The rectangular tile classification model based on Sentinel integrated images enhances grassland mapping accuracy: A case study in Ordos, China.

Arid zone grassland is a crucial component of terrestrial ecosystems and plays a significant role in ecosystem protection and soil erosion prevention. However, accurately mapping grassland spatial information in arid zones presents a great challenge. The accuracy of remote sensing grassland mapping in arid zones is affected by spectral variability caused by the highly diverse landscapes. In this study, we explored the potential of a rectangular tile classification model, constructed using the random forest algorithm and integrated images from Sentinel-1A (synthetic aperture radar imagery) and Sentinel-2 (optical imagery), to enhance the accuracy of grassland mapping in the semiarid to arid regions of Ordos, China. Monthly Sentinel-1A median value images were synthesised, and four MODIS vegetation index mean value curves (NDVI, MSAVI, NDWI and NDBI) were used to determine the optimal synthesis time window for Sentinel-2 images. Seven experimental groups, including 14 experimental schemes based on the rectangular tile classification model and the traditional global classification model, were designed. By applying the rectangular tile classification model and Sentinel-integrated images, we successfully identified and extracted grasslands. The results showed the integration of vegetation index features and texture features improved the accuracy of grassland mapping. The overall accuracy of the Sentinel-integrated images from EXP7-2 was 88.23%, which was higher than the accuracy of the single sensor Sentinel-1A (53.52%) in EXP2-2 and Sentinel-2 (86.53%) in EXP5-2. In all seven experimental groups, the rectangular tile classification model was found to improve overall accuracy (OA) by 1.20% to 13.99% compared to the traditional global classification model. This paper presents novel perspectives and guidance for improving the accuracy of remote sensing mapping for land cover classification in arid zones with highly diverse landscapes. The study presents a flexible and scalable model within the Google Earth Engine framework, which can be readily customized and implemented in various geographical locations and time periods.

Spatio-Temporal Characteristics of Trade-Offs and Synergies in Ecosystem Services at Watershed and Landscape Scales: A Case Analysis of the Yellow River Basin (Henan Section).

The changes and interrelationships of ecosystem services at different global and regional scales have been actively investigated. Clarifying the trade-offs and synergies between ecosystem services from a multi-scale scientific perspective is vital to improve the coordinated and sustainable development of the watershed and ecological protection. As an important ecological barrier region of the Yellow River Basin, the Henan section provides a variety of important ecosystem services. This study analyzes the characteristics of land use changes in the Yellow River Basin (Henan section) from 1990 to 2020. Based on the InVEST model, four ecosystem services-water production, soil conservation, carbon storage and food supply have been evaluated. The Spearman correlation coefficient was used to further reveal the spatial and temporal characteristics of the trade-offs and synergies at different levels of each service. The results showed that: (1) From 1990 to 2020, the basin was dominated by farmland conservation. The construction land area mainly exhibited an inflow behavior, while other land use types were mainly related to outflow. (2) From 1990 to 2020, the water yield, soil conservation and carbon storage first increased and then decreased, while food supply gradually increased. The spatial distribution of these ecosystem services was lower in the southwest and slightly higher in the northeast and farmland had the highest capacity of water production and food supply, while woodland had the highest capacity for soil conservation and carbon storage. (3) The Spearman rank correlation coefficient indicated that the trade-offs for the ecosystem services in the Yellow River Basin (Henan section) dominated before 2000, and the synergies gradually strengthened after 2000. (4) There were clear spatial heterogeneities in the ecosystem services of the basin; for instance, the functions in the middle and lower reaches of the Yellow River Basin (Henan section) were mainly trade-offs, while the higher elevations in the middle reaches exhibited synergistic relationships. This study aims to clarify the trade-offs and synergies between ecosystem services at the different levels. Based on our findings, countermeasures and suggestions for ecological protection and management are proposed to promote the coordinated development of social economy and ecological protection.

Estimation of Ecosystem Services Value at a Basin Scale Based on Modified Equivalent Coefficient: A Case Study of the Yellow River Basin (Henan Section), China.

The value of ecosystem services is an extremely important parameter that reflects regional ecological benefits and resources. Estimating the value of ecosystem services is essential for regional land-use optimization, ecological construction, and biodiversity protection. In this study, Landsat-TM/ETM remote sensing images were used to analyze land-use data in 1990, 2000, 2010, and 2020 of the Yellow River Basin (Henan section), China, defined by natural boundaries. An equivalent factor method was used to construct a model to calculate the ecosystem services value that introduced grain yield, regional difference coefficient, and social development stage coefficient. Thus, land-use changes and evolution of ecosystem services values in the Yellow River Basin (Henan section) in the past 30 years were analyzed. Land use in the basin changed significantly from 1990 to 2020. Except for an increase in area of construction land, areas of other land-use types decreased. Cultivated land area first increased and then decreased, whereas the water area first decreased and then increased. The total value of ecosystem services in the study area fluctuated but increased overall by 43.82 × 108 USD in the past 30 years. Spatially, the total value of ecosystem services was high in the southwest and low in the northeast. Among individual ecosystem service values, water conservation, gas regulation, and climate regulation accounted for a relatively high proportion of the total value. Regulation services were the main ecosystem service functions, followed by support and supply services, with cultural services accounting for the lowest proportion. Sensitivity coefficients of different land types in different periods were all less than one. Therefore, the value coefficients were reasonable, and the results were consistent with the actual situation of the study area. The study improves the method to estimate the ecosystem services value of the basin and also indicates ways to support ecological protection of the Yellow River Basin (Henan section), China.

