Irrigated dryland in China, largely distributed and expanding in arid and semi-arid regions, always poses challenges to water resource and ecosystems, thus deeply impacts the implementation of SDG 2, 6, 15 and so on. Spatial-temporal patterns of irrigated dryland with high resolution help pinpoint hotspots and key issues worth to concern, however, are still lacking in research. This study developed a zonal-specific methodology to identify irrigated dryland and its changes from 2000 to 2015 at national scale with 30 m resolution. The whole China was divided into five zones based on cropping patterns. Key phases of remote sensing data and environmental factors were combined to generate zonal-specific methodologies for the identification of irrigated dryland. Meanwhile changes of features were employed to identify changes of irrigated dryland. Results show that the ratio of vegetation indices to environmental factors exhibits stronger stability in the classification of each zone. That being said, these of slope and texture varied from zone to zone. Moreover, using difference data between two periods for change information extraction demonstrated high accuracy. This method not only avoids the error accumulation caused by overlaying the direct classification results of two periods but also addresses the issue of insufficient classification accuracy due to the shortage of samples and data in historical periods. The average overall accuracy (the kappa coefficient) on generated maps of irrigated dryland in 2000 and 2015 are 88.28% (0.758) and 87.65% (0.744). The irrigated dryland had been increased by 8.84% from 2000 to 2015 and their distribution became denser and shifted towards north of China. With the advancement of economy and technology, the influence of human factors on the distribution of irrigated drylands has gradually intensified. The stable development of irrigated drylands ensures China’s food security and contributes to global food security. Meanwhile, it poses significant challenges to water resources and the ecological environment. This research developed methodologies to obtain accurate irrigated dryland data and its change information, supporting to identify the interaction between SDG 2, SDG 6, and SDG 15, especially in arid and semi-arid regions with vulnerable ecosystem in the world.

In the rapidly urbanizing world, as one of the distinct anthropogenic alterations of global climate change, global warming has attracted rising concerns due to its negative effects on human well-being and biodiversity. However, existing studies mostly focused on the difference in temperature elevation among urbanized areas and non-urbanized areas, i.e., rural or suburban areas. The allometric urban warming at intra-urban scales was overlooked. This research aimed to expand our understanding of urbanization–temperature relationships by applying a concept of a “previous-new” dichotomy of urbanized areas. To quantify the land surface temperature (LST) dynamics of 340 cities in China, we analyzed the LST of different land use types through trend analysis and absolute change calculation models. The urban heat island (UHI) effect of two spatial units, i.e., newly expanded urbanized area (“new UA” hereinafter) during 2000–2015 and previously existing urbanized area (“previous UA” hereinafter) in 2000, were compared and discussed. Our findings reveal that urban growth in China coincided with an LST increase of approximately 0.68 °C across the entire administrative boundary, with higher increases observed in regions between the Yellow River and Yangtze River and lower increases in other areas. Moreover, the new UA exhibited significantly greater LST increases and urban heat island intensity (HUII) compared to the previous UA. The dynamics of LST corresponded to the speed and scale of urban growth, with cities experiencing higher growth rates and percentages exhibiting more pronounced LST increases. This study reveals the impact of the underlying surface on human settlements on a large scale.

Reclamation is an important cause of coastline changes,coastal wetland degradation,and offshore marine pollution.The control and management of reclamation are related to the protection of the national coastal zone and the construction of an ecological civilization.At present,high-frequency remote sensing monitoring of national-scale coastal reclamation types and their spatial distribution is lacking,and the tracking and monitoring of reclamation management measures based on remote sensing methods have not yet been effectively performed.By using the method of integrated remote sensing dynamic monitoring of the coastline and reclamation,and based on Landsat time-series satellite images,the spatial distributions of China's coastal reclamation in the periods of 2010-2015,2015-2018,and 2018-2020,and the spatial distributions of the measures of returning enclosures to the sea and wetland in the corresponding periods were extracted.The data outcomes were stored in the ArcGIS Shapefile format,and the compressed data volumes totaled 680 KB.The remote sensing dynamic monitoring of national-scale time-series coastal reclamation that is synchronized with the time of coastline change and shared the same satellite image basis is highly significant for the protection of coastline resources and the evaluation of the effect of coastal ecological and environmental management.The results showed that during the second decade of the 21st century,the area of newly coastal reclamation in China declined sharply and that the growth rate of coastal reclamation was effectively controlled.Meanwhile,the rate of measures for returning enclosures to the sea and wetland,which was mostly manifested as the restoration of aquaculture pits and ponds to mudflats and sea surfaces,was increased abruptly,particularly in 2018-2020.Achievements were directly related to the unprecedented strengthening of national policies for reclamation control and coastal zone protection in 2018.The remote sensing monitoring dataset of coastal reclamation dynamics can provide basic data guarantee for national ocean and coastal zone management and scientific research,and important support for the realization of Sustainable Development Goal 14.5.

