histogram Look Table (Scene based enhancement) YE CL Yellow substance (RS-P4 OCM only) Chlorophyll map (IRS-P4 OCM only) SE Sediment map (IRS-P4 OCM only) Format (Eighth character) 5 False color composite paper print 6 Digital data on LGSOWG/Super Structured, Band interleaved (BIL) 7 Digital data on LGSOWG/Super Structured format, Band Sequential (BSQ) B T R Fast format GeoTIFF (grey) GeoTIFF (RGB) H HDF Size capacity (Ninth character) mm (only for photographic products) J 650 MB CD-ROM V DVD 53

16 Concepts of Geospatial Data Levels of processing (Seventh character): Depending on the accuracy of the data products, they are categorised under different levels of processing and these levels of processing vary from country to country (Table 6.3). Table 6.3: Level of Processing 0 Raw data 1 Radiometrically corrected data 2 Standard product 6 DEM (external) P G R O M Precision Georeference Precision Georeference Ortho rectified (Stereo derived) Multi-sensor (P+SX) You will learn about the source of these errors and their correction in Block 4 Processing and Classification of Remotely Sensed Images of MGY- 002 Remote Sensing and Image Interpretation The input raw data received at a ground station is converted into a certain storage format (level 0). There are several remote sensing data processing levels, which can have different names and nomenclature among remote sensing operators. The standard products are generated after applying radiometric and geometric corrections. The raw data recorded at the Earth s station is corrected to various levels of processing at the Data Processing System (DPS). The most frequently used are the following levels of preliminary data processing: 0 raw (primary) data of the imaging equipment; 1A radiometrically corrected and calibrated data; 1B radiometrically corrected and geo-located data; 2A radiometrically and geometrically corrected data, represented in a map projection; The supply of data products to users, in response to their requests, is carried out at the data processing and product generation and distribution centre. Data processing and data product generation comprises transferring the raw data from the medium on which the raw data is recorded to the computer for data correction and formatting and finally to the required medium photographic or digital and data product quality checking. The remote sensing data provided to the users should closely represent the geometric and radiometric properties of the ground scene. However, there exist a number of errors in the raw data received at the ground station. These errors could be due to the sensor itself, platform, intervening atmosphere and data transmission and reception system. Therefore, the distorted image data has to be corrected for a more faithful representation of the original scene. The data products are produced after correction for geometric and radiometric errors (correction for atmospheric effect is usually not carried). The errors can be broadly classified as systematic and random errors. Systematic errors are those which are constant or can be modelled so that they can be eliminated by suitable operation on the data (e.g., Earth rotation, panoramic distortion, etc.). Random errors are difficult to eliminate totally e.g., detector, noise, jitter of spacecraft. 54

17 The levels of processing are followed by products of a higher processing level, when additional data is used to get such output products (ground control points, DEM for ortho-correction, etc.), usually generated for further thematic processing. Remote sensing products of higher than level 2A processing levels are usually distributed in popular archive formats (e.g. GeoTIFF) because in most cases they are georeferenced images and no more specific information about satellite orbital parameters and attitude at the time of imaging is required for their further use. The only requirement is that the format (Table 6.4) must contain raster georeference parameters (for example, in form of map projection description). Lower processing level products are supposed to contain (and in most cases it is secured) auxiliary information which is used further to generate higher level products. Unfortunately, there are no general formats to archive and distribute the lower processing level products, which can be explained by the uniqueness of satellites, their imaging instruments, imaging modes, etc. Probably, in future the remote sensing operators will come to an agreement and offer unified formats to the users. Table 6.4: Format and size capacity Remote Sensing Data Products and Formats Format (Eighth character) 5 False color composite paper print 6 Digital data on LGSOWG/Super Structured, Band interleaved (BIL) 7 Digital data on LGSOWG/Super Structured format, Band Sequential (BSQ) B T R H Fast format GeoTIFF (grey) GeoTIFF (RGB) HDF Size capacity (Ninth character) mm (only for photographic products) J V 650 MB CD-ROM DVD Here is an example of a product code: STOCYEMBV Standard Product (ST), with no Projection applied (O), Cubic Convolution resampling (C), Yellow substance-irs-p4 OCM only (YE), Multi-sensor Level of Processingpost P+XS (M), Fast Format (B), size capacity DVD (V). 6.7 PLACING AN ORDER FOR A DATA PRODUCT There are two ways to procure remote sensing data in India: by ordering online to various data providing agencies e.g. NRSC Data Centre in India, and by sending indents (in specified format - available on website) through post to NRSC Data Centre on the address given here: NRSC Data Centre National Remote Sensing Centre (ISRO) Dept. of Space, Govt. of India Balanagar, Hyderabad Andhra Pradesh, India 55

