Environmental variables improve the accuracy of remote sensing estimation of soil organic carbon content.

Accurately and quickly estimating the soil organic carbon (SOC) content is crucial in the monitoring of global carbon. Environmental variables play a significant role in improving the accuracy of the SOC content estimation model. This study focuses on modeling methodologies and environmental variables, which significantly influence the SOC content estimation model. The modeling methods used in this research comprise multiple linear regression (MLR), partial least squares regression (PLSR), random forest, and support vector machines (SVM). The analyzed environmental variables include terrain, climate, soil, and vegetation cover factors. The original spectral reflectance (OSR) of Landsat 5 TM images and the spectral reflectivity after the derivative processing were combined with the above environmental variables to estimate SOC content. The results showed that: (1) The SOC content can be efficiently estimated using the OSR of Landsat 5 TM, however, the derived processing method cannot significantly improve the estimation accuracy. (2) Environmental variables can effectively improve the accuracy of SOC content estimation, with climate and soil factors producing the most significant improvements. (3) Machine learning modeling methods provide better estimation accuracy than MLR and PLSR, especially the SVM model which has the highest accuracy. According to our observations, the best estimation model in the study area was the "OSR + SVM" model (R2 = 0.9590, RMSE = 13.9887, MAE = 10.8075), which considered four environmental factors. This study highlights the significance of environmental variables in monitoring SOC content, offering insights for more precise future SOC assessments. It also provides crucial data support for soil health monitoring and sustainable agricultural development in the study area.

Assessing the impact of climate warming on tree species composition and distribution in the forest region of Northeast China.

Global climate change has markedly influenced the structure and distribution of mid-high-latitude forests. In the forest region of Northeast China, the magnitude of climate warming surpasses the global average, which presents immense challenges to the survival and habitat sustainability of dominant tree species. We predicted the potential changes in aboveground biomass, dominant tree species composition, and distribution in the forest region of Northeast China over the next century under different climatic conditions encompassing the current scenario and future scenarios (RCP2.6, RCP4.5, and RCP8.5). Forest ecosystem process model LINKAGES 3.0 was used to simulate dynamic changes in species-level aboveground biomass under four climate scenarios at the homogeneous land-type unit level. The potential spatial distribution of tree species was investigated based on three indicators: extinction, colonization, and persistence. The results showed that LINKAGES 3.0 model effectively simulated the aboveground biomass of 17 dominant tree species in the forest region of Northeast China, achieving a high accuracy with R² = 0.88. Under the current, RCP2.6, and RCP4.5 climate scenarios, the dominant tree species presented gradual increases in aboveground biomass, whereas under RCP8.5, an initial increase and subsequent decline were observed. With increasing warming magnitude, cold-temperate coniferous tree species will gradually be replaced by other temperate broad-leaved tree species. Furthermore, a large temperature increase under RCP8.5 will likely produce a significant contraction in the potential distribution range of tree species like Larch, Scotch pine, Ribbed birch, Spruce and Fir, while most temperate broad-leaved tree species and Korean pine are expected to demonstrate a northward migration. These findings provide guidance for enhancing the adaptability and resilience of forest ecosystems in middle and high latitudes and addressing the threats posed by climate warming.

Stable gullies provide a suitable habitat for functional insects and reduce the threat of pests on crops in farmland of Northeast China.

Gullies with lower altitudes compared to the surrounding environment are widely distributed in farmland of the watershed and their numbers are still expanding. However, it is still unclear how these gullies regulate the functional insects in farmland. In this study, land use types combined with the herbaceous plant, herbicide application, soil moisture, topography and climatic factors during crop growth were considered to understand how gullies influence the dynamics of functional insects in farmland from a watershed (240 ha) of Northeast China. The primary findings demonstrate that the richness and abundance of functional insects are generally greatest in gullies, particularly in stable gullies, and decrease in the following order: forest belts, grasslands, and farmlands within the watershed. Notably, the ratios of beneficial insects to pests (BI/Pest) in terms of richness and abundance were lower in gullies before July but reversed after July, in comparison to farmland. Stable gullies exhibited higher BI/Pest abundance and diversity ratios than developing gullies. The richness and abundance of functional insects were higher in the middle sections of gullies compared to their heads and tails. Furthermore, the ratios of BI/Pest were generally lower in farmlands than in any gully position. Functional insect dynamics were mainly determined by season, followed by plant abundance and biomass in the gullies, and rarely by soil moisture in the both watershed and single gullies scales. Generally, the richness and abundance of functional insects in farmland were mainly influenced by gullies, especially influenced by the gully middle position. Insect composition in farmland influenced by stable gullies was stronger than by developing gullies, and stable gullies were more beneficial in reducing the threat of pests to crops in the farmland of the watershed.

