浙江天童国家森林公园景观的遥感分类与制图

利用Landsat-TM多时相数据,采用非监督分类方法,对浙江省天童国家森林公园的景观进行分类。并利用野外实地调查的数据进行检验和校正。结果表明,天童国家森林公园范围内的景观可分为常绿阔叶林、成熟常绿阔叶林、次生常绿-落叶阔叶林、山脊常绿-落叶阔叶林、谷地常绿-落叶阔叶林、林缘灌丛、次生灌丛、针叶林(杉木)、竹林、生长作物的农田／菜园地、旱地、裸土、居住区、水体14个类型,这14个景观类型,根据植物群落学分类的群落复合体(cammunity complex)和群落复合体的地-综合群落学(Geo-synsociology)的方法,归并为山坡常绿阔叶林、常绿落叶阔叶混交林、人工林(针叶林、竹林)、农田、水体、居住区6个景观单元。在景观分类和合并的基础上,对天童国家森林公园的景观进行了制图。     

森林生态系统生物物理参数遥感反演研究进展

论述了利用遥感技术反演推算森林生态系统主要生物物理参数：叶面积指数、吸收光合有效辐射、净第一性生产力和生物量的技术、方法和模型及各个参量之间的相互关系研究进展,阐述了各研究方法、模型的特点、优势及局限性。特别论述了净第一性生产力的森林冠层光合作用理论模型基础、微波遥感估算森林生物量的应用优势和理论模型,展示了遥感技术在森林生态学研究中广阔的应用前景,同时也指出现有研究中各生物物理参数的定量遥感估算还有待进一步深入研究。     

Assessing fragmentation and disturbance of west Kenyan rainforests by means of remotely sensed time series data and landscape metrics

Biodiversity in tropical rainforests is heavily influenced by land use/cover change (LUCC), but so far there have been few LUCC studies conducted in Africa. We present several methods that make use of remotely sensed data and landscape metrics and allow for assessment of the development of land cover and thus forest fragmentation and disturbance over a substantial period of time. The study covers Kakamega Forest and its associated forest areas in western Kenya, over the last 30 years. The accuracy of a supervised multispectral classification of Landsat time series data encompassing seven time steps between 1972 and 2001 is numerically assessed using ground truth reference data considering the 2001 time step. Here, buffering the forest areas by 1 km, highest user's accuracies for the forest classes ‘near natural + old secondary forest’ (87.50%), ‘secondary forest’ (80.00%) and ‘bushland/shrubs’ (81.08%) are revealed. Images of a spatially distributed fragmentation index derived from the land cover time series by applying a three by 3 pixel‐sized moving window to determine forest pixels’ adjacency, highlight trends in forest fragmentation, e.g. the splitting into two separate forests along the Yala/Ikuywa corridor. Calculations of mean fragmentation indices for the Biodiversity Monitoring Transect Analysis in Eastern Africa (BIOTA‐East Africa) focus research areas are used to evaluate the fragmentation index and to demonstrate its potential to extrapolate (e.g. biological) field findings in space and time. Here we argue for a correlation of the fragmentation indices results not only with forest management regimes, but with population distribution and accessibility (e.g. by roads). A cluster analysis applying the isodata‐algorithm on the classification results of all seven times steps allows for a rapid visual assessment of the distinct pattern of typical land cover development trends since 1972. This reveals that parts of Kakamega Forest have experienced severe forest loss while others, especially in the north‐east, show signs of succession.     

