Remote sensing imagery for resource inventories in central Africa: The importance of detailed field data

The rate of rain forest clearing throughout central Africa is of national and international interest because it affects both the region's contribution to global warming and impacts the sustainable productive capacity of its natural resource base. The size and inaccessibility of much of central Africa makes remote sensing imagery the most suitable data source for regional land cover mapping and land transformation monitoring. Present image availability is poor. Most regional studies have had to rely on coarse resolution AVHRR 1 km data that fails to detect the small-scale agricultural clearings that are the primary cause of land cover change throughout the region. This study demonstrates that higher spatial resolution Landsat MSS imagery, which comprises the most available, geographically comprehensive and longest time series dataset, is too coarse to map land cover in low population density areas typical of most of central Africa. Furthermore, this study cautions that the use of high resolution imagery without detailed collateral field data on population density and land use practices while generating superficially plausible results, will most probably produce highly inaccurate estimates of land cover and land transformation. Policies for future regional remote sensing surveys of central Africa should focus on acquisition of higher spatial, spectral, and radiometric resolution imagery and must be accompanied by detailed, systematic field data collection.     

A new global 1-km dataset of percentage tree cover derived from remote sensing

Accurate assessment of the spatial extent of forest cover is a crucial requirement for quantifying the sources and sinks of carbon from the terrestrial biosphere. In the more immediate context of the United Nations Framework Convention on Climate Change, implementation of the Kyoto Protocol calls for estimates of carbon stocks for a baseline year as well as for subsequent years. Data sources from country level statistics and other ground‐based information are based on varying definitions of ‘forest’ and are consequently problematic for obtaining spatially and temporally consistent carbon stock estimates. By combining two datasets previously derived from the Advanced Very High Resolution Radiometer (AVHRR) at 1 km spatial resolution, we have generated a prototype global map depicting percentage tree cover and associated proportions of trees with different leaf longevity (evergreen and deciduous) and leaf type (broadleaf and needleleaf). The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial datasets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks. The percentage tree cover dataset is available through the Global Land Cover Facility at the University of Maryland at http://glcf.umiacs.umd.edu .     

A land cover map of South America

A digital land cover map of South America has been produced using remotely sensed satellite data acquired between 1995 and the year 2000. The mapping scale is defined by the 1 km spatial resolution of the map grid‐cell. In order to realize the product, different sources of satellite data were used, each source providing either a particular parameter of land cover characteristic required by the legend, or mapping a particular land cover class. The map legend is designed both to fit requirements for regional climate modelling and for studies on land cover change. The legend is also compatible with a wider, global, land cover mapping exercise, which seeks to characterize the world's land surface for the year 2000. As a first step, the humid forest domain has been validated using a sample of high‐resolution satellite images. The map demonstrates both the major incursions of agriculture into the remaining forest domains and the extensive areas of agriculture, which now dominate South America's grasslands.     

Vegetation structure and greenness in Central Africa from Modis multi-temporal data

African forests within the Congo Basin are generally mapped at a regional scale as broad-leaved evergreen forests, with the main distinction being between terra-firme and swamp forest types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organization and their relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified 22 vegetation types (six savannas, two swamp forests, 14 forest types) improving existing vegetation maps. Among forest types, we showed strong variations in stand structure and deciduousness, identifying (i) two blocks of dense evergreen forests located in the western part of the study area and in the central part on sandy soils; (ii) semi-deciduous forests are located in the Sangha River interval which has experienced past fragmentation and human activities. For all vegetation types enhanced vegetation index profiles were highly seasonal and strongly correlated to rainfall and to a lesser extent, to light regimes. These results are of importance to predict spatial variations of carbon stocks and fluxes, because evergreen/deciduous forests (i) have contrasted annual dynamics of photosynthetic activity and foliar water content and (ii) differ in community dynamics and ecosystem processes.     

A large‐area,spatially continuous assessment of land cover map error and its impact on downstream analyses

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high‐resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel‐wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative “downstream” (map‐based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps’ spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ～45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National‐scale maps derived from higher‐resolution imagery were most accurate, followed by multi‐map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland‐adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%–500% greater than in input cropland maps, but ～40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land cover map users.     