作为人类活动的密集区,城镇用地的扩展对其他土地利用类型和周围环境都将产生重要影响.采用异速生长模型对Dinamica EGO模型的总量预测模块进行改进,在此基础上开展了多情景模拟下的中国城镇用地扩展预测.结果表明,相比2000—2015年,2015—2030年5种情景下中国城镇用地扩展面积降低了58.07％～64.17％,表明中国将要迈过城镇化速度峰值;中部和西部地区、中等城市的城镇用地扩展速率将加快,表明东中西部、大中小城市城镇发展的差距将会缩小,区域、城市协调发展战略效果显著;化石燃料为主的发展情景下,不同地区、不同规模城市的市均扩展面积差异较其他情景增大,表明该情景不但不利于气候变暖减缓,而且不利于区域协调发展.

Remote sensing images with different spatial resolutions have different performance capabilities for gully extraction, so it is very important to study the suitability of different spatial resolutions for this purpose. In this study, part of the black soil area in Northeast China with serious gully erosion was taken as the study area, and Google Earth images with seven spatial resolutions ranging from 0.51 to 32.64 m, commonly used in gully erosion research, were selected as data sources. Combined with auxiliary data, gullies were extracted by visual interpretation. The interpretation results of images of different spatial resolutions were analyzed qualitatively and quantitatively, and the interpretation suitability of images of different spatial resolutions for different types of gullies under different classification systems was emphatically explored. The results indicate that the image with a spatial resolution of 1.02 m has the best performance when not considering the types of gullies. However, the image with a spatial resolution of 2.04 m is the most cost-effective and, therefore, the most suitable for general research. When it is necessary to distinguish the type of gully, the image with a spatial resolution of 0.51 m can be adapted for all situations. However, research on ephemeral gullies is of little practical significance. Therefore, the image with a spatial resolution of 1.02 m is the most universally useful image, being cheaper and easier to obtain. When the spatial resolution is 2.04 m or lower, it is necessary to select the spatial resolution according to the gully type required for practical application. When the spatial resolution is 8.16 or lower, the interpretation of gullies becomes very difficult or even impossible.

Against the background of coordinated development of the Beijing–Tianjin–Hebei region (BTH), it is of great significance to quantitatively reveal spatiotemporal dynamics of urban expansion for optimizing the layout of urban land across regions. However, the urban expansion characteristics, types and trends, and spatial coevolution (including urban land, GDP, and population) have not been well investigated in the existing research studies. This study presents a new spatial measure that describes the difference of the main trend direction. In addition, we also introduce a new method to classify an urban expansion type based on other scholars. The results show the following: (1) The annual urban expansion area (UEA) in Beijing and Tianjin has been ahead of that in Hebei; the annual urban expansion rate (UER) gradually shifted from the highest in megacities to the highest in counties; the high–high clusters of the UEA presented an evolution from a “seesaw” pattern to a “dumbbell” pattern, while that of the UER moved first from Beijing to Tianjin and eventually to Hebei. (2) Double high speed for both UEA and UER was the main extension type; most cities presented a U-shaped trend. (3) Qinhuangdao has the largest difference between the main trend direction of spatial distribution of urban land, GDP and population; the spatial distribution of GDP is closer to that of urban land than population. (4) The area and proportion of land occupied by urban expansion varied greatly across districts/counties. BTH experienced dramatic urban expansion and has a profound impact on land use. These research results can provide a data basis and empirical reference for territorial spatial planning.