Stability in change: building a stable ecological security pattern in Northeast China under climate and land use changes.

Climate change and land use change caused by human activities have a profound impact on ecological security. Simulating the spatio-temporal changes in ecosystem service value and ecological security patterns under different carbon emission scenarios in the future is of great significance for formulating sustainable development policies. This study quantified the four major ecosystem services (habitat quality, water retention, soil erosion, and carbon storage) in Northeast China (NC), identified ecological source areas, and constructed a stable ecological security pattern. The results show that the spatial patterns of soil erosion, carbon storage, water retention, and habitat quality, the four major ecosystem services in NC, are relatively stable in the next 30 years, and there is no significant difference from the current spatial pattern distribution. The SSP1-2.6 carbon emission scenario is a priority model for the development of NC in the next 30 years. In this carbon emission scenario, the NC has the largest ecological resources (191,177 km2) and the least comprehensive resistance value (850.006 × 10-4). At the same time, the relative resistance of the corridor in this scenario is the smallest, and the area of the mandatory reserve pinch points is the least. The ecological corridors in the SSP1-2.6 scenario form a network distribution among the ecological sources, connecting several large ecological sources as a whole. This study fills the knowledge gap in building a stable ecological security pattern in NC under the background of global change, and provides a scientific basis for the decision-making of regional ecological security and land resource management.

Spatio-temporal pattern evolution of green development efficiency in Northeastern China and its driving factors.

Scientific analysis of green development efficiency is crucial for promoting healthy green development at home. The subjects of this study were 181 counties in three provinces in Northeast China. As a first step, the Super-SBM model is utilized to estimate the efficiency of 181 counties from 2006 to 2020; in addition, spatial autocorrelation analysis is applied to assess green development efficiency, spatially and temporally, of 181counties; and to examine the driving factors and spillover effects associated with the efficiency of 181 counties, the Spatial Durbin model (SDM) is utilized. The conclusions show that 181 counties have low levels of green development efficiency and are all on a downward trajectory. Liaoning Province has the highest level, Jilin Province has the second highest level, and Heilongjiang Province has the lowest level. According to the geographical distribution, the locations with high and very high green development efficiency are roughly located in Mohe City, Huma County, Xunke County, Daqing Municipal District, Harbin Municipal District, Changchun Municipal District, Wafangdian City, Dalian Municipal District, and Zhuanghe City. There is a favorable spatial connection of efficiency across regions, but the positive spatial agglomeration trend first diminishes and then gradually increases. Economic development, industrial structure, policy regulations, and environmental protection play significant roles in economic development, industrial structure, policy regulations, and environmental protection. The contribution of this essay is of paramount importance for understanding the status quo and potential for green development in different counties in Northeast China and for realizing coordinated regional green development.

Knowledge, concerns, and vaccine acceptance related to Mpox (Monkeypox) among university students in North and Northeast China: An online cross-sectional study.

The growing number of Mpox cases in China has posed a challenge to public health. The prevalence of men who have sex with men behaviors among students has been consistently increasing each year in China, accompanied by a high frequency of unprotected anal sex. As crowded places, schools are highly likely to cause an Mpox outbreak among students through long-term close contact. Understanding university students' perceptions about Mpox and willingness to vaccinate play a vital role in implementing preventive measures in schools. This study aimed to assess knowledge, concerns, and vaccine acceptance toward Mpox among university students in North and Northeast China. A cross-sectional study was conducted among 3831 university students from seven universities in North and Northeast China between September 10 and September 25, 2023. This study found a relative insufficiency in Mpox knowledge among university students (71.60%), with less than half expressing concern about the Mpox outbreak (39.57%), and the majority exhibiting a positive attitude to vaccination (76.30%). Multivariate regression analysis revealed that a good knowledge level was associated with age, study discipline, education level, and a high level of concern about Mpox. Male, elderly, or highly educated participants had a low level of concern about Mpox. Participants with a high level of knowledge toward Mpox were more likely to have the vaccination willingness. This study might help governments and schools to understand students' Mpox perceptions and vaccination intentions, enabling them to implement effective measures in addressing the issue of inadequate understanding regarding Mpox among university students.

