In recent years, remote sensing target recognition algorithms based on deep learning technology have gradually become mainstream in the field of remote sensing because of the great improvements that have been made in the accuracy of image target recognition through the use of deep learning. In the research of remote sensing image target recognition based on deep learning, an insufficient number of research samples is often an encountered issue; too small a number of research samples will cause the phenomenon of an overfitting of the model. To solve this problem, data augmentation techniques have also been developed along with the popularity of deep learning, and many methods have been proposed. However, to date, there is no literature aimed at expounding and summarizing the current state of the research applied to data augmentation for remote sensing object recognition, which is the purpose of this article. First, based on the essential principles of data augmentation methods, the existing methods are divided into two categories: data-based data augmentation methods and network-based data augmentation methods. Second, this paper subdivides and compares each method category to show the advantages, disadvantages, and characteristics of each method. Finally, this paper discusses the limitations of the existing methods and points out future research directions for data augmentation methods.

In the 1980s, China began to recognize the gravity of the problem of non-point agricultural source pollution and conduct research on it. Agricultural non-point source pollution in China, on the other hand, differs from foreign agricultural non-point source pollution and industrial point source pollution. Because the features of agricultural non-point source pollution are complicated, it is critical to investigate a whole-chain management policy system appropriate for China’s agricultural pattern. Based on the current situation of agricultural non-point source pollution in China, this study summarizes the four stages of agricultural non-point source pollution prevention and control policies, namely the discovery stage with macro policies as the main focus, the exploration stage with single research indicators, the initial systematic strengthening stage, and the focused stage with targeted characteristics. Simultaneously, it examined the technological approaches that are suitable for China’s national circumstances and have been investigated by relying on international experience in present-day Chinese management. However, there are still some problems and challenges in agricultural non-point source pollution management policies, such as a lack of non-point source information support, a lack of coordination between different departments, a lack of support in measurement and retroactive calculation and treatment, a lack of an in-depth concept of zoning and classification, a lack of policy, an institutional system, and insufficient capital investment. Based on these problems and combining them with Green Agriculture, Beautiful China, and other goals, this paper puts forward suggestions to strengthen the policy data support of the agricultural non-point source pollution management system, enhance the research and development of the law of pollutant migration and transformation, encourage the innovation of low-cost and high-benefit treatment technology, improve the construction of the management system, strengthen the collaboration of departments, increase the investment of funds, and make other suggestions so as to promote the treatment of agricultural non-point source pollution with high quality and efficiency.

The construction of transport facilities plays a pivotal role in enhancing people’s living standards, stimulating economic growth, maintaining social stability and bolstering national security. During the construction of transport facilities, it is essential to identify the distinctive features of a construction area to anticipate the construction process and evaluate the potential risks associated with the project. This paper presents a multi-objective semantic segmentation algorithm based on an improved U-Net network, which can improve the recognition efficiency of various types of features in the construction zone of transportation facilities. The main contributions of this paper are as follows: A multi-class target sample dataset based on UAV remote sensing and construction areas is established. A new virtual data augmentation method based on semantic segmentation of transport facility construction areas is proposed. A semantic segmentation model for the construction regions based on data augmentation and transfer learning is developed and future research directions are given. The results of the study show that the validity of the virtual data augmentation approach has been verified; the semantic segmentation of the transport facility model can semantically segment a wide range of target features. The highest semantic segmentation accuracy of the feature type was 97.56%.

Coordination between ecological security and economic development is crucial to sustainable development, with a development strategy that should be adjusted according to the type of region. Yunnan Province, China, is a treasure trove of biodiversity but is economically lagging. Clarifying the relationship between ecological security and economic development can provide a reference for the sustainable development of similar biodiversity hotspots in the world. The landscape index method and index evaluation method were used to calculate the ecological safety index (ESI) and the economic development index (EDI), respectively, and the median value of the indices was used for the comprehensive zoning. The coupled coordination degree model (CCDM) was used to assess the coordination status of ecological safety and economic development in each zone. The results show that (1) Yunnan’s ecological security pattern is high in the west and low in the east, mainly influenced by topography, climate, and human activities; its economic development is resource-dependent and shows a multi-point dispersed pattern due to poor transportation; (2) Yunnan was partitioned into the Coordinated Development Zone (CDZ), the Ecological Risk Zone (ERZ), the Economic Poverty Zone (EPZ), and the Dual Pressure Zone (DPZ). Among them, CDZs (15%) are mostly areas with outstanding advantageous resources, mature characteristic industries, and relatively spatially dispersed. There are two types of ERZs (35%): one is an area where the intensity of human activities exceeds the ecological carrying capacity, mainly located in the eastern plateau; the other is an area with fragile ecological background conditions, located in high mountains and river valleys. EPZs (35%) are mainly lagging in socioeconomics of DPZ (15%) and the fragile ecological environment constrains each to form a negative cycle. (3) Of the regional coordination levels in Yunnan Province, 76% are moderately coordinated, and there is still space for development from the high-quality coordination level. The order of the average coordination degree of each partition is CDZ > ERZ > EPZ > DPZ. The poor basis for coordination and the single approach to coordination have led to ecological safety and economic development often being more difficult to achieve in areas with large mountainous areas similar to Yunnan. (4) Due to the necessity for biodiversity protection, Yunnan Province should choose the sustainable path of ecological priority and green development. Specifically, CDZ should play to industrial advantages and brand effects, and promote industrial integration and innovative industrial development paths. The keys to ERZ are industrial restructuring, industrial ecologization, and ecological environment restoration and protection. EPZ should improve transportation and other infrastructure and revitalize economic development under the premise of ecological priority. Finally, DPZ should emphasize human and load reduction, and moderate development.

Watershed ecological compensation, as an important means to protect the environment and promote the sustainable and coordinated development of upstream and downstream has wide concern in China. At present, the compensation accounting method only assesses water quality. When applied to some northern rivers represented by the Yongding River, which are facing water shortage, the assessment of water quality indicators alone cannot effectively compensate the ecosystem service providers for their expenditure on the environment. This paper proposes a transboundary water quality and quantity ecological compensation standard model, which couples the water quality ecological compensation standard of pollutant reduction and the water quantity ecological compensation standard based on the restoration cost method. We set up two scenarios using the model to calculate the amount of compensation payable under the actual scenario in 2018, which is USD 68.2 million. The amount of compensation under the local environmental policy target scenario is USD 10.6–82.668–529 million. It was concluded that the funds obtained from this model can cover the rehabilitation cost and meet the benefits of the upstream and downstream, making compensation funds more reasonable. However, based on the cross-sectional assessment, there is still a lack of integrity and comprehensiveness for the river basin. The development of watershed ecological compensation should move from the game of upstream and downstream interests to a win–win situation.