(Luận văn) assessing the land cover change used satellite image and gis in y yen district nam dinh province

THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY LAI THANH QUANG ASSESSING THE LAND COVER CHANGE USED SATELLITE IMAGE AND GIS IN Y YEN DISTRICT NAM DINH PROVINCE BACHELOR THESIS an Lu n va Study mode : Full-time : Environmental science and management Faculty : International Training and Development Center ac th Major si w Batch : K43 - AEP d oa nl va an lu Thai Nguyen, September 2015 ll u nf t n oi m z z Thai Nguyen University of Agriculture and Forestry Degree program Bachelor of Environmental Science and Management Full name LAI THANH QUANG Student ID DTN1153050089 Assessing the land cover change used satellite image and Thesis title GIS in Y Yen district Nam Dinh province Supervisor MSC NGUYEN VAN HIEU Abstract: Land use/cover change mapping is one of the basic tasks for environmental monitoring and management This research was conducted to analyze the land use and land cover changes in Y Yen district, Nam Dinh province In recent years, a variety of change detection techniques have been developed The data sources used in this study were Landsat and Landsat images taken in June 2004, July 2010 and July 2015, respectively By using ArcGIS and ENVI software and remote sensing data, a supervised classification was performed based on fusion data from a composite image of the bands Using this output, available secondary data together with field Lu data in order to perform a Maximum Likelihood supervised classification Five an n va classes were classified, namely water, forest, residential, agriculture, and fallow With overall accuracy is 97.0115% and kappa = 0.9582 in 2004, overall ac th accuracy is 99.7006% and kappa = 0.9954in 2010, overall accuracy is 100% % si and kappa coefficient = in 2015 after conducted, we have: w d oa nl - Land cover map of Y Yen district in 2004, 2010 and 2015 - Land cover changes map of Y Yen district in period 2004 – 2010 and va an lu 2010 - 2015 With the results achieved, this thesis can realize the remote sensing and u nf ll GIS technology is effective method for high accuracy, cost savings in the n oi m t ii z z classification and analysis of land cover changes Y Yen, Nam Dinh, GIS, Land cover, Land cover change, Keywords ArcGIS software, ENVI software Number of pages 76 Date of submission September 30, 2015 Supervisor signature an Lu n va ac th si d oa nl w ll u nf va an lu n oi m t iii z z ACKNOWLEDGEMENT Studying and research in advanced programs of the University of Thai Nguyen First and foremost, I would like to thank my research supervisors, MSc Nguyen Van Hieu vice director in ―International Training and Development Center‖, who helped me a lot during the internship time Without the assistance and dedicated involvement in every step throughout the process, this research would have never been accomplished I also would like to show gratitude to the employees of spatial research laboratory, who helped and supported me to accomplish my research In addition, I would like to thank my family and my friends by always staying by my side, who encourage and help me in learning and researching Thai Nguyen, September 2015 Author Lu an LAI THANH QUANG n va ac th si d oa nl w ll u nf va an lu n oi m t iv z z TABLE OF CONTENTS LIST OF FIGURES LIST OF TABLE LIST OF ABBREVIATIONS PART I INTRODUCTION 1.1 Background and rationale 1.2 Research objectives 1.3 Research question 1.4 The significance PART II LITERATURE REVIEW 2.1 Theoretical basis 2.1.1 Definitions of land cover 2.1.2 Geographic information system (GIS) 11 2.1.3 Remote sensing (RS) 15 2.2 Practical basis 22 2.2.1 The research in the world 22 Lu an 2.2.2 The research in Viet Nam 25 n va PART III METHODS 28 ac th 3.1 Materials 28 si 3.1.1 The objects and scope of research 28 w 3.1.2 The content 28 d oa nl 3.2 Methods 28 va an lu 3.2.1 Collecting and selecting data 28 3.2.2 Inherited method 29 u nf ll 3.3 Field trips method 29 m n oi 3.4 Building the land cover changes map 30 t v z z 3.5 Normalized difference vegetation index (NDVI) 31 3.6 Accuracy assessment 31 PARTS IV RESULTS 33 4.1 The natural conditions and socioeconomic in research area 33 4.1.1 Natural conditions 33 4.1.2 Socioeconomic conditions 39 4.1.3 General assessment 42 4.2 The process of current status land cover mapping 44 4.2.1 Data preparation 44 4.2.2 Determining the general criteria 45 4.3 Analyze remote sensing image, determine land cover in Y Yen district 49 4.3.1 Geometric rectification 49 4.3.2 Enhanced Image quality 51 4.3.3 Interpretation and image classification 51 4.3.4 Evaluating the accuracy after classification 55 4.3.5 The process of calculate NDVI 58 4.3.6 Map editor 61 Lu an 4.4 Analysis of fluctuation 67 n va 4.4.1 