Dataset Information

Data on spatiotemporal land use land cover changes in peri-urban West Arsi Zone, Ethiopia: Empirical evidences from Shashemene peri-urban areas.

ABSTRACT: Urban expansion is one of the major problems in Ethiopia resulting in displacement of the rural people inhabiting areas bordering the cities/towns. It is also resulting in land use land cover (LULC) changes affecting the livelihoods of the people and the ecosystems (Messay et al., 2017; Ganamo, 2013) [[1], [2]]. The data presented in this article, therefore shows the spatiotemporal LULC changes of peri-urban expansion areas of Shashemene City. The data were generated from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper plus (ETM+) images (with path/row numbers 168/055) from EarthExplorer.usgs.gow and the data was classified, interpreted and cross-tabulated using ERDAS IMAGIN 2013 and ArcGIS 10.4.1 software packages. The accuracy of the image classification was verified by geo-location data collected from ground control points by using Geo Positioning System (GPS) receiver and the spatial resolution (1?m) and very recent (2016) Imagery downloaded from Google Earth. The result indicates that the built-up areas have increased by 1938.71?ha (19.3871?km2) with 73.4%, and 17.6% decline in forest land and grassland respectively between 1973 and 2016.

SUBMITTER: Girma T

PROVIDER: S-EPMC5996349 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Data on spatiotemporal land use land cover changes in peri-urban West Arsi Zone, Ethiopia: Empirical evidences from Shashemene peri-urban areas.

Girma Tarekegn T Lika Tebarek T Maru Molla M

Data in brief 20180322

Urban expansion is one of the major problems in Ethiopia resulting in displacement of the rural people inhabiting areas bordering the cities/towns. It is also resulting in land use land cover (LULC) changes affecting the livelihoods of the people and the ecosystems (Messay et al., 2017; Ganamo, 2013) [[1], [2]]. The data presented in this article, therefore shows the spatiotemporal LULC changes of peri-urban expansion areas of Shashemene City. The data were generated from Landsat Thematic Mapper ...[more]

PMID: 29900231

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Project description:The emergence of mosquito-transmitted viruses poses a global threat to human health. Combining mechanistic epidemiological models based on temperature-trait relationships with climatological data is a powerful technique for environmental risk assessment. However, a limitation of this approach is that the local microclimates experienced by mosquitoes can differ substantially from macroclimate measurements, particularly in heterogeneous urban environments. To address this scaling mismatch, we modeled spatial variation in microclimate temperatures and the thermal potential for dengue transmission by Aedes albopictus across an urban-to-rural gradient in Athens-Clarke County GA. Microclimate data were collected across gradients of tree cover and impervious surface cover. We developed statistical models to predict daily minimum and maximum microclimate temperatures using coarse-resolution gridded macroclimate data (4000 m) and high-resolution land cover data (30 m). The resulting high-resolution microclimate maps were integrated with temperature-dependent mosquito abundance and vectorial capacity models to generate monthly predictions for the summer and early fall of 2018. The highest vectorial capacities were predicted for patches of trees in urban areas with high cover of impervious surfaces. Vectorial capacity was most sensitive to tree cover during the summer and became more sensitive to impervious surfaces in the early fall. Predictions from the same models using temperature data from a local meteorological station consistently over-predicted vectorial capacity compared to the microclimate-based estimates. This work demonstrates that it is feasible to model variation in mosquito microenvironments across an urban-to-rural gradient using satellite Earth observations. Epidemiological models applied to the microclimate maps revealed localized patterns of temperature suitability for disease transmission that would not be detectable using macroclimate data. Incorporating microclimate data into disease transmission models has the potential to yield more spatially precise and ecologically interpretable metrics of mosquito-borne disease transmission risk in urban landscapes.

Dataset Information

Data on spatiotemporal land use land cover changes in peri-urban West Arsi Zone, Ethiopia: Empirical evidences from Shashemene peri-urban areas.

Publications

Data on spatiotemporal land use land cover changes in peri-urban West Arsi Zone, Ethiopia: Empirical evidences from Shashemene peri-urban areas.

Similar Datasets

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