Land is an important part of our living environment. As far as China is concerned, the research on Sustainable Utilization of land resources is relatively late. At present, there is not a complete set of principles of land resource evaluation index system in China. The relevant research is more theoretical, and the actual application cases are less. In the context of the urgent need for development of the national economy, it is an urgent problem to improve the sustainable utilization rate of land resources, which will directly affect the structural reform and the overall strategy of our country. Therefore, based on the big data of the Internet of things, combined with RS and GIS and other related intelligent technologies, this paper establishes a set of evaluation model for the sustainable use of land resources. The method in this paper is to establish the index evaluation system first, then carry out data preprocessing through GIS and RS technology, and finally use big data technology for data mining. According to the actual situation of land resources in China, Delphi method is used as the main qualitative technical analysis method to set a reasonable weight for the evaluation index system of land resources. In order to verify the effect of this method, when analyzing the land resource data of a county from 2009 to 2018, this paper carried out four experiments including the overall trend analysis of land sustainable utilization. The experimental data results show that the use of big data in this paper has achieved ideal results in the application of land resource sustainable utilization, and to a certain extent, it fills in the big data and land The case study in the field of sustainable utilization of resources is a good method and has a broad application prospect.

With the development of global economy, the sustainable use of land resources has become a key research topic in the current social and economic development. To do a good job in the sustainable use of land resources can solve such problems as waste of land resources, quality degradation, environmental damage, ecological imbalance and so on. How to realize the sustainable utilization of resources, the first thing to be solved is the sustainable monitoring of land resources. At present, many researches have been done in this field at home and abroad, but in conclusion, there are some problems, that is, the basic theory is not deep and the practical application is less. Therefore, this paper will study the application of the monitoring system of the sustainable use of soil and land resources under the support of the Internet of things big data technology, and establish a practical monitoring system of the sustainable use of land resources. The monitoring system in this paper makes full use of modern science and technology. On the basis of intelligent technology, combined with the actual situation of land resources in China, according to the practical problems, the construction principles of evaluation index system and index construction are established. In the aspect of monitoring system construction, we have greatly optimized the traditional construction method, which makes the system in this paper have better adaptability, scalability and accuracy. In order to further verify the reliability of the system, this paper carries out the performance test, accuracy test, and monitoring test in extremely harsh environment. Finally, the data show that the system can be applied to most of the land environment to monitor the sustainability of land resources.

The ecological security of land is related to the sustainable development of human beings. With the continuous progress of science, the evaluation standard of land ecological security is also changing. The traditional safety evaluation method is time-consuming and laborious, with high cost of data acquisition, small amount of data and large error of data itself. The establishment of intelligent land ecological security evaluation system through the Internet of things is conducive to a better understanding of the overall land situation in the region. Taking the land data of Cangzhou City, China as an example, this study uses the Internet of things technology to establish a set of intelligent evaluation and grading model. The random forest algorithm is used to evaluate the land ecological security, and combined with the existing data to predict the land ecological security in 2020-2025. Compared with other security evaluation methods, the intelligent land ecological security evaluation system in this study has the advantages of short operation time, low energy consumption and high accuracy. This method has a strong guiding significance for the future land ecological security management. INDEX TERMS Internet of things, intelligent land, random forest algorithm, short operation time, Cangzhou, evaluate.

Plant residue decomposition can significantly affect the water environment of wetland ecosystems. However, little is known about the trajectory and the key drivers of the different initial mass of residue (IMR) that regulate water quality. Here, we conducted a study of 210 days with an in situ experiment to examine the impact of the change in IMR and the key decomposition parameters of Phragmites australis on the water quality in the growing season of 2019 in Baiyangdian wetland in North China. Five IMR of the Phragmites were applied, ranging from 0 to 1000 g with 250 g increments. The chemical oxygen demand (COD_W), total organic carbon (TOC_W), total nitrogen (TN_W) and total phosphorus (TP_W) of the water, and the total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), cellulose, lignin, decomposition rate (k) and the remaining mass of the Phragmites in the bag (RM) were monitored. Our results showed that the IMR of the Phragmites only marginally influenced the decomposition of itself and; the variations in the level of the water indicators were ranked as TN > TP > COD > TOC and; the impacts of IMR were longer on TOC and COD than on TP and TN and; the change in water quality was significantly influenced by the Phragmites decomposition and highly correlated with the change in TOC, cellulose and k of decomposing Phragmites residue. These results indicated that the impact of 250 g of IMR on the water was negligible after 120 days, suggesting that the optimal harvest rate of the Phragmites should be above 75% in the Baiyangdian wetland, despite the strong impact at the beginning and; the impact of change in IMR on water quality can be explained by the change in the decomposition parameters of the ARTICLE HISTORY