Satellite remote sensing of wetlands

To conserve and manage wetland resources, it is important to inventoryand monitor wetlands and their adjacent uplands. Satellite remote sensing hasseveral advantages for monitoring wetland resources, especially for largegeographic areas. This review summarizes the literature on satellite remotesensing of wetlands, including what classification techniques were mostsuccessful in identifying wetlands and separating them from other land covertypes. All types of wetlands have been studied with satellite remote sensing.Landsat MSS, Landsat TM, and SPOT are the major satellite systems that have beenused to study wetlands; other systems are NOAA AVHRR, IRS-1B LISS-II and radarsystems, including JERS-1, ERS-1 and RADARSAT. Early work with satellite imageryused visual interpretation for classification. The most commonly used computerclassification method to map wetlands is unsupervised classification orclustering. Maximum likelihood is the most common supervised classificationmethod. Wetland classification is difficult because of spectral confusion withother landcover classes and among different types of wetlands. However,multi-temporal data usually improves the classification of wetlands, as doesancillary data such as soil data, elevation or topography data. Classifiedsatellite imagery and maps derived from aerial photography have been comparedwith the conclusion that they offer different but complimentary information.Change detection studies have taken advantage of the repeat coverage andarchival data available with satellite remote sensing. Detailed wetland maps canbe updated using satellite imagery. Given the spatial resolution of satelliteremote sensing systems, fuzzy classification, subpixel classification, spectralmixture analysis, and mixtures estimation may provide more detailed informationon wetlands. A layered, hybrid or rule-based approach may give better resultsthan more traditional methods. The combination of radar and optical data providethe most promise for improving wetland classification.     

森林生态系统生物多样性的遥感评估

目前的评估由于方法的原因,常常会遗留下一些含糊不清的地方。遥感则可以作一种观察生态系统多样性和单个生态系统中各种结构侧面的重要工具。它提供了一种能够跨越几个不同空间尺度实施评估的手段,并且对于评估生态系统格局随时间的变化也是必不可少。现在许多不同的遥感技术已经被应用在生态学研究中。大多数工作所用的数据主要是来自机载和星载平台提供的摄影和数字光学图像,目前则越来越强调激光扫描和合成孔径雷达数据的应用。这些技术手段为从景观到林分规模的不同现象的评估提供了机会。遥感提供了可用于确定森林生态系统中生物多样性景观尺度的元素最有效的工具。例如基质和斑块的相对百分比以及它们的配置。在中间尺度,遥感为评价廊道的存在和边界的特性提供了理想的工具。在林分尺度,遥感技术可用来获取关于森林分结构属性的信息,例如冠层表面的特性,是否存在冠内分层等等。随着的发展,遥感将更广泛地应用于生态学研究。     

Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.     

基于遥感生态指数的阜新市生态质量评估

城市化建设的不断推进及发展给生态环境带来了日益增加的压力,如何多方位、客观准确并且快速地对区域生态环境质量进行评估是目前研究的一个重要方向。以辽宁省阜新市为研究区域,选取2000年、2008年和2016年的遥感影像作为基础研究数据,借助ENVI5.1软件作为数据处理平台,再结合主成分分析方法,借助遥感生态环境质量评价指数RSEI对阜新市的生态质量进行评估。结果表明:2000年、2008年和2016年,阜新市的生态质量总体呈上升趋势;2000—2016年间,研究区RSEI主要由1、2级向3、4、5级转变,生态质量变好和变坏的面积分别占总面积的53.28%和2.38%,生态质量变差的区域主要集中在阜新市东北的风沙区和西南部盆地区;而阜新市西南部盆地区主要是市区,该区生态环境质量变差主要在于近年来的城市快速发展,东北部的风沙区与科尔沁沙地接壤,该区的环境变差在于所处地理位置以及防风固沙林中部分林木出现退化现象等,因此能否在快速城市化建设的同时重视生态环境的保护与修复,成为阜新市生态环境质量变化的重要决定因素。     

沈阳市市区和农村建设用地时空扩展分析

基于1985、1995、1997、2000和2004年的遥感影像和GIS技术,引入建设用地密度、扩展强度指数和分形维数,对1985-2004年间沈阳市市区和农村建设用地扩展的时空特征、空间分异和形态变化进行分析,并探讨了其主要驱动因素.结果表明：1985-2004年间,沈阳市市区建设用地的高密度区面积逐年增加;1997年以前,农村建设用地各级密度区面积的变化不大,1997年以后其高密度区面积逐渐增加;研究期间,市区建设用地的增加面积、扩展速度和扩展强度明显大于农村地区.市区和农村建设用地扩展的空间分异明显,高速扩展区主要集中在市区.市区建设用地分形维数值逐渐增大,总体形态日趋复杂,农村建设用地由于缺乏合理的规划建设,分形维数波动较大.经济发展、人口增长、交通、自然环境、政策导向和城市规划是沈阳市建设用地扩展的主要驱动力.     