利用IKONOS卫星数据和分形方法研究南麂岛土地覆盖状况

研究南麂岛的土地覆盖类型及其空间分布和结构特征。利用具有1米空间分辨率的IKONOS卫星遥感数据,提取南麂岛的植被覆盖和土地利用信息,获得草地、灌木林地、庄稼地和居民地等主要土地覆盖类型及其分布图。然后利用分形几何方法建立南麂岛土地覆盖类型特性分析模型,从斑块的面积效应、覆盖类型的分形分析、单个斑块的分形分析和覆盖类型分形特征差异显著性等方面进行分析讨论。研究结果表明,南麂岛的草地和灌木林地的分形维数较大,而庄稼地和居民地的分形维数较小,说明草地和灌木林地的斑块的结构特征和边界比庄稼地和居民地更为复杂。进一步研究表明,斑块的分形特性与其受人类活动的干扰程度密切相关。     

Continental estimates of forest cover and forest cover changes in the dry ecosystems of Africa between 1990 and 2000

Aim

This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium‐resolution satellite imagery which was processed consistently across the continent.

Location

The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi‐arid regions. This area covers the Sudanian and Zambezian ecoregions.

Methods

A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts.

Results

Land cover and land‐cover changes were estimated at continental and ecoregion scales and compared with existing pan‐continental, regional and local studies. The overall accuracy of our land‐cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area.

Main conclusions

Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies.     

1995～2000年中国沙地空间格局变化的遥感研究

利用遥感方法 ,在覆盖全国的 Landsat-TM数据的基础上 ,对 1 995年和 2 0 0 0年中国沙地的空间分布格局与动态变化进行了调查。结果显示了 2 0 0 0年中国沙地总面积为 5 9× 1 0 4 km2 ,主要分布于各主要沙漠和我国的 7个主要省份。1 995～ 2 0 0 0年 ,有 470 9.7km2的土地转化为沙地 ,同时又有 2 1 5 6.4km2的沙地转化为其它土地利用类型 ,沙地总面积扩大了2 5 5 3 .3 km2 。对变化为沙地的土地进行分析 ,发现草地占主要部分 ,但耕地所占的比重也非常突出 ,同时也表明有部分沙地变化为草地和耕地。根据土地沙化的空间分布特征 ,将土地沙化过程分为 5种格局 :沙地 -绿洲型、沙漠型、沙地 -黄土过渡型、沙地 -草地型和高原风蚀型。通过对中国发生土地风蚀沙化的主要省份在 1 995～ 2 0 0 0年间的土地利用动态变化发现 ,土地利用变化是促使土地发生沙化的一个重要因素。在 5 a的时间里 ,7个省份耕地总面积扩大了 90 3 9.7km2 ,草地减少了 1 1 5 97.9km2。耕地的增加部分几乎均表现为对草地的侵占 ,土地变为沙地也主要发生在草地区。人为因素导致的耕地面积扩大是促使土地沙化的重要原因。对主要省份的土地利用方式进行分析 ,探讨不同地区减轻土地沙化趋势下的土地利用布局。     

Changes in the area of optimal tree cover of a declining Afro-Palaearctic migrant across the species’ wintering range

Land use change in sub-Saharan Africa continues apace, but its role in driving the declines of Afro-Palaearctic migrant birds is unknown. This is due partly to a lack of knowledge of migrants’ requirements on the wintering grounds, and of spatially explicit assessments of land cover change. We compared tree cover data derived from satellite remote sensing (available for the period 2000–2014) with distributional data from surveys in four West African countries for the Wood Warbler Phylloscopus sibilatrix, one such declining migrant, to determine the extent of, and change in, optimal tree cover. Wood Warblers were most likely to occur where tree cover per hectare was between 40 and 61% (optimal tree cover). Extrapolation to the whole of the wintering range indicated there was a 46.7% net increase in extent between 2000 and 2014. This was due to an alarming 27 683 km² of previously closed forest being degraded from > 61% cover to between 40 and 61%, an area greater than that of the optimal tree cover that was lost. Increases in optimal tree cover were greatest in countries with greatest forest cover, such as Sierra Leone, Liberia, Côte d'Ivoire and Democratic Republic of Congo. The results suggest that loss of optimal tree cover in the wintering range might not be a key driver of population decline for Wood Warblers, but the degradation will probably impact species that rely upon dense tree cover.     

