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The purpose of this paper is to analyze the characteristics of spatio-temporal dynamics and the evolution of land use change is essential for understanding and assessing the status and transition of ecosystems. Such analysis, when applied to Horqin sandy land, can also provide basic information for appropriate decision-making.

By integrating long time series Landsat imageries and geographic information system (GIS) technology, this paper explored the spatio-temporal dynamics and evolution-induced land use change of the largest sandy land in China from 1983 to 2016. Accurate and consistent land use information and land use change information was first extracted by using the maximum likelihood classifier and the post-classification change detection method, respectively. The spatio-temporal dynamics and evolution were then analyzed using three kinds of index models: the dynamic degree model to analyze the change of regional land resources, the dynamic change transfer matrix and flow direction rate to analyze the change direction, and the barycenter transfer model to analyze the spatial pattern of land use change.

The results indicated that land use in Horqin sandy land during the study period changed dramatically. Vegetation and sandy land showed fluctuating changes, cropland and construction land steadily increased, water body decreased continuously, and the spatial distribution patterns of land use were generally unbalanced. Vegetation, sandy land and cropland were transferred frequently. The amount of vegetation loss was the largest. Water body loss was 473.6 km², which accounted for 41.7 per cent of the total water body. The loss amount of construction land was only 1.0 km². Considerable differences were noted in the rate of gravity center migration among the land use types in different periods, and the overall rate of construction land migration was the smallest. Moreover, the gravity center migration rates of the water body and sandy land were relatively high and were related to the fragile ecological environment of Horqin sandy land.

The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and GIS technology but also revealed notable spatio-temporal dynamics and evolution-induced land use change throughout the different time periods (1983-1990, 1990-2000, 2000-2010, 2010-2014, 2014-2016 and 1983-2016).

The purpose of this paper is to illustrate the benefits of reintroducing traditional grazing systems practices for improving arid rangelands. Grazing is the most extensive land use in southern Tunisia, but the rangelands have suffered many decades of severe degradation due to profound socioeconomic changes and the emergence of an agro-pastoral society in place of the former pastoral one. Traditional grazing systems (gdel and herd mobility), which had historically allowed for grazing deferment and control of grazing livestock were abandoned. Yet grazing management strategies are important tools to sustain integrated livestock rangeland production systems in dry areas in the face of ongoing climate change and human pressure.

This study assesses the revival of traditional best practices of rangeland resting in a representative community. Total plant cover, species composition, flora richness and range production were determined in six rangeland sites subjected respectively to one, two and three years of rest; one and two years of light grazing after rest; and free grazing (control).

Results showed that dry rangelands keep their resilience to the negative effects of climate change once human pressure is controlled. A maximum of two years of rest is enough to sustainably manage the rangelands in southern Tunisia, as this protection showed considerable and positive effects on the parameters scored.

The revival of the traditional best practices under new arrangements adapted to current biophysical and socioeconomic conditions would be an excellent tool to mitigate the negative effects of frequent droughts and reduce the animal feed costs that poor farmers face.

This study aims to investigate the most effective approach for governments and enterprises to combat desertification by considering the governance cycle. The focus is on understanding how the government can incentivize enterprises to actively engage in desertification combat efforts.

Both the government and the enterprise are treated as rational entities, making strategic choices for joint participation in combating desertification. Recognizing the dynamic nature of the desertification combat area, differential game models are employed to identify the optimal mode for combating desertification.

The findings underscore the significant influence of the governance cycle duration on the selection of desertification combat modes for government and enterprise. A cooperative mode is best suited to a short governance cycle, while an ecological subsidy mode is optimal for a longer cycle. Enhancing governance technology and shortening the governance cycle are conducive to combating desertification. Reducing taxes alone may not be an effective control strategy; rather, the government can better motivate enterprises by adopting tax rate policies aligned with the chosen governance mode.

This research contributes by elucidating the impact mechanism of the government cycle’s length on the desertification combat process. The results may offer valuable insights for governments in formulating strategies to encourage corporate participation in combating desertification and provide theoretical support for selecting optimal desertification combat modes.

Geographical conditions monitoring (GCM) has elicited significant concerns from the Chinese Government and is closely related to the “Digital China” program. This research aims to focus on object-based change detection (OBCD) methods integrating very-high-resolution (VHR) imagery and vector data for GCM.

The main content of this paper is as follows: a multi-resolution segmentation (MRS) algorithm is proposed for obtaining homogeneous and contiguous image objects in two phases; a post-classification comparison (PCC) method based on the nearest neighbor algorithm and an image-object analysis (IOA) technique based on a differential entropy algorithm are used to improve the accuracy of the change detection; and a vector object-based accuracy assessment method is proposed.

Results show that image objects obtained using the MRS algorithm attain the objectives of the “same spectrum within classes” and “different spectrum among classes”. Moreover, the two OBCD methods can detect over 85 per cent of the changed regions. The PCC strategy can obtain the categories of image objects with a high degree of precision. The IOA technique is easy to use and largely automated.

On the basis of the VHR satellite imagery and vector data, the above methods can effectively and accurately provide technical support for GCM implementation.

There is a recent growing interest to find a lasting intervention to rural poverty (RP) in developing countries based on farmer entrepreneurship and innovation. The purpose of this paper, therefore, is to examine the relation between entrepreneurship and RP alleviation in two resource-constrained provinces of China. This paper assesses the influence of three capabilities of farm entrepreneurs – educational, economic and socio-cultural – on farmer entrepreneurship growth and how these, in turn, impact alleviation of RP.

Household survey data comprising 363 respondents were taken from four deprived communities in two provinces of China. The paper employed structural equation modeling (SEM), using AMOS 21.0 alongside SPSS 20.0 to test the relations between the constructs.

The results show that a statistically significant and positive relation exists between entrepreneurship and RP alleviation in China. The findings of the study further reveal that qualitative growth of entrepreneurship has a stronger positive influence on RP alleviation than on quantitative growth, and socio-cultural capabilities of respondents significantly and positively affect entrepreneurial growth of farmers, rather than education and economic capabilities.

The use of data from four communities in two provinces tends to limit the ability to generalize the findings of the study. Furthermore, the survey did not collect information on non-farm entrepreneurs, making it impossible to compare the findings from farm entrepreneurs with non-farm entrepreneurs.

The findings have practical implications for policy makers in rural China toward addressing targeted RP. This paper, therefore, suggests that entrepreneurship should be pursued vigorously among farmers in rural areas of China to help solve poverty. The paper also presents a useful lesson for various stakeholders in poverty alleviation programs in other developing countries.

This paper contributes to the academic literature on the entrepreneurship–RP alleviation nexus by combining the theory of capability and SEM in the analysis of an emerging economy such as China.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.