Landscape-scale detection and mapping of invasive African Olive (Olea europaea L. ssp. cuspidata Wall ex G. Don Ciferri) in SW Sydney,Australia using satellite remote sensing

Question: Is satellite imagery an effective tool for mapping and examining the distribution of the invasive species Olea europaea L. ssp. cuspidata at a regional landscape scale? Location: Southwest Sydney, Australia. Methods: Remote sensing software was used to classify pixels of Olea europaea L. ssp. cuspidata (African Olive) and major vegetation types from satellite imagery, using a “supervised classification” technique across a 721 km² study area in the Cumberland Plain region of western Sydney. A map of African Olive distribution was produced from the image analysis and checked for accuracy at 337 random locations using ground observation and comparison with existing vegetation maps. The African Olive distribution data were then used in a GIS analysis with additional spatial datasets to investigate the relationship between the distribution of African Olive and environmental factors, and to quantify the conservation threat to endangered native vegetation. Results: A total area of 1907 ha of dense African Olive infestation was identified, with an omission error of 7.5% and a commission error of 5.4%. African Olive was found to occur on the steepest slopes (mean slope 14.3°) of the vegetation classes examined, with aspect analysis identifying a high prevalence on south- and southwest-facing slopes. The analysis also quantified the level of African Olive infestation in endangered ecological communities, with Western Sydney Dry Rainforest (25% affected) and Moist Shale Woodland (28% affected) identified as most vulnerable to African Olive invasion. Conclusion: The distribution of African Olive can be efficiently mapped at a landscape scale. This technique, used in association with additional spatial datasets, identified African Olive as a significant environmental weed in SW Sydney, occupying a greater area than previously recognised and threatening several endangered native vegetation communities.     

植被叶面积指数遥感监测模型

叶面积指数是植被定量遥感的重要参数,区域的时序列叶面积指数揭示了区域生态的演化过程,反演方法上主要是通过植被指数建立相关模型实现的,对于不同地区或不同气候带而言,模型的通用性以及各种植被指数在模型中的灵敏度都需做进一步的探讨。以江苏省宜兴市作为研究区,采用2002年8月22日获得的Landsat-5TM图像数据和2003年8月23～26日采用LAI-2000进行的野外实测植被叶面积指数(LAI)数据,分别探讨了植被指数(VI)与LAI的一元、多元线性回归模型和非线性回归模型,其中的非线性回归模型包括对数、指数、乘幂和多项式回归模型。结果表明,VI与LAI之间的最佳回归模型为多元线性回归模型,R2达0.864;采用逐步选择剔除法,遴选出了用于回归模型的植被指数为RVI、PVI、SAVIL=0.35、MSAVI、ARVIγ=1、ARVIγ=0.5和SARVI。经模型LAI=-ln((VI-VI∞)/(VIg-VI∞))/KVI检验,预测值(y)与实测值(x)的拟合度较好y=0.5345x 1.3304,R2为0.7379。RVI与LAI的三次多项式回归模型也较好,R2为0.7806。再次为RVI与LAI的一元线性回归模型,R2为0.7726,比值植被指数RVI在反演叶面积指数模型中具有较高的灵敏度。     

