Detecting clear-cut deforestation using Landsat data : a time series analysis of remote sensing data in Covasna County, Romania between 2005 and 2015
(2016) In Student thesis series INES NGEM01 20161Dept of Physical Geography and Ecosystem Science
- Abstract
- Forested areas represent a fundamental component of the environment. Deforestation and forest fragmentation represent a global issue mostly caused by human influence and Romania is not an exception. Nowadays forests cover approximately a third of Romania’s surface, meaning that the deforestation is a national issue. To handle this problem, a monitoring tool is necessary.
The aim of the present study is to detect clear-cut deforestation using time series analysis between 2005 and 2015 in Covasna County, Romania. To achieve this objective, the analysis focuses on solving three main issues: (i) assess if clear-cut deforestation can be detected in the study area, (ii) determine the spatio-temporal distribution of the clear-cut deforestation,... (More) - Forested areas represent a fundamental component of the environment. Deforestation and forest fragmentation represent a global issue mostly caused by human influence and Romania is not an exception. Nowadays forests cover approximately a third of Romania’s surface, meaning that the deforestation is a national issue. To handle this problem, a monitoring tool is necessary.
The aim of the present study is to detect clear-cut deforestation using time series analysis between 2005 and 2015 in Covasna County, Romania. To achieve this objective, the analysis focuses on solving three main issues: (i) assess if clear-cut deforestation can be detected in the study area, (ii) determine the spatio-temporal distribution of the clear-cut deforestation, and (iii) confront these results with the official deforestation rates.
A time series decomposition method (BFAST - Breaks For Additive Seasonal and Trend) has been used on Landsat imagery to detect forest cover changes. To identify the most suitable spectral index for detecting clear-cut deforestation, the algorithm was initially tested on a smaller test area. BFAST applied on Normalized Difference Moisture Index (NDMI) has been proved to have more consistent results than BFAST applied on Normalized Difference Vegetation Index (NDVI).
This study concludes that clear-cut deforestation can be detected using BFAST algorithm considering forest type and the scale of the study area. Between 2005 and 2015, in Covasna County, Romania, 1.71% of forest cover, representing 2953 ha, was deforested. Contrary to the official deforestation rate, that mainly shows an increase of the deforestation rate for the last 10 years, the results of this study present a decrease in clear-cut deforestation between 2005 and 2015. The detection process was estimated to have an overall accuracy of 84%.
Therefore, the presented method is a promising tool for monitoring clear-cut deforestation in Romania at national scale. (Less) - Popular Abstract
- Deforestation represents a major issue in Romania. Covasna County in Romania is one of the most threatened areas concerning illegal deforestation risk which is why this county was selected for this study. The forests in Covasna County are composed of both coniferous and deciduous species, the most prevalent being spruce, fir and beech.
This study is aimed at detecting clear-cut deforestation using satellite images. The study was conducted for the 2005-2015 interval and it followed three main research questions: how can clear-cut deforestation be detected in Covasna; where and when the clear-cut deforestation is happening and how are these results compared to the official deforestation rates?
The method that was used to conduct this study... (More) - Deforestation represents a major issue in Romania. Covasna County in Romania is one of the most threatened areas concerning illegal deforestation risk which is why this county was selected for this study. The forests in Covasna County are composed of both coniferous and deciduous species, the most prevalent being spruce, fir and beech.
This study is aimed at detecting clear-cut deforestation using satellite images. The study was conducted for the 2005-2015 interval and it followed three main research questions: how can clear-cut deforestation be detected in Covasna; where and when the clear-cut deforestation is happening and how are these results compared to the official deforestation rates?
The method that was used to conduct this study was BFAST (Breaks For Additive Seasonal and Trend), a time series analysis, which represents a succession of satellite images recorded in the same area at different moments in time. Two different spectral indices were used in this study: one representing the presence of vegetation and the other measures the vegetation moisture. The study concluded that the most appropriate index considering this type of forest and this specific study area is that related to the vegetation moisture.
This study indicates that the BFAST algorithm can be successfully used to detect clear-cut deforestation considering the forest type and its geographical position, this fact being confirmed by a high overall accuracy. In addition, it resulted that the clear-cut deforestation recorded decrease between 2005 and 2015. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8892796
- author
- Buhalau, Tudor LU
- supervisor
-
- Dan Metcalfe LU
- Hongxiao Jin LU
- organization
- course
- NGEM01 20161
- year
- 2016
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Landsat, BFAST, Covasna, Physical Geography and Ecosystem Analysis, deforestation, time series, NDVI, NDMI
- publication/series
- Student thesis series INES
- report number
- 399
- funder
- Erasmus Mundus Programme
- language
- English
- id
- 8892796
- date added to LUP
- 2016-10-03 16:59:09
- date last changed
- 2016-10-03 16:59:09
@misc{8892796,
abstract = {{Forested areas represent a fundamental component of the environment. Deforestation and forest fragmentation represent a global issue mostly caused by human influence and Romania is not an exception. Nowadays forests cover approximately a third of Romania’s surface, meaning that the deforestation is a national issue. To handle this problem, a monitoring tool is necessary.
The aim of the present study is to detect clear-cut deforestation using time series analysis between 2005 and 2015 in Covasna County, Romania. To achieve this objective, the analysis focuses on solving three main issues: (i) assess if clear-cut deforestation can be detected in the study area, (ii) determine the spatio-temporal distribution of the clear-cut deforestation, and (iii) confront these results with the official deforestation rates.
A time series decomposition method (BFAST - Breaks For Additive Seasonal and Trend) has been used on Landsat imagery to detect forest cover changes. To identify the most suitable spectral index for detecting clear-cut deforestation, the algorithm was initially tested on a smaller test area. BFAST applied on Normalized Difference Moisture Index (NDMI) has been proved to have more consistent results than BFAST applied on Normalized Difference Vegetation Index (NDVI).
This study concludes that clear-cut deforestation can be detected using BFAST algorithm considering forest type and the scale of the study area. Between 2005 and 2015, in Covasna County, Romania, 1.71% of forest cover, representing 2953 ha, was deforested. Contrary to the official deforestation rate, that mainly shows an increase of the deforestation rate for the last 10 years, the results of this study present a decrease in clear-cut deforestation between 2005 and 2015. The detection process was estimated to have an overall accuracy of 84%.
Therefore, the presented method is a promising tool for monitoring clear-cut deforestation in Romania at national scale.}},
author = {{Buhalau, Tudor}},
language = {{eng}},
note = {{Student Paper}},
series = {{Student thesis series INES}},
title = {{Detecting clear-cut deforestation using Landsat data : a time series analysis of remote sensing data in Covasna County, Romania between 2005 and 2015}},
year = {{2016}},
}