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Accurately assessing and predicting the impacts of land use changes on ecosystem carbon stocks in the Yellow River Basin (YRB) and exploring the optimization of land use structure to increase ecosystem carbon stocks are of great practical significance for China to achieve the goal of "double carbon". In this study, we used multi-year remote sensing data, meteorological data and statistical data to measure the ecosystem carbon stock in the YRB from 2000 to 2020 based on the InVEST model, and then simulated and measured the ecosystem carbon stock under four different land use scenarios coupled with the FLUS model in 2030. The results show that, from 2000 to 2020, urban expansion in the YRB continued, but woodland and grassland grew more slowly. Carbon stock showed an increasing trend during the first 20 years, with an overall increase of 7.2 megatons, or 0.23%. Simulating the four land use scenarios in 2030, carbon stock will decrease the most under the cropland protection scenario, with a decrease of 17.7 megatons compared with 2020. However, carbon stock increases the most under the ecological protection scenario, with a maximum increase of 9.1 megatons. Furthermore, distinct trends in carbon storage were observed across different regions, with significant increases in the upstream under the natural development scenario, in the midstream under the ecological protection scenario and in the downstream under the cropland protection scenario. We suggest that the upstream should maintain the existing development mode, with ecological protection prioritized in the middle reaches and farmland protection prioritized in the lower reaches. This study provides a scientific basis for the carbon balance, land use structure adjustment and land management decision-making in the YRB. [ABSTRACT FROM AUTHOR]

This paper firstly investigated the land-use and land-cover change (LUCC) in the Hun-Taizi River watershed, Northeast China from 1988 to 2004 based on remotely sensed images and geographic information systems (GIS) technology. Then, using the famous land-use change model of Conversion of Land Use and its Effects at Small regional extent (CLUE-S), this paper simulated the land use changes under historical trend (HT), urban planning (UP) and ecological protection (EP) scenarios considering urban planning and ecological protection over the next 20 years. The simulated results under UP scenario in 2020 were compared with the planning map to assess the feasibility of using land-use change model to guide regional planning. Results show that forest land, dry farmland, paddy, and shrub land were the main land-use categories. Paddy and dry farmland being converted to urban area and rural settlement characterized the land-use change from 1988 to 2004. The main land-use categories changed over time. Landscape-pattern fragmentation will be worse under HT and UP scenarios, but better in EP scenario. The comparing results of simulated map with planning map in 2020 show that land-use change model is powerful tool to guide regional planning. Land-use scenarios can support regional planning and policy-making through analyzing future consequences scientifically. [ABSTRACT FROM AUTHOR]

Land cover and land use data are important for watershed assessment and runoff modeling. Satellite and airborne remote sensors can map land cover/use effectively. Whenever a strong linkage exists between land cover/use and runoff water quality, remotely sensed land cover trends can help predict long-term changes in water and habitat quality of downstream estuaries and bays. This paper reviews practical remote sensing techniques for land cover change monitoring and presents a case study that relates land cover/use, landscape patterns, and temporal scales to the water quality of runoff from a coastal watershed in SE China. The results of the case study show that the percentage of built-up land was a good predictor for downstream water quality and that the linkage among NH4+ -N, CODMnand landscape variables during wet precipitation years was stronger than during dry precipitation years. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the impacts of land-use/cover changes (LUCC) on sediment loads at the outlets office sub-watersheds of the Poyang Lake watershed by integrating remote sensing and GIS with statistical analysis. The intensively formed watershed is characterized by a mountainous and hilly topography and a rainy climate. The primary goal of this paper is to help a better understanding of land-use/cover change and its driving forces. We discuss spatio-temporal variations in rainfall and sediment loads and identify factors contributing to those variations, analyze the comprehensive impacts of land-use/cover change on changing climate and human activities, and conclude that the changing rates of forest cover and climate regimes are primary factors for sediment discharges in the Poyang Lake watershed. Our results suggest that the eco-system still have large capacities to support human activities in the area. [ABSTRACT FROM AUTHOR]

Due to the combined effects of the natural environment, climate change and human activities, profound changes have occurred in terms of the eco-environmental effects of land use/cover change (LUCC) in the Baiyangdian basin. Therefore, based on land remote sensing monitoring data from 2000 to 2020, the Eco-environmental Quality Index (EQI) was introduced in this study to measure the eco-environmental effects of land use change in the Baiyangdian basin. Subsequently, the GeoDetector model was applied to detect the formation mechanism of the eco-environmental effects in the Baiyangdian basin from 2000 to 2020. The results of the study showed that cropland, woodland and grassland were the most widely distributed land use types in the Baiyangdian basin. The area of cropland declined the most and was mostly converted to construction land. The EQI increased slightly during the study period. The eco-environment of the mountainous areas in the western part of the basin and in Baiyangdian Lake was better than that of other areas. Land use intensity had a significantly stronger influence on the quality of the eco-environment than other factors. The interaction between the influencing factors was mainly a non-linear enhancement and a two-factor enhancement, with non-linear enhancement dominating. [ABSTRACT FROM AUTHOR]