基于遥感生态指数的雄安新区生态质量评估

城镇化建设的持续推进给生态环境带来的压力日益增加,多方位、客观、准确、快速测算区域生态环境质量是生态学研究的一个重点.本研究从绿度、湿度、热度、干度4方面分别提取了归一化植被指数(NDVI)、湿度指数(WET)、地表温度(LST)、归一化建筑-土壤指数(NDBSI)4个分量指标,采用基于ENVI平台的主成分分析技术集成所选指标,基于新型遥感生态指数(RSEI)对1995—2015年雄安新区生态质量进行评估.结果表明: 1995、2004和2015年,雄安新区的RSEI均值分别为0.724、0.710、0.682,生态质量总体呈下降趋势;1995—2015年间,研究区RSEI主要由4、5级向1、2、3级转变,生态质量改善和恶化的面积分别占总面积的8.9%和20.9%,生态改善区域主要位于雄县东部和南部,主要原因在于该区域大面积的林地和园地受到当地政府的高度重视和严格保护,生态质量恶化区域主要位于城镇外围以及白洋淀周边,原因在于白洋淀水域面积的锐减和城市化的不断推进;RSEI与各分量指标的平均相关系数为0.804,均高于各分量指标间的平均相关系数,表明RSEI能较好地综合各分量指标信息,全面准确反映研究区生态质量状况.     

Inferring species decline from collection records: roller dung beetles in Italy (Coleoptera, Scarabaeidae)

The decline of roller dung beetles (Coleoptera, Scarabaeidae) in Italy, at national and regional level, was described using a database of both literature and unpublished data, since the late of 19th century. The probability of finding roller species was assessed for each decade of the 20th century in order to detect changes in their distribution and status. An analysis of decline was performed using a complementary approach of different extinction indexes, according to IUCN criteria. During the 20th century, both the absolute number of records and the UTM cells where roller beetles were found increased clearly as a consequence of the escalation of entomological surveys. Nevertheless, comparing R species (rollers) with all the scarab dung beetles from the first to the last quarter of the 20th century, the relative frequency of roller records decreased by 31%, while the relative number of occupied UTM cells dropped by 23%. Six roller species showed a significant decline in Italy from the first to the second part of the 20th century, and nine in the last 30years. Other two species disappeared from the majority of the northern regions. Finally, the values of all the extinction indexes were strongly correlated and detected a high risk of extinction in Italy for six species. A gradual change in land use during the last three decades, consisting of a reduced extension of grasslands in favour of either intensive agriculture or reforestation after abandonment of livestock raising, was likely the main factor inducing decline and local extinction of roller species.     

林地叶面积指数遥感估算方法适用分析

叶面积指数是与森林冠层能量和CO2交换密切相关的一个重要植被结构参数,为了探讨估算林地叶面积指数LAI的遥感适用方法和提高精度的途径,利用TRAC仪器测定北京城区森林样地的LAI,从Landsat TM遥感图像计算NDVI、SR、RSR、SAVI植被指数,分别建立估算LAI的单植被指数统计模型、多植被指数组合的改进BP神经网络,获取最有效描述LAI与植被指数非线性关系的方法并应用到TM图像估算北京城区LAI。结果表明,单植被指数非线性统计模型估算LAI的精度高于线性统计模型;多植被指数组合神经网络中,以NDVI、RSR、SAVI组合估算LAI的精度最高,估算值与观测值线性回归方程的R2最高,为0.827,而RMSE最低,为0.189,神经网络解决了多植被指数组合统计模型非线性回归方程的系数较多、较难确定的问题,可较为有效的应用于遥感图像林地LAI的估算。     

Measuring Rao's Q diversity index from remote sensing: An open source solution

Measuring biodiversity is a key issue in ecology to guarantee effective indicators of ecosystem health at different spatial and time scales. However, estimating biodiversity from field observations might present difficulties related to costs and time needed. Moreover, a continuous data update for biodiversity monitoring purposes might be prohibitive. From this point of view, remote sensing represents a powerful tool since it allows to cover wide areas in a relatively low amount of time. One of the most common indicators of biodiversity is Shannon's entropy H′, which is strictly related to environmental heterogeneity, and thus to species diversity. However, Shannon's entropy might show drawbacks once applied to remote sensing data, since it considers relative abundances but it does not explicitly account for distances among pixels’ numerical values. In this paper we propose the use of Rao's Q applied to remotely sensed data, providing a straightforward R-package function to calculate it in 2D systems. We will introduce the theoretical rationale behind Rao's index and then provide applied examples based on the proposed R function.     

