Land cover changes based on plant successions: Deforestation,rehabilitation and degeneration of forest in the upper Dadu River watershed

The land use/cover classification system is the foundation for land use/cover change study. Remote sensing data were firstly used for land use and land cover classification in the United States in 1971 and the Anderson Classification System was proposed in 1976[1], which was put into use in mapping 1:250000 land use and land cover of the United States. A series of new land cover classification systems have been established in recent years through research projects such as FAO LCCS and Bi…     

太湖流域上游土地利用变化机制的实证分析--以浙江省安吉县为例

近10年来,太湖流域上游地区经济发展逐步趋于活跃,受此影响,区域人口-资源、环境-发展(PRED)出现了新的特点与趋势。基于上游地区土地利用/覆被变化对流域整体水环境与生态安全格局所具有的重要意义,本文选择安吉县作为典型案例,分析其区域土地利用的基本特征,土地利用变化与景观格局动态的过程,以及驱动因素与机制,由此揭示山区土地利用/覆被变化的一般性规律,为太湖流域上游地区经济发展与土地利用、环境保护相互协调,提供决策借鉴与依据。     

Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau(1981―2006):Impacts of climate changes and human activities

Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981-2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981―1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990―1998; (3) vegetation cover declined rapidly during 1999―2001; and (4) vegetation cover increased rapidly during 2002―2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology.     

Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau (1981–2006): Impacts of climate changes and human activities

Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981–2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981–1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990–1998; (3) vegetation cover declined rapidly during 1999–2001; and (4) vegetation cover increased rapidly during 2002–2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology. Supported by the National Natural Science Foundation of China (Grant No. 40671019) and the Knowledge Innovation Project of the Institute of Geographical Sciences and Natural Resources Research of Chinese Academy of Sciences     

Abundance, diversity and succession of aquatic Coleoptera and Heteroptera in a cluster of artificial ponds in the North German Lowlands

Our study describes and evaluates environmental influences on assemblages of aquatic Coleoptera and Heteroptera in artificial ponds situated near Lake Steinhude in Lower Saxony (Germany). We determined temporal dynamics and colonization patterns for 14 ponds of different age. In total, we recorded 4941 individuals that represented 87 species of aquatic beetles and bugs. Between 30 and 40 species were found in most of the ponds. Heteropteran species of the families Corixidae and Notonectidae acted as pioneer species in new ponds, while aquatic coleopterans predominated in older ponds. The results of Canonical Correspondence Analyses (CCA) showed that among the key factors affecting community structure were land use, vegetation cover, water chemistry and the age of the ponds. We found that the distribution of adjacent ponds on areas with different land use has a positive influence on the diversity and abundance of the aquatic insect fauna.     

应用MODIS数据监测千岛湖流域植被覆盖动态(2001-2013年)

流域植被覆盖状况对于水源地生态环境保护具有重要的指示作用.当前的水质目标管理不仅要着眼于湖库水质参数控制,更应该从整个流域的角度维系生态平衡.在此背景下,依托长时间序列MODIS遥感数据对千岛湖流域2001-2013年植被覆盖状况进行监测,采用最小二乘法趋势分析和Mann-Kendall显著性检验方法分析了千岛湖流域植被的空间分布特征、时间变化特征与长期变化趋势.研究表明该方法能够有效地监测流域植被覆盖的时空动态变化:1)从空间分布上来看,千岛湖流域植被覆盖状况整体较好,但同时也发现受人为干扰较大的地域如河、湖附近的城镇建设用地、农业用地以及园地,其NDVI值明显低于自然林地;2)从时间变化特征上看,2001-2013年千岛湖流域植被年际NDVI在0.69~0.73之间波动,且近年来有增长趋势,年内季节性NDVI动态分析表明高时间分辨率的MODIS数据能够用来区分常绿植被与落叶植被的物候特征,以分析不同植被类型对流域氮、磷流失的风险差异;3)从变化趋势上看,2001-2013年植被覆盖状况改善的区域远大于退化的区域,其中改善区域约占流域面积的55.90%,呈现出一定退化状态的区域约占29.60%(严重退化区域仅占3.97%),而相对稳定不变区域约占14.51%.经与气温与降水等气候因子进行相关性分析表明,植被NDVI与气温呈显著正相关,而降水则不敏感,说明气温是研究区植被生长的主导气候因子.同时发现,人类活动对局部植被变化影响较大.研究结果可为流域水资源与生态环境保护提供空间数据支撑.     

