Tasseled Cap transformation Technique in ArcGIS

• 1. Using Tasseled Cap Transformation Technique To Study The Urban Environment, And Its Effect On Pollution, In Lahore, Pakistan Submitted To: Dr.Arifa Lodhi Submitted By: Atiqa Ijaz Khan Roll No. : Geom-02 Institute of Geology, University of the Punjab

2. GREEN FIEND GREENFIENDSlide No. 2,Tuesday, May 06, 2014 Table of Contents Urbanization 03 Pollution and Climate Change 05 Study Area and its Specs 06 Objective and Scope of the Project 08 Software Used 09 Background Concepts of TCT 11 Tasseled Cap Transformation Technique Procedure 12 Datasets (Landsat ETM+) 23 Results 26 3. GREEN FIEND GREENFIENDSlide No. 3,Tuesday, May 06, 2014 INTRODUCTION 4. 4,Tuesday, May 06, 2014 Urbanization 1. Urbanization is a process of relative growth in a countrys urban population accompanied by an even faster increase in the economic, political, and cultural importance of cities relative to rural areas. 2. There is a worldwide trend toward urbanization. 3. In most countries it is a natural consequence. 4. At the same time, urbanization is progressing much faster in developing countries than in developed countries. 5. 5,Tuesday, May 06, 2014 Pollution and Climate Change1. Many forms of atmospheric pollution affect human health and the environment at levels from local to global. 2. These contaminants are emitted from diverse sources, and some of them react together to form new compounds in the air. 3. Air pollutants are major contributors to climate change. 4. Global climate change has the potential to magnify air pollution problems by raising Earth's temperature (contributing to tropospheric ozone formation) and increasing the frequency of stagnation events. 6. 6,Tuesday, May 06, 2014 Study Area and its Specs 1. Lahore is the 2nd largest city of the Pakistan, and the capital city of the Province Punjab. It is located between 31 15 -31 45 N and 74 01 and 74 39 E it covers an area of 1014 km2 . 2. The climate here is hot, semi-arid, with long hot summers, and short dry winters. 3. Regular monitoring of ambient air quality is still not systematic in Pakistan. 4. All the available information is based on random and short term sampling conducted to assess the concentrations of various pollutants. Many such studies have reported the ambient concentration of air pollutants in various urban and rural centers of Pakistan, including Karachi, Hyderabad, Jamshoro, Lakhra, Multan, Dera Ghazi Khan, Faisalabad, Lahore, Gujranwala, Pind Dadan Khan, Sargodha, Fateh Jang, Khewra, Sialkot, Rawalpindi and Peshawar. 5. The major sources of air pollution that are needed to be addressed are: 1. Emission from vehicles 2. Emission from industry 7. 7,Tuesday, May 06, 2014 8. 8,Tuesday, May 06, 2014 Objective and Scope of the ProjectThe main objectives of this study are: 1. Extent of urbanization in Lahore city, since 2000; 2. Land cover and land use change detection for past decade (2000-2010); 3. Estimation of degradation of Green-cover; 4. Understanding the relationship between urbanization and climate changes, especially temperature. 5. Using the technique of Tasseled Cap Transformation for the urban change in Lahore (Hopefully for the 1st time). This will helps in the assessment of potential accuracy of Tasseled Cap technique especially in urban area. And put one step towards the understanding of PCA (principal component technique) and CVA (Change Vector Analysis). 9. 9,Tuesday, May 06, 2014 Software Used For this project, the software used are: 1. ArcGIS 10.1 2. ERDAS 13 3. Microsoft Word 2013 4. Microsoft Excel 2013 10. GREEN FIEND GREENFIENDSlide No. 10,Tuesday, May 06, 2014 LITERARTURE REVIEW 11. 11,Tuesday, May 06, 2014 Background Concept 1. The concept of tasseled cap transformation was introduced in 1976 by R.J. Kauth and G.S. Thomas. 2. Originally constructed for understanding important phenomena of crop development in spectral space, the transformation has potential applications in revealing key forest attributes such as species, age and structure (e.g. Cohen et al. 1995). 3. Essentially, two tasseled cap transformations have been developed based on Landsat Thematic Mapper (TM), based on: 1. Digital number (Crist and Cicone 1984); 2. Reflectance factor (Crist 1985). 