High-accuracy, long-time-series and large-scale land classification mapping are essential for assessing the evolutionary patterns of land systems and developing sustainability studies. In this paper, using Google Earth Engine (GEE) and Landsat satellite remote sensing images, based on the Random Forest (RF) algorithm, we carried out remote sensing classification to obtain a year-by-year land use/cover data set in Vietnam over the past 21 years (2000–2020). Further applying principal component analysis and multiple linear regression methods, we examined the spatio-temporal characteristics, dynamic changes and driving mechanisms of land use change. The results show the following: (1) The RF classification algorithm supported by the GEE can quickly and accurately obtain a land use/cover data set. The overall classification accuracy is 0.91 ± 0.01. (2) The land cover types in Vietnam are dominated by woodland and cropland, with an area share of 54.62% and 37.90%, respectively. In the past 20 years, the area of built-up land has increased the most (+93.49%), followed by the area of water bodies (+54.19%), while the area of woodland has remained almost unchanged. (3) The expansion of built-up land is driven by regional economic development; the area changes in cropland, water bodies and woodland are influenced by both national economic development and climate change. The results of the study provide a basis for assessing land use policies in Vietnam and a reference methodological framework for rapid land mapping and analysis in other countries in the China–Indochina Peninsula.

Guangdong Chaoan Fenghuangdancong Tea (GCFT) Cultural System is the second batch of China’s Nationally Important Agricultural Heritage Systems (China-NIAHS), identified by the Ministry of Agriculture and Rural Affairs in 2014 as having rich biodiversity, valuable knowledge of indigenous technology, and unique ecological and cultural landscape. Under the dual background of rapid urbanization and agricultural industry structure transformation, China-NIAHS-GCFT is facing the reality of structural changes in land use/cover and landscape patterns. Therefore, it is important to systematically portray land use/land cover (LULC) changes in China-NIAHS-GCFT sites and clarify the spatial pattern differences due to the impact of China-NIAHS-GCFT recognition on tea garden areas and the tea industry. This study was conducted in Chaozhou City, Guangdong Province, where GCFT is located, to compare and analyze the LULC characteristics of the core area of the heritage site (Chaoan, Chaozhou) and the control area (Raoping, Chaozhou) before and after recognition. We assessed the spatial variation in tea garden area and the intrinsic driving mechanisms of the change by integrating social factors, such as China-NIAHS-GCFT recognition, and natural factors, such as elevation, precipitation, and temperature. The results show that: (1) Around 2010, the change in LULC of the core and control areas progressed from slight changes to dramatic changes, mainly shifting from natural to anthropogenic landscapes. The decrease in the cropland and grassland and the increase in built-up land in the core area were obviously larger than those in the control area. (2) Before and after GCFT was recognized as China-NIAHS in 2014, the changing pattern of tea garden shifts from “basically stable and small growth” to a trend of “substantial expansion”. Specifically, the recognition brought about tea garden area expansion and tea industry development in the core area, especially Fenghuang. Meanwhile, a radiating effect extends to the control area, especially the townships adjacent to Fenghuang. (3) Similar natural climatic conditions of temperature and precipitation in the two regions provide a basic growing environment for tea trees; however, elevation was the key natural resource condition affecting the distribution of tea gardens. The elevation conditions of the core area are more suitable for growth of tea trees compared to the control area.

Soil erosion results in land degradation and desertification in northern China. The Xilingol League of Inner Mongolia is an important part of the “Two Barriers and Three Belts”, and has been given the main function of “a windbreak and sand-fixing belt of northern China”. Accurate measuring of soil erosion moduli, analyzing the differences in soil erosion moduli across different periods and regions, are the basis for carrying out soil conservation and evaluating the effectiveness of ecological governance. Some radioisotopes are good environmental tracers because they are closely combined with the fine particles of the surface soil and are only affected by the mechanical movement of soil particles. In this paper, Taipusi Banner and Zhengxiangbai Banner, which are in the farming–pastoral ecotone in northern China, were selected as the study area. A regional reference inventory, that is, the activity of ¹³⁷Cs and ²¹⁰Pb_ex in the sample without any soil erosion, accumulation/deposition, or any kind of manual disturbances, as well as the soil erosion moduli, were determined by ¹³⁷Cs and ²¹⁰Pb_ex composite tracing technology and multiple lines of evidence. The results are as follows: (1) The regional ¹³⁷Cs reference inventory was 1928 Bq∙m⁻², and the regional ²¹⁰Pb_ex reference inventory was 10,041 Bq∙m⁻². (2) On a 50-year time scale, the soil erosion moduli in the study area ranged from 140 t∙km⁻²∙a⁻¹ to 1030 t∙km⁻²∙a⁻¹; on a 100-year scale, the soil erosion moduli in the study area ranged from 35 t∙km⁻²∙a⁻¹ to 2637 t∙km⁻²∙a⁻¹; the entire study area was in a lightly eroded state. (3) Compared with two periods before and after the 1970s, the southern parts (cultivated land and grassland) experienced an increasing trend in soil erosion moduli due to land reclamation, grassland grazing, and other activities. Due to weakening wind and increasing precipitation, soil erosion moduli in the northern parts (southern margin of the Hunshandake Sandy Land) slowed down. The study also discussed the uncertainty and application potential of isotope-tracing technology in sandy land of typical grasslands in northern China.

Global greening and its relationship with climate change remain the hot topics in recent years, and are of critical importance for understanding the interactions between the terrestrial ecosystem carbon cycle and the climate system. China, especially north China, has contributed a lot to global greening during the past few decades. As a water-limited ecosystem, human activities, not precipitation amount, were thought as the main contributor to the greening of north China. Considering the importance of precipitation event characteristics (PEC) in the altered precipitation regimes, we integrated long-term normalized difference vegetation index (NDVI) and meteorological datasets to reveal the role of precipitation regimes, especially PECs, on vegetation growth across temperate grasslands in north China. Accompanied with a significantly decreased growing season precipitation (GSP), NDVI increased significantly in the largest area of the temperate grasslands during 1982–2015, i.e., greening. We found that 28.44% of the area was explained by PECs, including more heavy or extreme precipitation events, alleviated extreme drought, and fewer light events, while only 0.92% of the area was associated with GSP. NDVI did not always increase over the 30 years and there was a decrease during 1996–2005. Taking afforestation projects in desertified lands into account, we found that precipitation, mainly PECs, explained more the increase and decline of NDVI during 1982–1995 and 1996–2005, respectively, while an equivalent explanatory power of precipitation and afforestation projects to the increase in NDVI after 2005. Our study indicates a possible higher productivity under future precipitation regime scenario (e.g., fewer but larger precipitation events) or intensive afforestation activity, implying more carbon sequestration or livestock production of temperate steppe in the future.