THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY HA HOANG NGAN IMPACT OF LAND COVER CHANGE ON METEOROLOGICAL PARAMETER IN THAI NGUYEN PROVINCE BACHELOR THESIS Study mode : Full-time Major : Environmental science and management Faculty : Advanced education program office Batch : K46-N01 Thai Nguyen, September 2018 h DOCUMENTATION PAGE WITH ABSTRACT Thai Nguyen University of Agriculture and Forestry Degree program Bachelor of Environmental Science and Management Full name HA HOANG NGAN Student ID DTN1454290022 Impact of land cover change on Meteorological parameter Thesis title in Thai Nguyen Prof. Tang-Huang Lin (National Central University, Taiwan) Supervisor Dr. Duong Van Thao (Thai Nguyen University of Agriculture and Forestry) Abstract: Land use and land cover (LULC) in the Thai Nguyen province has changed significantly since 2007 because of the population growth and socioeconomic development. The purpose of this research is to valuate the impact on meteorology from the changes of land use and land cover types through satellite Remote Sensing (RS), and Geographic Information System (GIS).
The LULC maps in 2007 and 2017 tools are respectively generated from satellite image, using ArcGIS and ENVI software with the Maximum Likelihood Algorithm of Supervised Classification. The accuracy of the classified maps was assessed using Confusion Metrics. Four classes were classified, namely water, forest, residential and agricultural. With overall accuracy is 96.95 in 2007, overall accuracy is 91.
The LULC from Landsat images map showed about 35361.04%) area has been changed from agriculture to residential. The most stable cover types are forest land and agricultural land (26.75% of total area respectively). i h Furthermore, associated with MATLAB software in processing meteorological parameters from the re - analysis dataset. The impacts of LULC transitions on regional meteorology are examined and quantified, including temperature, water vapor and rainfall in Thai Nguyen province.
From 2007 to 2017, rainfall was the most significantly affected by LULC change. Thai Nguyen province, Land use and land cover change, Keywords ArcGIS, ENVI, Re-analysis dataset, regional meteorology, Number of pages 46 Date of submission September 20, 2018 Supervisor signature ii h ACKNOWLEDGEMENT First and foremost, I wish to express my endless thanks and gratefulness to my supervisor Prof. Tang-Huang Lin. His kind support and continuous advices went through the process of completion of my thesis at Center for Space and Remote Sensing Research (CSRSR) of National Central University (NCU).
I also wish to express my deep gratitude to Dr. Duong Van Thao who gave me an opportunity and guidance and support me to complete the thesis. I would also like to thank Ms. Chang Yi-Ling for her constant support, suggestions related to my study.
Last but not least, I would like to give my special thanks to my parents for their endless love, care and having the most assistance and motivation throughout my whole life. Thai Nguyen, September 2018 HA HOANG NGAN iii h TABLE OF CONTENTS LIST OF FIGURES .vi LIST OF TABLES.vii LIST OF ABBREVIATIONS. Methods build-up land cover change map in period 2007-2017. Methods build up LULC changes impact on meteorological parameter.
The natural conditions and socioeconomic in research area. Evaluating the accuracy after classification of Thai Nguyen in 2007 and 2017. Land Cover Maps. Analysis of fluctuation.
Land use Land cover changes impact on meteorological parameter. DISCUSSION AND CONCLUSION. 45 iv h LIST OF FIGURES Figure 2. Remote sensing system.
The process of land cover mapping. Landsat images cover the research area in 2007 (a), 2017 (b). Images Thai Nguyen province after cutting. Image noise filtering and smoothing.
The process of LULC change on meteorological changes. The Geographical location map of Thai Nguyen province. Land current status maps in 2007 and 2017. Land cover change map of Thai Nguyen 2007 - 2017.
38 v h LIST OF TABLES Table 2. Land cover classification. Parameters of ETM Landsat (Landsat 5). Parameters of LDCM Landsat (Landsat 8).
The information of Landsat. Results of the accuracy evaluation in 2007. Results of the accuracy evaluation in 2017. Statistical fluctuations of land cover change in the period 2007-2017.
Changes of land cover in six grids. The percentage of changes on meteorological parameter. 42 vi h LIST OF ABBREVIATIONS DBMS: Database Management System ECMWF: European Centre for Medium-Range Weather Forecasts ESRI: Environmental Systems Research Institute ETM: Enhance Thematic Mapper GIS: Geographic information systems GSMAP: Global Satellite Mapping of Precipitation LCC: Land Cover Change LDCM: Landsat Data Continuity Mission LULC: Land Use Land Cover RS: Remote sensing USGS: Unit States Geological Survey vii h PART I. Research rationale Land use and land cover (LULC) not only reflects human activity, but it also impacts climate.
