Agricultural Production on Erosion-Affected Land from the Perspective of Remote Sensing

In this article, we discuss the influence of soil erosion on crop yield in the erosion-prone chernozem region of South Moravia. Erosional and depositional areas show significant differences in soil properties, which are also reflected in total crop yield. Plots of winter wheat, grown during the years 2016–2019 were used for analysis. The Enhanced Vegetation Index (EVI), referred to in literature as one of the best correlates of yield, was used to provide indirect information on yield. Although erosional areas are visible on orthophoto images on chernozem soils, the necessary orthophoto images are not always available. Thus, we have proposed a method for the identification of such erosion-affected areas based on the use of Sentinel 2 satellite images and NDVI or NBR2 indices. The relationship between yield and erosion was expressed through Pearson’s correlation on a sample of pixels randomly selected on the studied plots. The results showed a statistically significant linear reduction in yield depending on the level of degradation. All plots were further reclassified, according to level of degradation, as high, medium, or low state of degradation, where the average EVI values were subsequently calculated. Yield on non-degraded soil is 16 ± 1% higher on average.

Benthic habitat classification using multiscale GEOBIA on orthophoto images of Karimunjawa waters

The scale value is an important part of the segmentation stage which is part of Object-Based Image Analysis (OBIA). Selection of scale value can determine the size of the object which affects the results of classification accuracy. In addition to setting the scale value (multiscale), selection of machine learning algorithm applied to classify shallow water benthic habitat objects can also determine the success of the classification. Combination of setting scale values and classification algorithms are aimed to get optimal results by examining classification accuracies. This study uses orthophoto images processed from Unmanned Aerial Vehicle (UAV) mission intended to capture benthic habitat in Karimunjawa waters. The classification algorithms used are Support Vector Machine (SVM), Bayes, and K-Nearest Neighbors (KNN). The results of the classification of combination are then tested for accuracy based on the sample and Training Test Area (TTA) masks. The result shows that SVM algorithm with scale of 300 produces the best level of accuracy. While the lowest accuracy is achieved by using SVM algorithm with scale of 100. The result shows that the optimal scale settings in segmenting objects sequentially are 300, 200, and 100

A Study on 3D Model Construction by Controlling Unmanned Aerial Vehicle of Camera Angle

In this study, the camera angle of a UAV (Unmanned Aerial Vehicle) was adjusted to take aerial photographs, and 2D and 3D models were constructed to evaluate the quantitative impact. The study area was Waryong Bridge, located in Dalseong-gun, Daegu Metropolitan City. The camera angles of the UAV were 90°, 75°, and 60°; DSM, orthophoto, and the 3D model were analyzed. As a result of the analysis of DSM and orthophoto, images were 1.05 times in 75° and 1.10 times in 60° compared to 90°, and matching was 1.09 times in 75° and 1.60 times in 60° compared to 90°. The point cloud for building 3D models increased analysis points to 1.17 times for 75° and 1.47 times for 60° compared to 90°. However, the area of an orthophoto of 1 pixel increased by 1.10 times for 75° and 1.34 times for 60° compared to 90°, resulting in a decrease in resolution. As the camera angle of the UAV decreases, the overlapping ratio of aerial photographs increases and the structure of wide areas can be implemented. However, since a large difference occurs in the precision of the 3D model, a shooting plan according to the purpose should be established.

THE USING OF TERRESTRIAL LASER (POINT CLOUD) SCANNING TECHNOLOGIES ON URBAN SCALE: EXAMPLE OF THE HISTORICAL URBAN TEXTURE OF LAPSEKİ

Aim: This study aims to comparatively evaluate the use potential of orthophoto images obtained by terrestrial laser scanning technologies on an urban scale through the "Old Lapseki Finds Life Project" prepared using terrestrial laser scanning technologies and the "Enez Historical City Square Project" prepared using traditional methods. Method: In the study, street improvement projects of 29.210 m2 Lapseki and 29.214 m2 Enez city designed on an urban scale were evaluated and compared with descriptive statistics based on different parameters. Results: In the study, it has been determined that terrestrial laser (point cloud) technologies are 99,9% accurate when compared to traditional methods, save time by 83,08% and reduce workforce by 80%. In addition, it has been determined that terrestrial laser scanning technologies accelerate project processes compared to traditional methods. Conclusion: In this study, the use of laser scanning technologies, which are basically reverse engineering applications, in architectural restoration projects, determination of the current situation and damage, architectural documentation of structures and preparation of three-dimensional models, in terms of efficiency in survey studies are evaluated. It has been observed that orthophoto images obtained by terrestrial laser scanning technologies in architectural relief-restoration-restitution projects have potentials' worth using in different stages of the project.

OVERALL QUALITY CONTROL OF 1:10000 ORTHOPHOTO PRODUCTS IN THE THIRD NATIONAL LAND SURVEY

Orthographic image is an important reference data source for the third national land survey, as well as the positioning benchmark and statistical basis of the national land survey, which determines the accuracy of the third national land survey results and the progress of follow-up work, and is also an important component of the third national land survey results. In order to ensure that the production of 1:10000 high-resolution orthophoto images meets the needs of the third national land survey work, and meets the relative requirements to the production of orthophoto products, it is really necessary to carry out quality control of orthophoto products.Based on the checking and accepting of 1:10000 orthophoto images at the national level, this paper discusses the quality control method of 1:10000 orthophoto products from the overall inspection. First of all, this paper studies and analyzes the key nodes of quality control in the overall inspection and clarifies the quality control requirements of each quality control key node;On the basis of carefully sorting out the typical problems found in the overall inspection of orthophoto products, carry out in-depth analysis of the causes and give corresponding solutions.This paper provides a technical reference for the quality inspection of other scale orthophoto products, and also provides a solution to the quality improvement of 1:10000 orthophoto products.

RESEARCH ON HORIZONTAL ACCURACY METHOD OF HIGH SPATIAL RESOLUTION REMOTELY SENSED ORTHOPHOTO IMAGE

At present, in the inspection and acceptance of high spatial resolution remotly sensed orthophoto image, the horizontal accuracy detection is testing and evaluating the accuracy of images, which mostly based on a set of testing points with the same accuracy and reliability. However, it is difficult to get a set of testing points with the same accuracy and reliability in the areas where the field measurement is difficult and the reference data with high accuracy is not enough. So it is difficult to test and evaluate the horizontal accuracy of the orthophoto image. The uncertainty of the horizontal accuracy has become a bottleneck for the application of satellite borne high-resolution remote sensing image and the scope of service expansion. Therefore, this paper proposes a new method to test the horizontal accuracy of orthophoto image. This method using the testing points with different accuracy and reliability. These points’ source is high accuracy reference data and field measurement. The new method solves the horizontal accuracy detection of the orthophoto image in the difficult areas and provides the basis for providing reliable orthophoto images to the users.