基于多光谱影像的森林树种识别及其空间尺度响应

当前,不同空间分辨率卫星影像对森林类型识别结果中普遍存在的尺度效应,而且纹理参量对不同尺度下树种识别精度的影响仍缺乏广泛认知.本研究以中国东北旺业甸林场为研究区,采用观测时相同步、地理坐标匹配的GF-1 PMS、GF-2 PMS、GF-1 WFV,以及Landsat-8 OLI卫星传感器数据组成空间尺度观测序列(1、2、4、8、16、30 m),并结合支持向量机(SVM)模型,探讨了区域内5种优势树种遥感识别结果的尺度变化规律及其纹理特征参数的影响,同时检验了基于尺度上推转换影像的树种识别结果差异.结果表明: 影像空间分辨率对区域树种识别结果具有显著影响,其中,研究区森林树种识别的最佳影像分辨率为4 m,当分辨率降低至30 m时,树种识别结果最差.在1～8 m影像分辨率范围内,增加纹理信息能够显著提高不同优势树种的识别精度,使总分类精度提升了2.0%～3.6%,但纹理信息对16～30 m影像的识别结果没有显著影响.与真实尺度卫星影像相比,基于升尺度转换影像的树种识别结果及其尺度响应特征存在显著差异,表明在面向多个空间尺度的遥感观测和应用研究中,需要采用真实分辨率影像以确保结果的准确性.     

Habitat discrimination of juvenile sardines in the Aegean Sea using remotely sensed environmental data

Despite the importance of the recruitment process for small pelagic fish and the high economic importance of European sardine (Sardina pilchardus, Walbaum 1792) in the Mediterranean Sea, knowledge on the distribution and environmental characteristics of its nursery grounds is very limited. In the present study, we used pelagic trawl data collected during 1995–2006 to explore the spatial distribution of sardine juveniles in the Aegean Sea in early summer. Based on sardine abundance per length class, a cluster analysis was initially used to define hauls dominated by juveniles. In a subsequent step, Discriminant Function Analysis (DFA) was applied to discriminate stations with high relative abundance of juveniles using satellite environmental data and bottom depth. The parameters contributing mostly to the discrimination of juvenile grounds were sea level anomaly, photosynthetically active radiation, sea surface temperature, chlorophyll-α and bottom depth. The classification functions of DFA were finally used to post classify unsampled areas in the Greek Seas and the Mediterranean Sea in order to map grounds that meet characteristic environmental conditions for young sardine. Such areas were mostly located inshore, in semi-closed productive areas and often in proximity to river mouths, a pattern that is generally supported by existing information. Guest editor: V. D. Valavanis Essential Fish Habitat Mapping in the Mediterranean     

Univariate analysis of tsetse habitat in the common fly belt of Southern Africa using climate and remotely sensed vegetation data

Abstract Tsetse are vectors of trypanosomes that cause diseases both in humans and livestock. Traditional tsetse surveys, using sampling methods such as Epsilon traps and black screen fly rounds, are often logistically difficult, costly and time-consuming. The distribution of tsetse, as revealed by such survey methods, is strongly influenced by environmental conditions, such as climate and vegetation cover, which may be readily mapped using satellite data. These data may be used to make predictions of the probable distribution of tsetse in unsurveyed areas by determining the environmental characteristics of areas of tsetse presence and absence in surveyed areas. The same methods may also be used to characterize differences between tsetse species and subspecies. In this paper we analyse the distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes in southern Africa with respect to single environmental variables. For G.m.centralis the best predictions were made using the average NDVI (75% correct predictions; range > 0.37) and the average of the maximum temperature (70% correct predictions; 27.0–29.2°C). For G.m.morsitans the best prediction was given by the maximum of the minimum temperature (84% correct predictions; range > 18.8°C), and for G.pallidipes , also by the maximum of the minimum temperature (86% correct predictions; range > 19.6 °C). The following paper compares a range of multivariate techniques for making predictions about the distribution of these species in the same region.     

基于卫星遥感数据的黄淮海地区植被覆盖时空变化特征

利用1982—2003年GIMMS NDVI遥感数据,在进行合成、重采样和时间序列滤波处理的基础上,采用线性趋势分析、经验正交函数分解等方法,对中国黄淮海地区植被覆盖的时空特征进行了研究。结果表明:22年来黄淮海地区植被覆盖总体上呈略微增加的趋势,且该区域生长季有提前和延长的趋势;黄淮海大部分地区植被活动在增强的同时,局部地区出现了植被退化现象;从季节变化上看,春季上升和夏季下降趋势明显;林地为主的自然植被、草甸类自然植被和所有农业植被未变化类别占主导地位,而草原植被则以增加趋势为主。主要生长季的NDVI距平EOF分析表明,第1模态的主要特征是区域中间、北部和南端为正,四周为负变化;第2模态的主要特征是从东南向西北由正到负变化且正值区明显偏多;第3模态从东南向西北呈现"正-负-正"的空间分布,其中负值区大部分为以林地为主的自然植被区和一年一熟农业植被,正值区大部分为农耕区和草原牧区,该模态大致反映了农牧区和林区的NDVI分布型。     