新区开发建设及其生态效应——以雄安新区为例

雄安新区自2017年设立为国家级新区以来,已进行了大量的开发建设,但迄今尚未见对开发建设所产生的生态效应的研究报道。因此,选取2017年和2020年的Landsat 8影像,分别代表雄安新区未开始建设和建设3年后的两个时期来对此进行对比。利用遥感空间信息技术反演出2017—2020年雄安新区开发建设以来主要地表覆盖类型的变化,并采用遥感生态指数(RSEI)对这些地表覆盖类型变化产生的生态效应进行评估。结果表明：(1)雄安新区2017—2020年间的开发建设已使建筑用地面积增加了60.01 km²,水体面积增加了8.95 km²,植被面积减少了69.29 km²。雄安新区现阶段的开发建设主要集中在区内的容城县和雄县,而安新县的开发强度较小。(2)雄安新区2017—2020年间开发建设的生态效应体现在生态改善面积大于退化面积,生态等级良好以上的面积占比有所提升。因此,新区的生态质量总体略有上升,RSEI均值从0.668上升到0.677。但3个县的表现不一,雄县和安新县的生态有所提升,而容城县则略有下降。(3)雄安新区虽经开发...     

Impact of ENSO on East African ecosystems: a multivariate analysis based on climate and remote sensing data

1 The El Niño‐Southern Oscillation (ENSO) is an important driver of inter‐annual variations in climate and ecosystem productivity in tropical regions. Most previous studies have analysed ENSO‐induced changes in climate based on a single variable, such as rainfall. Also, it is generally assumed that the ENSO impact in East Africa is geographically uniform. 2 The objective of this study is to improve understanding of the impact of ENSO on East African ecosystems, by measuring teleconnections between an ENSO index and a number of ecosystem variables in a spatially explicit way and for different time lags. We analysed the spatial patterns of teleconnections in the region by combining time series of climate variables measured for meteorological stations with time series of a vegetation index and surface temperature data measured by remote sensing. 3 Our results confirm the ENSO impact on the climatic and ecological variability in East Africa. However, the pattern of teleconnections is much more complex than generally assumed, both in terms of spatial distribution and impact on different ecosystem variables. Not all climate and land surface variables are teleconnected to ENSO in the same way, which leads to a complex impact of ENSO on the ecosystem. Moreover, the ENSO impact is highly differentiated in space, as the direction, magnitude and timing of this impact are controlled by the local climate system, the presence of large lakes, proximity to the coast and, possibly, local topography and land cover.     

基于TM的渤海海岸带1988～2000年生态环境变化

海岸带作为海陆之间的过渡地带,是全球生态环境最为复杂和特殊之处。研究海岸带土地利用变化对于了解该区域生态环境演变具有重要意义。利用1988和2000年的Landsat-TM数据,在GIS技术支持下,通过一系列空间分析,得到渤海海岸带土地利用/土地覆盖变化,结合社会经济统计资料分析该区域生态环境的动态变化情况及其驱动因素。结果表明,1988~2000年,由于渤海海岸带社会经济的快速发展,海岸带土地利用格局发生了巨大的变化。耕地大面积减少,城乡工矿用地、养殖池塘、盐田急剧扩张;林地、湿地等具有重要生态价值的土地类型面积显著下降。表明强烈的人类活动已经使自然生态系统受到破坏,渤海海岸带生态环境质量总体上呈现下降趋势。     

Impact of short-term rainfall fluctuation on interannual land cover change in sub-Saharan Africa

Aim Interannual land cover change plays a significant role in food security, ecosystem processes, and regional and global climate modelling. Measuring the magnitude and location and understanding the driving factors of interannual land cover change are therefore of utmost importance to improve our understanding and prediction of these impacts and to better differentiate between natural and human causes of land cover change. Despite advances in quantifying the magnitude of land cover change, the interpretation of the observed land cover change in terms of climatic, ecological and anthropogenic processes still remains a complex issue. In this paper, we map land cover change across sub‐Saharan Africa and examine the influences of rainfall fluctuations on interannual change. Location The analysis was applied to sub‐Saharan Africa. Methods Ten‐day rainfall estimates (RFE) obtained from National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Center (CPC) were used to extract information on inter and intra‐annual rainfall fluctuations. The magnitude of land cover change was quantified based on the multitemporal change vector method measuring year‐to‐year differences in bidirectional reflectance distribution function (BRDF) corrected 16‐day enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectro‐radiometer (MODIS). Statistical models were used to estimate the relationship between short‐term rainfall variability and the magnitude of land cover change. The analysis was stratified first by physiognomic vegetation type and second by chorological data on species distribution to gain insights into spatial variations in response to short‐term rainfall fluctuations. Results The magnitude of land cover change was significantly related to rainfall variability at the 5% level. Stratification considerably strengthened the relationship between the magnitude of change and rainfall variability. Explanatory power of the models ranged from R² = 0.22 for the unstratified model to 0.40–0.96 for the individual models stratified by patterns of species distribution. The total variability explained by the combined models including the influence of rainfall and differences in vegetation response ranged from 22% for the model not stratified by vegetation to 76% when stratified by chorological data. Main conclusions Using this methodology, we were able to measure the contribution of natural variation in precipitation to land cover change. Several ecosystems across sub‐Saharan Africa are highly sensitive to short‐term rainfall variability.     

