Analytical Approach for Soil and Land Classification Using Image Processing with Deep Learning Yerrolla Aparna M.TECH scholar, Department of CSE CMR Technical campus Hyderabad, Telangana, India aparna.yerrolla5297@gmail.com Dr. K.Srujan Raju Professor, Department of CSE CMR Technical Campus Hyderabad, Telangana, India ksrujanraju@gmail.com Dr. Giddaluru Somasekhar Associate professor Department of CSE CMR Technical Campus Hyderabad, Telangana, India giddalurisomasekhar@gmail.com G. Divya Assistant Professor, Department of IT CMR Technical Campus Hyderabad, Telangana, India divyasep9@gmail.com Nuthanakanti Bhaskar Associate Professor, Department of CSE CMR Technical Campus Hyderabad, Telangana, India bhaskar4n@gmail.com Dr. K. Reddy Madhavi Professor, School of Computing Mohan babu University Tirupati, India kreddymadhavi@gmail.com Abstract— Agriculture highly depends on soil. Soils are available in a number of types. Each type of soil has unique characteristics, and various crops grow in each type of soil. For a number of reasons, researchers have recently developed an interest in land mappings and classifications. Soil health and analysis of soil health, that are important for the healthy crop productions, are receiving more attention from the research community as a result of the rising demanding for the agricultural fields. The soil classification is the process of categorizing soil sets into groups with comparable qualities and behaviors. Soil is a mineral storehouse. Farmers depends on the soil to grow various crops; however, most farmers are aware of which crops grow in particular soil. The classification of soil and land is essential. Soil type identification is necessary to avoid quantitative losses in agricultural productivity. Therefore, an analytical approach for soil and land classification using image processing and deep learning is presented in this methodology. The process of applying different operations to an image in order to either improve it or extract useful information from it is described as image processing. Using a deep learning algorithm based a convolutional neural network, this method categorizes images of soil and land. Keywords—Agriculture, Soil, Land, Image processing, Deep Learning (DL). I. INTRODUCTION For a large population of India's population, agriculture provides as one of their primary responsibilities and sources of income. The demand for production has increased significantly over time [1]. The main factor of the Indian economy is agriculture. India is sometimes considered to as an agricultural country. In Agriculture the soil is that the main and basic thing. As the result of earlier surface processes, soil is a term used by geologists that has different things to different people. It represents for physical and chemical processes that are now taking place to a penologist. Soil is the solid foundation that can be utilized as the foundation for homes, factories, buildings, roads, etc., in the views of an engineer. For various purposes, different people may define soils in a number of ways. Identifying externally visible patterns on soil is what is intended by "soil study." For a reasonable agricultural industry, soil grouping is very important. Identifying soil characteristics is essential for reducing product quantity losses. For countries that export a range of agricultural commodities, it is important. Food is extremely important and it is produced by crops, either directly or indirectly. The most key component in the production of any kind of crop is the soil. However, not all types of soil are perfect for all kinds of crops. Since types of soil have various characteristics that are suitable for various crops. For example, requires a lot of water for sand soil. On the other side, less water is required for clay soil as it has higher water holding capacity. Therefore, the basic requirements before beginning any crop cultivation are to identify and select the type of soil [5]. Now the farmers are using the standard methods because normal method farmers didn't get satisfactory results means the amount of crops isn't increasing to extend the amount of crops need good quality of soil [7]. When choosing the right crop for the right type of land, we might significantly increase productivity. To achieve this, the soil can first be evaluated before being classified into various soil groups. The best and most beneficial crop can be chosen based on these soil types and the geographic location [8]. For the purposes of land cover research, soil study, and mapping, it is crucial to quickly and accurately classify various types of soil [6]. Numerous factors, such as the Power of Hydrogen (PH), the percentage of exchangeable sodium, the moisture content, etc., have an influence on the structure of the soil. Their characteristics differ by region and rely on the amount of these are in the soil. The social economy and ecosystem are significantly impacted by changes in land cover, which also lead to modifications in the climate and environmental characteristics. Different kinds of soil represent the majority of the land cover. According to the region of the soil's 2023 2nd International Conference for Innovation in Technology (INOCON) Bangalore, India. Mar 3-5, 2023 979-8-3503-2092-3/23/$31.00 ©2023 IEEE 1 2023 2nd International Conference for Innovation in Technology (INOCON) | 979-8-3503-2092-3/23/$31.00 ©2023 IEEE | DOI: 10.1109/INOCON57975.2023.10101169 Authorized licensed use limited to: VIT University. Downloaded on April 28,2023 at 14:05:34 UTC from IEEE Xplore. Restrictions apply.