18 Concepts of Geospatial Data There are some organisations/agencies which provide specified remote sensing data for free. To procure data from these agencies, one has to register oneself online. These registrations are completely free. Once one gets registered to these agencies websites, it is easy to download after giving the required specifications. Following are two such websites: and ACTIVITY 1) Following is an example of data format in which a 3 band image data of size 3 3 (i.e. 3 rows and 3 columns) are stored in the BIL format. How would the image look like after you have converted it into an image? Band 1 Band 2 Band 3 2) If the same data file is stored in BIP format in the above figure, how would the image look like after you have converted it into an image? Band 1 Band 2 Band SUMMARY 56 Remote sensing data are supplied to a variety and number of users for various applications and information extraction, in the form of a data product. The data products are made available to users of our country by the National Data Center (NDC) of National Remote Sensing Center (NRSC) of the Indian Space Research Organisation (ISRO) located at Hyderabad. Remote sensing image data, stored in data files/image files on magnetic tapes, compact disks (CDs/DVDs) or other media, consists of only digital numbers. All remote sensing data products carry a specific index number. Remote sensing data products vary depending on the level of processing, output media/scale, and area of coverage. There are certain standards when the data is supplied as softcopy in digital form. Digital products are commonly supplied in the following formats LGSOWG, Fast Format, GeoTIFF and HDF. NRSC has prepared a unique product code in a short form that fully describes and takes care of all the specifications of a desired product.

19 Image data format can be defined as the sequential arrangement of pixels, representing a digital image in a computer compatible storage medium such as a compact disk (CDs/DVDs). Basically there are three types of data formats Band Interleaved by Pixel (BIP), Band Interleaved by Line (BIL), and Band Sequential (BSQ). There are two ways to procure remote sensing data- by ordering online or by sending indents through post to NRSC Data Centre UNIT END QUESTIONS 1) What do you understand by remote sensing data products? 2) Discuss in brief the method of assigning product code to remote sensing data. 3) What are various remote sensing data formats? 4) How can you obtain desired remote sensing data? Spend 30 mins Remote Sensing Data Products and Formats 6.11 REFERENCES Joseph, G. (2005), Fundamentals of Remote Sensing. 2 nd Ed., University Press, 488p. The above websites were accessed between 15 and 25 June FURTHER/SUGGESTED READING Campbell, J. B. (2002), Introduction to remote sensing, 3rd Ed. The Guilford Press, New York. 620 p. Jensen, J. R. (2005), Digital Image Processing: A Remote Sensing Perspective, 3 rd Ed. Prentice Hall, 526 p ANSWERS Check Your Progress I 1) Data Products are: data from various sensors in a suitable and standard format, which can be readily used by user. 2) Remote sensing data can be procured by ordering from NDC, NRSC (ISRO) Hyderabad or from some other websites. 3) Types of remote sensing data product depend upon three factors namely level of processing, output media/scale and area of coverage. 4) Value added products are basically of four types viz. Geocoded products Merged products, and Ortho products Template registered products 57

20 Concepts of Geospatial Data Check Your Progress II 1) Data format can be defined as the sequential arrangement of pixels, representing a digital image in a computer compatible storage medium such as CDs, DVDs, etc. 2) Types of Data Formats: there are three types of data formats namely, BIP, BIL and BSQ. 3) Null volume directory file marks the end of logical volume. It is referred to as null because it defines a non-existent (empty) logical volume. File contains a volume descriptor record. Unit End Questions 1) Your answer should include points covered in sections 6.2, 6.3 and ) You should discuss important points discussed in Tables 6.2, 6.3 and ) You should discuss three basic types of data formats BIP, BIL and BSQ, along with certain standards ones where the data are supplied as softcopy in digital form i.e. LGSOWG, Fast Format, GeoTIFF, HDF. 4) Refer to section