Frostid: Aplikasi Pelaporan Jalan Banjir Berbasis Warga Pada Navigasi Berlalu Lintas

Di Indonesia, banjir merupakan masalah utama yang dialami saat musim penghujan setiap tahunnya. Jalan banjir membawa dampak kerugian kepada pengendara kendaraan bermotor misalnya dapat menyebabkan kerusakan mesin, serta penyebab utama terjadinya karat pada kendaraan bermotor. Oleh karena itu, diperlukan upaya peringatan dini, berupa sistem pelaporan banjir, yang memberikan informasi kepada pengendara sehingga mereka dapat mengantisipasi jalan banjir. Pada penelitian ini diusulkan aplikasi pelaporan jalan banjir secara online yang berfokus pada peta navigasi berlalu-lintas untuk pengguna jalan. Aplikasi ini melibatkan partisipasi warga secara aktif (crowdsourcing) yaitu pengumpulan dan penyebaran informasi banjir dilakukan oleh kerumunan (crowd) warga dan dinamakan dengan Flooded Road Reporting System Indonesia (Frostid). Aplikasi mobile Frostid dikembangkan dalam lingkungan sistem operasi Android. Pendekatan pengembangan agile Mobile-D diterapkan. Penerimaan pengguna terhadap aplikasi dievaluasi menggunakan model TAM (Technology Acceptance Model). Metriks yang dievaluasi meliputi kegunaan yang dirasakan, kemudahan pengunaan yang dirasakan, sikap pengguna terhadap aplikasi, dan niat untuk menggunakan. Berdasarkan hasil analisis statistik deskriptif hasil pengujian penerimaan pengguna, dapat disimpulkan bahwa konsep crowdsourcing dalam aplikasi pelaporan jalan banjir diterima oleh pengguna. Kesediaan pengguna untuk merekomendasikan kepada orang lain, juga selaras dengan konsep crowdsourcing, dimana nilai dari aplikasi akan optimal jika banyak pengguna yang berkontribusi

A Review of Citizen Science and Crowdsourcing in Applications of Pluvial Flooding

Pluvial flooding can have devastating effects, both in terms of loss of life and damage. Predicting pluvial floods is difficult and many cities do not have a hydrodynamic model or an early warning system in place. Citizen science and crowdsourcing have the potential for contributing to early warning systems (EWS) and can also provide data for validating flood forecasting models. Although there are increasing applications of citizen science and crowdsourcing in fluvial hydrology, less is known about activities related to pluvial flooding. Hence the aim of this paper is to review current activities in citizen science and crowdsourcing with respect to applications of pluvial flooding. Based on a search in Scopus, the papers were first filtered for relevant content and then classified into four main themes. The first two themes were divided into (i) applications relevant during a flood event, which includes automated street flooding detection using crowdsourced photographs and sensors, analysis of social media, and online and mobile applications for flood reporting; and (ii) applications related to post-flood events. The use of citizen science and crowdsourcing for model development and validation is the third theme while the development of integrated systems is theme four. All four main areas of research have the potential to contribute to EWS and build community resilience. Moreover, developments in one will benefit others, e.g., further developments in flood reporting applications and automated flood detection systems will yield data useful for model validation

Citizen Science: Reducing Risk and Building Resilience to Natural Hazards

Natural hazards are becoming increasingly frequent within the context of climate change—making reducing risk and building resilience against these hazards more crucial than ever. An emerging shift has been noted from broad-scale, top-down risk and resilience assessments toward more participatory, community-based, bottom-up approaches. Arguably, non-scientist local stakeholders have always played an important role in risk knowledge management and resilience building. Rapidly developing information and communication technologies such as the Internet, smartphones, and social media have already demonstrated their sizeable potential to make knowledge creation more multidirectional, decentralized, diverse, and inclusive (Paul et al., 2018). Combined with technologies for robust and low-cost sensor networks, various citizen science approaches have emerged recently (e.g., Haklay, 2012; Paul et al., 2018) as a promising direction in the provision of extensive, real-time information for risk management (as well as improving data provision in data-scarce regions). It can serve as a means of educating and empowering communities and stakeholders that are bypassed by more traditional knowledge generation processes. This Research Topic compiles 13 contributions that interrogate the manifold ways in which citizen science has been interpreted to reduce risk against hazards that are (i) water-related (i.e., floods, hurricanes, drought, landslides); (ii) deep-earth-related (i.e., earthquakes and volcanoes); and (iii) responding to global environmental change such as sea-level rise. We have sought to analyse the particular failures and successes of natural hazards-related citizen science projects: the objective is to obtain a clearer understanding of “best practice” in a citizen science context