Evaluation of NPP using three models compared with MODIS-NPP data over China.

Estimating net primary productivity (NPP) is significant in global climate change research and carbon cycle. However, there are many uncertainties in different NPP modeling results and the process of NPP is challenging to model on the absence of data. In this study, we used meteorological data as input to simulate vegetation NPP through climate-based model, synthetic model and CASA model. Then, the results from three models were compared with MODIS NPP and observed data over China from 2000 to 2015. The statistics evaluation metrics (Relative Bias (RB), Pearson linear Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE)) between simulated NPP and MODIS NPP were calculated. The results implied that the CASA-model performed better than the other two models in terms of RB, RMSE, NSE and CC whether on the national or the regional scale. It has a higher CC with 0.51 and a smaller RMSE with 111.96 g C·m-2·yr-1 in the whole country. The synthetic model and CASA-model has the same advantages at some regions, and there are lower RMSE in Southern China (86.35 g C·m-2·yr-1), Xinjiang (85.53 g C·m-2·yr-1) and Qinghai-Tibet Plateau (93.22 g C·m-2·yr-1). The climate-based model has widespread overestimation and large systematic errors, along with worse performances (NSEmax = 0.45) and other metric indexes unsatisfactory, especially Qinghai-Tibet Plateau with relatively lower accuracy because of the unavailable observation data. Overall, the CASA-model is much more ideal for estimating NPP all over China in the absence of data. This study provides a comprehensive intercomparison of different NPP-simulated models and can provide powerful help for researchers to select the appropriate NPP evaluation model.

Carbon Storage Change Analysis and Emission Reduction Suggestions under Land Use Transition: A Case Study of Henan Province, China.

The significant spatial heterogeneity among river basin ecosystems makes it difficult for local governments to carry out comprehensive governance for different river basins in a special administrative region spanning multi-river basins. However, there are few studies on the construction of a comprehensive governance mechanism for multi-river basins at the provincial level. To fill this gap, this paper took Henan Province of China, which straddles four river basins, as the study region. The chord diagram, overlay analysis, and carbon emission models were applied to the remote sensing data of land use to analyze the temporal and spatial patterns of carbon storage caused by land-use changes in Henan Province from 1990 to 2018 to reflect the heterogeneity of the contribution of the four basins to human activities and economic development. The results revealed that food security land in the four basins decreased, while production and living land increased. Ecological conservation land was increased over time in the Yangtze River Basin. In addition, the conversion from food security land to production and living land was the common characteristic for the four basins. Carbon emission in Henan increased from 134.46 million tons in 1990 to 553.58 million tons in 2018, while its carbon absorption was relatively stable (1.67-1.69 million tons between 1990 and 2018). The carbon emitted in the Huai River Basin was the main contributor to Henan Province's total carbon emission. The carbon absorption in Yellow River Basin and Yangtze River Basin had an obvious spatial agglomeration effect. Finally, considering the current need of land spatial planning in China and the goal of carbon neutrality by 2060 set by the Chinese government, we suggested that carbon sequestration capacity should be further strengthened in Yellow River Basin and Yangtze River Basin based on their respective ecological resource advantages. For future development in Hai River Basin and Huai River Basin, coordinating the spatial allocation of urban scale and urban green space to build an ecological city is a key direction to embark upon.

Factors affecting farmers' behaviour in pesticide use: Insights from a field study in northern China.

Quantitative understanding of farmers' behaviour in pesticide use is critical to enhance sustainability of chemical pest control and protect farmers' health and the environment. However, reports on the levels of knowledge and awareness of farmers and the practices of pesticide use are often insufficient. Here, we conducted a comprehensive analysis on the effects of knowledge and awareness of farmers as well as the influence of the associated stakeholders (i.e. pesticide retailers and the government) on farmers' behaviour in pesticide use by using a detailed survey of 307 agricultural households (79 grain farms, 65 fruit farms, 53 vegetable farms and 110 mixed-crop farms) in the Wei River basin in northern China. Eight protective behaviours (PBs) were exhibited by farmers. Careful and safe storage of pesticides, changing clothes or showering after applying pesticides, and reading instructions of the container labels before application were the most frequent PBs. Vegetable and fruit farmers had higher levels of education and knowledge than grain farmers, but the former were less willing to reduce pesticide use because of fear of low profits and lack of trust in the government and pesticide retailers. The PBs of farmers were strongly affected by the perception of the consequences of their behaviour (standardised path coefficient, SPC=0.42) and the level of farmers' knowledge (SPC=0.33). Pesticide retailers and the government had a moderate and weak influence, respectively, on farmers' PBs, suggesting a large gap of trust among farmers, pesticide retailers, and the government. Training and supervising retailers, educating farmers, and improving information transparency across farmers, pesticide retailers and the staff of the Agricultural Extension and Technology Service are recommended for bridging the gap of trust between farmers and the associated stakeholders as well as for promoting the use of PBs among farmers.