4. Tasseled cap coefficients are calculated for the TOA reflectance data from the Landsat 7 ETM+ sensor by Huang et al (2002). 5. These coefficients are directly applicable for Landsat 7 ETM+ TOA reflectance data, and can be used with Landsat 5 TM data using a further transformation described in Vogelmann et al. (2001). 12. 12,Tuesday, May 06, 2014 Cont In practice, the procedure is based on a linear transformation of data from the original image into three new axes which become features of the transformation and may be described as follows: 1. Brightness (Urbanization) 2. Greenness (Agriculture and Forestation) 3. Wetness (Moisture) 4. Fog 5. Others Landsat Bands 13. 13,Tuesday, May 06, 2014 Cont 1. Brightness: According to Jensen (2000) the brightness band in Tasseled Cap Transformation is used to identify urbanization areas which are particularly evident in this band. 2. Greenness: The greenness band is an important source which provides information about vegetation. (et al. Jensen, 2000) 3. Wetness: Moisture status of the wetland information presents in the wetness band. TCT could be helpful for use anywhere to disaggregate the quantity of soil brightness, vegetation, and moisture content in independent pixels in satellite imagery (Jensen 2000). 4. Thermal Band: According to Jensen (2000), thermal band calculates the quantity of infrared energy 14. 14,Tuesday, May 06, 2014 LANDSAT MSS: LANDSAT 5 TM 15. GREEN FIEND GREENFIENDSlide No. 15,Tuesday, May 06, 2014 METHODOLOGY 16. 16,Tuesday, May 06, 2014 Procedure Step by Step 1. The 1st step is remove the 0-values from the images, or to set them to NO-data values. This can be done using ERDAS 13. For this, set Clear to NO-data values in the metadata of every band of each image. 2. All the following steps are performed in ArcGIS 10.1 Raster Calculator. 3. Convert Landsat 5 DN Values into Landsat 7 DN Values: 17. 17,Tuesday, May 06, 2014 4. Before converting to reflectance data, one must convert the DN data to radiance. This is done using the following expression: Where, L is the calculated radiance [in Watts / (sq. meter * m * ster)], DN7 is the Landsat 7 ETM+ DN data (or the equivalent calculated in step 2), and the gain and bias are band-specific numbers. The latest gain and bias numbers for the Landsat 7 ETM+ sensor are given in Chander et al. (2009) and are shown in the following table: 18. 18,Tuesday, May 06, 2014 5. While radiance is the quantity actually measured by the Landsat sensors, a conversion to reflectance facilitates better comparison among different scenes. 6. It does this by removing differences caused by the position of the sun and the differing amounts of energy output by the sun in each band. Where, R is the reflectance (unit less ratio), L is the radiance, d is the earth- sun distance (in astronomical units), Esun, is the band-specific radiance emitted by the sun, and SE is the solar elevation angle. ArcGIS Raster Calculator takes angular measurements in radians, so must convert them, as: 19. 19,Tuesday, May 06, 2014 7. The solar elevation angle and the day of year are listed in the header file for each scene. 8. This file is included with the data and ends with _MTL.txt. 9. Search the file for the solar elevation angle labeled SUN_ELEVATION and the day of the year labeled DATE_HOUR_CONTACT_PERIOD. 10. The solar elevation angle is given in degrees and the date is in the format YYDDDHH Where the 3 D digits denote the day of the year. For example, 0624117 means the 241st day of 2006 at 17 UTC. 20. 20,Tuesday, May 06, 2014 Earth-sun Distance in Astronomical Units as Function of Days 21. 21,Tuesday, May 06, 2014 11. During the conversion from DN data to reflectance, it is possible to create small negative reflectance. 12. Now finally calculate the TCTs using following formula: 22. 22,Tuesday, May 06, 2014 13. The magnitude of vectors was calculated from the Euclidean Distance between the difference in positions of the same pixel from different data-takes within the space generated by the axes Greenness and Brightness as follows: (Optional Step) 14. Clip the final images of both years to the boundary limit of Lahore. 23. GREEN FIEND GREENFIENDSlide No. 23,Tuesday, May 06, 2014 DATASETS (TM & ETM+) 24. 