Mapping tree canopy cover in the semi-arid Sahel using satellite remote sensing and Google Earth imagery
(2017) In Student thesis series INES NGEM01 20162Dept of Physical Geography and Ecosystem Science
- Abstract
- Tree vegetation is an essential element in the daily life of the people in the Sahel region of Africa. It is also considered as a robust indicator of the Sahel ecosystem status and health. In this thesis, a method to estimate tree vegetation was developed and used in mapping the tree canopy cover in semi-arid Sahel. The developed method utilized Normalized Difference Vegetation Index (NDVI) as the predictor variable coupled with estimations of tree canopy cover from Google Earth imagery as the response variable. The developed estimation regression was applied in the Sahel of Africa for the dry season (November to May). The results showed a strong correlation between NDVI derived from Landsat 8 imagery and Tree Canopy Cover (TCC)... (More)
- Tree vegetation is an essential element in the daily life of the people in the Sahel region of Africa. It is also considered as a robust indicator of the Sahel ecosystem status and health. In this thesis, a method to estimate tree vegetation was developed and used in mapping the tree canopy cover in semi-arid Sahel. The developed method utilized Normalized Difference Vegetation Index (NDVI) as the predictor variable coupled with estimations of tree canopy cover from Google Earth imagery as the response variable. The developed estimation regression was applied in the Sahel of Africa for the dry season (November to May). The results showed a strong correlation between NDVI derived from Landsat 8 imagery and Tree Canopy Cover (TCC) estimations from Google Earth imagery. The developed method errors were evaluated using two different validation approaches. Moreover, two estimation regressions were developed using NDVI products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Inventory Modeling and Mapping Studies (GIMMS). The correlation between MODIS and GIMMS NDVI was weak which could be due to the coarse spatial resolution of these NDVI products. Mapping tree cover in the Sahel using Landsat 8 derived NDVI require high computational power and large storage capacity. Therefore, Landsat 8 NDVI based estimation regression was applied to MODIS and GIMMS NDVI products to the map tree canopy cover for the entire Sahel. All the datasets used in this study is available for public use, and therefore this method is applicable for more development and improvements. (Less)
- Popular Abstract
- Tree vegetation is an essential element in the daily life of the people in the Sahel region of Africa, particularly through agroforestry, timber extraction, and the provision of non-wood products such as food, fodder, and medicine. It is also considered as a robust indicator of the Sahel ecosystem status and health. In this thesis, a method to estimate tree vegetation was developed and used in mapping the tree canopy cover in semi-arid Sahel. The developed method utilized vegetation index from remotely sensed satellite data coupled with estimations of tree canopy cover from Google Earth imagery. The developed method was applied in the Sahel of Africa for the dry season (November to May). The results showed a strong relationship between the... (More)
- Tree vegetation is an essential element in the daily life of the people in the Sahel region of Africa, particularly through agroforestry, timber extraction, and the provision of non-wood products such as food, fodder, and medicine. It is also considered as a robust indicator of the Sahel ecosystem status and health. In this thesis, a method to estimate tree vegetation was developed and used in mapping the tree canopy cover in semi-arid Sahel. The developed method utilized vegetation index from remotely sensed satellite data coupled with estimations of tree canopy cover from Google Earth imagery. The developed method was applied in the Sahel of Africa for the dry season (November to May). The results showed a strong relationship between the vegetation index derived from Landsat 8 imagery and Tree Canopy Cover estimations from Google Earth imagery. The developed method errors were evaluated using two different validation approaches. Moreover, two estimation regressions were developed using vegetation index products from two other satellite with different properties for a comparative reason. All the datasets used in this study are available for public use, and therefore this method is applicable for more development and improvements. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8902561
- author
- Mohamed, Abdalla Eltayeb Abdalla LU
- supervisor
-
- Hakim Abdi LU
- Jonas Ardö LU
- organization
- course
- NGEM01 20162
- year
- 2017
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Sahel, physical geography and ecosystem analysis, tree cover, NDVI, Google Earth, Landsat 8, geomatics
- publication/series
- Student thesis series INES
- report number
- 409
- funder
- Svenska Institutet
- language
- English
- id
- 8902561
- date added to LUP
- 2017-02-07 09:55:29
- date last changed
- 2017-02-07 09:55:29
@misc{8902561,
abstract = {{Tree vegetation is an essential element in the daily life of the people in the Sahel region of Africa. It is also considered as a robust indicator of the Sahel ecosystem status and health. In this thesis, a method to estimate tree vegetation was developed and used in mapping the tree canopy cover in semi-arid Sahel. The developed method utilized Normalized Difference Vegetation Index (NDVI) as the predictor variable coupled with estimations of tree canopy cover from Google Earth imagery as the response variable. The developed estimation regression was applied in the Sahel of Africa for the dry season (November to May). The results showed a strong correlation between NDVI derived from Landsat 8 imagery and Tree Canopy Cover (TCC) estimations from Google Earth imagery. The developed method errors were evaluated using two different validation approaches. Moreover, two estimation regressions were developed using NDVI products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Inventory Modeling and Mapping Studies (GIMMS). The correlation between MODIS and GIMMS NDVI was weak which could be due to the coarse spatial resolution of these NDVI products. Mapping tree cover in the Sahel using Landsat 8 derived NDVI require high computational power and large storage capacity. Therefore, Landsat 8 NDVI based estimation regression was applied to MODIS and GIMMS NDVI products to the map tree canopy cover for the entire Sahel. All the datasets used in this study is available for public use, and therefore this method is applicable for more development and improvements.}},
author = {{Mohamed, Abdalla Eltayeb Abdalla}},
language = {{eng}},
note = {{Student Paper}},
series = {{Student thesis series INES}},
title = {{Mapping tree canopy cover in the semi-arid Sahel using satellite remote sensing and Google Earth imagery}},
year = {{2017}},
}