基于对象特征的山东省丘陵地区多时相遥感土地覆被自动分类

对于基于像元的土地覆被分类来说,植被的分类是难点。使用多时相面向对象分类方法可以较好的解决这个问题。以山东省烟台市丘陵地区为研究区,采用Landsat TM(Landsat Thematic Mapper remotely sensed imagery)、DEM(Digital Elevation Model)、坡度、坡位、坡向等多种数据,利用基于对象特征的多时相分类方法对研究区进行土地覆盖自动分类。首先对影像进行多尺度分割并检验分割结果选取合适的分割尺度,然后分析对象的光谱、纹理、形状特征。根据各类地物的光谱特征、地理相关性、形状、空间分布等特征,明确类别之间的差异。建立决策树使用隶属度函数进行模糊分类,借助支持向量机提高分类精度。研究结果表明,通过使用多时相影像采用面向对象分类方法,相对于传统的基于像素的分类可以明显提高分类精度,尤其是解决了乔灌草的区分问题。     

A new basal dicynodont from the Upper Permian of South Africa

The skull of a small anomodont therapsid, from the Tapinocephalus Assemblage Zone (Abrahamskraal Formation, Beaufort Group, Upper Permian) in Northern Cape Province, South Africa, represents a new basal dicynodont and is described in detail. Colobodectes cluveri gen. et sp. nov. is distinguished from other dicynodonts by an anteroposteriorly extensive caniniform process, parietals that were broadly overlapped posterolaterally by posterodorsal processes of the postorbitals, diverging anterior palatal ridges, and a dorsoventrally low foramen magnum. A phylogenetic analysis indicates that Colobodectes is the basalmost member of a dicynodont clade that excludes Eodicynodon . This position is not particularly strong, as two additional steps are needed to make Colobodectes and Eodicynodon oosthuizeni exchange places on the most parsimonious tree. Another discovery of the phylogenetic analysis is that there is little basis for recognizing Eodicynodon oelofseni as the closest relative of E. oosthuizeni . The former species is identified as the sister taxon of a clade that includes the latter and all other dicynodonts.     

Satellite-based evidence highlights a considerable increase of urban tree cooling benefits from 2000 to 2015

Tree planting is a prevalent strategy to mitigate urban heat. Tree cooling efficiency (TCE), defined as the temperature reduction for a 1% tree cover increase, plays an important role in urban climate as it regulates the capacity of trees to alter the surface energy and water budget. However, the spatial variation and more importantly, temporal heterogeneity of TCE in global cities are not fully explored. Here, we used Landsat-based tree cover and land surface temperature (LST) to compare TCEs at a reference air temperature and tree cover level across 806 global cities and to explore their potential drivers with a boosted regression tree (BRT) machine learning model. From the results, we found that TCE is spatially regulated by not only leaf area index (LAI) but climate variables and anthropogenic factors especially city albedo, without a specific variable dominating the others. However, such spatial difference is attenuated by the decrease of TCE with tree cover, most pronounced in midlatitude cities. During the period 2000–2015, more than 90% of analyzed cities showed an increasing trend in TCE, which is likely explained by a combined result of the increase in LAI, intensified solar radiation due to decreased aerosol content, increase in urban vapor pressure deficit (VPD) and decrease of city albedo. Concurrently, significant urban afforestation occurred across many cities showing a global city-scale mean tree cover increase of 5.3 ± 3.8% from 2000 to 2015. Over the growing season, such increases combined with an increasing TCE were estimated to on average yield a midday surface cooling of 1.5 ± 1.3°C in tree-covered urban areas. These results are offering new insights into the use of urban afforestation as an adaptation to global warming and urban planners may leverage them to provide more cooling benefits if trees are primarily planted for this purpose.