基于改进遥感生态指数的宁夏沿黄平原区生态环境质量评价

区域生态环境质量评价是国民经济建设与可持续性发展规划的基础，是生态学研究的主要方向之一。以土地利用/覆盖数据和Landsat OLI数据为基础，分别在ArcGIS和GEE平台上进行景观多样性指数（Landscape Diversity Index，LDI）与归一化植被指数（Normalized Difference Vegetation Index，NDVI）、湿度（Wet Index，WI）、归一化裸土和建筑指数（Normalized Difference Building-Soil Index，NDBSI）、遥感生态指数（Remote Sensing Based Ecological Index，RSEI）和改进遥感生态指数（Modified Remote Sensing Ecological Index，MRSEI）的计算。在LDI最佳尺度约束下分析表明，宁夏沿黄平原区景观多样性指数具有显著尺度依赖特征（P<0.001），阈值出现在3000 m×3000 m。主成分分析（Principal Component Analysis，PCA）解释了研究区改进遥感生态指数主要受到NDVI和LDI影响，其中NDVI是PC1（特征值贡献率68.98%）的决定因子，特征向量为0.8901；LDI为次要决定因子，特征向量为-0.4146，该分量在MRSEI计算中分值较高。LDI是PC2（特征值贡献率28.76%）的决定因子，特征向量为0.9100；NDVI为次要决定因子，特征向量为0.4056，该分量在MRSEI计算中分值较低。从MRSEI在应用中可信性来看，其在分析中采用LDI替代LST有效地避免了RSEI分析中NDBSI和LST之间存在的生态学意义重复表达和多因子向量投影中的高度聚集。研究区空间异质性主要以"差"和"较差"级别分布在不同土地利用/覆盖类型交错区且以环绕研究区为主要特点。在"差"到"好"梯度上，斑块密度为减少趋势由8.3个/km²减少到5.9个/km²，而平均斑块面积呈增加趋势由0.120 km²增加到0.169 km²。综合来看宁夏沿黄平原区生态环境质量总体MRSEI值为0.0117刚好超过"较好"水平下限。     

A parcel-scale assessment tool to measure sustainability through urban ecosystem components: The MUSIX model

In recent years a number of urban sustainability assessment frameworks are developed to better inform policy formulation and decision-making processes. This paper introduces one of these attempts in developing a comprehensive assessment tool—i.e., Micro-level Urban-ecosystem Sustainability IndeX (MUSIX). Being an indicator-based indexing model, MUSIX investigates the environmental impacts of land-uses on urban sustainability by measuring urban ecosystem components in local scale. The paper presents the methodology of MUSIX and demonstrates the performance of the model in a pilot test-bed—i.e., in Gold Coast, Australia. The model provides useful insights on the sustainability performance of the test-bed area. The parcel-scale findings of the indicators are used to identify local problems considering six main issues of urban development—i.e., hydrology; ecology; pollution; location; design, and; efficiency. The composite index score is used to propose betterment strategies to guide the development of local area plans in conjunction with the City's Planning Scheme. In overall, this study has shown that parcel-scale environmental data provides an overview of the local sustainability in urban areas as in the example of Gold Coast, which can also be used for setting environmental policy, objectives and targets.     

基于遥感生态指数的道路网络生态效应分析——以福州市为例

以2000年和2016年两期Landsat影像为基础数据源,借助遥感生态指数（RSEI）对福州市生态环境进行评价,在此基础上,从道路缓冲区、城乡梯度带、剖面线三种不同取样方法定量探讨RSEI对路网的响应机制;再以500 m×500 m、1000 m×1000 m、1500 m×1500 m、2000 m×2000 m、2500 m×2500 m、3000 m×3000 m不同尺度的网格划分空间单元,运用全局空间自相关、地理加权回归分析等方法分析了道路核密度（KDE）和RSEI及其之间关系的空间异质性。结果表明：从2000年到2016年,福州市生态环境好的区域面积增幅大于生态环境差的区域面积,生态环境质量向好的方向发展。各类型道路缓冲区的RSEI变化规律都是呈从0 m到3000 m逐渐上升的趋势,其中国道、省道、县道、乡镇道路影响的阈值分别在900、900、450、750 m左右。在城乡梯度分析中,RSEI曲线的变化规律都是随着与行政中心距离的增大而增大,到达一定阈值后趋于平缓,甚至还有小幅度的下降,区级的影响阈值在20 km左右,县级的影响阈值在12 km左右;而KDE曲线的变化规律与RSEI相反,其变化阈值与RSEI正好对应。剖面线所经过的行政中心处,其RSEI为低值,KDE为高值,西北方向的内陆地区RSEI高于东南方向的沿海地区。在多尺度的地理加权回归分析中,1500 m×1500 m和2000 m×2000 m这两个网格单元采样下的空间集聚性较强,空间异质性明显,总体上来看,RSEI与KDE呈现负相关关系,且相关关系存在空间分异,负回归系数主要分布在研究区的中心区域。研究结果可为福州市生态建设和路网规划提供参考依据。     