Based on Remote Sensing (RS) and Geographical Information System (GIS) technology, urban expansion of 75 cities in China from the 1970s to 2020 was reconstructed by visual-interpretation method, which described the growing process of urban lands and its influences on local land use structures synchronously. By employing annual expansion area per city and urban expansion density, spatial-temporal characteristics and macro patterns of urban expansion were analyzed from the aspects of regional-distributions, administrative-levels and population-sizes comprehensively. Results indicate that: 1) urban expansion in China was universal, distinct, persistent, periodic and fluctuating. In the past five decades, urban lands of 75 monitored cities in China expanded dramatically from 3606.26 km(2) to 30 521.13 km(2). 2) Though urban expansion presented significant differences from the aspects of regional distribution, administrative levels, and population sizes, it exhibited a deceleration trend in the 13th Five-Year Plan among all kinds of cities. 3) Cultivated lands were the first land resource for urban expansion, and 55.17% of newly-expanded urban lands appeared by encroaching this land use type. China's urban expansion has caused sustained pressure on cultivated land protection, especially in super megacities, and the contradiction between urban expansion and cultivated land protection will always exist. 4) The compactness of urban lands in China increased before 1987 and reduced in the next three decades, which was consistent with the implementation of major policies and the deployment of national strategies, and is expected to become compact with a stopping declining or even rebounding after the 13th Five-Year Plan.

There are, in general, two aspects of land use, which is the most direct human activity on terrestrial ecosystems: land-use type and land-use intensity. However, studies on land-use intensity, which lacks the adoption of established concept models, indicator systems, as well as unified method frameworks, significantly fall behind those on land-use type. With the increasing intensity of human disturbance in the terrestrial ecosystem, the concept of land-use intensity is, once again, garnering significant attention. Studies on land-use intensity can be summarized into three branches: 1) Those concerned with the estimation of human activity intensity based on population density; 2) those in which traditional methods of input and output intensity, the multiple crop index, τ-factor method, the technical efficiency method, etc. are used; 3) those in which the conceptual model of land-use intensity based on social-economic circulation mechanisms of materials and energy, represented by the HANPP index, is used. Combined with studies on the driving mechanism of land-use intensity, research trends on land-use intensity reveal that 1) the population density, which used to be taken as an indicator of land-use intensity, is gradually being replaced by the conceptual models of land-use intensity; 2) land-use intensity studies are shifting from indicator constructs to the distinction between human and natural factors, which is one of the key challenges associated with index comparisons between different natural environments; 3) remote sensing data and methods have immense potential in the study of the quantitative recognition of human activities; 4) the assessment mechanisms for land-use intensity are closely related to agricultural land and the utilization and protection mechanisms for grassland and forest ecosystems are not valued. The balanced development of the assessment mechanisms of land-use intensity and index technology systems is expected to become the inevitable future trends in land-use intensity studies.The most direct human activity on terrestrial ecosystem-land use-generally cover two aspects: land use type and land use intensity. However, the development of researches on land use intensity, which lacks mature concept model, indicator system, as well as the unified methods framework, seriously fall behind the researches on land use type. As human intensifying disturbance in the terrestrial ecosystem, the attentions of scientists to the concept of land use intensity were again aroused. The evolution of the study on the land use intensity could be summarized into three branches: 1) studies on human activity intensity calculations based on the population density; 2) land use intensity researches represented by traditional method of input and output intensity, and the multiple crop index, τ-factor method, the technical efficiency method, etc. 3) the conceptual model of land use intensity based on social-economic circulation mechanism of material and energy, represented by the HANPP index. Combined with researches on driving mechanism of land use intensity, the research trends on land use intensity shows that 1) the population density taken as an indicator of land use intensity is gradually replaced by the conceptual model of land use intensity; 2) the land use intensity researches incline from indicators constructs to the distinction between the human and natural factors, which is the key problems of index comparison between different natural environment; 3) remote sensing data and methods have huge potential in the study of quantitative recognition of human activities; 4) the assessment mechanism for land use intensity were closely related to the agricultural land, the utilization and protection mechanism for the grassland and forest ecosystems were not valued. Balanced development of assessment mechanism of land use intensity and index technology system become the inevitable trends in the future research of land use intensity.