Mapping tsetse habitat suitability in the common fly belt of Southern Africa using multivariate analysis of climate and remotely sensed vegetation data

Abstract The distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes are described in part of southern Africa, using a range of multivariate techniques applied to climate and remotely sensed vegetation data. Linear discriminant analysis is limited in its predictive power by the assumption of common co-variances in the classes within multivariate environment space. Maximum likelihood classification is one of a variety of alternative methods that do not have this constraint, and produce a better prediction, particularly when a priori probabilities of presence and absence are taken into account. The best predictions are obtained when the habitat is subdivided, prior to classification, on the basis of a bimodality detected on the third component axis of a principal component analysis. The results of the predictions were good, particularly for G.m.centralis and G.m.morsitans , which gave overall correct predictions of 92.8% and 85.1 %, with a Kappa index of agreement between the predion and the training data of 0.7305 and 0.641 respectively. For G.pallidipes , 91.7% of predictions were correct but the value of Kappa was only 0.549. Very clear differences are demonstrated between the habitats of the two subspecies Gmxentralis and G.m.morsitans.     

Measuring and controlling data quality in biological assemblage surveys with special reference to stream benthic macroinvertebrates

1. Biological assemblage surveys primarily aim to characterise species composition and relative abundance at one or more spatial or temporal scales. Data interpretation and conclusions are dependent on how well samples characterise the assemblage of interest. 2. Conventional measures of data quality, e.g. standard deviations or coefficients of variation, were designed for single variable estimation, and they are either insufficient or invalid for assessing the quality of data describing entire assemblages. Similarity indices take species composition and relative abundance into account and may be used to effectively measure and control the quality of data used to characterise assemblage structure. 3. The average Jaccard coefficient (JC) calculated across multiple pairs of replicate samples, i.e. autosimilarity JC (AJC), is conceptually and numerically related to the average coefficient of variation in the densities of all species recorded, a measure of sampling precision, and to the proportion of total species richness sampled, a measure of sampling accuracy. 4. We explored how AJC can be used to assess the effect of different potential sources of error on the quality of assemblage survey data, including the sampling effort used both within regions and at individual sites, the individuals collecting samples, sub‐sampling procedures, and consistency of taxon identification. 5. We found that the autosimilarity‐based approach overcomes most weaknesses associated with conventional measures of data quality and can be used to effectively measure and control the quality of assemblage survey data.     

近50年北京植被对全球变暖的响应及其时效--基于遥感数据和物候资料的分析

植被对全球变暖的响应方式及其程度问题是全球变化研究的焦点之一。利用1951～2000年的气温、降水等气候资料、1982～2000年的NOAA／AVHRR遥感数据和1951～2002年山桃始花的物候数据,分析了北京各气候参量与生态系统植被在年际和年内时间尺度上的变化规律及其关系。结果表明,北京近20年增温1．2E,增温态势显著;过去50年中,降水的年际变化小于生长季内的波动幅度。年NDVI最大值(VP)、平均值(VM)的年际变化曲线呈波动中缓慢上升的趋势,表明植被的生长状况总体上在变好或生长季在延长。VP出现日期(VPI))提前,20世纪90年代比80年代提前4．5d。山桃始花物候期的分析表明,北京1988年以后春季开始日期提前9．63d。时间尺度不同,各个气候指标对各植被指标的影响程度不同：①年际时间尺度,年均温影响VP、VM的时效为1年;月际水平上,除温度影响VM的时效为2个月外,各气候参量影响VP、VM的时效为1个月。年际尺度上,温度影响山桃始花时效为2年;月际尺度上,2、3、4月份温度影响山桃始花日期。     

