FOSS4G 2022 academic track

Nobusuke Iwasaki

Dr. Nobusuke Iwasaki has been a board member of the OSGeo Japan chapter since 2007, as Vice Representative since 2014 and Representative since 2018. From 2009 to 2015, He participated in projects of the Japanese Ministry of Education to localize FOSS4G Tools, such as GRASS and QGIS, and to create tutorials. Currently, he is working on the utilization of Web Map tiles for deep learning and the development of map algebra tools using WebGL.


Client-side Web Mapping system for vineyard suitability assessment
Nobusuke Iwasaki

Currently, various kinds of geospatial data are provided as open data/or map tile data. This implies that geospatial data have become easier to obtain and use than older data with traditional licenses and formats. By combining map tile data with Web Mapping clients, such as Open Layers and Leaflet, we can browse maps of any location without complicated procedures, i.e., downloading data, transforming coordinate system, extracting area of interest, and installing software. These web mapping technologies have been developed mainly in the field of human interpretation of map images.

In addition, there has been the development of technologies for usage of map tiles not only background image of Web Mapping, but also processing and visualizing data in a client-side Web browser. The Geological Survey of Japan (GSJ) has proposed Data PNG and related format (1) for distributing data as map tiles. This format provides data in the PNG format which allows retaining numerical attributes, such as temperature, elevation, and geological classification. It is also possible to develop web applications with good responsiveness to user requests and promote diverse data use (Nishioka, 2019). The GSI published a demonstration site for the Data PNG tile (2) (3). Kitao (2020) developed a Web application for visualizing mapping point cloud data provided as Data PNG. Mapbox Terrain-RGB provides elevation data in PNG format and Mapbox GL JS visualizes these data as a 3D map. These applications were implemented with the capabilities of WebGL. WebGL is a cross-platform, open web standard JavaScript API for 2D and 3D graphics in modern Web browsers that allows the GPU-accelerated usage of image processing without the use of plug-ins.

As described above, there are many applications for client-side data visualization using WebGL. However, an implementation of data analysis using WebGL, especially the map algebra function, has not been progressively developed. This paper aims to develop map algebra functions for Data PNG tiles with WebGL in a client-side Web mapping system.

In this study, we attempted to develop map algebra functions for vineyard suitability assessment in Nagano Prefecture, Japan. In recent years, “Japan Wine,” made exclusively from grapes grown in Japan, has been gaining international recognition, and new wineries in Japan are also increasing. Thus, there is an urgent need to provide information to support the selection of appropriate vineyard sites and grape varieties. There have been attempts to assess the suitability of agricultural fields for crop production applying GIS. Despite these efforts, suitable site evaluation of vineyards has not been fully disseminated due to the lack of the following components: (1) sufficient quality, quantity, and accurate information necessary to determine the suitable site; (2) appropriate criteria for evaluating suitable sites based on the information, and (3) methods for providing evaluation results to consumers, such as new farmers. Therefore, we attempt to develop the client-side Web mapping system, using only a Web browser without any special skills and specific software, which enables new farmers to evaluate suitable sites for vineyards.

A variety of environmental information is required for assessing vineyard suitability. In this report, we converted spatial information about geology, soils, topography, and meteorology, which is available as open data, to Data PNG tiles with FOSS4G tools, such as QGIS, TileMill, and MBUtil for suitability assessment. The vineyard suitability assessment system consists of the following map algebra functions:

1) Generate assessment values from a Data PNG tile layer by performing quadrature calculations, specifying the order of operations using parentheses, and classification based on logical operation formulae.

2) Comprehensive assessment function that performs a quadratic calculation, specifies the order of operations using parentheses, and classification based on logical operation formulae between the layers generated by the above procedure.

3) Vineyard suitability visualize function based on the comprehensive assessment

The Web Mapping interface was developed with Leaflet, which has a graphical interface to input map algebra formulae and a function to display and export the image of vineyard suitability based on the comprehensive assessment result described above. A prototype of the vineyard suitability assessment system is available in the following URL:

In this system, data used for assessment are provided as Data PNG tiles, and a map algebra function is performed by WebGL on a client-side. In other words, unlike many other Web Mapping systems, our system does not require server-side systems and/or middleware and can be operated using only a web browser. This means that various entities can be operated on the same system at a low cost or on a free Web service, such as GitHub pages. Additionally, the functions implemented in this system can be applied to various evaluations using the map algebra functions.

However, our system contains only seven items for assessing suitable locations, which is not sufficient. The arithmetic functions of the system are limited to four arithmetic and logical operations, and it is not capable of implementing the complex model calculations required for highly realistic assessment. We are currently constructing a suitability assessment model using machine learning, information on the distribution of vineyards obtained from field surveys, and various environmental factors derived from field monitoring and published open data. In the future, we will use these data to improve the system and make it more practical.

Room Modulo 3