An ecological assessment process based on integrated remote sensing model: A case from Kaikukang-Walagan District,Greater Khingan Range,China

As the impacts of global climate change, rapid economic development, and anthropogenic activities on the environment are intensifying, it is becoming increasingly apparent that we need to understand ecological conditions and their responses to climate change and human disturbances. The objective of this study was to present an ecological assessment of the Kaikukang–Walagan District using the remotely sensed ecological index (RSEI) and the newly introduced integrated ecological environment index (IEEI). This assessment will reveal the ecological responses to disturbances, and place-specific emphasis on ecological conservation. Various data such as Landsat images, advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM), moderate-resolution imaging spectroradiometer (MODIS) water vapor products, meteorological records, soil thickness, and soil N content data were collected and sampled. First, land surface temperature (LST), normalized difference vegetation index (NDVI), brightness, and wetness were obtained. Second, the RSEI was determined using LST, NDVI, brightness, and wetness via principal component analysis (PCA). Subsequently, IEEI was derived from the band operation between the standardized RSEI (RSEI_S) and slope, soil thickness, and soil N content data. The results show that the mean RSEI_S for 2000, 2002, 2007, 2011, and 2017 ranged from 0.26 to 0.48, and the coefficient of variation was 0.22. The number of areas with very good or excellent ecological conditions increased between 2000 and 2002, then fluctuated between 2002 and 2011, and reached a peak in 2017. The influence of climate change in the study area was not evident. The standardized IEEI (IEEI_S) revealed that most of the study areas possessed excellent or very good ecological conditions; areas with good or fair ecological conditions were primarily located and bare land surrounded by vegetation, and areas with poor ecological conditions were primarily distributed in the urban areas of Walagan and Xiufeng. It was also shown that the IEEI is suitable for a comprehensive ecological assessment incorporating multiple ecological factors.     

基于多源遥感数据的农业干旱监测模型构建及应用

干旱监测问题是干旱灾害模拟与预警及旱灾防灾减灾的关键。基于2001-2013年淮河流域40个气象站资料、28个土壤墒情站点和中分辨率成像光谱仪（MODIS）多源遥感数据,采用SEN趋势法和标准化降水蒸散指数（SPEI）等方法,综合了大气-植被-土壤相互作用等多元成因,构建了适用于淮河流域多源综合遥感干旱监测模型,探讨淮河流域干旱时空规律。研究表明：（1）基于多源数据构建综合干旱监测模型,利用土壤墒情和典型年份干旱监测对综合干旱监测模型适用性进行评价,通过了P < 0.01的显著性检验,构建的模型可综合反映出农业和气象干旱多源信息;（2）淮河流域干旱面积和干旱频率大都集中在4-5月和7-9月,9月份受旱面积最大。河南省是淮河流域受旱频率最高,其干旱面积占淮河流域多年平均干旱面积比重最大（38%）,其次是安徽（22%）,旱地受旱面积比重大于水田受旱面积比重;（3）淮河流域2、3和5月干旱有显著减弱趋势;而1、4和6月则有增强趋势。淮河流域小麦灌浆-成熟时期（4-6月）缺水对小麦粮食产量影响显著,综合淮河流域干旱趋势变化,需强化淮河流域4月份小麦的干旱监测与旱灾预警。     

Radar aeroecology: exploring the movements of aerial fauna through radio-wave remote sensing

An international and interdisciplinary Radar Aeroecology Workshop was held at the National Weather Center on 5-6 March 2012 on the University of Oklahoma campus in Norman, OK, USA. The workshop brought together biologists, meteorologists, radar engineers and computer scientists from 22 institutions and four countries. A central motivation behind the Radar Aeroecology Workshop was to foster better communication and cross-disciplinary collaboration among a diverse spectrum of researchers, and promote a better understanding of the ecology of animals that move within and use the Earth's lower atmosphere (aerosphere).     

