Despite being of paramount importance to humanity, tangible cultural heritage is often at risk from natural and anthropogenic threats worldwide. As a result, heritage discovery and conservation remain a huge challenge for both developed and developing countries, with heritage sites often inadequately cared for, be it due to a lack of resources, nonrecognition of the value by local people or authorities, human conflict, or some other reason. This paper presents an online geo-crowdsourcing system, termed Share Our Cultural Heritage (SOCH), which can be utilized for large-scale heritage documentation and sharing. Supported by web and mobile GIS, cultural heritage data such as textual stories, locations, and images can be acquired via portable devices. These data are georeferenced and presented to the public via web-mapping. Using photogrammetric modelling, acquired images are used to reconstruct heritage structures or artefacts into 3D digital models, which are then visualized on the SOCH web interface to enable public interaction. This end-to-end system incubates an online virtual community to encourage public engagement, raise awareness, and stimulate cultural heritage ownership. It also provides valuable resources for cultural heritage exploitation, management, education, and monitoring over time.

Cultural heritage structural documentation is of great importance in terms of historical preservation, tourism, educational and spiritual values. Cultural heritage across the world, and in Nepal in particular, is at risk from various natural hazards (e.g. earthquakes, flooding, rainfall etc), poor maintenance and preservation, and even human destruction. This paper evaluates the feasibility of low-cost photogrammetric modelling cultural heritage sites, and explores the practicality of using photogrammetry in Nepal. The full pipeline of 3D modelling for heritage documentation and conservation, including visualisation, reconstruction, and structure analysis, is proposed. In addition, crowdsourcing is discussed as a method of data collection of growing prominence.

Heritage documentation has become increasingly urgent due to both natural impacts and human influences. The documentation of countless heritage sites around the globe is a massive project that requires significant amounts of financial and labour resources. With the concepts of volunteered geographic information (VGI) and citizen science, heritage data such as digital photographs can be collected through online crowd participation. Whilst photographs are not strictly geographic data, they can be geo-tagged by the participants. They can also be automatically geo-referenced into a global coordinate system if collected via mobile phones which are now ubiquitous. With the assistance of web-mapping, an online geo-crowdsourcing platform has been developed to collect and display heritage structure photographs. Details of platform development are presented in this paper. The prototype is demonstrated with several heritage examples. Potential applications and advancements are discussed.

Energy is a fundamental need of modern society and a basis for economic and social development, and one of the major Sustainable Development Goals (SDG), particularly SDG7. However, the UN’s SDG Report 2021 betrays millions of people living without electricity and one-third of the world’s population deprived of using modern energy cooking services (MECS) through access to electricity. Achieving the SDG7 requires standard approaches and tools that effectively address the geographical, infrastructural, and socioeconomic characteristics of a (rural) municipality of Nepal. Furthermore, Nepal’s Constitution 2015 incorporated a federal system under the purview of a municipality as the local government that has been given the mandate to ensure electricity access and clean energy. To address this, a methodology is developed for local government planning in Nepal in order to identify the optimal mix of electrification options by conducting a detailed geospatial analysis of renewable energy (RE) technologies by exploring accessibility and availability ranging from grid extensions to mini-grid and off-grid solutions, based on (a) life cycle cost and (b) levelized cost of energy. During energy assessment, geospatial and socio-economic data are coupled with household and community level data collected from a mobile survey app, and are exploited to garner energy status-quo and enable local governments to assess the existing situation of energy access/availability and planning. In summary, this paper presents a geo-enabled municipal energy planning method and a comprehensive toolkit to facilitate sustainable energy access to local people.

Spatially enabled yield forecasting is a key component of farm Management Information Systems (MISs) for broadacre grain production, enabling management decisions such as variable rate fertilization. However, such a capability has been lacking for soft (fleshy)-tree-fruit harvest load, with relevant tools for automated assessment having been developed only recently. Such tools include improved estimates of the heat units required for fruit maturation and in-field machine vision for flower and fruit count and fruit sizing. Feedback on the need for and issues in forecasting were documented. A mango ‘harvest forecast engine’ was designed for the forecasting of harvest timing and fruit load, to aid harvest management. Inputs include 15 min interval temperature data per orchard block, weekly manual or machine-vision-derived estimates of flowering, and preharvest manual or machine-vision-derived estimates of fruit load on an orchard block level across the farm. Outputs include predicted optimal harvest time and fruit load, on a per block and per week basis, to inform harvest scheduling. Use cases are provided, including forecast of the order of harvest of blocks within the orchard, management of harvest windows to match harvesting resources such as staff availability, and within block spatial allocation of resources, such as adequate placement of harvest field bin and frost fans. Design requirements for an effective harvest MIS software artefact incorporating the forecast engine are documented, including an integrated database supporting spatial query, data analysis, processing and mapping, an integrated geospatial database for managing of large spatial–temporal datasets, and use of dynamic web map services to enable rapid visualization of large datasets.

A farm management information system (MIS) entails record keeping based on a database management system, typically using a client-server architecture, i.e., an information system, IS, coupled with a variety of tools/methods/models for the support of operational management. The current review adopts a multivocal approach to consider academic and commercial developments in MISs for orchard management, based primarily on the refereed literature but extending to grey literature and interviews of Australian mango orchard managers. Drivers for orchard MIS development include increasing the orchard size and management complexity, including regulatory requirements around labour, chemical spray use and fertilisation. The enablers include improvements in within-orchard communications, distributed (web) delivery systems using desktop and mobile devices, and sensor systems and predictive models, e.g., for pest management. Most orchard MIS-related publications target the commodities of apple, grape, mango and olive in the context of management of plant health (pest and disease), plant development, irrigation and labour management. Harvest forecast and MIS modules are only now beginning to emerge, in contrast to a long history of use in grain production. The commercial systems trend towards an incorporation of financial information, an integration of data from multiple sources and a provision of dashboards that are tailored to the user. Requirements for industry adoption of a MIS are discussed in terms of technical and design features, with a focus on usability and scalability.