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 Study mode : Full-time Major : Environmental science and management Faculty : International Training and Development Center Batch : K43 - AEP Thai Nguyen, September 2015 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 5 and Landsat 8 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 data in order to perform a Maximum Likelihood supervised classification. Five classes were classified, namely water, forest, residential, agriculture, and fallow.
With overall accuracy is 97.9582 in 2004, overall accuracy is 99.9954in 2010, overall accuracy is 100% % and kappa coefficient = 1 in 2015 after conducted, we have: - 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 2010 - 2015. With the results achieved, this thesis can realize the remote sensing and GIS technology is effective method for high accuracy, cost savings in the ii 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 iii 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 LAI THANH QUANG iv TABLE OF CONTENTS LIST OF FIGURES. 1 LIST OF TABLE. 3 LIST OF ABBREVIATIONS.
Background and rationale. Definitions of land cover. Geographic information system (GIS). The research in the world.
The research in Viet Nam. The objects and scope of research. Collecting and selecting data. Field trips method.
Building the land cover changes map. Normalized difference vegetation index (NDVI). The natural conditions and socioeconomic in research area. The process of current status land cover mapping .2 Determining the general criteria.
Analyze remote sensing image, determine land cover in Y Yen district. Enhanced Image quality. Interpretation and image classification. Evaluating the accuracy after classification .5 The process of calculate NDVI.
Analysis of fluctuation. Assessment of land use change/ land cover period 2004-2010. Assessment of land use change/ land cover period 2010-2015. General comments on the applicability of remote sensing and GIS mapping to assessing land cover changes.
DISCUSSION AND CONCLUSION. 74 vi LIST OF FIGURES Figure 2.1: Remote sensing system .1: The process of land cover mapping. The land use map of Y Yen district in 2010. Landsat images cover the research area in 2004 (a), 2010 (b) .4: Result of Stacking layer .5:Open File boundary country .6: Images Y Yen District after cutting .7: a) Image diversions; b)Original image .9: Image after straightening .10: Result of sampling .11: ROI Separability dialog box Report .13: Image noise filtering and smoothing .15: Inmage Analysis option .16: The NDVI value.
Data frame tool. Other map elements .62 Figure 4:22: Land current status maps in 2004, 2010 and 2015 .27: Land cover change mapof Y Yen district 2004 – 2010 .28: Land cover change mapof Y Yen district 2010 – 2015 .67 2 LIST OF TABLE Table 2.1: Land cover classification .2: Landsat satellite system .3: Parameters of ETM Landsat (Landsat 5) .4: Parameters of LDCM Landsat (Landsat 8) .1: Statistics sample collection .2: Statistics between population and labor .3: The information of Landsat .4: Land cover classification.5: Comparison Handling and interpreting digital photos visual .6 : Results of the accuracy evaluation in 2004 .7: Results of the accuracy evaluation in 2010 .8: Results of the accuracy evaluation in 2015 .10: Statistical fluctuations of land cover in the period 2004 - 2010 .11: Statistical fluctuations of land cover in the period 2010– 2015 .70 3 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 4 PART I. Background and rationale Land is a valuable asset of a country, especially productive assets and is most important component of life which had been formed and undergone long history. Our country from a backward agricultural country, currently on the rise ahead of industrialization - Modernization of the country, leading to the change of land use purposes also vary according to the land development process country.
Therefore the use of the land has been great interest. Y Yen District is no exception to these issues, The projects transport have been constructed and are brought into use as national highways 10, Highway 38B and north- south rail crossing. At the time of 2008, the construction of expressways Cau Gie – Ninh Binh passed through the town to the west of the district. The district has provincial roads as 484 (ex 64 Street); Provincial Road 485 (old Road 57); Provincial Road 486 (old Road 12).
The district has one town and 31 communes with the development of traffic and economic had been transformed land use and land surface cover Y Yen district over the years 2004 to 2015. In the world GIS has been formed since early 70s and is developing significantly on the foundation of advanced computer technology, computer graphic spatial data analysis and data management. Since the 80s onwards, GIS and remote sensing technology with growth Leap Forward in quality have become an effective tool in the management and decision support system put technology to automatically establish the map and data processing. Remote sensing technology is increasingly used in many fields, sectors of 5 meteorology - hydrology, geology, environment to agriculture - forestry - fishery,.
which has monitoring changes in the type of class land covered with high precision, which can help manage more resources to monitoring land use changes. This is seen as one solution to issues posed. On the other hand, this method has not been tested in application areas Y Yen district, Nam Dinh province and I decided to implement the project: “Assessing the land cover change used satellite image and GIS in Y Yen district Nam Dinh province”. Research objectives - Research to understand overview of the land cover map, satellite images and geographic information systems (GIS).