Study on spatial pattern of land-use change in China during 1995—2000

Land-use/cover change has become an event being of paramount importance to the study of global environmental change[1,2]. Land-cover change is closely related to the terrestrial surface material cycles and life-support processes[3], i.e., the interaction …     

生态补水对白洋淀湿地植被格局的影响

白洋淀位于雄安新区腹地,是雄安新区重要的生态屏障与后花园,生态补水与植被恢复是白洋淀生态修复的重要内容.本文运用遥感影像资料,对比分析了雄安新区设立以来(2017年和2020年)白洋淀挺水植被、沉水植被、陆生植被、开阔水域、建设用地和裸地6种土地利用类型的变化趋势,深入剖析了挺水植被、沉水植被和陆生植被的时空分布格局、生长期内逐月生物量变化及其演替规律,探讨了水位变化对挺水植被和沉水植被生物量的影响,分析了雄安新区设立以来生态补水对淀区植被恢复的整体效果.结果表明:白洋淀水生植被主要分布在淀区北部、西北、西南和沿岸水深较浅的区域,相比2017年雄安新区设立之初,生态补水作用下,2020年淀区水位平均上涨0.63 m,沉水植被、陆生植被分布面积分别扩大了7.5%和21.4%,挺水植被和裸地面积则缩减了19%;挺水植被在8月生物量达到最大值,其分布面积和生物量随水位的增加整体呈减小趋势,同时受季节演替影响,温度升高则会显著促进挺水植被生长;与之相反,沉水植被随季节演替,其年内生物量最大出现在5、9和10月,但分布面积未有明显变化,且其生物量变化受水位影响不明显.总体而言,雄安新区设立以来,白洋淀年内植被生物量明显增加,为淀区水环境质量和水生态安全提供保障.     

Study on spatial pattern of land-use change in China during 1995–2000

It is more and more acknowledged that land-use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. Supported by the Landsat TM digital images, spatial patterns and temporal variation of land-use change during 1995 –2000 are studied in the paper. According to the land-use dynamic degree model, supported by the 1km GRID data of land-use change and the comprehensive characters of physical, economic and social features, a dynamic regionalization of land-use change is designed to disclose the spatial pattern of land-use change processes. Generally speaking, in the traditional agricultural zones, e.g., Huang-Huai-Hai Plains, Yangtze River Delta and Sichuan Basin, the built-up and residential areas occupy a great proportion of arable land, and in the interlock area of farming and pasturing of northern China and the oases agricultural zones, the reclamation of arable land is conspicuously driven by changes of production conditions, economic benefits and climatic conditions. The implementation of “returning arable land into woodland or grassland” policies has won initial success in some areas, but it is too early to say that the trend of deforestation has been effectively reversed across China. In this paper, the division of dynamic regionalization of land-use change is designed, for the sake of revealing the temporal and spatial features of land-use change and laying the foundation for the study of regional scale land-use changes. Moreover, an integrated study, including studies of spatial pattern and temporal process of land-use change, is carried out in this paper, which is an interesting try on the comparative studies of spatial pattern on change process and the change process of spatial pattern of land-use change.     

Sensitivity of surface air temperature change to land use/cover types in China

Using CRU high resolution grid observational temperature and ERA40 reanalysis surface air temperature data during 1960–1999, we investigated the sensitivity of surface air temperature change to land use/cover types in China by subtracting the reanalysis from the observed surface air temperature (observation minus reanalysis, OMR). The results show that there is a stable and systemic impact of land use/cover types on surface air temperature. The surface warming of each land use/cover type reacted differently to global warming. The OMR trends of unused land (⩾0.17 °C/decade), mainly comprised by sandy land, Gobi and bare rock gravel land, are obviously larger than those of the other land use/cover types. The OMR over grassland, farmland and construction land shows a moderate decadal warmingabout 0.12°C/decade, 0.10°C/decade, 0.12°C/decade, respectively. Woodland areas do not show a significant warming trend (0.06°C/decade). The overall assessment indicates that the surface warming is larger for areas that are barren and anthropogenically developed. The better the vegetation cover, the smaller the OMR warming trend. Responses of surface air temperature to land use/cover types with similar physical and chemical properties and biological processes have no significant difference. The surface air temperature would not react significantly until the intensity of land cover changes reach a certain degree. Within the same land use/cover type, areas in eastern China with intensive human activities exhibit larger warming trend. The results provide observational evidence for modeling research on the impact of land use/cover change on regional climate. Thus, projecting further surface climate of China in regional scale should not only take greenhouse gas increase into account, but also consider the impact of land use/cover types and land cover change. Supported by National Basic Research Program of China (Grant No. 2005CB422006), National Natural Science Foundation of China (Grant Nos. 90202012, 40771206)     