Nowadays, the population has increased dramatically released to population density rise and industrial zone, the private industry park and raise strength economic society and other issues have had a strong impact on land, especially for developing rapidly with high industrialization and urbanization rate such as Thai Nguyen. By the end of 2016, the population of Thai Nguyen province is about 1,227,400 people, the natural population growth rate is about 0. The expansion of urban construction land in Thai Nguyen leads to regional meteorological changes. In addition, LULC changes involve not only urban expansion, but also transformations from natural LULC in recent decades, which also impact the climate in the study area.
Study building the LCC map by satellite image and GIS technology helps to shorten the time compared to other technology mapping ago and it is factor important contributions in the management and assessing the current state of the environment. Remote sensing technology is increasingly used in many fields, sectors of meteorology - hydrology, geology, environment to agriculture - forestry - fishery,. which has monitored changes in the type of class land covered with high precision, which can help manage more resources to monitoring land use changes. Therefore, it’s an efficient way to monitor the changes of land cover and its impact on climate change.
Thus, having this project conducted: “Impact of land cover change on Meteorological parameter in Thai Nguyen province”. Research objectives Using remote sensing and reanalysis dataset to identify the impact of LULC changes in regional weather including: a. The situation of Land cover/Land use changes from 2007 to 2017 in Thai Nguyen province; b. The quantitative analysis of LULC changes in regional temperature, water vapor and rainfall rate.
The requirement - To acquire adequate data of a natural condition, socioeconomic and spatial data. - Collecting Landsat 5 and Landsat 8 images serving for the analysis and false imagery of land cover status. - Collecting reanalysis data set: temperature, water vapor and rainfall data - To accuracy assessment of land cover map in 2007-2017. - To evaluate the impact of distribution land cover change on regional weather.
The significance The significance of learning and research: to understand about two software ENVI and Arcgis and to find ways to evaluate the changes in land cover changes and analyze the impact of land cover change on meteorological parameter. This study is intended to use remotely sensed data to map and detect changes in land cover of the land cover type in the last 10 years (2007 - 2017). Definitions Land cover is defined as the physical and biological cover over the surface of land, including water, vegetation, bare soil, and/or artificial structures. When considering land cover in a very pure and strict sense it should be confined to describe the vegetation and the man-made features.
Consequently, areas where the surface consists of bare rock or bare soil describe land itself rather than land cover. Also water surfaces can be disputed as being a real land cover. However, in practice the scientific community is used to describe those aspects under the term land cover (Ellis et al. 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. The 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, the 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 3 h n data channels). The samples were made of the vectors in a n-dimensional space (the feature space).
A supervised classifier uses the distribution of the samples training for each class to estimate density functions in the feature space and to divide the space into class regions (Thach, 2012). 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 h 4. Forest 41 Green forest 42 Deciduous forest 43 Mixed forest 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 planted 7. 71 Lake has dried 72 Beach (Source: Thach, 2012) 2. The land covers change Land-cover change (LCC) therefore is the human modification of the earth's terrestrial surface. Humans have been modifying land to obtain food and other essentials for thousands of years; current rates, extents and intensities of LCC are far greater than ever in history, driving unprecedented changes in ecosystems and environmental processes at local, regional and global scales.
These changes encompass the greatest environmental concerns of human populations today, including climate change, biodiversity loss and the pollution of water, soils and air (Ellis, 2013). Geographic information system (GIS) a. Definition: A geographic information system (GIS) is a computer system designed to capture, store, manipulate, analyze, manage, and present all types of spatial or geographical data. The acronym GIS is sometimes used in geographical information science or geospatial information studies to refer to the academic discipline or career of working with geographic information systems and is a large domain within the broader academic discipline of Geo-informatics.
What goes beyond a GIS is a spatial data infrastructure, a concept that has no such restrictive boundaries (GIS,2018). Basic Elements of GIS Hardware: Hardware is the computer system on which a GIS operates. Today, GIS software runs on a wide range of hardware types, from centralized computer servers to desktop computers used in stand-alone or networked configurations. Software: GIS software provides the functions and tools needed to store, analyze, and display geographic information.
A review of the key GIS software subsystems is provided above. Data: Perhaps the most important component of a GIS is the data. Geographic data and related tabular data can be collected in-house, compiled to custom specifications and requirements, or occasionally purchased from a commercial data provider. A GIS can integrate spatial data with other existing data resources, often stored in a corporate DBMS.
The integration of spatial data (often proprietary to the GIS software), and tabular data stored in a DBMS is a key functionality afforded by GIS. 6 h People: GIS technology is of limited value without the people who manage the system and develop plans for applying it to real world problems.