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Alien invasive plants have been found in the semi-arid region of Northeast China for a long time, but the overall invasion situation is rarely reported. In this study, we established a database of alien invasive plants in the semi-arid area of Northeast China through field investigation, specimen collection, research of specimen online information platform and literature. The results showed that there were 34 species of alien invasive plants belonging to 26 genera and 10 families in the semi-arid area of Northeast China, among which the Composite family had the largest number of richness, with 9 genera (34.6%) and 11 species (32.4%). There were 15 species (44.1%) in 11 genera (42.3%) of Legumes, Solanaceae and Gramineae. In all the alien invasive plants, 33 species were herbaceous plants, being overwhelmingly dominant (97.1%). There were both 7 species of countrywide invasive plants with invasive grade 1 and 2, each accounting for 20.6% of the total. The number of species with invasive grade 4 was the largest, 17 species, accounting for 50% of the total. The invasive plants originated in North America and Europe was the most, accounting for 64.7%, while those from South America, Asia and Africa accounted for 35.3%. Totally, 44.1% of all the invasive alien plants were intentionally introduced, while 55.9% were unintentionally introduced. In the semi-arid area of Northeast China, 81.3% of the counties (cities) had the distribution of alien invasive plants, and the invasion situation was very serious.

[Spatial and temporal distribution characteristics of extreme wind and its effect on wind erosion in Northeast China]. / ä¸œåŒ—åœ°åŒºæžç«¯å¤§é£Žæ—¶ç©ºåˆ†å¸ƒç‰¹å¾åŠå ¶å¯¹é£Žèš€é‡çš„å½±å“.

Under the background of climate change, extreme wind events occur frequently in Northeast China, and the soil erosion caused by these extreme wind events has attracted progressively more attention from scholars. We used the methods of linear analysis, Sen+Mann-Kendal trend analysis, and Kriging interpolation to analyze the spatial and temporal characteristics of extreme wind in Northeast China from 2005 to 2020, and used the RWEQ wind erosion estimation model to calculate the annual soil wind erosion of typical wind erosion sites and wind erosion under extreme wind conditions. The results showed that the extreme wind frequency in Northeast China presented a significant upward trend from 2005 to 2020, with an increase of 2.9 times·a-1. The annual average extreme wind frequency in Northeast China ranged from 1 to 49 times·a-1, and the high frequency areas were distributed in the northwest of Xilin Gol, the west of the Hulunbuir Plateau, and the northeast of Changbai Mountain. The average contribution rate of extreme wind to soil wind erosion in four typical sites (Xilinhot, New Barhu Right Banner, Nenjiang, and Tongyu) was 31%.

Identification of Gene-Allele System Conferring Alkali-Tolerance at Seedling Stage in Northeast China Soybean Germplasm.

Salinization of cultivated soils may result in either high salt levels or alkaline conditions, both of which stress crops and reduce performance. We sampled genotypes included in the Northeast China soybean germplasm population (NECSGP) to identify possible genes that affect tolerance to alkaline soil conditions. In this study, 361 soybean accessions collected in Northeast China were tested under 220 mM NaHCO3:Na2CO3 = 9:1 (pH = 9.8) to evaluate the alkali-tolerance (ATI) at the seedling stage in Mudanjiang, Heilongjiang, China. The restricted two-stage multi-locus model genome-wide association study (RTM-GWAS) with gene-allele sequences as markers (6503 GASMs) based on simplified genome resequencing (RAD-sequencing) was accomplished. From this analysis, 132 main effect candidate genes with 359 alleles and 35 Gene × Environment genes with 103 alleles were identified, explaining 90.93% and 2.80% of the seedling alkali-tolerance phenotypic variation, respectively. Genetic variability of ATI in NECSGP was observed primarily within subpopulations, especially in ecoregion B, from which 80% of ATI-tolerant accessions were screened out. The biological functions of 132 candidate genes were classified into eight functional categories (defense response, substance transport, regulation, metabolism-related, substance synthesis, biological process, plant development, and unknown function). From the ATI gene-allele system, six key genes-alleles were identified as starting points for further study on understanding the ATI gene network.

Pathogenicity Analyses of Rice Blast Fungus (Pyricularia oryzae) from Japonica Rice Area of Northeast China.

