Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3
Monitoring land degradation (LD) to inform the sustainable development goal (SDG) 15.3.1 (\proportion of land that is degraded over total land area") is key to ensure a more sustainable future. At the moment, there are only default medium-resolution datasets available to assess LD in Tanzania. They...
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| Formato: | Tesis |
| Lenguaje: | Inglés |
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University of Bonn
2020
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| Acceso en línea: | https://hdl.handle.net/10568/113186 |
| _version_ | 1855531770019053568 |
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| author | Reith, J.A. |
| author_browse | Reith, J.A. |
| author_facet | Reith, J.A. |
| author_sort | Reith, J.A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Monitoring land degradation (LD) to inform the sustainable development goal (SDG) 15.3.1 (\proportion of land that is degraded over total land area") is key to ensure a more sustainable future. At the moment, there are only default medium-resolution datasets available to assess LD in Tanzania. They do not reflect local characteristics and cannot help to target exposed areas spatially.
Therefore, this thesis adapts local datasets in interplay with high-resolution imagery to find out how much land is degraded in the semi-arid districts of Kiteto and Kongwa (KK). This approach follows the recommended practice by the United Nations Convention to Combat Desertification (UNCCD). It incorporates freely available datasets like Landsat and uses open-source software in interplay with cloud-computing. Human-induced LD was assessed using the Normalized Difference Vegetation Index (NDVI) correcting it for precipitation variability with the Rain Use Efficiency (RUE). Based on Mann-Kendall's tau and using the mean NDVI per growing season, evidence suggests that 18.9% of the study area degraded, while further 14.9% showed early signs of decline. The land cover map by the Regional Centre for Mapping of Resource for Development (RCMRD) spans the years 2000-2018. It showed that in 9.3% of the area there was land cover change and in 7.8% degradation could be found. Forests lost a quarter of their initial size and grasslands decreased by 9.5 %, while croplands increased by over 30 %. Lastly, soil organic carbon (SOC) declined in 8.6% of the study area. A total of 2.6 million tons SOC was lost, most of it in grass- and forestlands.
In total, 16.4% of the area in KK districts is degraded for the LDN baseline period. The LD rose to 27.7% for the first monitoring period in 2019. Thus, the regional baseline for the SDG 15.3.1 indicator is set and the first target period assessed. In order to verify these results and make the assessment more precise, an additional collection of SOC data and larger scale ground truth is necessary. To nonetheless achieve LD neutrality until 2030, spatial planning should focus on hotspot areas and implement sustainable land management practices. |
| format | Tesis |
| id | CGSpace113186 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | University of Bonn |
| publisherStr | University of Bonn |
| record_format | dspace |
| spelling | CGSpace1131862025-11-12T07:04:18Z Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 Reith, J.A. sustainable development goals natural resources management land degradation Monitoring land degradation (LD) to inform the sustainable development goal (SDG) 15.3.1 (\proportion of land that is degraded over total land area") is key to ensure a more sustainable future. At the moment, there are only default medium-resolution datasets available to assess LD in Tanzania. They do not reflect local characteristics and cannot help to target exposed areas spatially. Therefore, this thesis adapts local datasets in interplay with high-resolution imagery to find out how much land is degraded in the semi-arid districts of Kiteto and Kongwa (KK). This approach follows the recommended practice by the United Nations Convention to Combat Desertification (UNCCD). It incorporates freely available datasets like Landsat and uses open-source software in interplay with cloud-computing. Human-induced LD was assessed using the Normalized Difference Vegetation Index (NDVI) correcting it for precipitation variability with the Rain Use Efficiency (RUE). Based on Mann-Kendall's tau and using the mean NDVI per growing season, evidence suggests that 18.9% of the study area degraded, while further 14.9% showed early signs of decline. The land cover map by the Regional Centre for Mapping of Resource for Development (RCMRD) spans the years 2000-2018. It showed that in 9.3% of the area there was land cover change and in 7.8% degradation could be found. Forests lost a quarter of their initial size and grasslands decreased by 9.5 %, while croplands increased by over 30 %. Lastly, soil organic carbon (SOC) declined in 8.6% of the study area. A total of 2.6 million tons SOC was lost, most of it in grass- and forestlands. In total, 16.4% of the area in KK districts is degraded for the LDN baseline period. The LD rose to 27.7% for the first monitoring period in 2019. Thus, the regional baseline for the SDG 15.3.1 indicator is set and the first target period assessed. In order to verify these results and make the assessment more precise, an additional collection of SOC data and larger scale ground truth is necessary. To nonetheless achieve LD neutrality until 2030, spatial planning should focus on hotspot areas and implement sustainable land management practices. 2020-06-22 2021-03-31T12:28:26Z 2021-03-31T12:28:26Z Thesis https://hdl.handle.net/10568/113186 en Open Access application/pdf University of Bonn Reith, A. J. 2020. Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3. MSc thesis in Geography. Bonn, Germany: University of Bonn. |
| spellingShingle | sustainable development goals natural resources management land degradation Reith, J.A. Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 |
| title | Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 |
| title_full | Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 |
| title_fullStr | Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 |
| title_full_unstemmed | Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 |
| title_short | Assessment of land degradation in semi-arid Tanzania: Using remote sensing to inform the Sustainable Development Goal 15.3 |
| title_sort | assessment of land degradation in semi arid tanzania using remote sensing to inform the sustainable development goal 15 3 |
| topic | sustainable development goals natural resources management land degradation |
| url | https://hdl.handle.net/10568/113186 |
| work_keys_str_mv | AT reithja assessmentoflanddegradationinsemiaridtanzaniausingremotesensingtoinformthesustainabledevelopmentgoal153 |