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Fluctuation curves of GDP growth rate and value added of each industry in the three provinces: (a) GDP of Heilongjiang, (b) GDP of Jilin, (c) GDP of Liaoning, (d) primary industry of Heilongjiang, (e) primary industry of Jilin, (f) primary industry of Liaoning, (g) secondary industry of Heilongjiang, (h) secondary industry of Jilin, (i) secondary industry of Liaoning, (j) tertiary industry of Heilongjiang, (k) tertiary industry of Jilin, and (l) tertiary industry of Liaoning.
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The Chinese economy has developed rapidly since the reform and opening up, but economic growth in Northeast China has declined dramatically after the 21st century. In this context, exploring the characteristics of economic and industrial fluctuations in the northeast of China and their relationship is beneficial to alleviating economic fluctuations...
Citations
... The effect of LULC change on this region's habitat quality is a significant and intricate problem. Harbin's industrialization and urbanization have advanced further as a result of the country's reform and opening-up policies as well as the resuscitation of the former industrial base in Northeast China [46,47]. Northeast China's construction land area has grown quickly, and a sizable portion of natural land has been transformed into urban centers. ...
Biodiversity is profoundly influenced by habitat quality, and Harbin, a provincial capital situated in a cold climate zone, stands out as one of China’s regions most susceptible to the repercussions of climate change. To ensure the city’s continued sustainable growth, a thorough assessment of habitat quality must be conducted. This study employs a comprehensive approach integrating the InVEST model, the PLUS model, a landscape pattern analysis, geographic detector, and a geographically weighted regression model. The goal is to assess how land use and habitat quality have changed in Harbin City, investigate factors contributing to spatial heterogeneity in habitat quality, thoroughly examine evolutionary patterns under the inertial development scenario from 2030 to 2050, and propose spatial optimization strategies. There are four key findings. First, from 2000 to 2020, agricultural land and forest were Harbin City’s two most prevalent land use types. The most notable transition occurred from forest to grassland, and the expansion of construction land primarily resulted from its encroachment into agricultural areas. Second, within the area of study, the landscape heterogeneity increased while simultaneously experiencing a decrease in connectivity, and the landscape had a tendency toward a more fragmented spatial distribution. Third, overall habitat quality rose between 2000 and 2020 but declined between 2030 and 2050. There was a “weak in the west and high in the east” distribution pattern in the spatial heterogeneity of habitat quality. Fourth, population density has the most impact on habitat quality, with the NDVI and GDP close behind. Conversely, precipitation and slope had comparatively smaller influences on habitat quality. Natural factors combined had a primarily favorable influence on habitat quality across the research region in terms of spatial distribution. Conversely, population density had a discernibly detrimental impact. Given these findings, this study suggests targeted strategies to optimize habitat quality. These recommendations are relevant not only for biodiversity conservation but also for the development of an ecologically sustainable community, particularly in a cold climate region.
... During the study period, different land use types demonstrated a complex two-way conversion between them. Influenced by the reform and opening-up policy and the policy of revitalizing the old industrial bases in Northeast China, urbanization and industrialization have continued to advance, and the area of land used for construction in Northeast China has expanded rapidly [60,61]. The FP displayed a geographic distribution pattern of "high in the west and low in the east" in the years 2000, 2010, and 2020, but the other ESs displayed a pattern of "low in the west and high in the east." ...
Land use intensity (LUI) is an important indicator for assessing human activities, and quantitatively studying the impact of LUI on ESs can help to realize the scientific management of urban ecosystems as well as sustainable development. In this study, we quantified five important ecosystem service bundles in the study area with the aid of the R-language “kohonen” package and used bivariate spatial autocorrelation modeling to examine the effects of LUI on the ESs in Harbin City from 2000 to 2020. These ESs include food supply (FP), water conservation (WC), soil conservation (SC), carbon storage (CS), water purification (WP), and habitat quality (HQ). The results show the following: (1) The LUI in Harbin City had a trend from 2000 to 2020 of “decreasing and then growing”, with a spatial distribution pattern of “high in the west and low in the east.” (2) Except for FP, all other ESs exhibit a similar spatial pattern of “west-low-east-high”; WC and WP exhibit a trend of continuous increase, SC exhibits a trend of decreasing and then increasing, and CS and HQ are generally more stable, with less fluctuation. The built-up area is situated in the high-value area of LUI, and the area exhibits a significant expansion trend. (3) Ecological conservation bundles, FP–WP synergistic bundles, ecological transition bundles, CS–WP–HQ synergistic bundles, and FP bundles are the five ecosystem service bundles that were discovered in Harbin. (4) From 2000 to 2020, there is a predominately “low LUI-high ESs” and “high LUI-low ESs” aggregation type, with a substantial positive correlation between LUI and FP and a significant negative correlation between LUI and other ESs. Harbin City should strengthen the management of ESs in the western part of the city and, at the same time, maintain the favorable ecological conditions in the ecological barriers of Zhangguangcai Range and Xiaoxing’an Mountains.