In order to understand the pathogenicity differentiation of rice blast fungus (Pyricularia oryzae Cavara), a total of 206 isolates of P. oryzae were collected from three Japonica rice regions in Jilin Province, northeast China. Pathogenicity test showed that the reaction pattern of 25 monogenic differential varieties (MDVs) of rice (Oryza sativa L.) demonstrated a wide pathogenic diversity among the isolates. Those MDVs harbor 23 resistance (R) genes with the susceptible variety Lijiangxintuanheigu (LTH) as control. Virulent isolates of MDVs harboring R genes Pish, Pit, Pia, Pii, Pik-s, Pik, Pita (two lines), and Pita-2 (two lines) had high frequencies ranging from 80 to 100%, to MDVs harboring R genes Pib, Pi5(t), Pik-m, Pi1, Pik-h, Pik-p, Pi7(t), Piz, Piz-5, and Piz-t showed intermediate frequencies ranging from 40 to 80%, and to MDVs with R genes Pi3, Pi9(t), Pi12(t), Pi19(t) and Pi20(t) presented low frequencies ranging only from 0 to 40%. The U-i-k-z-ta pattern of race-named criteria categorized the 206 isolates into 175 races. Sub-unit U73 for Pib, i7 for Pi3 and Pi5(t), k177 for Pik-m/Pik-h/Pik-p, z17 for Pi9(t), and ta332 for Pi20(t) were crucial on pathogenic differences in regions. Twenty-seven standard differential blast isolates (SDBIs) were selected to characterize resistance in rice accessions. This study could help to build a durable identification system against blast in the Japonica rice area of northeast China and enhance our understanding of the differentiation and diversity of blast races in the world.

Sources of highly regional 129I in soils in northeast China.

The transport and deposition pathways of anthropogenic radionuclides at the global scale, particularly volatile 129I, remain somewhat elusive due to a dearth of comprehensive investigations. To gain a better understanding of the transport dynamics and deposition mechanism of anthropogenic 129I in the terrestrial environment, one hundred surface soil samples collected from northeast China were analyzed for 129I and 127I concentrations in this study. Our findings reveal that 129I/127I atomic ratios in the mid-eastern Inner Mongolia (MIM) were approximately an order of magnitude higher than the rest of the investigated area. This is, besides the global fallout and the long-range transport of 129I released from the European nuclear reprocessing plants via westerly winds, possibly attributed to the dust with high 129I levels from the East Asian arid regions. In addition to the significant dust-induced 129I input, the unique meteorological conditions and topographical features in the MIM synergistically contribute to the pronounced accumulation and deposition of 129I in this region. This study will provide novel insights into the transport and deposition mechanism of anthropogenic radionuclides, which is significant for the assessment of anthropogenic nuclear activities on the environment in the future.

Long-term variations in surface ozone at the Longfengshan Regional Atmosphere Background Station in Northeast China and related influencing factors.

Surface ozone (O3) is a crucial air pollutant that affects air quality, human health, agricultural production, and climate change. Studies on long-term O3 variations and their influencing factors are essential for understanding O3 pollution and its impact. Here, we conducted an analysis of long-term variations in O3 during 2006-2022 at the Longfengshan Regional Atmosphere Background Station (LFS; 44.44°N, 127.36°E, 330.5 m a.s.l.) situated on the northeastern edge of the Northeast China Plains. The maximum daily 8-h average (MDA8) O3 fluctuated substantially, with the annual MDA8 decreasing significantly during 2006-2015 (-0.62 ppb yr-1, p < 0.05), jumping during 2015-2016 and increasing clearly during 2020-2022. Step multiple linear regression models for MDA8 were obtained using meteorological variables, to decompose anthropogenic and meteorological contributions to O3 variations. Anthropogenic activities acted as the primary drivers of the long-term trends of MDA8 O3, contributing 73% of annual MDA8 O3 variability, whereas meteorology played less important roles (27%). Elevated O3 at LFS were primarily associated with airflows originating from the North China Plain, Northeast China Plain, and coastal areas of North China, primarily occurring during the warm months (May-October). Based on satellite products of NO2 and HCHO columns, the O3 photochemical regimes over LFS revealed NOx-limited throughout the period. NO2 increased first, reaching peak in 2011, followed by substantial decrease; while HCHO exhibited significant increase, contributing to decreasing trend in MDA8 O3 during 2006-2015. The plateauing NO2 and decreasing HCHO may contribute to the increase in MDA8 O3 in 2016. Subsequently, both NO2 and HCHO exhibited notable fluctuations, leading to significant changes in O3. The study results fill the gap in the understanding of long-term O3 trends in high-latitude areas in the Northeast China Plain and offer valuable insights for assessing the impact of O3 on crop yields, forest productivity, and climate change.

Response of Harbin aerosol to latest clean air actions in China.

