This paper presents the Coastal Altimetry Waveform Retracking Expert System (CAWRES), a novel method to optimise the Jason satellite altimetric sea levels from multiple retracking solutions. CAWRES’ aim is to achieve the highest possible accuracy of coastal sea levels, thus bringing measurement of radar altimetry data closer to the coast. The principles of CAWRES are twofold. The first is to reprocess altimeter waveforms using the optimal retracker, which is sought based on the analysis from a fuzzy expert system. The second is to minimise the relative offset in the retrieved sea levels caused by switching from one retracker to another using a neural network. The innovative system is validated against geoid height and tide gauges in the Great Barrier Reef, Australia for Jason-1 and Jason-2 satellite missions. The regional investigations have demonstrated that the CAWRES can effectively enhance the quality of 20 Hz sea level data and recover up to 16% more data than the standard MLE4 retracker over the tested region. Comparison against tide gauge indicates that the CAWRES sea levels are more reliable than those of Sensor Geophysical Data Records (SGDR) products, because the former has a higher (≥0.77) temporal correlation and smaller (≤19 cm) root mean square errors. The results demonstrate that the CAWRES can be applied to coastal regions elsewhere as well as other satellite altimeter missions.

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.

Over recent years, the phenomena, Web 2.0 has led to the growth of volunteered geographic information (VGI). The emergence of VGI has played an important role in providing timely data when the costs and its availability is a major concern particularly during emergency and humanitarian efforts. The worldwide crowdsourcing efforts through OpenStreetMap (OSM), the most successful open platform for collaborative mapping have managed to assist authorities such as during the 2017 Mexico earthquake and Hurricane Irma and Maria that impacted several countries in America continent. However, there are lots of arguments on the quality of VGI, particularly in regard to OpenStreetMap (OSM). Therefore, this study was carried out to assess the quality of OSM against authoritative sources using a dataset of Putrajaya, Malaysia. This study assessed the quality of OSM, including completeness, positional and thematic accuracy. From the preliminary assessment, the results showed that the OSM data was good in terms of relative positioning accuracy, particularly in road feature, but still poor in terms of completeness and thematic correctness against the reference dataset. This study is significant with an expected contribution to the assessment of quality of VGI in developing countries that commonly facing slow-paced progress in mapping the OSM. The findings could be used as a basis for various parties that plan to use OSM in Malaysia, particularly Putrajaya as a supplementary data to authoritative sources, including data supplied by the professional surveyors.

Jackfruit is identified as targeted produced for premium fruit and vegetable (EPP 7). Meanwhile in Johor, jackfruit is the third biggest fruit produced in 2016. Jackfruit contains a lot of benefits which certainly good for living things and have been used in various sector such as medicine, food, anti-bacterial and anti-oxidant, antifungal effect, immunomodulatory effect and else. However, the existence of pests and diseases have threatened the productivity of jackfruit plant particularly in tropical countries including Malaysia. There are many factors that can affect the occurrence of pests and plant diseases of jackfruit such as shoot borers, bark borers, mealy bug and scale insects, blossoms and fruit rots and bacterial die-back. Several studies have been devoted to model the plant pests and diseases epidemiology, though the contexts that focus in tropical environment and jackfruit plant are limited. Therefore, this paper aims to discuss abiotic factors and spatial methods that have been used to define dispersal pattern and relationship between abiotic factors including major climatic variables with plant pests and diseases occurrence data, particularly in tropical climate. This paper could be used as a basis to understand the epidemiological models in combating pest and plant disease and to support towards the effective management of jackfruit pests and diseases in tropical countries, particularly Malaysia.