Abstract. Based on the requirements of quality supervision inspection for national surveying and mapping, this paper has carried out research on sampling and auxiliary sampling technology and sampling system for quality inspection targets for different objects and different types of surveying results. The study designed the quantitative random sampling scheme of the random inspection objects considering the principle of supervision and spot check of surveying and mapping quality. It also designed the stratification scheme of surveying and mapping results under different quality inspection targets and object conditions, and the stratified adjustment scheme with prior quality information. Based on the above scheme, the national surveying and mapping supervision inspection sampling system based on the project rolling pool and the stratified random auxiliary sampling prototype system for the quality inspection target of surveying and mapping results are implemented. In recent years, they have been widely used in the national surveying and mapping geographic information supervision inspection and surveying and mapping results quality inspection, which guaranteed the scientific and reasonable determination of surveying and mapping quality supervision inspection objects, and solved problems in the quality inspection of surveying results, such as unreasonable stratification in manual sampling, and inevitable error in random sampling. This is of great significance for further improving sampling efficiency, reducing sampling error, reducing sampling risk, and promoting informatization of quality inspection.

Abstract. Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a research hotspot when it comes to the natural resources results involving remote sensing big-data. A sequential quality evaluation model based on root mean square error (RMSprop) optimization algorithm is constructed by theoretical analysis with an numerical experiments to validate the effectiveness of this method.

Abstract. At present, social and economic development has entered a new era. The establishment of the Ministry of Natural Resources has strengthened the functions of the natural resources department to provide the government and the public with standard, accurate, authoritative and reliable geomatics data recognized by various sectors, and has also put forward higher requirements for the quality of geomatics data.The definition of some elements in the geomatics standards is ambiguous or even contradictory, which interferes with the work level of production personnel, affects the ability of quality inspectors to determine quality problems accurately and efficiently, reduces the consistency of geographic information data, and limits the promotion and use of the products.The fundamental way to solve this problem is to unify the understanding of products, quality inspection and application, to comprehensively consider different scales, different terrain types and different types of results, and to define geomatics elements precisely, clearly and uniformly so that practitioners in different links can reach a consensus and have no ambiguity in the understanding of the elements. This work is not only conducive to reducing friction among products, quality inspection and application, but also the basis for realizing the co-construction and sharing of geographic information data among various sectors.