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首页> 美国卫生研究院文献>PLoS Clinical Trials >Satellite image fusion to detect changing surface permeability and emerging urban heat islands in a fast-growing city
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Satellite image fusion to detect changing surface permeability and emerging urban heat islands in a fast-growing city

机译：卫星图像融合可检测快速增长的城市中不断变化的表面渗透率和新兴的城市热岛

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Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of Urban Heat Islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they mostly involve time consuming and expensive field studies and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and temperature and UHI emergence in a fast growing city, i.e. Tirunelveli, Tamilnadu, India. IRS-LISSIII and Landsat-7 ETM+ imageries were fused for 2007 and 2017, and classified using a Rotation Forest (RF) algorithm. Surface permeability and temperature were then quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Finally, we assessed the relationship between SAVI and LST for entire Tirunelveli as well as for each LULC zone, and also detected UHI emergence hot spots using a SAVI-LST combined metric. Our fused images exhibited higher classification accuracies, i.e. overall kappa coefficient values, than non-fused images. We observed an overall increase in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall and also for almost all LULC zones. The LST values showed an overall increase of surface temperature in Tirunelveli with the highest increase for urban built-up areas between 2007 and 2017. LST also exhibited a strong negative association with SAVI. Southeastern built-up areas in Tirunelveli were depicted as a potential UHI hotspot, with a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability, temperature and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.
机译：近几十年来，快速而广泛的城市化通过降低地表渗透率和出现城市热岛（UHI），对人类和生态实体产生了不利影响。尽管对地面渗透率和UHI进行详细而连续的评估对于城市规划和土地利用区域的管理至关重要，但它们主要涉及耗时且昂贵的实地研究以及单传感器衍生的大规模航空和卫星图像。我们展示了融合来自多个传感器的图像以进行土地利用和土地覆盖（LULC）变化评估以及评估快速发展的城市（即印度泰米尔纳德邦Tirunelveli）的表面渗透率和温度以及UHI出现的优势。对IRS-LISSIII和Landsat-7 ETM +图像进行了融合，分别用于2007年和2017年，并使用旋转森林（RF）算法对其进行分类。然后分别使用土壤调整植被指数（SAVI）和土地表面温度（LST）指数对表面渗透率和温度进行定量。最后，我们评估了整个Tirunelveli以及每个LULC区域的SAVI与LST之间的关系，并使用SAVI-LST组合指标检测了UHI出现热点。我们的融合图像显示出比非融合图像更高的分类精度，即总体Kappa系数值。我们观察到2007年至2017年之间Tirunelveli的城市（干旱，房地产地块和建成区）的覆盖范围总体增加，而Tirunelveli的植被（农田和森林）区域的覆盖范围有所减少。SAVI值表明地表的减少整个Tirunelveli以及几乎所有LULC区域的渗透率。 LST值显示Tirunelveli的地表温度总体升高，在2007年至2017年之间是城市建成区的最高升高。LST与SAVI也表现出强烈的负相关性。 Tirunelveli的东南部建成区被描述为潜在的UHI热点地区，并警告了2017年出现UHI的西部河岸带。我们的结果为地面渗透率，温度和UHI监测提供了重要指标，并告知了城市和区域规划当局关于卫星图像融合的优势。

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