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Estimation of vegetation density using image analysis and its effect on hydraulic characteristics of an open channel


Citation

Abdullah, Osela Nooradin (2015) Estimation of vegetation density using image analysis and its effect on hydraulic characteristics of an open channel. Masters thesis, Universiti Putra Malaysia.

Abstract / Synopsis

Vegetation density is one of the factors that affect the flow behaviour and resistance in vegetated channels and wetlands. Many approaches have been explored to quantify the vegetation density such as by counting the number of vegetation or determining the area covered by the vegetation per unit area. However, in reality, the aquatic vegetation in the field is diverse in types and has varying properties, and if the vegetation is submerged, the vegetation density estimation becomes even more challenging. The use of remote sensing imagery for vegetation mapping is now gaining popularity due to the rapid development of remote sensing technology and readily available remote sensing imageries from various sources. In this study, the use of satellite image of a PLEIADES is explored to estimate the vegetation density in the Putrajaya Wetlands. Arc Map 10.1 software is used for data entry, image display and output. The vegetation type classification is derived using the Supervised Maximum Likelihood Classification and Support Vector Machine. The environment for Visualizing Images (ENVI) software is used to derive the Normalised Difference Vegetation Index (NDVI) for the selected study area and the area covered by the vegetation for different NDVI. NDVI is the ratio between the maximum absorption of radiation in the red (R) spectral band (0.66 μm) versus the maximum reflection of radiation in the near infrared (NIR) spectral band (~0.83 μm). The percentage area covered by vegetation obtained through ENVI software is then validated with ground truth. In the field survey, areas with different densities are chosen and divided into small cells of 1 m2. The percentage area covered by vegetation for each cell is estimated by observation. Then, the relationship between the percentage area covered by the vegetation and NDVI is established and it is found that the NDVI has a polynomial relationship with the percentage area covered by vegetation. Also, the relationship between NDVI and hydraulic parameters in the wetland (velocity and resistance coefficient) is derived. The velocity at various locations of different densities in the wetland is measured on site using the Acoustic Doppler Velocitimeter (ADV). From the image analysis and ground truth validation, a map of vegetation distribution based on types for the selected zone of Putrajaya Wetland has been produced. It has been found that the land cover classes in the study area fall into four classifications; that are the Hanguana Malayana, Phragmites Karka, Scirpus Grossus and water bodies. The accuracy measured using matrix confusion for the overall classification accuracy for Maximum Likelihood is 78.81% and Kappa coefficient is 0.7187% and for Support Vector Machine 81.36% for overall and 0.7512 for kappa coefficient. In addition, the NDVI values representing the vegetation distribution and density have also been generated and the NDVI values for the selected area are found to be in the range of -0.1058 - 0.7825. The velocity at various locations of different densities in the wetland showed that the density of vegetation had a significant effect on the velocity. In addition, it was observed that the flow resistance increases with the increasing in the density, which is also showed in the increasing of NDVI values.


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Additional Metadata

Item Type: Thesis (Masters)
Subject: Vegetation monitoring
Subject: Image analysis
Subject: Vegetation dynamics - Remote sensing
Call Number: FK 2015 113
Chairman Supervisor: Badronnisa bt. Yusuf, PhD
Divisions: Faculty of Engineering
Depositing User: Mas Norain Hashim
Date Deposited: 29 Mar 2019 09:46
Last Modified: 29 Mar 2019 09:46
URI: http://psasir.upm.edu.my/id/eprint/67776
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