基于GIS和物联网的城市废弃地空间数据分析

Lavanya Vikram, Monalisa Bhardwaj
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摘要

城市周边的大型城市发展往往导致空置、废弃或无生产力的地块,有时被称为“荒地”。城市空地有多种类型,包括后工业用地、废弃用地、无植被、无人看管用地、自然用地和交通用地。传统的收集数据来研究和管理如此巨大的荒地的方法非常耗时。地理信息系统(GIS)和遥感应用可以提取周期性空间变化,使其更容易收集和生成底图,评估某一城市的荒地数量,以及远程评估荒地/空地/退化土地的面积范围。地理信息系统还有助于作为一种有价值的工具来识别邻近的土地用途、湖泊、绿化覆盖和道路网络,这可以被视为任何研究的基础工作,以获得准确的信息。在这些荒地的物联网应用中,采用了大数据和云辅助技术等新技术,以形成智能环境。因此,通过GIS和物联网应用的结合,可以更好地制定劳动力、时间、劳动力、运输、资金和所有其他物流等因素的战略;这些都是城市地区荒地监测和管理做法的组成部分。本文旨在展示GIS、遥感和物联网如何帮助我们进行城市荒地空间数据的监测、分析、外推、处理、存储和整合;并成为现场规划和管理计划决策的依据。
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Assessment of Urban Wastelands using GIS and IoT as Tools for Spatial Data Analysis
Large urban development around cities often results in vacant, abandoned or unproductive land parcels, sometimes called ‘wastelands’. There are various types of urban vacant land identified as post-industrial, derelict, land without any vegetation and left unattended, natural, and transportation-related vacant lands. The traditional way of collecting the data to study and manage such massive wastelands is hugely time consuming. Geographical Information Systems (GIS) and Remote sensing applications can extract periodic spatial changes and make it easier to collect and generate base maps, assess the number of wastelands in a given city, and remotely assess the extent of the area of wastelands/ vacant/ degraded lands. GIS also helps as a valuable tool to identify the neighboring land uses, lakes, green cover, and road networks, which could be considered as base work for any study to progress further with accurate information. Newer technologies like big data and cloud-assisted technology are employed in IoT applications for these wastelands to formulate an intelligent environment. Factors such as workforce, time, labor, transportation, money, and all other logistics can thus be strategized better with the combination of GIS and IoT applications; these are integral to wasteland monitoring and management practices for urban regions. This review paper aims to demonstrate how GIS, remote sensing, and IoT facilitate us to carry out monitoring, analyze, extrapolate, process, store, and integrate the spatial data for urban wastelands; and becomes a basis for planning and decision-making for on-site and management plans.
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