Assessment of land use change/ land cover period 2004-2010 67 ac th 4.4.2 Assessment of land use change/ land cover period 2010-2015 70 si 4.5 General comments on the applicability of remote sensing and GIS mapping to w assessing land cover changes 71 d oa nl PART V DISCUSSION AND CONCLUSION 72 5.1 Discussion 72 va an lu 5.2 Conclusion 72 ll u nf REFERENCES 74 n oi m t vi z z LIST OF FIGURES Figure 2.1: Remote sensing system .16 Figure 3.1: The process of land cover mapping 30 Figure 4.1 The land use map of Y Yen district in 2010 .33 Figure 4.2 Landsat images cover the research area in 2004 (a), 2010 (b) 45 Figure 4.3: Packs image 45 Figure 4.4: Result of Stacking layer 46 Figure 4.5:Open File boundary country 47 Figure 4.6: Images Y Yen District after cutting 47 Figure 4.7: a) Image diversions; b)Original image 50 Figure 4.8: Control points 50 Figure 4.9: Image after straightening 51 Figure 4.10: Result of sampling 53 Figure 4.11: ROI Separability dialog box Report 54 Figure 4.12: Image classification 55 Lu Figure 4.13: Image noise filtering and smoothing 58 an n va Figure 4.14: add bands 59 ac th Figure 4.15: Inmage Analysis option 59 si Figure 4.16: The NDVI value 59 w Figure 4.17: NDVI map 2004 60 d oa nl Figure 4.18: NDVI map 2010 60 va an lu Figure 4.19: NDVI map 2015 61 Figure 4.20 Data frame tool 62 u nf Figure 4.21 Other map elements 62 ll m n oi Figure 4:22: Land current status maps in 2004, 2010 and 2015 63 t z z Figure 4.23: Add field 64 Figure 4.24: Image overlay .65 Figure 4.25: Caculator Geometry 65 Figure 4.26: Display classes 66 Figure 4.27: Land cover change mapof Y Yen district 2004 – 2010 66 Figure 4.28: Land cover change mapof Y Yen district 2010 – 2015 67 an Lu n va ac th si d oa nl w ll u nf va an lu n oi m t z z LIST OF TABLE Table 2.1: Land cover classification Table 2.2: Landsat satellite system 19 Table 2.3: Parameters of ETM Landsat (Landsat 5) 21 Table 2.4: Parameters of LDCM Landsat (Landsat 8) 22 Table 3.1: Statistics sample collection 29 Table 4.1: Economic structure .39 Table 4.2: Statistics between population and labor .42 Table 4.3: The information of Landsat 44 Table 4.4: Land cover classification 48 Table 4.5: Comparison Handling and interpreting digital photos visual 52 Table 4.6 : Results of the accuracy evaluation in 2004 56 Table 4.7: Results of the accuracy evaluation in 2010 56 Table 4.8: Results of the accuracy evaluation in 2015 57 Table 4.9: Assigning values 64 Lu Table 4.10: Statistical fluctuations of land cover in the period 2004 - 2010 68 an n va Table 4.11: Statistical fluctuations of land cover in the period 2010– 2015 70 ac th si d oa nl w ll u nf va an lu n oi m t z z LIST OF ABBREVIATIONS GIS: Geographic information systems NDVI: Normalized Difference Vegetation Index RS: Remote sensing FAO: Food and Agriculture Organization ETM: Enhance Thematic Mapper ROI: Region of Interest IRS: Indian Remote Sensing SPOT: System Pour observation de la Terre USGS: Unit States Geological Survey an Lu n va ac th si d oa nl w ll u nf va an lu n oi m t z z Figure 4.20 Data frame tool - Adding a data frame to the page layout The data frame displays a collection of layers drawn in a particular order for a given map extent and map projection Adding a data frame to the page layout using the Insert menu From this menu, insert additional data frames These additional data frames may be for locator or detail maps If you are using multiple data frames, you may want to consider using extent indicators to show the extent of one data frame within another data frame A good locator map will also contain an indicator, such as an outline, showing where the extent of the detail map fits within a larger extent For example, the locator map might show the location of a state within a country - Adding other map elements to the page layout an Lu Using the Insert menu to select other map elements to add to layout Using this va n menu add a title to the page The added text will be the same as the text entered for the th ac title in the Map Document Properties dialog box Along with a title, it’s can be add si ad o nl w (static) Text and Dynamic Text l ul nf va an lu m n oi Figure 4.21 Other map elements 62 t z z - Printing and exporting layout After completed this work on the layout, printing the map or create other types of output formats—PDF files, PostScript files, or Illustrator files Under the file menu, using options to open the Page and Print Setup dialog box, Print Preview,Print the page, or to Export Map an Lu n va ac th si ad o nl w va an lu l ul nf Figure 4:22: Land current status maps in 2004, 2010 and 2015 n oi m Looking at the map we can make some reviews as follows: 63 t z z - Two largest overlays in Land current status maps through 2004, 2010 and 2015 are Agricultural