24,Tuesday, May 06, 2014 1. The datasets used for this transformation are: ( including All Bands, 1-5, & 7) Serial No. Satellite and Sensor Names Pathro w Date of Acquisition (DD-MM- YYYY) Total Days Earth-sun Distance (astronomical unit) Solar Elevation (Degrees) 01. Landsat 5 (TM) 1493 8 19-03- 2000 79 0.99584 49.692020 28 02. Landsat 7 (ETM+) 1493 8 02-03- 2010 61 0.99108 34.945302 925 25. GREEN FIEND GREENFIENDSlide No. 25,Tuesday, May 06, 2014 RESULTS & CONCLUSIONS 26. 26,Tuesday, May 06, 2014 Results 27. 27,Tuesday, May 06, 2014 CVA Result 28. 28,Tuesday, May 06, 2014 Urbanization trend 2000 & 2010 29. 29,Tuesday, May 06, 2014 Agricultural Trend 2000 & 2010 30. 30,Tuesday, May 06, 2014 Moisture Trend 2000 & 2010 31. 31,Tuesday, May 06, 2014 Greenness and Wetness Comparison 32. 32,Tuesday, May 06, 2014 Google Earth Archieve Lahore 2000 Lahore 2010 33. 33,Tuesday, May 06, 2014 Analysis Analysis of Lahore TCT Images: Analysis and Results available from Literature: Serial No. Urbanization Greenness Wetness Yr. 2000 Relatively Less Relatively High Moderate Yr. 2010 Increment Decrement Moderate Serial No. Brightness Greenness Results 01. High High Biomass Loss or Moisture Reduction 02. High Low Urbanization and De-forestation 03. Low High Re-forestation 04. Low Low Burning Loss or high Moisture content 34. 34,Tuesday, May 06, 2014 Temperature variation of Lahore in 2000 & 2010 jan feb march april may jun jul aug sep oct nov dec Temp(2000) 8 16 22 32 34 30 28 32 32 28 22 8 Mon (2010) 0 0 0 0 0 0 0 0 0 0 0 0 Temp (2010) 8 16 24 24 32 34 32 32 32 30 24 18 0 5 10 15 20 25 30 35 40 TEMPREATURE MONTHS OF YEARS Temperature Variation in 2000 & 2010 Temp(2000) Mon (2010) Temp (2010) 35. 35,Tuesday, May 06, 2014 Conclusions 1. It can be concluded from the results of this technique, that overall, the Greenness content of Lahore shows decline since 2000. It also shows that, with the passage of time, the agricultural growth decreases. That has a major effect on the economy. 2. On the other hand, the increase in Urbanization plays a part for the support of the economy. But, it leads to the pollution content. That has a serious effect on the human health and climate of the Lahore over the past decade. As by increased in the content of air pollution, industrial waste, and dust. This then directly effects the temperature. Which also shows increment from 2000 to 2010, and so on. 3. But, wetness graph shows a moderate or less variation since 2000, on the basis of satellite data. 36. GREEN FIEND GREENFIENDSlide No. 36,Tuesday, May 06, 2014 PROBLEMS FACED & RECOMMENDATIONS 37. 37,Tuesday, May 06, 2014 Problems Problems Faced: 1. Just a few problems faced, and they are as follows: 2. Acquisition of Landsat data along with Sensor information 3. Validity of Tasseled Cap Transformation methods. 4. Computationally lengthy procedure. 5. Much lengthier to perform on ArcGIS. 38. 38,Tuesday, May 06, 2014 Recommendations Recommendations: 1. Few of the recommendations regarding this technique are: 2. Its better to perform on ERDAS or ENVI, than ArcGIS. 3. The Landsat should have proper sensor information regarding scenes. 4. For more accurate results, TCT technique should be used with CVA (Change Vector Analysis) and PCA (Principal Component Analysis), or at-least with NDVI (or others). 39. GREEN FIEND GREENFIENDSlide No. 40,Tuesday, May 06, 2014 1. A Change Vector Analysis Technique To Monitor Land Use/Land Cover In Sw Brazilian Amazon: Acre State, by, Rodrigo Borrego Lorena, Joo Roberto Dos Santos, Yosio Edemir Shimabukuro, Irving Foster Brown, and, Hermann Johann Heinrich Kux, 2. A Comparison Of Forest Change Detection Methods And Implications For Forest Management, By Ronnie D. Lea, Dr. C. Mark Cowell, Thesis Supervisor December 2005 3. Calculating Vegetation Indices From Landsat 5 Tm And Landsat 7 Etm+ Data, By Colorado State University 4. Shams Zi. HealthAnd Environment:Lead Pollution In Karachi Is A Serious Health Hazard. Karachi, Pakistan, University of Karachi Environs Institute of Environmental Studies, 1998. 5. Use of the Tasseled Cap Transformation for the Interpretation of Satellite Images Iosif Vorovencii, Conf. Dr. Ing. Ec. Universitatea Transilvania Din Braov, [email protected] 40. GREEN FIEND GREENFIEND