Effects of mid‐twenty‐first century climate and land cover change on the hydrology of the Puget Sound basin,Washington

The distributed hydrology–soil–vegetation model (DHSVM) was used to study the potential impacts of projected future land cover and climate change on the hydrology of the Puget Sound basin, Washington, in the mid‐twenty‐first century. A 60‐year climate model output, archived for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), was statistically downscaled and used as input to DHSVM. From the DHSVM output, we extracted multi‐decadal averages of seasonal streamflow, annual maximum flow, snow water equivalent (SWE), and evapotranspiration centred around 2030 and 2050. Future land cover was represented by a 2027 projection, which was extended to 2050, and DHSVM was run (with current climate) for these future land cover projections. In general, the climate change signal alone on sub‐basin streamflow was evidenced primarily through changes in the timing of winter and spring runoff, and slight increases in the annual runoff. Runoff changes in the uplands were attributable both to climate (increased winter precipitation, less snow) and land cover change (mostly reduced vegetation maturity). The most climatically sensitive parts of the uplands were in areas where the current winter precipitation is in the rain–snow transition zone. Changes in land cover were generally more important than climate change in the lowlands, where a substantial change to more urbanized land use and increased runoff was predicted. Both the annual total and seasonal distribution of freshwater flux to Puget Sound are more sensitive to climate change impacts than to land cover change, primarily because most of the runoff originates in the uplands. Both climate and land cover change slightly increase the annual freshwater flux to Puget Sound. Changes in the seasonal distribution of freshwater flux are mostly related to climate change, and consist of double‐digit increases in winter flows and decreases in summer and fall flows. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.     

Integrative fuzzy set pair model for land ecological security assessment: a case study of Xiaolangdi Reservoir Region, China

Due to the increasingly serious ecological degradation of land systems, the land ecological security issues have attracted more and more attention of policy makers, researchers and citizens. Aiming at overcoming the disadvantages in subjectivity and complexity of the currently used assessment methods, an integrative fuzzy set pair model for assessing the land ecological security was developed by integrating fuzzy assessment and set pair analysis (SPA). The approximate degree of land ecological security to the optimal standard set was calculated to describe the secure level by combining multiple indices. The indices and weights were determined by a pressure-state-response model and the fuzzy analytic hierarchy process (AHP), respectively. Aided by a geographic information system, this model was applied to evaluate comprehensively the status of land ecological security in Xiaolangdi Reservoir Region, China, taking the administrative division as the assessment unit. The results showed that 20% of the total area maintained a slightly secure status, while 50% of the study area was of a middle or seriously low grade of land ecological security. The remaining portion (30%) was the most ecologically insecure. From the spatial prospective, obvious variations were observed. The land eco-security gradually decreased from the Xiaolangdi Dam to its surrounding regions. It was concluded that the status of the integral land ecological security of Xiaolangdi Reservoir Region was in the middle level, and increasingly intense human activities speeded up the degradation of regional land ecosystem in recent years and thus induced the crisis of land ecological security.     

Land degradation assessment with the aid of geo‐information techniques

This research integrated selected land degradation indicators (vegetation cover, proportion of drifting sand area, desertification rate, and population pressure) with geo‐information techniques (remote sensing, geographic information system and global positioning system) to assess the severity of land degradation risk. The northern part of Shaanxi province in China was taken as a case study. A computerized land degradation severity assessment was implemented, and ERmapper ver.6.2 and ARC/INFO GIS ver.8.3 environments were used to manage and manipulate thematic data, and to process satellite images and tabular data. Two Landsat TM images in October 1987 and October 1999 were used to produce land use/cover maps of the study area based on the maximum likelihood classification method. These maps were then used to generate land use, land cover change, vegetation degradation and land degradation maps for the study area during the study period, and their corresponding data were integrated into a systematic analysis. Results showed that the overall severity of land degradation in the study area worsened during the study period from 1987 to 1999 with severely, highly and moderately degraded land accounting for 73·8 per cent of the total area. While the area affected by desertification has increased, the rate of desertification has also accelerated to reach 41·5 km² a^?1. Risk of land degradation in the study area has increased, on average, by 39·4 per cent since 1987. Incorporation of both natural and anthropogenic factors in the analysis provided realistic assessment of the risk of desertification. The study area, in general, is exposed to a high risk of land degradation. Copyright © 2006 John Wiley & Sons, Ltd.     