The black soil region in Northeast China is an important production base of commodity grain. However, soil erosion is a major threat that has caused a decline in arable land area and productivity and a series of environmental problems in recent years. To understand the current situation of soil erosion and its changes in the whole black soil region, including six treatment regions, we used the spatial-temporal analysis of soil erosion from 2000 to 2015 and the overlay analysis with its drivers; additionally, soil erosion was evaluated qualitatively with the integrated evaluation method, and its change was indicated by the soil erosion change index (SECI). We found that soil erosion that caused soil loss occurred in each treatment region mainly at the light level in 2015. Water erosion, the most widely distributed erosion type, affected the largest area, while most serious erosion at intensive or higher levels stemmed from wind erosion. Although the situation of water erosion was improved in 2015 compared to that in 2000, the overall situation of soil erosion was worse due to the deterioration of wind and freeze-thaw erosion. Grassland, woodland, and cultivated land changes, such as the conversion from grassland to cultivated land, from woodland to sparse woodland and from dry land to paddy land, revealed these changes to a great extent.

Gully erosion is a widespread natural hazard. Gully mapping is critical to erosion monitoring and the control of degraded areas. The analysis of high-resolution remote sensing images (HRI) and terrain data mixed with developed object-based methods and field verification has been certified as a good solution for automatic gully mapping. Considering the availability of data, we used only open-source optical images (Google Earth images) to identify gully erosion through image feature modeling based on OBIA (Object-Based Image Analysis) in this paper. A two-end extrusion method using the optimal machine learning algorithm (Light Gradient Boosting Machine (LightGBM)) and eCognition software was applied for the automatic extraction of gullies at a regional scale in the black soil region of Northeast China. Due to the characteristics of optical images and the design of the method, unmanaged gullies and gullies harnessed in non-forest areas were the objects of extraction. Moderate success was achieved in the absence of terrain data. According to independent validation, the true overestimation ranged from 20% to 30% and was mainly caused by land use types with high erosion risks, such as bare land and farm lanes being falsely classified as gullies. An underestimation of less than 40% was adjacent to the correctly extracted gullied areas. The results of extraction in regions with geographical object categories of a low complexity were usually more satisfactory. The overall performance demonstrates that the present method is feasible for gully mapping at a regional scale, with high automation, low cost, and acceptable accuracy.

Against the background of coordinated development of the Beijing–Tianjin–Hebei region, it is of great significance to quantitatively reveal the contribution rate of the influencing factors of urban land for optimizing the layout of urban land across regions and innovating the inter-regional urban land supply linkage. However, the interaction effects and spatial effects decomposition have not been well investigated in the existing research studies on this topic. In this study, based on the cross-sectional data in 2015 and using the spatial lag model, spatial error model and spatial Durbin model, we analyzed the relationship between urban land and regional economic development at the county level in the Beijing–Tianjin–Hebei region. The results show that: (1) there are endogenous interaction effects of urban land, and the growth of urban land in a county will drive the corresponding growth of urban land in neighboring counties; (2) the local population, average wages, highway mileage density, and actual utilization of foreign capital have positive effects on the scale of urban land in local and neighboring counties; local GDP in the secondary/tertiary sector and the urbanization rate have positive effects on local urban land scale, but negative effects on the urban land scale of neighboring counties; (3) the contribution degree of the direct effect is ranked as follows: GDP in the secondary/tertiary sector > total population > urbanization rate. The order of factors with a significant spatial spillover effect on the scale of urban land in neighboring counties is as follows: average wages > total population > highway mileage density. The GDP in secondary/tertiary sector, population, and urbanization rate are the main influencing factors for the scale of urban land at the county level in the Beijing–Tianjin–Hebei region. It is an important finding that average wages are the most prominent among the spatial spillovers. We should attach importance to the spillover effect of geographic space and construct an urban spatial pattern coordinated with economic development.

