Dataset: Tourism opportunities drive woodland and wildlife conservation outcomes of community-based conservation in Namibia’s Zambezi Region
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| Title: | Main Title: Dataset: Tourism opportunities drive woodland and wildlife conservation outcomes of community-based conservation in Namibia’s Zambezi Region |
| Description: | Abstract: This data set contains a panel data frame for analysis of land use change from 1984-2017 in Zambezi Region, Namibia. The region is located in one of the study areas of the CRC/Transregio 228: “Future Rural Africa: Future-Making and Social-Ecological Transformation”. Data contains remote sensing and spatial socio-economic data, derived and/or processed by the authors. |
| Identifier: | 10.5880/TRR228DB.3 (DOI) |
| Citation Advice: | Meyer, M., 2020. Dataset: Tourism opportunities drive woodland and wildlife conservation outcomes of community-based conservation in Namibia’s Zambezi Region. |
Responsible Party
| Creator: | Maximilian Meyer (Author) |
| Contributors: | Ekkehard Klingelhoeffer (Contact Person), Robin Naidoo (Producer), Vladimir Wingate (Producer), Jan Börner (Supervisor) |
| Funding Reference: | Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 228: Future Rural Africa: Future-making and social-ecological transformation |
| Publisher: | CRC/TRR228 Database (TRR228DB) |
| Publication Year: | 2020 |
Topic
| TRR228 Topic: | Economy |
| Related Subproject: | A1 |
| Subjects: | Keywords: Carbon Storage Dynamics, Conservation, Econometrics, Impact Evaluation, Empirical Research, Land Use Change, Remote Sensing DDC: 545 Quantitative analysis GEMET Inspire Spatial Data Themes: Land cover, Land use, Species distribution, Protected sites GEMET Thesaurus entries: environmental impact, environmental economics, Land use, environmental conservation, wildlife conservation |
| Geogr. Information Topic: | Environment |
File Details
| Filename: | LULCC_zambeziregion_namibia_1984-2017.zip |
| Data Type: | Dataset - Dataset |
| File Size: | 38.8 MB |
| Date: | Created: 01.04.2020 |
| Mime Type: | application/zip |
| Data Format: | ZIP (26.03.2020) |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Only Project Members (Download Embargo will be lifted after project end) |
| General Access and Use Conditions: | According to the TRR228DB data policy agreement. |
| Access Limitations: | According to the TRR228DB data policy agreement. |
| Licence: | [TRR228DB] Data policy agreement |
Geographic
Specific Information - Data
| Temporal Extent: | 01.01.1984, 14:43:00 - 31.12.2017, 14:43:00 |
| Lineage: | Woodland cover is derived from classified satellite images of Landsat 5, 6, 7 and 8. Following Wingate et al. (2016, doi: 10.3390/rs8080681), we use a supervised Random Forest classifier, generating five land use (LU) classes. The images are median composite scenes, obtained on a five-year time interval, starting from 1985 until 2017 and spanning the January-June period in order to enhance the presence of woody vegetation. For methodological details see Wingate et al. (2016, doi: 10.3390/rs8080681). The time interval entails earlier periods, before conservancy establishment in order to capture potential underlying time trends of Land Use Land Cover Change (LULCC) that occurred in the area. The different LU classes of each pixel at 30 by 30 meter resolution are aggregated to 300 by 300 meter resolution. The share of all woodland classified pixels on an aggregated pixel are calculated to generate the percentage share of woodland of each pixel. Data on elephant presence is provided by the Environmental Information Service Namibia (EIS) and consists of 1 x 1km square polygons, available annually from 1992 to 2009 that is rasterized using the grid resolution assuming equal probability of animal sighting in grid cells that overlap with an original polygon and constitutes a dummy (1 or 0) for each year. Temporal alignment with LULCC measures is achieved by aggregating dummy variables and generating a count variable that runs from zero to five, representing the five-year intervals. The two outcome variables are measured on 166,099 grid cells covering our study area from wall to wall. The treatment variable is derived from EIS conservancy polygon layers that are rasterized to the grid resolution. The demarcation of the conservancies includes all conservancies registered until 2017, where physical boundaries remain unchanged until this date. Community forests (CF) are also considered, which are part of some conservancies but do not match the community conservancy boundaries. Covariate data is collected from multiple public sources. This includes bio-physical and socio-economic data provided by EIS, Open Street Map (OSM), ArcGIS, International Soil Reference and Information Centre (ISRIC) and National Aeronautics and Space Administration (NASA). Raster data was fitted to the resolution. Polygon data was rasterized, according to the resolution. |
| Subtype: | Natural Science Data |
Metadata Details
| Metadata Creator: | Maximilian Meyer |
| Metadata Created: | 26.03.2020 |
| Metadata Last Updated: | 26.03.2020 |
| Subproject: | A1 |
| Funding Phase: | 1 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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Dataset Statistics
| Page Visits: | 507 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 5 |
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