Engaging the flood volunteers through mobile and web based neogeography platforms for efficient aid and relief coordination

The recent flood disaster that hits certain areas in Malaysia has given massive loss to the affected victims and huge damaged to certain areas. Nevertheless, the instant aid and relief supplies and supports from various sources including individuals have reduce the flood victims’ burden at some extent. However, there is an ar-gument that arises on the effectiveness of the aid and relief coordination and distribution to the affected area. This paper proposed the use of mobile and Web based Neogeography platforms to collectively centralize the aid and relief activities data among volunteers (that draw from NGOs, ad-hoc volunteer teams and individual volunteers) so that it could be shared to other volunteer teams and authority to plan for aid and relief disaster recovery activities. The proposed platforms are anticipated able to assist the authorities for effectively coor-dinating the aid and relief actions that involving various parties

Classification of translational landslide activity using vegetation anomalies indicator (VAI) in Kundasang, Sabah

This paper introduced a novel method of landslide activity mapping using vegetation anomalies indicators (VAIs) obtained from high resolution remotely sensed data. The study area was located in a tectonically active area of Kundasang, Sabah, Malaysia. High resolution remotely sensed data were used to assist manual landslide inventory process and production on VAIs. The inventory process identified 33, 139, and 31 of active, dormant, and relict landslides, respectively. Landslide inventory map were randomly divided into two groups for training (70%) and validation (30%) datasets. Overall, 7 group of VAIs were derived including (i) tree height irregularities, (ii) tree canopy gap, (iii) density of different layer of vegetation, (iv) vegetation type distribution, (v) vegetation indices (VIs), (vi) root strength index (RSI), and (vii) distribution of water-loving trees. The VAIs were used as the feature layer input of the classification process with landslide activity as the target results. The landslide activity of the study area was classified using support vector machine (SVM) approach. SVM parameter optimization was applied by using Grid Search (GS) and Genetic Algorithm (GA) techniques. The results showed that the overall accuracy of the validation dataset is between 61.4-86%, and kappa is between 0.335-0.769 for deep-seated translational landslide. SVM RBF-GS with 0.5m spatial resolution produced highest overall accuracy and kappa values. Also, the overall accuracy of the validation dataset for shallow translational is between 49.8-71.3%, and kappa is between 0.243-0.563 where SVM RBF-GS with 0.5m resolution recorded the best result. In conclusion, this study provides a novel framework in utilizing high resolution remote sensing to support labour intensive process of landslide inventory. The nature-based vegetation anomalies indicators have been proved to be reliable for landslide activity identification in Malaysia

Engaging indigenous people as geo-crowdsourcing sensors for ecotourism mapping via mobile data collection: a case study of the Royal Belum state park

Web 2.0 and the proliferation of built-in Global Positioning System (GPS) on smartphones have influenced the increase of geo-crowdsourcing activities in a number of different contexts. The aim of this paper is to evaluate the performance of indigenous people’s use of mobile collection applications that are embedded in a smartphone to facilitate ecotourism asset mapping. In order to achieve this, field usability testing was conducted where structured observational method was used to assess the performance. The findings indicate majority of them can complete the data entry tasks using mobile data collection. The performance of data entries using radio button, icons, camera and audio methods were identified as better than free text and drop-down list methods. There was a correlation between the level of education with the ability of using radio button, drop-down list and image icon as data entry methods. The paper also discusses the extent of local knowledge relating to ecotourism within the community. The findings should be useful in the understanding of the design of mobile geo-crowdsourcing tools for use within other contexts that focus on data collection by semiliterate and indigenous groups