Satellite remote sensing of grasslands: from observation to management

Aims Grasslands are the world's most extensive terrestrial ecosystem, and are a major feed source for livestock. Meeting increasing demand for meat and other dairy products in a sustainable manner is a big challenge. At a field scale, Global Positioning System and ground-based sensor technologies provide promising tools for grassland and herd management with high precision. With the growth in availability of spaceborne remote sensing data, it is therefore important to revisit the relevant methods and applications that can exploit this imagery. In this article, we have reviewed the (i) current status of grassland monitoring/observation methods and applications based on satellite remote sensing data, (ii) the technological and methodological developments to retrieve different grassland biophysical parameters and management characteristics (i.e. degradation, grazing intensity) and (iii) identified the key remaining challenges and some new upcoming trends for future development.Important findings The retrieval of grassland biophysical parameters have evolved in recent years from classical regression analysis to more complex, efficient and robust modeling approaches, driven by satellite data, and are likely to continue to be the most robust method for deriving grassland information, however these require more high quality calibration and validation data. We found that the hypertemporal satellite data are widely used for time series generation, and particularly to overcome cloud contamination issues, but the current low spatial resolution of these instruments precludes their use for field-scale application in many countries. This trend may change with the current rise in launch of satellite constellations, such as RapidEye, Sentinel-2 and even the microsatellites such as those operated by Skybox Imaging. Microwave imagery has not been widely used for grassland applications, and a better understanding of the backscatter behaviour from different phenological stages is needed for more reliable products in cloudy regions. The development of hyperspectral satellite instrumentation and analytical methods will help for more detailed discrimination of habitat types, and the development of tools for greater end-user operation.     

Landscapes of human evolution: models and methods of tectonic geomorphology and the reconstruction of hominin landscapes

This paper examines the relationship between complex and tectonically active landscapes and patterns of human evolution. We show how active tectonics can produce dynamic landscapes with geomorphological and topographic features that may be critical to long-term patterns of hominin land use, but which are not typically addressed in landscape reconstructions based on existing geological and paleoenvironmental principles. We describe methods of representing topography at a range of scales using measures of roughness based on digital elevation data, and combine the resulting maps with satellite imagery and ground observations to reconstruct features of the wider landscape as they existed at the time of hominin occupation and activity. We apply these methods to sites in South Africa, where relatively stable topography facilitates reconstruction. We demonstrate the presence of previously unrecognized tectonic effects and their implications for the interpretation of hominin habitats and land use. In parts of the East African Rift, reconstruction is more difficult because of dramatic changes since the time of hominin occupation, while fossils are often found in places where activity has now almost ceased. However, we show that original, dynamic landscape features can be assessed by analogy with parts of the Rift that are currently active and indicate how this approach can complement other sources of information to add new insights and pose new questions for future investigation of hominin land use and habitats.     

Indices of bird-habitat preference from field surveys of birds and remote sensing of land cover: a study of south-eastern England with wider implications for conservation and biodiversity assessment

Aim This paper describes the development of novel indices of bird‐habitat preference to examine bird species’ use of habitats and their distributions relative to habitats. It assesses the implications for bird conservation regionally and the scope for biodiversity assessments generally. Location A 200 km by 400 km area of farmland with seminatural and urban areas, covering south‐eastern England. Methods Cluster analysis was used to link birds to landscapes. Cluster centroid coordinate values were processed to derive indices of bird‐habitat preference. Further developments assessed the relative values of individual habitats for birds. Results Clustering objectively linked birds to landscapes. Maps of the clusters showed strong regional patterns associated with distinctive habitat assemblages. Derived indices related bird species directly to individual habitats and habitats to birds. Even rare species and scarce habitats showed successful linkages, often to each other. Objective corroboration strongly supported the associations of coastal, wetland, urban and woodland birds and habitats; but, it suggested that farmland birds, whose numbers have nearly halved since 1977, may prefer alternative habitats. Main conclusions Land cover maps from remote sensing provide an effective way to link birds to habitats and vice versa. Thus, generalized habitat maps might be used to extrapolate localized or sample‐based bird observations or the results of autecological studies, helping to predict and understand bird distributions in the wider countryside. The weak links between farmland birds and farmland habitats in a region dominated by farming, suggests that reasons for the decline in farmland birds may be deep seated and thus hard to reverse. The procedures described are repeatable elsewhere and applicable more generally to evaluate landscapes and biodiversity. It is suggested that remote sensing could rarely be bettered as a means of assessing habitats, comprehensively, over wide areas, in most parts of the world.