Methodology for credibility assessment of historical global LUCC datasets

Land use-induced land cover change(LUCC) is an important anthropogenic driving force of global change that has influenced, and is still influencing, many aspects of regional and global environments. Accurate historical global land use/cover datasets are essential for a better understanding of the impacts of LUCC on global change. However, there are not only evident inconsistencies in current historical global land use/cover datasets, but inaccuracies in the data in these global dataset revealed by historical record-based reconstructed regional data throughout the world. A focus in historical LUCC and global change research relates to how the accuracy of historical global land cover datasets can be improved. A methodology for assessing the credibility of existing historical global land cover datasets that addresses temporal as well as spatial changes in the amount and distribution of land cover is therefore needed. Theoretically, the credibility of a global land cover dataset could be assessed by comparing similarities or differences in the data according to actual land cover data(the "true value"). However, it is extremely difficult to obtain historical evidence for assessing the credibility of historical global land cover datasets, which cannot be verified through field sampling like contemporary global land cover datasets. We proposed a methodological framework for assessing the credibility of global land cover datasets. Considering the types and characteristics of the available evidence used for assessments,we outlined four methodological approaches:(1) accuracy assessment based on regional quantitative reconstructed land cover data,(2) rationality assessment based on regional historical facts,(3) rationality assessment based on expertise, and(4) likelihood assessment based on the consistency of multiple datasets. These methods were illustrated through five case studies of credibility assessments of historical cropland cover data. This framework can also be applied in assessments of other land cover types, such as forest and grassland.     

A classification scheme for Earth’s critical zones and its application in China

As the thin layer at the Earth's terrestrial surface, the critical zone(CZ) ranges from the vegetation canopy to the aquifer or the interface between saprolite and bedrock and varies greatly in space. In the last decade, much attention has been paid to the establishment of Critical Zone Observatories(CZOs) that focus on various aspects of CZ science over different time scales. However, to the best of our knowledge, few studies have explicitly contributed to CZ classification or regionalization;thus, the spatial patterns of similar CZs have not been clearly identified. This study proposed a three-category CZ classification scheme by integrating environmental factors that greatly affect the transfer of energy and mass in the Earth's near-surface environment and thus dominate CZ formation and evolution, i.e., climate, parent material, soil type, groundwater table depth,geomorphology and land use. The main goal was to highlight the zonality of these driving forces, of which the high-category classification units were overlaid to delineate the CZ boundaries. The CZ regionalization of China was performed as a case study,resulting in 44 major regions(1 st category), 100 submajor regions(2 nd category) and 1448 regions(3 rd category). The spatial distributions and driving factors of the ten largest regions were identified, followed by a simple comparison of the CZO network.Then, the proposed CZ regionalization was compared with recent studies on regionalization in China to evaluate its successes and weaknesses. By linking together CZ studies from the last decade, we advocate that a theoretical framework integrating the CZ evolution processes with ecological functions acts as one of the frontiers of CZ science. Our study demonstrates that the proposed three-category CZ classification scheme effectively identifies the spatial variations in CZs and could thus be further applied in other areas to advance terrestrial environmental research and provide decision support for the sustainable management of natural resources.     

Measurement of ecological capital of Chinese terrestrial ecosystem based on remote sensing

The biosphere of the Earth is the material founda-tion of human survival and development.With the increasing problems of the resources,the environment and population,most countries in the world have paid special attention to the measurement and evaluation of ecological capital,which refers to the sum of the direct natural resources value and the indirect ecosystem services value.Ecological capital depends on not only the quality of the national ecological environment,butalso the social recogni…     

Thresholds of land cover to control runoff and soil loss

This research focused on the determination of land cover thresholds that have a significant impact on runoff generation and soil loss at the pedon scale. For this purpose, six erosion micro-plots were set up on grassland and shrubland types of rangeland in the northeast of Iran, and the amounts of vegetation cover, litter, runoff and soil loss on them were measured. A factorial statistical analysis was carried out on the completely randomized design using land cover and rainfall factors. The results show that the effect of rainfall on soil loss and runoff was greater than that of land cover. Also, the effect of land cover on soil loss was greater than that on runoff generation. Furthermore, two specific thresholds were identified: the first was from 10 to 30% of landcover and the second from 50 to 70%.