land and Residential land The smallest overlay is Forest land - The overlay tend to increase in the area is agricultural land mainly due to planning and land reclamation of the district - The residential lands are also many changes and mainly converted to agricultural land 4.3.6.2 Building fluctuations map Right-click each vector file 2004, 2010 and 2015 to open selected Attribute table In the properties panel, select Opption/Add field: Figure 4.23: Add field an Lu The result values are assigned as follows: va Table 4.9: Assigning values n ac th Class name Ma_2004, (Ma_2010), (Ma_2015) si l ul nf Fallow va an lu Agriculture ad Residential o nl Forest w Water (Source: Data analysis) n oi m 64 t z z To overlay, select Analysis tool/ Overlay/ Intersect Figure 4.24: Image overlay To analyze the changes we need to make conversion code and convert area on table Atribute_table 2004_2010 - Right-click on field ma_Cdoi, then we select Field Calculator In Field calculator enter the code [ma_2000] &" to " & [ma_2013] then click OK - To calculate the convert area: On DT_Cdoi column, right click and select Calculator Geometry, Geometry Calculator dialog box appears an Lu n va ac th si ad o nl w l ul nf va an lu Figure 4.25: Caculator Geometry n oi m 65 t z z Finally, our results fluctuate To clearly displays We right-click on overlay was calculated / Properties /Symbology / Categories / Unique values We use the value in field "2004_2010" and then select the appropriate color Figure 4.26: Display classes We have land cover change map: an Lu n va ac th si ad o nl w l ul nf va an lu m n oi Figure 4.27: Land cover change mapof Y Yen district 2004 – 2010 66 t z z Figure 4.28: Land cover change mapof Y Yen district 2010 – 2015 With: W: stands for water F: stands for forest an Lu R: stands for Residential n va A: stands for agriculture ac th Fw: stands for Fallow si 4.4 Analysis of fluctuation w 4.4.1 Assessment of land use change/ land cover period 2004-2010 o nl ad From the land cover map and the statistical results of 2004 and 2010, va an lu conducted layer stacking to get land cover change in the period 2004 - 2010 We l ul nf exported table to excel n oi m 67 t z z - Conversion Tool/ Excel/ Table To Excel.And Use SUMIF functions to statistical fluctuations land Results of statistical fluctuations are shown as table: Table 4.10: Statistical fluctuations of land cover in the period 2004 - 2010 a) Unit: Class Water Forest Residential Agriculture Water 1156.41 36.09 1876.04 1166.04 2.07 Forest 177.93 142.56 153.18 76.32 0.27 Residential 1304.1 115.47 2969.01 2278.44 635.4 Agriculture 1125.9 46.08 4939.92 4086.9 1.62 Fallow 499.86 106.56 1078.65 492.57 23.49 Total 4264.2 446.76 11016.09 8100.27 662.78 b) Fallow Unit: % an Lu Class Forest 27.12 8.07 17.03 14.4 0.3 31.9 1.4 0.94 0.4 25.8 26.9 28.1 95 50.5 0.2 6.06 4.1 100 100 100 Water n va Water Residential Agriculture Fallow ac Residential 30.6 Agriculture 26.4 o nl th Forest 44.8 Fallow 11.68 23.93 9.87 Total 100 100 4.2 si w 10.3 ad l ul nf va an lu (Source: Data analysis) n oi m 68 t z z Based on the results of the table above, we can see the land cover changing unevenly All of land covers transform significantly between 2004 and 2010 The most stable land cover type is agricultural land (50.5% of areas) are retained While all remaining cover change a lot (over 60% of areas changing) - The water surface area has 1,156.41(ha) and kept only 27.12% from 2004 to 2010 The greatest part of area is converted into residential land (30.06%) and agriculture land (26.4%) - For the residential land cover has 2,969.01(ha) and kept constant only 26.9% areas Most of the area is convert to agricultural land (44.8%) - Fallow land cover was decreased rapidly because it is transfer established the roads in Residential land cover The main cause transform land cover is: Adjusting the land use planning of districts during period 2006-2010 was established in the context of market economies exciting development, economic development situation is unstable Especially the period of 2006-2010 business sectors an Lu strong development of district, domestic markets including many investors domestic va n and foreign investment in the district leads to many indicators, the demand for land is th ac not suitable for the socio-economic development Assembly On the other hand, si o nl w innovation policy mechanisms, the result of the work of land consolidation have created conditions for many households invest in building farms, breeding fish to ad l ul nf va an lu make high economic efficiency and then the land cover of the district will transform n oi m 69 t z z 4.4.2 Assessment of land use change/ land cover period 2010-2015 From the land cover map and the statistical results of 2010 and 