土地利用空间格局研究是土地利用/覆盖变化(LUCC)理论和实践的基础,对土地利用空间格局进行有效刻画有利于国土资源空间优化,提升土地利用规划和管理水平.由于土地利用空间格局的研究范畴尚不明晰,目前土地利用空间格局的研究对形状、斑块分布和结构等方面关注较少,缺乏对不同土地利用类型间相互关系的研究;同时,格局指标繁多且存在较大的相关性,如何建立指标与土地利用空间格局的对应关系值得进一步研究.本文在深刻理解土地利用空间格局内涵的基础上,将面积、形状和斑块分布总结为土地利用几何特征,将结构和多样性总结为土地利用类型特征,建立了土地利用空间格局刻画指标体系,利用模糊C均值聚类分析,明确了指标与空间格局间的对应关系.结果 表明,中国土地利用几何特征可以划分为简单大斑块型、复杂大斑块型、复杂小斑块型、简单小斑块型和散布型五种,不同的几何特征反映了不同土地利用类型的面积、形状和斑块分布的特点,体现了区域土地利用类型的组合关系.2010年中国土地利用共存在61种不同的结构,但主要的结构类型仅有14种,结构特征具有明显的空间聚集性,体现了不同土地利用类型的空间分异性.中国土地利用多样性以3～5类为主,占比达66.69％,其特征总体上呈现“东北、东南高,西北低”的态势.该研究丰富了土地利用空间格局研究的理论体系,填补了中国土地利用整体空间格局刻画的空白.

人工造林被认为是增加碳汇、保持水土和提高水质最有效的方法之一,造林林种的不同将产生不同的生态效应。通过调研土壤、气象及生态化学计量参数等对CENTURY模型进行本地化,模拟冀西北水源涵养区主要针叶造林树种[落叶松（dahurian larch）、油松（pinus tabulaeformis）、侧柏（oriental arborvitae）和樟子松（Pinus sylvestris var. mongolical）]的生态效应,并结合文献数据评价模型拟合精度。模型模拟结果显示:与幼龄林相比,落叶松、油松、侧柏和樟子松中龄林的土壤C、N、P总储量分别增加了3.37%、3.98%、2.84%和1.82%,土壤含水量增加了151.25%、73.62%、41.83%和94.98%。不同林种两个林龄平均蒸发量比较显示,落叶松（338.85 mm）＜油松（399.86 mm）＜侧柏（400.52 mm）＜樟子松（401.82 mm）。落叶松可以作为水源涵养区造林的优选树种。樟子松和落叶松具有较强的N、P吸收能力,建议在农业污染的下游区域推广樟子松和落叶松的种植。

Understanding the process of urban expansion in megacities is considerably important. In this study, megacity Mumbai was selected as the study area. Based on the urban maps retrieved from Landsat images in 1973–2018, we mapped and quantified the detailed urban expansion process of Mumbai by adopting the expansion area and speed indices, centroid shift model, urban expansion type method, hot-zone identification method and landscape metrics. The results indicated that: (1) urban land remarkably expanded, and its centroid moved from the southwest to the northeast direction, mainly adopting the edge-expansion form. (2) Distinctly spatiotemporal heterogeneities existed in eight directions, faster in the north, northeast and east directions, whereas slower in the five other directions. (3) The number of hot-zones increased from two to three and moved outward in space from urban centroid. (4) The urban landscape of Mumbai showed the ‘diffusion, aggregation, re-diffusion’ pattern and presented differences in eight directions.

As a large and populous developing country, China has entered the rapid urbanization stage since 2000. Until 2018, China has accounted for nearly 1/5 of global megacities. Understanding their urbanization processes is of great significance. Given the deficiencies of existing research, this study explored the interannual urbanization process of China’s six megacities during 2000–2018 from four aspects, namely, the basic characteristics of urban land expansion, expansion types, cotemporary evolution of urban land–population–economy, and urbanization effects on the local environment. Results indicated that (1) urban lands in China’s six megacities increased by 153.27%, with distinct differences across megacities; (2) all of six megacities experienced the expansion processes from high-speed to low-speed, but they varied greatly in detail; (3) the speeds of urban land expansion in China’s megacities outpaced the population growth but lagged behind in GDP increase; and (4) urbanization has triggered an environmental crisis, which is represented by the decline in vegetation coverage and the increase in land surface temperature in newly expanded urban lands. This study enriched the content of urbanization, supplemented the existing materials of megacities, and provided a scientific reference for designing rational urban planning.

