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The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data are used to verify the performance of the proposed RMA.

Remote sensing technology is widely used in various industries in China, and plays its own role. In geological surveying and mapping, its remote sensing technology can optimize the process of geological surveying and mapping, change the traditional working methods, and make its geological surveying and mapping results more accurate. Therefore, it is necessary to understand the applications of remote sensing technology in geological mapping. In this paper, we need to understand the content of remote sensing technology first, and then explain the specific application of remote sensing technology in geological surveying and mapping, explain the development prospect of remote sensing technology, and provide reference for the corresponding researchers.

With the continuous development of science and technology, remote sensing technology has become more and more mature and more advanced in our country, and the application of remote sensing technology to the monitoring of geological environment is also an important research problem in continuous improvement in recent years. China has a vast land area, rich mineral resources, strong geological diversity and complex geological environment, and the geological exploration of the origin of mineral resources is a prerequisite for the rationality of mineral development. Therefore, the remote sensing dynamic monitoring of geological environment plays a decisive role in mineral development. With the development of mineral resources, China’s mineral environment is getting worse and worse. In order to ensure the long-term development of mineral resources and the safety of mining personnel. Remote sensing dynamic monitoring of geological environment in mineral areas is of great significance. Based on this, this paper will study the remote sensing monitoring data of mining, and provide help for the remote sensing monitoring of geological environment of mineral development in China.

To support the Puerto Rico hurricane disaster scenario, we develop a DroneGo disaster response system by establishing the following models. First, we establish a location analysis model for ISO containers based on the coverage of video reconnaissance and the priority comparison between the two required missions–medical supply delivery and video reconnaissance. According to the locations of 11 harbors in Puerto Rico, we select three suitable harbors to position three cargo containers called CON 1, 2 and 3 to conduct the missions. Second, we build two packing configuration models to design the packing configuration for containers. In one model, we recommend a drone fleet for CON 1 and 3 according to reconnaissance conditions, and then put drones into containers in order. In another model for CON 2, we determine the type of drones according to the medical supply demands of hospitals. For both models, the number of drones of each type is determined by the enumeration method and the packing placement is determined by the greedy algorithm. The algorithms are coded in Visual C++ and MATLAB. The computational results show that the space utilizations for the three containers are all above 80.8%. Third, we design a drone flight plan model based on graph theory. According to the time and space constraints of drones, we devise flight plans as well as delivery routes and schedule. The computational results show that the coverage of video reconnaissance is up to 70.1%. Finally, we carry out the error and sensitivity analysis, discuss the strengths and weaknesses of our models, and design the future work. In addition, a two-page memo that summarizes our modeling results, conclusions, and recommendations is given at the end of the paper.

Radar remote sensing has the ability of all-day and all-weather monitoring, has certain penetration ability to vegetation, and is sensitive to the shape, structure and dielectric constant of vegetation scatterers. These characteristics make it have great potential in agricultural application. Firstly, this paper introduces the application fields of radar remote sensing in agriculture, and summarizes the current research literature in many fields, such as crop identification and classification, farmland soil moisture inversion, crop growth monitoring and so on. Then, the application status and research achievements of radar scatterometer and various SAR features (including SAR backscattering features, polarization features, interference features and tomography features) in various fields of agriculture are described respectively. Finally, the problems and reasons existing in the current research are summarized according to the agricultural application requirements and the development of SAR technology, and the future development is prospected.

With the development and application of Internet technology, cloud computing, big data technology, Internet of things technology and other new generation information technology, smart city has gradually become the focus of global urban development. Remote sensing technology big data is the combination of remote sensing technology and big data technology. Remote sensing technology has the characteristics of long-distance, non-contact detection and wide coverage. And the data information collected by remote sensing equipment is analyzed by using big data technology to improve the application value of remote sensing technology. This paper first describes the characteristics of remote sensing big data and the connotation of smart city, and that the remote sensing big data technology can promote the intelligent supervision of urban pollution, urban planning, urban traffic intelligent response, and construction more reasonable and humanized, then it can help realize the development of urban traffic intelligent.