Investigation and evaluation of soil texture and density in different land uses using Google Earth Engine system

Introduction
Awareness of soil quality in agricultural lands and natural resources is essential to achieve maximum production and environmental sustainability. Although soil quality is not directly assessed, the use of soil quality indicators is widely used today. Among these, physical indicators of soil quality are of great importance in estimating soil quality due to the direct impact on plant growth and chemical and biological properties of soil. It is necessary to evaluate the quality of the soil and to consider its changes when using the land for the designated uses, before exploiting the land. The use of satellite imagery and GIS to extract the required information and map soil indicators to make optimal decisions has become an integral part of sustainable land management. Soil quality varies in different land uses due to changes in the physical, chemical and biological properties of the soil as well as land degradation by humans. Therefore, by having a land use map, the soil quality index can be obtained in each unit. Various studies on soil index in relation to land uses have been performed using remote sensing techniques, which show that unscientific and uninformed changes in land use have negative effects on the desired physical and chemical properties of soil. The purpose of this study is to investigate the condition of soil texture and density in different land uses and evaluate its quantification using Google Earth Engine system.
Material and Methods
Rudan basin is one of the sub-basins of the Minab watershed. Rainfall distribution in the study area is not uniform and is a pattern with about 242 mm of average annual rainfall data, of which more than 77% occurs during the rainy season (autumn and winter). On the other hand, the average minimum, maximum and average annual temperatures for the period 1980 to 2020 are 18.1, 33.02 and 25.7 ° C, respectively, and the average annual evaporation is 2858 mm. The study area was divided into 5 uses of medium and poor pastures, agricultural and garden lands and canals. In different applications, a total of 218 samples were taken from the surface of zero to 10 cm of soil and experiments to determine the texture, percentage of sand and density and density were performed using hydrometric and paraffin black methods. Open Land map is used in Google Earth Engine. For this purpose, the location of the study area in the Google Earth Engine system was first defined. The data used include Landsat series images with a resolution of 250 meters and related to the statistical period of January 1, 1950 to January 1, 2018. The location of the captured points was determined using GPS in Arc GIS 10.3 software. To evaluate and validate the results, the statistical coefficient of analysis of variance, overall accuracy and kappa coefficient was used.
Result and Conclusion
 Validation of the results obtained from the Google Earth Engine service shows 95% of the total accuracy and kappa coefficient of 0.93. Also, during the change of use with extensive coverage of agricultural lands, the amount of clay and silt will decrease and the percentage of sand will increase. This is consistent with the findings of Bewket and Stroosnijder (2003); Martinez et al. (2008) and Riahi et al., (2016) who found in their studies that during the change of forest use to agricultural and garden lands, the amount of clay and silt decreased and The amount and percentage of sand will be increased. According to studies (Aghdami et al., 2019; Zare et al., 2011; Wang et al., 2012) the physical properties of soil, especially soil texture is one of the most important determinants in the distribution of plant communities in different uses. According to the different uses and agricultural activities in the region, which is the occupation of the majority of the population and according to the strategic document of the province, the study area is considered as agricultural territory (Hormozgan Management and Planning Organization, 2019) witnesses a variety of land use changes. We are in different regions (Hormozgan Agricultural Jihad Office, 2021), On the other hand, any conversion of one land use to another may lead to the loss of natural resources and agricultural biodiversity (Rawat and Kumar, 2015; Seyum et al., 2019). Given the importance of agriculture in the region, any change in land use should be considered in the medium and long term planning. Therefore, I need detailed, up-to-date, low-cost and fast surveys to prepare development plans for various types of applications that use the data available in the online image processing system of Google Earth satellite engine, Landsat satellite images in a fraction of the minutes are processed and analyzed for evaluation and planning. This system is a safe and cost-free way to process large volumes of satellite images from various sources, which speeds up processing very well, which saves a lot of time.