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Spatially Explicit Scenario Analysis of Habitat Quality in a Tropical Semi-arid Zone: Case Study of the Sokoto-Rima Basin

机译:空间显式场景分析的栖息地质量在热带半干旱区域:案例研究Sokoto-Rima盆地

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Global biodiversity has been steadily dwindling since the turn of the twentieth century. The semi-arid ecological zone has also been decimated to varied degrees due to natural and human-caused reasons. To counteract this trend, a variety of multi-scale techniques with differing degrees of spatiotemporal uncertainty have been used. We study landcover-based scenarios related with the condition of biodiversity in the Sokoto-Rima basin (SRB) of northwestern Nigeria to address this gap. The Future Landuse Simulation Software (FLUS) and the spatially explicit InVEST Habitat Quality (HQ) model were used to simulate four alternative HQ scenarios: business as usual (BAUS), accelerated crop expansion (ACES), woodland expansion (WES), and sustainable development scenario (SDS). The data used was ESA CCI landcover (1992-2015), with underlying drivers of landcover prediction including multi-sourced terrain, population, settlements, highways, rivers, waterbodies, rainfall, and temperature. With a kappa coefficient of 0.83, overall accuracy of 93 percent, and a figure of merit of 0.15, the landcover data meets the requirements for multi-scenario modelling. Cropland dominated the SRB between 1992 and 2015, and this tendency is projected to continue in the future. By 2038, it is expected that WES and SDS will improve biodiversity, as represented by a high HQ index of 0.75, whereas BAUS and ACES will degrade the SRB more, as indicated by a low HQ index. As a result, efforts to increase the SRB's biodiversity necessitate the strict implementation of environmentally friendly laws. This research can be used to examine similar semiarid zones using a scenario-based approach.
机译:全球生物多样性不断减少自二十世纪初。半干旱生态区域也被摧毁由于自然和人为多样度的原因。多尺度和不同程度的技术时空的不确定性已经使用。研究landcover-based场景相关的Sokoto-Rima生物多样性的条件盆地(SRB)西北尼日利亚的地址这种差距。(流感)和空间显式投资的栖息地质量(总部)模型被用来模拟四种选择总部场景:一切照旧(鲍起静),加速作物扩张(ace),林地扩张(韦斯)和可持续开发场景(SDS)。CCI landcover(1992 - 2015),与底层司机landcover预测包括想见,地形、人口、定居点,高速公路、河流水体、降雨和温度。图的整体精度为93%,价值为0.15,landcover数据符合multi-scenario造型的要求。农田主导国储局在1992年至2015年之间,和这种趋势预计将继续的未来。将改善生物多样性,表示为一个吗高总部指数为0.75,而鲍起静和ace的意志降低国储局,显示低的总部索引。生物多样性需要严格的环保法律的实施。本研究可用于检查相似半干旱地区使用一个基于场景的方法。

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