- Building the land cover map in Y Yen District, Nam Dinh province. Assess the current state of the land cover in Y Yen District, Nam Dinh Province. The requirement: - Collecting the data on economic conditions - socio- of Y Yen district. - Collecting Landsat 5 and Landsat 8 images serving for the analysis and false imagery of land cover status.
- Collecting the land use map of Y Yen District over the years 2004 -2015 - Fluency ENVI and ArcGIS software to overlay mapping. - Construction maps of land use Y Yen District, Nam Dinh Province based on geographic information applications of GIS and remote sensing (using satellite imagery 2004, 2010 and 2015). Research question - How to make the land cover and land cover change map exactly? - How many transform areas land cover in Y Yen district? 1. The significance The significance of learning and research: - Improving the proficient skills using GIS software and remote sensing applications.
- Extensive knowledge and understanding of GIS, remote sensing, interpretation of the reality on the ground overlay geographical Y Yen District. - Contributing to introduce GIS and remote sensing as well as promoting the study of the technology in students. Practical significance: - The results of the study to provide important updated documentation to contribute to building, improving policies and land management practices in Y Yen District, Nam Dinh province. Definitions of land cover 2.
Land cover a) Definitions Land cover is the physical material at the surface of the earth. Land covers include grass, asphalt, trees, bare ground, water, etc. Earth cover is the expression used by ecologist Frederick Edward Clements that has its closest modern equivalent being vegetation. The expression continues to be used by the Bureau of Land Management.
b) Land cover classification: Digital image classification is the process of assigning pixels to class. Usually each pixel is treated as an individual unit composed of values in several spectral bands. Unsupervised classification method is used to identify natural groups, or structure, within multispectral data. Only afterwards information labels are assigned to the resulting groups.
The disadvantage and limitation of these methods primarily arise from reliance upon ―natural‖ grouping and difficulties in matching these groups to the informational categories that are of interest to the interpreter. In addition, the interpreter limit controls over the menu of classes and their specific identities. By contrast, supervised classification method is the process of using samples of known identity (training area or training field) and extends it to the entire image. Each primitive image is characterized by n observations (the values in n data channels).
The samples training are vectors in an n-dimensional space (the feature space). A supervised classifier uses the distribution of the samples training for each 8 class to estimate density functions in the feature space and to divide the space into class regions.1: Land cover classification Level 1 Level 2 1.Urban 11 Residential 12 Downtown and services 13 Industrial plants. 14 Traffic 15 Public buildings 16 Welfare buildings 17 Sports Recreation Area 18 Mixture Zone 19 Open land and other land 2.Rice - Crops 21 Crops and grassland 22 Fruit trees 23 Barn 24 Other Agriculture 3.Fallow lands 31 Pastoral land 32 Shrub land 33 Mixed land 4.Forest 41 Green forest 42 Deciduous forest 43 Mixed forest 9 44 Bare forest 45 Forest has burnt out 5.Water 51 Streams and canals 52 Lakes 53 Water collection tank 54 Bays and estuaries 55 Sea water 6.Wetlands 61 Wetlands have plant created forest 62 Wetlands have plant can’t created forest 63 Wetlands haven’t plant 7. 71 Lake has dry 72 Beach (Source: Thach, 2012) 2.
Normalized Difference Vegetation Index The Normalized Difference Vegetation Index (NDVI) is an index of plant ―Greenness‖ or photosynthetic activity, and is one of the most commonly used vegetation indices. Vegetation indices are based on the observation that different surfaces reflect different types of light differently. Photo synthetically active vegetation, in particular, absorbs most of the red light that hits it while reflecting much of the near infrared light. Vegetation that is dead or stressed reflects more red lights and less near infrared light.
Likewise, non-vegetated surfaces have a much more even reflectance across the light spectrum.