Since 1970s, China has experienced the large-scale losses of croplands during urban expansion process, which has drawn great attentions to Chinese government. Although in-depth studies about cropland losses have been executed widely, relatively little attention has been paid to describe long term and high frequency influences of urban expansion on it and reveal its differences systematically. Based on remote sensing and GIS technology, we quantified, analyzed, and mapped cropland losses in China due to urban expansion from the national, administrative-level, population-size, and city scales. Results indicated that (1) Since the 1970s, croplands were the primary contributor to urban expansion in China, and their losses due to urban expansion underwent five obvious stages. The consciousness of cropland protection is being strengthened continuously and has developed from the initial to the deep execution stages. (2) Cropland losses were unbalanced in China, with the loss magnitude, rate, and influences on urban expansion positively related to the administrative-level and large population-size. That is, obvious losses always emerged in cities with high administrative-level and large population-size. (3) Seven basic trends of cropland losses were quantitatively recognized, which was conducive to the formulation of different policies or strategies for cropland protection for different cities.

Urban areas and its evolution are important anthropogenic indicators and human ecological footprints, and play decisive roles in environmental change analysis, global geo-conditional monitoring, and sustainable development. China has the highest rate of urban expansion and has emerged as an urban expansion hotspot worldwide. In this paper, the progress of studies on Chinese urban expansion based on remote sensing technology are summarized and analyzed from the aspects of urban area definition, remotely sensed imagery applied in urban expansion, monitoring methods of urban expansion, and urban expansion applications. Existing issues and future directions of Chinese urban expansion are discussed and proposed. Results indicate that: 1) The fusion of multi-source remotely sensed imagery is imperative to meet the needs of urban expansion with various monitoring terms and frequencies on different scales and dimensions. 2) To guarantee the classification accuracy and efficiency and describe urban expansion and its influences on local land use simultaneously, the combination of visual interpretation and automatic classification is the tendency of future monitoring methods of urban areas. 3) Urban expansion data have become the prerequisite for recognizing the urban development process, excavating its driving forces, simulating and predicting the future development directions, and also is conducive to revealing and explaining urban ecological and environmental issues. 4) In the past decades, Chinese scholars have promoted the application of remote sensing technology in the urban expansion field, with data construction, methods and models developing from the quotation stage to improvement and innovation stage; however, an independent and consistent urban expansion data on the national scale with long-term and high-frequency (such as annual monitoring) monitoring is still lacking.

Over the past few decades, built-up land in China has increasingly expanded with rapid urbanization, industrialization and rural settlements construction. The expansions encroached upon a large amount of cropland, placing great challenges on national food security. Although the impacts of urban expansion on cropland have been intensively illustrated, few attentions have been paid to differentiating the effects of growing urban areas, rural settlements, and industrial/transportation land. To fill this gap and offer comprehensive implications on framing policies for cropland protection, this study investigates and compares the spatio- temporal patterns of cropland conversion to urban areas, rural settlements, and industrial/ transportation land from 1987 to 2010, based on land use maps interpreted from remote sensing imagery. Five indicators were developed to analyze the impacts of built-up land expansion on cropland in China. We find that 42,822 km2 of cropland were converted into built-up land in China, accounting for 43.8% of total cropland loss during 1987–2010. Urban growth showed a greater impact on cropland loss than the expansion of rural settlements and the expansion of industrial/transportation land after 2000. The contribution of rural settlement expansion decreased; however, rural settlement saw the highest percentage of traditional cropland loss which is generally in high quality. The contribution of industrial/transportation land expansion increased dramatically and was mainly distributed in major food production regions. These changes were closely related to the economic restructuring, urban-rural transformation and government policies in China. Future cropland conservation should focus on not only finding a reasonable urbanization mode, but also solving the “hollowing village” problem and balancing the industrial transformations.

China is experiencing rapid land-use change and shifts in farm management. However, the interactive effects of these drivers on cropping system sustainability are unclear. Here, we evaluate spatio-temporal trade-offs among crop production and five key environmental indicators, including land use, water consumption, excess nitrogen and phosphorous use, and greenhouse gas emissions in China. From 1987 to 2010, as crop kilocalorie production increased (+66%), so did the total environmental impact of all indicators (+1.3–161%) except greenhouse gas emissions (−18%). Concurrently, environmental intensity—impact per kilocalorie produced—decreased for all indicators (−51–−13%) except excess phosphorus (+57%). Despite substantial loss and displacement of cropland to urban expansion, counterfactual scenario analysis indicates that farm management explained >90% of changes in crop production and environmental impact. However, cropland is expanding in regions of relatively high land and irrigation intensity. Although efficiency gains partly compensated for increased environmental pressures, continued geographic shifts in cropland could challenge progress towards agricultural sustainability in China.