2015, conducted layer stacking to get land cover change in the period 2010 - 2015 Results of statistical fluctuations are shown as table: Table 4.11: Statistical fluctuations of land cover in the period 2010– 2015 a) Unit: Class Water Forest Resident Agriculture Fallow Water 900.45 118.26 391.05 574.56 137.25 Forest 197.82 87.76 394.47 209.07 112.5 Resident 684.99 165.42 5124.15 1328.58 445.68 Agriculture 2240.28 70.47 704.7 7183.8 797.67 Fallow 347.94 109.53 687.51 905.13 643.59 total 4371.48 551.44 7301.88 10201.14 2136.69 b) Unit: % n va Water Forest Resident Agriculture Fallow 20.6 21.4 5.3 5.6 6.43 15.9 5.4 2.04 5.3 29.9 70.1 13 20.9 70.4 37.3 8.96 30.07 100 100 100 (Source: Data analysis) Forest ac Resident 15.7 Agriculture 51.2 o nl th Water l ul nf an Lu Class 9.7 Fallow 20 9.5 Total 100 100 4.5 si w 12.8 ad va an lu n oi m 70 t z z From the tables above, we can see that the most stable cover types are residential land and agriculture land (account for more than 70% of total area) Other layers change remarkably ( more than 60% areas changed) The most changing layer is forest layer with 15,9% stably area The remaining parts are converted to residential land (29,9%), water surface (21,4%), agriculture land (12,8%) and vacant land (20%) The main reason of changes is because of the conversion of land use purposes The fallow land layer is changed a lot due to the convention to agriculture land and residential land The changing areas account for 69.03% of total areas The land cover change the period 2010 - 2015 has many causes but the main impact in changing that is the land use planning of districts, economic growth, many projects construction and transportation being complete and rural urbanization 4.5 General comments on the applicability of remote sensing and GIS mapping to assessing land cover changes The application of satellite imagery and GIS is to establish vegetation mapping and monitoring changes in vegetation have been applied in many parts of the world as an Lu well as in Vietnam and we also achieved success in many areas , areas with types of terrain and various levels of detail After each study, the scientists have drawn va n experience as well as the characteristics of the method were conducted Through th ac references to previous studies and the application and development research method in si Y Yen District showed some important advantages of this approach are: o nl w + Short time to + The amount of information abundant ad + Honestly reflect the shape and status of vegetation va an lu + Apply well for macro applications + Develop a multi-time map l ul nf n oi m 71 t z z PART V DISCUSSION AND CONCLUSION 5.1 Discussion From analytical results map shows the distribution of the land cover changes over each period The largest of land covers areas is of agricultural land and residential, water and then fallow land and forest land have areas smallest From 2004 to 2015 the land cover has transform strongly Because of many reasons but the mains cause are the planning of the district land use, economic growth rates so high, many transport projects done Remote sensing data interpretation directly analyzes land cover, we can find useful for monitoring of human activities in the urban environment With this information enhances our understanding of urban environment and we can be further used to improve environment quality Because of restrictions on funding, my thesis have been using free satellite imagery with medium-resolution, not high quality Therefore, the results obtained have not achieved the highest accuracy In order to achieve higher accuracy, the next research should be use different types of Image with higher resolution Moreover, the an Lu next thesis should be combined and other remote sensing methods performing va n interpretation to achieve better results ac th 5.2 Conclusion si o nl w Application Remote Sensing and GIS in digital image processing to establish and monitor and evaluate plant cover: ad va an lu + Satellite images may allow retrieval of information in different levels and thereby may establish land cover maps for each specific application l ul nf n oi m 72 t z z + Study and application of remote sensing technology to combination GIS mapping perform the yen District government in 2004, 2010, 2015, and map land cover changes from 2004 to 2010 and from 2010 to 2015 to help the management of natural resources environmental, urban planning can more accurately assess the current state of in Y Yen + Using the classification method independently to conduct mapping changes in the conditions of Y Yen is appropriate an Lu n va ac th si ad o nl w l ul nf va an lu n oi m 73 t z z REFERENCES Application GIS and remote sensing 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