Cities in Northeast China, e.g., Harbin, were brought to the forefront of air pollution control by a national-level policy promulgated in 2021, i.e., the Circular on Further Promoting the Pollution Prevention and Control Battle (the FP3CB Circular) which aimed at eliminating heavy or severe air pollution events. In this study, we explored the response of Harbin aerosol to the FP3CB Circular, based on observational results from two campaigns conducted during 2020-2021 and 2021-2022. A clear decreasing trend was identified for the impact of domestic biomass burning between the two winters, presumably driven by the clean heating actions. The 2021-2022 winter was also characterized by reduced formation of secondary organic aerosol but enhanced production of nitrate, which could be attributed to the less humid conditions but higher temperatures, respectively, compared to the 2020-2021 winter. The overall effect of these changes was a decrease in the contribution of organic species to wintertime aerosol in Harbin. In addition, the number of heavy or severe pollution days rebounded in the 2021-2022 winter compared to 2020-2021 (5 vs. 3), indicating that the emissions of primary particles and gaseous precursors must be further reduced to achieve the ambitious goals of the FP3CB Circular.

Large Seasonal Variation in Nitrogen Isotopic Abundances of Ammonia Volatilized from a Cropland Ecosystem and Implications for Regional NH3 Source Partitioning.

Ammonia (NH3) volatilization from agricultural lands is a main source of atmospheric reduced nitrogen species (NHx). Accurately quantifying its contribution to regional atmospheric NHx deposition is critical for controlling regional air nitrogen pollution. The stable nitrogen isotope composition (expressed by δ15N) is a promising indicator to trace atmospheric NHx sources, presupposing a reliable nitrogen isotopic signature of NH3 emission sources. To obtain more specific seasonal δ15N values of soil NH3 volatilization for reliable regional seasonal NH3 source partitioning, we utilized an active dynamic sampling technique to measure the δ15N-NH3 values volatilized from maize cropping land in northeast China. These values varied from -38.0 to -0.2‰, with a significantly lower rate-weighted value observed in the early period (May-June, -30.5 ± 6.7‰) as compared with the late period (July-October, -8.5 ± 4.3‰). Seasonal δ15N-NH3 variations were related to the main NH3 production pathway, degree of soil ammonium consumption, and soil environment. Bayesian isotope mixing model analysis revealed that without considering the seasonal δ15N variation in soil-volatilized NH3 could result in an overestimate by up to absolute 38% for agricultural volatile NH3 to regional atmospheric bulk ammonium deposition during July-October, further demonstrating that it is essential to distinguish seasonal δ15N profile of agricultural volatile NH3 in regional source apportionment.

Decoupling the effects of air temperature change on soil erosion in Northeast China.

Changes in the air temperature tend to indirectly affect soil erosion by influencing rainfall, vegetation growth, economic development, and agricultural activities. In this study, the partial least squares-structural equation model (PLS-SEM) was used to decouple the impacts of temperature change on soil erosion in Northeast China from 2001 to 2019, and the indirect effect of temperature change on the pathways of natural and socioeconomic factors was analyzed. The results showed that temperature increase in Northeast China caused an increase in soil erosion by increasing rainfall and promoting economic development. Under the pathway of natural factors, in spring, the promoting effect on soil erosion under the influence of temperature change on rainfall was greater than the inhibiting effect on soil erosion under by the influence of temperature change on vegetation. In summer, the opposite effect was observed. Under the pathway of natural factors, over time, the promoting effect of temperature increase on soil erosion increased by 22.7%. Under the pathway of socioeconomic factors, temperature change not only aggravated soil erosion by promoting economic development, but also indirectly increased investments in agriculture and water conservation by improving the economy, thus inhibiting soil erosion to a certain extent. Over time, the contribution of temperature change to soil erosion through socioeconomic pathway was reduced by 44.4%. When the pathway of natural factors is compared with that of socioeconomics factors, temperature change imposed a more notable effect on the change in soil erosion through the socioeconomic pathway, indicating that human activities are the driving factors with a greater effect on soil erosion. Based on this, reasonable human intervention is an important means to alleviate soil erosion aggravation caused by rising temperatures.

Simulating the effects of optimizing sowing date and variety shift on maize production at finer scale in northeast China under future climate.

