High-standard farmland destruction monitoring by high-resolution remote sensing methods: a 2017-2018 case study of Hebei and Guangdong, China.

Remote sensing has emerged as a new technique for collecting farmland data due to its rapid advancement, rising popularity, and application in social production practice. In order to understand and manage farmland resources in China, it is essential to account for and monitor high-standard farmland and its usage. Therefore, this work used satellite remote sensing empowered with various abilities for monitoring high-standard farmland by employing GF-2 high-resolution satellite images to identify targets and objects in Hebei and Guangdong provinces. Farmland occupation and utilization were analyzed by detecting destructions, underutilization, and overutilization, and converting farmland for other economic activities registered on a special field sheet for quantification. A statistical summary was compiled for the two provinces, and the results reveal that high-standard farmland irregularities were detected in both Hebei and Guangdong provinces. However, in Hebei province, this was due to domestic purposes, such as building home shelters and domestic factories. On a contract, the result shows that in Guangdong province, farmland was being converted for economic purposes on an industrial scale, such as high residential apartment blocks and new industrial zones, and environmental destruction. Furthermore, the results reveal that there is still a steady and continuous decline in arable land due to accelerated industrialization and population pressure, especially in the Guangdong provinces, which is a threat to national food security. The high interpretation accuracy demonstrates that high-resolution remote sensing is an effective farmland monitoring tool that can be used to advance policy formulation.

Practicability of monitoring soil Cd, Hg, and Pb pollution based on a geochemical survey in China.

Repeated visiting, i.e., sampling and analysis at two or more temporal points, is one of the important ways of monitoring soil heavy metal contamination. However, with the concern about the cost, determination of the number of samples and the temporal interval, and their capability to detect a certain change is a key technical problem to be solved. This depends on the spatial variation of the parameters in the monitoring units. The "National Multi-Purpose Regional Geochemical Survey" (NMPRGS) project in China, acquired the spatial distribution of heavy metals using a high density sampling method in the most arable regions in China. Based on soil Cd, Hg, and Pb data and taking administrative regions as the monitoring units, the number of samples and temporal intervals that may be used for monitoring soil heavy metal contamination were determined. It was found that there is a large variety of spatial variation of the elements in each NMPRGS region. This results in the difficulty in the determination of the minimum detectable changes (MDC), the number of samples, and temporal intervals for revisiting. This paper recommends a suitable set of the number of samples (nr) for each region under the balance of cost, practicability, and monitoring precision. Under nr, MDC values are acceptable for all the regions, and the minimum temporal intervals are practical with the range of 3.3-13.3 years.