| 研究生: |
吳孝典 Martin, Yves-Bernard St |
|---|---|
| 論文名稱: |
以遙測影像與水文模式分析海地Azuei湖面積擴張之可能因素 The Evidence from Optical Satellite Imagery of the Expansion Surface Area of Lake AZUEI in Haiti. |
| 指導教授: |
張智華
Chang, Chih-Hua |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 環境工程學系 Department of Environmental Engineering |
| 論文出版年: | 2017 |
| 畢業學年度: | 105 |
| 語文別: | 英文 |
| 論文頁數: | 67 |
| 外文關鍵詞: | Lake Azuei, Hurricane, Remote Sensing, Satellite Imagery, ArcGIS, Landsat, Sentinel 2A, MODIS, Land Cover |
| 相關次數: | 點閱:174 下載:3 |
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Over the past 30 years, Haiti has experienced several severe tropical cyclones, causing an increase in precipitation which results in overloading of excess rainwater. As a result, the rivers / streams of the country have grown in size and have flooded many surrounding areas. One of the watersheds that has drawn world attention is Lake Azuéi. The size of the lake has considerably increased from the years 1986 to 2016, which has flooded the surrounding agricultural, resulting in the loss of people's livelihood, causing social, environmental and economic impacts.
In this study, we use satellite imagery to assess control on the recent lake level rises. Various theories have been proposed by technical groups, national and international organizations to explain the growth of the lake. Among the hypothesis there is: (1) Regional Climate change, (2) deforestation of the watershed. However, many people believe that precipitation is the main factor that causes the expansion of the Lake Azuéi. This study analyzed two main theories (precipitation and land cover change) to determine whether they are at the origin of the growth.
The size change of the lake was determined (from 1986 to 2016) and analyzed using Satellite data (LANDSAT and SENTINEL images), and Geographic Information System (GIS). Deforestation was studied using remote sensing of land cover (Moderate Resolution Imaging Spectroradiometer (MODIS) MCD12Q1) over the years 2001 to 2012 and analyzing vegetation changes. By analyzing the precipitation data and changes in Lake Surface, although there is evidence of land cover change, however, the changes themselves have not been significant enough to influence major changes in the hydrological balance. The results show that the main threat to the Lake Azuéi was the extreme events (hurricanes, tropical storms, torrential rains) that struck the region during several years period. The aim of this study is to determine the different factors that contribute to the expansion of this mysterious lake, seeking a possible explanation for the rising level of the lake and provide a starting point for a future research.
1. Harp, E.L., Jibson, R.W. and Dart, R.L. (2013) the effect of complex fault rupture on the distribution of landslides triggered by the 12 January 2010, Haiti earthquake. In Landslide Science and Practice.
2. Dolisca, F., McDaniel, J.M., Teeter, L.D. and Jolly, C.M. (2007) Land tenure, population pressure, and deforestation in Haiti: the case of Forêt des Pins Reserve. Journal of Forest Economics, 13(4), 277-289.
3. Hodell, D.A., Curtis, J.H., Jones, G.A., Higuera-Gundy, A., Brenner, M., Binford, M.W. and Dorsey, K. T. (1991). Reconstruction of Caribbean climate change over the past 10, 500 years.
4. Knutson, T.R., McBride, J.L., Chan, J., Emanuel, K., Holland, G., Landsea, C. and Sugi, M. (2010) Tropical cyclones and climate change. Nature Geoscience, 3(3), 157-163.
5. CFET (1997) Centre de Formation et d’Encadrement Technique. Diagnostic des communautés vivant au sein et dans le voisinage de la Forêt des Pins. Assistance Technique pour la Protection des Parcs et Forêts (ATPPF)/Ministere del’Environnement (MDE), Port-au-Prince, Haiti.
6. Smucker, G.R., White, T. A. and Bannister, M. E. (2000) Land Tenure and the Adoption of Agricultural Technology in Haiti. CGIAR Systemwide Program on Property Rights and Collective Action, International Food Policy Research Institute.
7. Versluis, A. and Rogan, J. (2010) Mapping land-cover change in a Haitian watershed using a combined spectral mixture analysis and classification tree procedure. Geocarto International, 25(2), 85-103.
8. Harmsen, E.W., Mecikalski, J., Mercado, A. and Cruz, P.T. (2010) Estimating Evapotranspiration in the Caribbean Region Using Satellite Remote Sensing. Proceedings of the AWRA Summer Specialty.
9. Luna, E. and Poteau, D. (2011) Water Level Fluctuations of Lake Enriquillo and Lake Azuei in Response to Environmental Change. Master’s Thesis, Cornell University, Ithaca.
10. Lugo, A. (2000). Effects and Outcomes of Caribbean Hurricanes in Climate Change Scenarios. International Institute of Tropical Forestry, Puerto Rico, USA. Received November 21, 1999; accepted April 7, 2000
11. Ferguson, R.L.; Korfmacher, K. Remote sensing and GIS analysis of seagrass meadows in North Carolina, USA. Aquat. Bot. 1997, 58, 241–258.
12. Vogelmann, J.E.; Sohl, T.; Howard, S.M. Regional characterization of land cover using multiple sources of data. Photogramm. Eng. Remote Sens. 1998, 64, 45–57.
13. Lawrence, R.L.; Wright, A. Rule-based classification systems using classification and regression tree (CART) analysis. Photogramm. Eng. Remote Sensing 2001, 67, 1137–1142.
14. Lathrop, R.G.; Montesano, P.; Haag, S. A multi-scale segmentation approach to mapping seagrass habitats using airborne digital camera imagery. Photogramm. Eng. Remote Sens. 2006, 72, 665–675.
15. Yu, Q.; Gong, P.; Clinton, N.; Biging, G.; Kelly, M.; Schirokauer, D. Object-based detailed vegetation classification with airborne high spatial resolution Remote Sensing imagery. Photogramm. Eng. Remote Sens. 2006, 72, 799–811.
16. Conchedda, G.; Durieux, L.; Mayaux, P. An object-based method for mapping and change analysis in mangrove ecosystems. ISPRS J. Photogramm. Remote Sens. 2008, 63, 578–589.
17. Johansen, K.; Arroyo, L.A.; Phinn, S.; Witte, C. Comparison of geo-object based and pixel-based change detection of riparian environments using high spatial resolution multi-spectral imagery. Photogramm. Eng. Remote Sens. 2010, 76, 123–136.
18. Blaschke, T. Object based image analysis for remote sensing. ISPRS J. Photogramm. Remote Sens.
19. Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.; Queiroz Feitosa, R.; van der Meer, F.; van der Werff, H.; van Coillie, F.; et al. Geographic object-based image analysis—Towards a new paradigm. ISPRS J. Photogramm. Remote Sens. 2014, 87, 180–191.
20. Campbell, M.; Congalton, R.G.; Hartter, J.; Ducey, M. Optimal land cover mapping and change analysis in northeastern oregon using Landsat imagery. Photogramm. Eng. Remote Sens. 2015, 81, 37–47.