... Since 1992, China's population surge, the support of agricultural policies, and the denationalisation of Russian agriculture after the disintegration of the Soviet Union have led to the continuous expansion of croplands (Kuosmanen et al., 2016;Mao et al., 2018Mao et al., , 2019. Reform and opening-up policies and the revitalisation of the old industrial base of Northeast China policy have continuously stimulated urbanisation and industrialisation, thus leading to the rapid expansion of construction land in Northeast China (Shen et al., 2020;Zhou et al., 2021). Due to the lack of a coordinated forest policy and uncertainty in legal regulations governing forestry practices, forests in Russia continued to decline, posing serious challenges to forest conservation (Newell and Simeone, 2014;Proskurina et al., 2018). ...
Understanding the spatiotemporal characteristics of land use, ecosystem services, and their relationship provides a basis for the sustainable development of ecosystems. However, the effect of land use change on multiple ecosystem services has not been widely quantified, especially in transnational areas. This study analysed the spatiotemporal characteristics of land use change in the China–Mongolia–Russia Economic Corridor using the ESA-Global Land Cover product from 1992 to 2019. We used the InVEST model to evaluate the changes in carbon storage, habitat quality, water yield, and soil retention and quantified the contribution of land use to the changes in ecosystem services by calculating the ecosystem service contribution index (ESCI). The results showed that from 1992 to 2019, the urban/built-up environment and croplands increased by 22,010 km² and 32,946 km², respectively, which led to the continuous decline of forests. The implementation of ecological projects significantly decreased the barren environment. The value of four ecosystem services gradually decreased depending on the distance from the coastline and improved overall from 1992 to 2019. Land use conversion significantly affected ecosystem services. The expansion of croplands, urbanisation, and desertification had a significant negative impact on ecosystem services and the conversion to grasslands. Forests had a significant positive impact on ecosystem services. The findings will enrich our understanding of ecosystem services in transnational areas and help balance the relationship between ecological conservation and social-economic development in the China-Mongolia-Russia Economic Corridor.
... Recently, video surveillance camera has been widely used outdoors and indoors for security reasons in many fields: industry, medicine, education and so forth, and the cameraproduced video needs to be processed outside the circuit to handle it [20]. Most of images need to reduce noise, which is considered as preprocessing stage to prepare for extracting useful data from it; many algorithms for noise reduction were suggested in literature [21] and used to prepare the image without contribution. ...
This paper presents a new method to recognize human activities based on weighted classification for the features extracted by human body. Towards this end, new features depend on weight taken from image or video used in proposed descriptor. Human pose plays an important role in extracted features; then these features are used as the weight input with classifier. We use machine learning during two steps of training and testing images of standard dataset that can be used during benchmarking the system. Unlike previous methods that need size or length of shapes mainly to represent the cues when machine learning is used to recognize human activities, accurate experimental results coming from appropriate segments of the human body proved the worthiness of proposed method. Twelve activities are used in challenging of availability comparison with dataset to demonstrate our method. The results show that we achieved 87.3% in training set, while in testing set, we achieved 94% in terms of precision.
At present, China is transforming into a green development mode in all respects, and improving green energy efficiency is a key component of this transformation. Using panel data of 2011–2018, this research adopts the Super-SBM (Slack-Based Model) to calculate the green energy efficiencies of China’s 29 provinces and a GML (Global Malmquist-Luenberger) index method to explain the efficiency changes. Empirical analysis draws the following conclusions: 1) China’s green energy efficiency presented a slowly decreasing rather than increasing trend. 2) Technological progress was a major factor in efficiency improvement. However, its contribution was canceled by energy overuse. 3) Provinces with low green energy efficiency tend to geographically gather in the regions with rich energy resource endowment. Instead, provinces with high green energy efficiency are relatively geographically scattered, and most of them are China’s most developed regions. 4) Green energy efficiencies among China’s four major regions have significant differences. Generally, the mean level is east > northeast > west > central. 5) The key policy directions to improve China’s green energy efficiency include using transfer payment to balance the regional development, breaking down the barriers among provinces to facilitate energy circulation, and refining energy price structure to mitigate rebound effects.
