Because it is geo-referenced, the location of the UDAP and the topology of the net are real. We propose a routing model between UDAPs, based on minimum spanning tree algorithm (MST) to find the minimum number of links in a specific geo-referenced area. This paper optimizes the cost of deployment of universal data aggregation points (UDAP) for advanced smart metering infrastructure (AMI), considering coverage and capacity. Third, a barrier (obstacle) might be provided to ensure that the MST is fit for purpose as political boundaries or other restrictive socio-economic issues can be considered. In this way, researchers might consider continuous geographical characteristics while estimating the costs of edges in addition to the discrete measure distance. Second, the updated version can handle raster data. The updated version determined MSTs much faster, reaching up to 30-fold improvements. The execution time of the two versions was assessed by determining MST on a randomly generated dataset consisting of 5000 polygons and New York City’s census blocks consisting of 38799 polygons. First, the updated version is much faster in execution. ![]() The updated version of the plugin (v2.0) offers three substantial improvements with respect to its former version (v1.0). This paper proposes a QGIS plugin that determines MST on geographical data using Kruskal’s algorithm. There is no built-in functionality in QGIS, an open-source Geographical Information System (GIS) software, which can determine MST. One of the algorithms that operate on graphs is ‘Minimum Spanning Tree (MST)’, which is a tree that connects all the nodes of a graph with minimum cost. Graphs describing the relation between nodes and edges are common in geographic information science. The toolbox may be used by public and private organizations to make timely decisions on agricultural and environmental issues. This toolbox also applied to Cycle II data from the Government of India’s Soil Health Card (SHC) scheme and timely produced 12-parameters soil nutrient maps for 630 districts in a uniform format. The results show that the user can quickly generate maps and save time, improve accuracy, and reduce human intervention and ensure uniformity among maps. ![]() The SFMToolbox was validated as part of the following case study: village – Kashipur, tehsil – Balrampur, district – Balrampur, state – Uttar Pradesh, Country – India. ![]() During the execution of the tools, various processes, such as Inverse Distance Weighted (IDW) – a technique of interpolation, reclassification, adding color, merging, projection, area calculation, and legend are done automatically for all12 parameters at the same time. It is easy to use, where users can only provide input the output files are automatically created from the name of the sample point and saved in the defined workspace. Through SFMToolbox, users can automatically produce 12 soil fertility parameter maps as a batch at one time. SFMToolbox is an ArcGIS Python toolbox developed in ArcGIS Desktop (ArcMap) to perform preprocessing tasks for the automatic creation of maps of soil fertility parameters.
0 Comments
Leave a Reply. |