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For the low-carbon multimodal transportation planning problem with fuzzy demands and carbon emission limit, this paper proposed a multi-objective multimodal transportation mathematical model to minimize the path cost and carbon emission. Firstly, it used the chance constrained programming to deal with the uncertain demand represented by trapezoidal fuzzy number according to the characteristics of the model. Secondly, it designed the path relinking algorithm, multiple crossover operators, and mutation operators to replace the search process of original Harris hawks optimizer algorithm. It successfully applied the algorithm to the discrete optimization problems on the premise of preserving the original characteristics of this algorithm. Finally, it studied the multimodal transportation from Nanning city to Harbin city as a case, which gave multiple reasonable route scheme. HHHO was compared with other algorithms. The results show that HHHO, NSGA-Ⅱ, GA, SA and PSO all obtain a set of near-optimal solutions with five solutions in an ideal time, and the solution set of HHHO is closer to the optimal solution set. The running time of HHHO and the other four algorithms are 86.50 s, 118.26 s, 101.67 s, 81.22 s and 68.40 s, respectively. HHHO is faster than GA and NSGA-Ⅱ in running time. Therefore, these results verify the feasibility of the model and the effectiveness of hybrid Harris hawks optimizer algorithm. [ABSTRACT FROM AUTHOR]

Taking Harbin city as the research object, the paper extracted the vegetation cover based on Landsat TM/ OLI remote sensing images in 2004, 2010, 2015 and 2020, which combined the normalized vegetation index and dimidiate pixel model. Then, we integrated the transfer matrix to analyze the spatial and temporal dynamic changes of vegetation coverage. Based on the results of vegetation coverage classification, four landscape pattern indices namely patch area, number of patches, contagion index, and Shannon's diversity index, were calculated by Fragstats4. 2 software to study the spatial and temporal evolution characteristics of the landscape pattern in Harbin. The results showed that the sum of areas with high vegetation coverage and medium-high vegetation cover accounted for 77. 81%, 72. 54%, 73. 01% and 83. 31% of the total area in 2004—2020, respectively, and the vegetation coverage exhibited an overall increasing trend in Harbin City. The landscape percentage of high vegetation coverage was the highest from 2004 to 2020, followed by medium-high vegetation coverage, and the number of patches exhibited a first increasing and then decreasing trend for the most vegetation coverage region. At the landscape level, the aggregation of patches decreased and the landscape diversity increased slightly. This study explores the dynamic changes of vegetation coverage and landscape patterns in Harbin city, which can provide guidance and reference for the planning design and landscape pattern optimization of the city. [ABSTRACT FROM AUTHOR]

[Objective] In the present study, the decoupling relationship between spatial-temporal heterogeneity of carbon storage in cultivated land use transition and the grain production were analyzed, providing scientific basis for realizing low-carbon agriculture and ensuring grain security. [Method] Taking Harbin section of Songhua River Basin as the study area, based on the carbon storage calculation method and the nuclear density analysis model, the paper revealed the temporal and spatial heterogeneity of the carbon storage in the study area's cultivated land use transition from 1990 to 2020, and explored the decoupling effect between the carbon storage loss in the cultivated land use transition and grain production using Tapio decoupling model. [Result] (i) The cultivated land area gradually decreased in 1990-2020, and the transition between cultivated land and construction land was the most significant. The carbon storage in the transition of cultivated land use showed a significant downward trend, increasing by 388 630 tons in 1990-2000, decreasing by 60 121 750 tons in 2010-2020, losing nearly 155.701 times; (ii) The gravity center of carbon storage in cultivated land use transition was basically stable, with 13. 396 kilometers moving to the northeast in 1990-2020. The spatial distribution showed the pattern of 'dense edges and middle sparse', and the aggregation was gradually enhanced, showing transformation of single core distribution to multi-core distribution, and the fragmentation was intensified; (iii) The decoupling relationship between carbon storage loss and grain production in the study area was the non-benign in 1990-2020, showing the process of strong decoupling-weak decoupling-expansion connection'; (iv) The spatial heterogeneity of decoupling in the study area was significant in 1990-2020. The internal spatial difference was large, showing inequality and the transformation from two-level differentiation to three-level differentiation. [Conclusion] In the process of cultivated land utilization transformation in Harbin section of Songhua River Basin from 1990 to 2020, carbon stocks continue to decline, and the degree of spatial fragmentation is significant, and the loss of carbon stocks seriously affects food security. The study area should pay attention to the threat of grain carbon stock loss to food security. [ABSTRACT FROM AUTHOR]

In order to construct a high-precision prediction model of forest surface litter moisture content, this paper takes three typical forests in Harbin City, Heilongjiang Province as the research object, and uses a self-made portable meteorological factor detector for real-time detection. Three representative machine learning methods of RF ( Random Forest ), BP ( Back Propagation ), and LSTM ( Long Short Term Memory ) were used to construct litter moisture content prediction models for the three stands. Results showed that, the prediction accuracy of the prediction model constructed by different forest stands under different machine learning methods was different. The prediction accuracy of the three stands in different machine learning models was LSTM > BP > RF. LSTM had the best effect in the study of surface litter moisture content prediction model. The results of this study indicated that LSTM was outstanding in the prediction of surface litter moisture content, which had important theoretical significance and practical guiding value for improving the accuracy of surface litter moisture content model based on meteorological element method. [ABSTRACT FROM AUTHOR]