Validating maps of land cover and land degradation with citizen science and mobile gaming

Peatland comprises around 24% of South Sumatra, a province on the island of Sumatra in Indonesia. Following catastrophic fires in 2015, peat restoration has become a priority for this area. To identify candidate areas for restoration, both land cover over time and land degradation have been mapped using optical and radar remote sensing. Limited field data have been used to help validate these maps but more validation data are still needed. One way to fill this gap is to tap into the power of citizen science, which has become an emerging area of interest. In citizen science, any member of the public can take part in scientific research, whether this is through data collection, analysis of the data or hypothesis generation. Here we present the results from a citizen science campaign using the Urundata mobile gaming application, which has been developed as part of the Restore+ project. Urundata has two main components: a rapid image assessment tool that allows users to classify satellite imagery by the type of land cover/land use visible or to examine pairs of images for detection of change over time (developed from an application called Picture Pile). The second component sends users to specific locations on the ground via a mobile device and asks for information related to land cover and evidence of land degradation (developed from an application called FotoQuest Go). Together these two components have been used to help validate land cover and land degradation maps of South Sumatra through citizen science

Building up local knowledge on restoration: lessons learnt from organizing a set of crowdsourcing campaigns

Restoration of degraded land is an important national goal to achieve Indonesia’s environmental targets. To map both land cover and land degradation, Indonesia needs timely, high quality data and the necessary tools. We have addressed this issue by running a sequence of crowdsourcing campaigns. Our aim is not only to collect the data but to also potentially present a way for citizens to contribute to larger environmental policies and strategies. Focusing on land cover identification and tree cover change, we planned and ran a set of pilot crowdsourcing campaigns in two provinces in Indonesia. We analysed the data from these pilot campaigns, and then used the insights obtained in the subsequent crowdsourcing campaign on land cover identification, upscaled to national level, which is currently ongoing. The campaigns were run using a mobile application developed as part of the RESTORE+ project. Through this application, we presented volunteers with simple microtasks by showing them satellite images and asking a simple yes/no question as to whether the image shows a particular land cover class. The application implemented a scoring system, which additionally performs a quality control of the data contributed by the crowd, and users competed with each other to classify the satellite images displayed by the application. 692 volunteers have actively engaged in the pilot crowdsourcing campaigns and have contributed more than 2.5 million satellite image interpretations. Based on the insights from the pilot campaigns, as well as an expert consultation session in Indonesia, the crowdsourcing application was modified to ensure, first, a uniform number of interpretations across the images, and secondly, higher quality data by allowing users to focus on geographical areas familiar to them, as well as to see the larger area surrounding the target sample. We analyzed the data collected and will present issues regarding data quality, comparing the accuracy of the contributions from the volunteers with the accuracy of the data collected by a set of experts. We show that a citizen science approach is promising and can complement scientific analyses and can provide potential inputs to policies on landscape restoration. A crowdsourcing approach to image interpretation can also help to shorten the time needed for data collection, making the process more cost-effective. In addition, the collective ownership of the results ensures their legitimacy and increases the chances of data acceptance. We also focus on transparency and the importance of open data. We present how we have made data generated by the crowd accessible in order to empower citizens in exploring and process the data further, thereby actively participating in environmental decision making

Livelihood Revitalization In Peatlands: Woven Crafts From Purun AS A Sustainable Business Option In Ogan Komering Ilir (Oki) Regency, South Sumatra

This study is conducted to better understand the potential of purun weaving as a suitable business approach that could support peatland restoration in South Sumatra. It aims to analyze the obstacles of purun weaving and its market potential as green products. This study applies qualitative and quantitative methods, including in-depth interviews and surveys. The in-depth interviews invove local business actors in Pedamaran Sub-district, Ogan Komering Ilir Regency (i.e. harvesters, weavers, and traders) and the policy-makers. Online and intercept surveys are conducted to analyze current condition and market potential of purun handicrafts, especially as the example of green products. Identified challenges include lack of market knowledge and connections, unstable supply of raw materials, lack of financial capitalization, and low product quality. The market potential for green products, however, is highly promising, as more than 80% of respondents are willing to pay a higher price for these products. Gaps between existing production system and market potential could be narrowed down by adjusting policies for existing peat swamp areas, improving access to microfinance, and implementing specific capacity building for the weavers. Moreover, suitable marketing strategies are required to support the business sustainability of purun weaving