Timo Toivanen

Participatory Sensing in Environmental Monitoring -- Experiences

In this paper we describe our experiences in applying the concept of participatory sensing to environmental monitoring. We have run pilot trials for air quality, water quality and plant disease monitoring. In these pilots, users have reported their personal observations or measurements of various environmental phenomena, using special location-based applications in their mobile phones. We found a relevant correlation between algae observations by untrained citizens and by professionals, which supports the feasibility of participatory sensing as a complementary information source for algae monitoring. One key issue in collecting useful participatory datasets is managing to motivate people for acting as mobile environmental sensors. Other important issues discussed in the paper include privacy preservation and reliability of user observations.

Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping

Due to the high cost of traditional forest plot measurements, the availability of up-to-date in situ forest inventory data has been a bottleneck for remote sensing image analysis in support of the important global forest biomass mapping. Capitalizing on the proliferation of smartphones, citizen science is a promising approach to increase spatial and temporal coverages of in situ forest observations in a cost-effective way. Digital cameras can be used as a relascope device to measure basal area, a forest density variable that is closely related to biomass. In this paper, we present the Relasphone mobile application with extensive accuracy assessment in two mixed forest sites from different biomes. Basal area measurements in Finland (boreal zone) were in good agreement with reference forest inventory plot data on pine ( R 2 = 0 . 75 , R M S E = 5 . 33 m 2 /ha), spruce ( R 2 = 0 . 75 , R M S E = 6 . 73 m 2 /ha) and birch ( R 2 = 0 . 71 , R M S E = 4 . 98 m 2 /ha), with total relative R M S E ( % ) = 29 . 66 % . In Durango, Mexico (temperate zone), Relasphone stem volume measurements were best for pine ( R 2 = 0 . 88 , R M S E = 32 . 46 m 3 /ha) and total stem volume ( R 2 = 0 . 87 , R M S E = 35 . 21 m 3 /ha). Relasphone data were then successfully utilized as the only reference data in combination with optical satellite images to produce biomass maps. The Relasphone concept has been validated for future use by citizens in other locations.

Water quality analysis using an inexpensive device and a mobile phone

BackgroundWater transparency is one indicator of water quality. High water transparency is an indication of clean water. A common method for measuring water transparency is Secchi depth. In this paper, we present an approach to water quality (Secchi depth and turbidity) monitoring using mobile phones and a small device designed for water quality measurements.ResultsThe water quality parameters were analysed automatically from the images taken using mobile phone cameras. During the summer of 2012, we conducted a field trial in which 100 test users gathered 1,146 observations using the system. The results of the automatic Secchi3000 depth analysis were compared against reference measurements, and they indicate that our approach can be used for quantitative water quality measurements.ConclusionsResults show that overall the system performs well. Both Secchi depth and turbidity are estimated with excellent or good accuracy when the measurements are taken with care.

Participatory surface algal bloom monitoring in Finland in 2011–2013

BackgroundAlgal mass occurrences are one of the most distinguishing effects of eutrophication in lakes and the coastal waters of the Baltic Sea. Algal bloom occurrence in water bodies varies greatly in terms of both space and time, even during short periods, which makes reliable monitoring of blooms difficult. In this paper, we explore the possibilities to extend the sensor network both spatially and temporally by applying participatory sensing to surface algal bloom monitoring in Finnish lakes and the coastal areas of the Baltic Sea.ResultsTwo participatory sensing systems were used to collect visual algae observations by citizens: the mobile phone application Levävahti (Algae Watch) and the collaborative web service Järviwiki (Lake wiki), during the summers of 2011–2013. Citizen observations were compared with the visual observations performed by trained expert observers, and mean correlations between citizen and expert observations were calculated using the bootstrapping method: 0.72, 95% confidence interval (CI) [0.53 0.86]; 0.65, 95% CI [0.35 0.86]; and 0.56, 95% CI [0.29 0.76] for the years 2011, 2012 and 2013.ConclusionsSurface algal bloom monitoring is needed to obtain data on algal bloom frequency and intensity, in particular in lakes where the use of satellite remote sensing has limitations and/or phytoplankton monitoring is infrequent or totally lacking. The correlations between expert and citizen observations suggest that citizen observers can provide additional information to support algal bloom monitoring of inland and coastal waters.

Relasphone — Mobile phone and interactive applications to collect ground reference biomass data for satellite image analysis

The availability of ground reference forest data can be a bottleneck in remote sensing studies. Data may be available in only limited areas because of the cost and lengthy process of traditional forest inventory data collection by professionals. In certain cases, forest inventory data may not be easy to obtain, if not impossible.

Keyword Extraction from Short Documents Using Three Levels of Word Evaluation

In this paper we propose a novel approach for keyword extraction from short documents where each document is assessed on three levels: corpus level, cluster level and document level. We focus our efforts on documents that contain less than 100 words. The main challenge we are facing comes from the main characteristic of short documents: each word occurs usually only once within the document. Therefore, the traditional approaches based on term frequency do not perform well with short documents. To tackle this challenge we propose a novel unsupervised keyword extraction approach called Informativeness-based Keyword Extraction (IKE). We compare the performance of the proposed approach is against other keyword extraction methods, such as CollabRank, KeyGraph, Chi-squared, and TF-IDF. In the experimental evaluation IKE shows promising results by out-performing the competition.

Advances in combining optical citizen observations on water quality with satellite observations as part of an environmental monitoring system

Citizen observations, environmental data gathered by volunteers without professional observation capabilities, have been extensively used for Finnish water quality monitoring tasks. Recently, mobile smartphones and their digital cameras have enabled more direct measurements of transparency related water quality variables with inexpensive technology suitable for volunteers. These “Secchi3000” ideas of measurement technology by viewing known targets through multiple viewing path lengths within measured water were used to develop an iQwtr measurement device for water transparency related citizen observations. Past experiences with crowdsourcing and use of in situ water transparency data with satellite observations are reviewed and future challenges outlined.

Participative forest in-situ measurements for biomass mapping in satellite images over Durango State, Mexico

Citizen Science, propelled by the growing popularity of smartphones, can provide valuable reference information for remote sensing image analysis. We demonstrate that the Relasphone, a biomass measuring application previously developed and tested in boreal forests of Finland, can be adapted to temperate-cold pine forests in Durango State, Mexico. Relasphone measurements were in good agreement with reference data over 55 plots (R2 = 0.94), and have been used to produce a biomass map over Durango from a Landsat 8 image. The results suggest the Relasphone can be easily deployed in other biomes.