Study on Dune Morphology in Computer Mapping Based on 3S Technology

Take the parabolic dune of Hobq desert in Inner Mongolia as research object. Based on the GIS platform by using differential GPS data and spatial interpolation to generate DEM, then using Multi-periods high resolution images to acquire the environmental background, at the same time combine with regional wind regime and vegetation condition to measure and analyze the morphology of the parabolic dune. The result shows that the parabolic dune showed U shape in plane, and dune arms point to the west which was also wind direction. The windward slope of longitudinal profile is gentler, while leeward slope is steeper. And cross section wasn’t symmetric. The dune’s average moving speed is 11.76 m/yr. Desert ridge line’s medial axis direction is WNW-ESE, in accord with the direction of prevailing wind and resultant drift potential. Artemisia Ordosicas mainly distribute on leeward slope, two arms, and the plane ground between them, and the annual average vegetation coverage decreased 0.95%. In the long-term effect of resultant wind, the dune keeps moving forward and Artemisia Ordosica between two arms show gradual natural stage recovery which presented zonal distribution. 3S technology has already become important research method in modern Aeolian sand morphology.

Flood Disaster Identification and Decision Support System using Crowdsource Data Based on Convolutional Neural Network and 3S Technology

<span>Every flood causes damages to many lives and properties. Moreover, it affects the economy and lifestyle of people in the society in a short period and a long period. In consequence, this research would demonstrate techniques and flood detection analyzed through digital images and web application development for receiving reports and inspection of flood situation in every area. The process requires crowdsource data and uses 3S technology so it will receive the accurate and real-time data for making a decision in the flood management and aids to the people in the disastrous area. In this research, Convolutional neural network was applied for flood detection and classification using digital images and data from people or the victims. According to the study, it was found that convolutional neural network for flood classification has accuracy of data at the high level or 95.50%, 93.00%, 97.89%, and 0.91 which are the results of accuracy, producer accuracy, user accuracy, and kappa statistics, respectively. Besides, the use of this technique saves cost, time, and labors. Furthermore, the method could be applied to other disasters such as landslide, earthquake, and fire. It is able to monitor the incident in each type of disasters and also examines the damaged site after the incident</span><em><span>.</span></em>

Application of "3S" Technology in Land Resource Management

Land is the foundation of human existence, and it is also an important prerequisite and foundation for social construction and economic development. However, with the continuing construction and development of society and economy, a large number of trees have been felled, and the level of land desertification has been increasing. Therefore, it is very necessary to pay attention to strengthening land resource management. The application of "3S" technology in land resource management not only solves some problems in land resources, but also promotes the development of China's economy. The author conducted research and analysis on "3S" technology, and put forward an effective strategy for the application of "3S" technology in land resource management, hoping to help the smooth progress of land resource management activities.

Grassland utilization estimation method and system based on environmental sense

The utilization of natural grassland is an important part of grazing animal husbandry. Effective monitoring and accurate estimation of the utilization of natural grassland is an inevitable requirement for the sustainable development of grazing animal husbandry. In order to estimate the utilization process of natural grassland effectively, this paper proposes a grassland utilization estimation method based on environmental sense. In this paper, the distribution of feed intake was obtained by the GPS track data, and the distribution of grassland biomass was obtained by the satellite remote sensing estimation model of natural grassland. The feed intake and grassland biomass are classified and compared respectively. According to the value of the two, the utilization of grassland in each region was obtained. And this study designed a grassland utilization estimating system based on this estimating method and 3S technology. The results show that this method is of great significance to the rational utilization of grassland and the implementation of rotational grazing. The system can provide decision-making basis for ranchers and grassland livestock management departments to manage grazing and grassland. It enables ranchers to make reasonable and effective grazing plans, so as to make balanced utilization of grassland resources and promote the sustainable development of grazing animal husbandry.