About One Approach to the Construction of Clustering and Classification Grid-Type Algorithms
Anatolii Kuzmin,
Leonid Grekov,
Nataliia Kuzmina,
Oleksii Petrov
Issue:
Volume 10, Issue 2, December 2022
Pages:
30-38
Received:
10 August 2022
Accepted:
29 August 2022
Published:
5 September 2022
DOI:
10.11648/j.ajrs.20221002.11
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Abstract: Applied problems of studying the earth's surface using satellite images of remote sensing of the Earth are considered for the study of forest, agricultural, water and other natural resources, where clustering and classification algorithms are instrumental research methods. It is noted that the most well-known procedures for classifying and segmenting multispectral space images in GIS systems, such as ArcGIS, ERDAS, ENVI, are built-in. The need to expand the toolkit for a more efficient solution of applied problems of this class is noted. New universal clustering and classification algorithms based on a unified approach are proposed. Both methods belong to grid-type algorithms, and at the first stage of their work they group points of a set of n - dimensional vectors into grid cells, each cell saves only the numbers of points belonging to it and is characterized by a unique code. The vector grid spacing is a parameter of the method and is set by the user using a single integer value. At the next stage, the clustering algorithm combines the cells and the points belonging to them into clusters using the cell neighborhood principle. In this case, the algorithm does not attach the next cell to the cluster in the case when its density is less than the specified value. The classification algorithm refers the points of the cell of the main set to the class to which the cell with the same code of the training set belongs. The algorithms can be used to process large data sets of large spatial dimensions, including satellite images. Clustering and classification algorithms do not require a preliminary specification of the number of clusters and information about the nature of the distribution of points in the input set.
Abstract: Applied problems of studying the earth's surface using satellite images of remote sensing of the Earth are considered for the study of forest, agricultural, water and other natural resources, where clustering and classification algorithms are instrumental research methods. It is noted that the most well-known procedures for classifying and segmenti...
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Remote Sensing for Land Resources: A Review on Satellites, Data Availability and Applications
Winfred Mbinya Manetu,
John Momanyi Mironga,
Jackob Haywood Ondiko
Issue:
Volume 10, Issue 2, December 2022
Pages:
39-49
Received:
3 October 2022
Accepted:
1 December 2022
Published:
10 January 2023
Abstract: Remote sensing is a technology that offers a unique opportunity of gathering land information by measuring and recording its emitted and reflected energy usually from a satellite or an aircraft. The capabilities of remote sensing satellite data in mapping, monitoring and managing land resources are intensifying with the rapid advancements in satellite technology. In addition, increased users demand in sustainable management of land resources has escalated the need for remote sensing technology. As a result, this article presents an overview of the remote sensing satellites that are best for mapping land resources and monitoring, focusing specifically on the necessary satellites, data availability and key land application areas. Currently, several remote sensing satellites are providing microwave, multispectral and hyperspectral data with a wide array of spatial, temporal and spectral resolutions used on land applications. Microwave remote sensing has seen the development of both active and passive remote sensing systems for remote sensing activities. Consequently, microwave data is now available with high spatial resolution and providing land information in all cloudy weather condition. On the other hand, optical remote sensing is providing space-based remote sensing data in a variety of spatial, spectral and temporal resolutions meeting the needs of many land applications. Similarly, hyperspectral remote sensing is providing digital imagery of earth resources in many narrow contiguous spectral bands. Additionally, other remote sensing techniques like Unmanned Aerial Vehicles (UAV) and Light Detection and Ranging (LiDAR) have helped in deriving detailed information of land resources to support land related studies. Besides having commercial satellites that are providing satellite data at a high cost, today several remote sensing data have been made available from open data sources and users can freely search and download areas of interest.
Abstract: Remote sensing is a technology that offers a unique opportunity of gathering land information by measuring and recording its emitted and reflected energy usually from a satellite or an aircraft. The capabilities of remote sensing satellite data in mapping, monitoring and managing land resources are intensifying with the rapid advancements in satell...
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