BACKGROUND: Global warming and the rising occurrences of climate extremes have become formidable challenges for maize production in northeast China. The optimization of sowing date and variety choice stand out as two economic approaches for maize to enhance its resilience to climate change. Nevertheless, assessment of the potential of optimizing sowing date and variety shift on maize yield at finer scale remains underexamined. This study investigated the implications of optimizing sowing date and implementing variety shift on maize yield from a regional perspective. RESULTS: Compared to the reference period (1986-2005), climate change would decrease by 11.5-34.6% (the range describes the differences among climate scenarios and agro-ecological regions) maize yield in the 2050s (2040-2059) if no adaption measure were to be implemented. The combined adaption (optimizing sowing date and variety shift) can improve maize yield by 38.8 ± 11.3%, 42.7 ± 9.7% and 33.9 ± 7.6% under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, respectively. The current sowing window typically falls within the projected optimal sowing window, defined as the period capable of achieving 90% of the maximum yield within the potential sowing window under future climate conditions. Consequently, the potential of the effect of optimizing sowing window on maize yield is limited. In contrast, variety shift results in higher yield improvement, as temperature rise creates favorable conditions for transplanting varieties with an extended growth period, particularly in high latitudes and mountainous regions. Under future climate, cumulative precipitation and compound drought and hot days during maize growing seasons are two key factors influencing maize production. CONCLUSIONS: The optimization of sowing date and variety choice can improve maize yield in northeast China. In addition, maize production should consider varieties with longer growth period and drought and heat tolerance to adapt to climate change. © 2023 Society of Chemical Industry.

Towards sustainable transport: quantifying and mitigating pollutant emissions from heavy-duty diesel trucks in Northeast China.

Heavy-duty diesel trucks (HDDTs) have caused serious environmental pollution in China. Accurate estimation of their pollutant emission characteristics is essential to reduce emissions and associated environmental and public health impacts. To achieve sustainable development for transport emissions in Northeast China, we developed localized emission factors and a high-resolution emission inventory of HDDTs, based on on-board test, Guidebook and international vehicle emission (IVE) model. The results show that the total emissions of CO, NO, NO2, and PM from HDDTs in Northeast China in 2020 were 172.2 kt, 531.5 kt, 11.2 kt, and 921.4 t, respectively. In terms of spatial distribution, emissions decreased from the city center to the city fringe. Temporally, the NOx emission variation curves of different types of roads presented a "single-peak" emission characteristic, which was different from the peak of traffic flow. Three emission reduction scenarios are further developed in the paper. Scenario analysis shows that elimination of HDDTs that follow the old China III emission standard and installing tailpipe treatment devices are the most effective pollutant reduction measure. The reduction percentages for CO, NO, NO2, and PM ranged from 62.9 to 83.89%. The results of our study could inform policymakers to devise feasible strategies to reduce vehicle pollution in Northeast China.

Assessment of the cultivated land quality in the black soil region of Northeast China based on the field scale.

In some developing countries, particularly China, a significant number of individual farmers manage small field scale of cultivated land. However, the existing research on cultivated land quality assessment mainly focuses on large-scale regions, establishing comprehensive index systems from a macro perspective, while lacking evaluations customized to individual farmers, who constitute a crucial component in agricultural production, and a demand-driven field-scale assessment of cultivated land quality. Therefore, we developed a field-scale index system that meets the needs of individual farmers in the black soil region of Northeast China. Additionally, we proposed a machine learning model for field-scale cultivated land quality assessment. The experimental results showed that our model achieved an [Formula: see text] value of 0.9660 and an [Formula: see text] of [Formula: see text] under fourfold cross-validation, which represents an improvement of 5.19% and a reduction of 1.13%, respectively, relative to the XGBoost model. Ultimately, we conducted obstacle factor diagnosis, aiming to assist individual farmers in identifying the existing issues in their cultivated land fields. This study not only provides guidance to individual farmers but also addresses the research gap in cultivated land quality assessment by offering an individual farmer demand-driven index system for field-scale studies.

Spatio-temporal characteristics and influencing factors of urban shrinkage in county level of Heilongjiang Province, Northeast China.

Urban shrinkage has become increasingly prevalent in the context of global urbanization. Understanding its spatio-temporal characteristics and influencing factors is of great significance for promoting sustainable development and high-quality urbanization. This paper identified county-level shrinking cities in Heilongjiang Province from the perspective of urban entities. It employed spatial autocorrelation methods to analyze their spatial-temporal characteristics and explored the factors that contributed to this phenomenon. The results indicated that between 2010 and 2020, the phenomenon of urban shrinkage at the county level in Heilongjiang Province was primarily concentrated in the province's hinterland. Moreover, they exhibited characteristics of the Great Recession and Small Growth. The main factors influencing the shrinkage included the urban industrial structure, living standards, and population composition.