The quality of animal habitats estimated from track activity and remote sensing data

A method is proposed for estimating the quality of animal habitats from field counts with positioning routes and tracks by means of GPS, multichannel Landsat data, digital elevation model, and discriminant analysis. The distribution of American and European minks is analyzed to demonstrate the principle of choosing an optimal method for analyzing the environmental characteristics that determine the distribution of species and for mapping and estimating the quality of habitats and the probability of track detection. The outlook and some problems of implementation of the proposed approach are discussed.     

多源数据融合技术在汶川地震生态环境影响应急评估中的应用

在实施汶川地震生态环境影响应急评估工作过程中,考虑到时间紧、范围大的现实情况,对空间数据处理技术与方法上进行了深入探索,成功地采用多源数据集成与融合技术,将不同传感器、不同空间分辨率、光谱分辨率、时间分辨率和不同格式的数据进行了集成与融合,大大提高了遥感影像的有效覆盖范围和灾害信息判读精度,快速、全面地实现了地震灾害对生态环境影响的初步评估,探索出应对巨灾后生态环境遥感监测与评估的基本方法与技术。最后,建议我国要加强生态环境本底数据库建设,完善部门间数据共享机制,促进多源数据集成与融合技术的推广与应用,为更好应对未来的生态灾难做准备。     

Sensitivity of Mexican water bodies to regional climatic change: three study alternatives applied to remote sensed data of Lake Patzcuaro

Historical aerial photography over closed basins enables the observation of lake surfaces at variable water levels and climatic conditions. Thus, the assessment at the landscape level of subtle variations in inundated areas depends on a suitable framework for processing historical imagery, frequently available at different scales and resolutions.The present paper deals with Lake Patzcuaro as a case study and the application of three analytical procedures to remote sensed data of 1974, including two maps commercially available and nine aerial photographs. Computer-based processing of images and further incorporation into GIS led to three different outputs: topographic map (TM-GIS), photomosaic 1 (P₁) and photomosaic 2 (P₂). Aerial photographs assemblages were georeferenced by means of GCP's, 86 located by means of INEGI vectorial polygons (P₁), and 40 determined directly at the field by GPS (P₂).In conclusion, TM-GIS lack of photointerpretation for the lake as an image derived from a topographic map; while P₂ involved an unacceptable RMS. P₁ thus became the best option for the calculation of areas not only because of the lower RMS associated, but the additional photointerpretation of limnological zones exclusive to aerial photographs. As a background picture, P₁ also facilitates the analysis of historical images on a comparative basis.     

玉米叶面积指数动态模拟的最适野外观测资料

基于锦州农田生态系统野外观测站2005-2011年多个品种的玉米大田试验资料,结合已经建立的玉米叶面积指数动态普适模型,探讨了准确模拟玉米叶面积指数动态所需的最适野外观测资料.结果表明: 准确模拟玉米叶面积指数动态至少需要3年的野外观测数据,且每年在生育期内至少需要进行4次观测.玉米生育期内的理想观测应为在出苗后20 d左右进行第1次观测,此后每月观测1次.
     

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.     

基于遥感的官厅水库水质监测研究

遥感监测具有监测面积广、速度快、成本低等优势,常用于大面积水质监测。以北京官厅水库为研究对象,通过野外和实验室测量数据建立水质参数遥感反演的生物光学模型,对夏季官厅水库的非色素颗粒物浓度、叶绿素a浓度和有色可溶性有机物(CDOM)浓度进行了反演。该模型研究的目的就是通过建立反演模型,利用卫星数据进行水质参数反演,从而得到大面积水体的水质分布图。采用CHRIS/Proba高光谱数据反演官厅水库的水体组分浓度,对库区水质反演要素的空间分布规律进行了分析。结果表明,所采用的遥感反演模型基本适用于官厅水库水质监测,反演出的叶绿素a、总悬浮物和CDOM的空间分布与实际测量值的空间分布基本吻合。