Abstract: The effect of roads on forests is ambiguous. Many studies conclude that building and upgrading roads increases pressure on forests but some find that new and better roads may reduce the rate of deforestation. In this paper we use satellite remote sensing images of forest cover in Jiangxi Province, China, to test whether the existence and the size of roads (ranging from expressways to tertiary roads) in 1995 affected the level of forest cover in 2000 or the rate of change between 1995 and 2000. To account for road access for each of our 1km2 (“pixel”) units of forest cover we measure whether or not and what type of roads penetrate the “watershed” in which the pixel lies. These watersheds allow more plausible measures of accessibility than do traditional “crowfly” distance measures that ignore topography. To account for possible confounding we also use 12 additional covariates: geographic and climatic variables (e.g., elevation, slope, rainfall, temperature, soil properties); demographic and economic variables (e.g., local population and GDP per square kilometer); and distance variables (e.g., distance to the nearest provincial capital). Although simple univariate OLS regressions show that forest levels are lower and deforestation rates higher either when there is a road, or when there is a higher quality road, these results are not robust. Controlling for all of the covariates and also using recently developed covariate matching techniques to estimate treatment effects, we find that roads in China’s Jiangxi Province can most safely be described as having no impact on the level of forests and no impact on the rate of deforestation. [ABSTRACT FROM AUTHOR]

Abstract: Rapid land use change has taken place in many arid and semi-arid regions of China over the past decade, such as in Yellow River Basin. In this paper, changes in the land use pattern of the Yellow River Basin were analyzed using Landsat TM data in 1990, 1995 and 2000. The aim was to improve the understanding of changes in land use with a view to identifying potentially more sustainable systems of land use. Firstly, the mathematical methodology was explored and developed for spatial pattern changes of land use, which include the degree index model of land use dynamic, index model of land use degree, mean center model of land use and transformation model of land use. Based on these models, the changing spatial patterns of land use were calculated and analyzed. During the period 1990–2000, the areas of cropland, built-up land and unused land all increased, the area of cropland increased dramatically by 2917km2, while the areas of grassland and woodland decreased by 4668 and 33km2, respectively. Meanwhile, the spatial pattern of land use also experienced a great change. Then the driving factors of land use change were investigated, the governmental policies on eco-environmental protection, population growth and meteorological conditions were the major factors that caused the land use change in the past decade. [Copyright &y& Elsevier]

It is of great significance for the coordinated development of the environment and the economy to study the impact of the human driving factors of land use change (LUC) on ecosystem service value (ESV). In this study, we combined the biomass and remote sensing data of the Lijiang River Basin (LRB), which is a typical karst basin with a fragile ecological environment, to establish an ESV model to calculate the ESV. We also introduced the Lorenz curve and Gini coefficient to further analyze the impacts of the human driving factors of LUC on ESV. The results show that (1) the ESV in the LRB from 1995 to 2015 decreased from 8640.03 million yuan to 8595.38 million yuan, with a total decrease of 44.65 million yuan, indicating that the overall ESV in the region has a decreasing trend; (2) the obvious changes in land use caused a significant loss in ESV and changes in the structure of ecosystem services; and (3) the human driving factors of the total population, GDP, and urbanization rate are inversely related to the ESV in the LRB. [ABSTRACT FROM AUTHOR]

Understanding the relationship between land use and surface water quality is necessary for effective water management. We estimated the impacts of catchment-wide land use on water quality during the dry and rainy seasons in the Dongjiang River basin, using remote sensing, geographic information systems and multivariate statistical techniques. The results showed that the 83 sites can be divided into three groups representing different land use types: forest, agriculture and urban. Water quality parameters exhibited significant variations between the urban-dominated and forest-dominated sites. The proportion of forested land was positively associated with dissolved oxygen concentration but negatively associated with water temperature, electrical conductivity, permanganate index, total phosphorus, total nitrogen, ammonia nitrogen, nitrate nitrogen and chlorophyll-a. The proportion of urban land was strongly positively associated with total nitrogen and ammonia nitrogen concentrations. Forested and urban land use had stronger impacts on water quality in the dry season than in the rainy season. However, agricultural land use did not have a significant impact on water quality. Our study indicates that urban land use was the key factor affecting water quality change, and limiting point-source waste discharge in urban areas during the dry season would be critical for improving water quality in the study area. [ABSTRACT FROM AUTHOR]