4/8/2023 0 Comments Esri webmap free![]() ![]() Remote sensing (RS) can be an effective alternative to field work because it is cheaper and faster compared to conventional cadastral surveys, and it is a useful data source for many base map-updating activities. Although field surveying acquires accurate land information, it is extremely time-consuming and requires well-trained manpower for wide-area implementation. Traditionally, cadastral surveying is performed by field work, aerial monitoring, and satellite data acquisition. As the step of extracting relevant features, both up-to-date spatial and non-spatial information, such as parcel boundaries and land category, can be generated. The procedure of updating cadastral maps can be divided into three steps: (1) extracting meaningful features and generating new data, (2) comparing new data with the existing base map and detecting changes, and (3) updating the base map with those changes and verifying the consistency of the updated map and actual information. Frequent updates of cadastral information can better manage illegal land use, whereby landowners register false land uses to reduce their taxes. Furthermore, from the aspect of tax imposition, which is a main purpose of land use management by cadastral mapping, updating cadastral maps is crucial because the tax imposed on land owners depends on their land use type. For example, updating is necessary when the land is suddenly changed by new sub-divisions, transfer of land use, and natural disasters. Therefore, the items of land category can be assigned according to their land use type, such as “Building site,” “Parking lot,” and “Road.” Cadastral map updates are essential for not only recording the most recent land ownership and property division changes in a timely manner but also effectively managing the land information. The land use type, which indicates the purpose of use, is registered and managed as an attribute of “land category” in a cadastral system. High-quality cadastral mapping requires updating the changes in land use information and the spatial division of property units. Therefore, it is generalizable to various cadastral systems and the discrepancy ratios will provide practical information and significantly reduce the time and effort for land monitoring and field surveying.Ī cadastral map is updated by modifying the spatial and non-spatial data of the existing cadastral maps to reflect the latest land information. Although the performance of the proposed method depends on the classification results obtained from UAV imagery, the method allows a flexible modification of the matching criteria between the land categories and land coverage. The method automatically reveals the inconsistent parcels requiring updates of their land category. Finally, discrepancy maps between the land cover maps and existing cadastral maps were generated and visualized. ![]() The overall classification accuracies of six land classes at Sites 1 and 2 were 99.93% and 99.75% and those at Sites 1 and 2 are 39.4% and 34.4%, respectively, which had discrepancy ratios of 50% or higher. As a case study, the proposed method was evaluated using hyperspectral UAV images acquired at two sites of Jeonju in South Korea. Second, a discrepancy map, which contains the ratio of the area that is being used differently from the registered land use in each parcel, is constructed through a three-stage inconsistency comparison. These images are effectively classified by a hybrid two- and three-dimensional convolutional neural network. First, an up-to-date land cover map is generated from hyperspectral unmanned aerial vehicle (UAV) images. Our proposed method operates in two steps. For this purpose, the present study analyzes the discrepancy between the existing cadastral map and the actual land use. A cost-effective, fast alternative to the current surveying methods would improve the efficiency of land management. Although land categories can be updated by remote sensing techniques, the update is typically performed through manual analysis, namely through a visually interpreted comparison between the newly generated land information and the existing cadastral maps. Since non-spatial information, such as land category, is usually updated by field-based surveys, it is time-consuming and only a limited area can be updated at a time. The non-spatial information of cadastral maps must be repeatedly updated to monitor recent changes in land property and to detect illegal land registrations by tax evaders. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |