Mangrove mapping in Ecuador: The impact of shrimp pond construction

A cooperative mangrove mapping project between the Ecuadorian Center for Remote Sensing (CLIRSEN) and the University of Delaware was begun in August 1982. The objectives of the project were to create historical maps of mangrove ecosystem extent and change, while transferring aerial photographic interpretation techniques to Ecuadorian personnel. The result of this cooperation was a series of three 125,000 scale maps of historical mangrove extent and change from 1966 to 1982 in the southern Gulf of Guayaquil. This multitemporal study showed a 16% decrease in mangrove extent and a 27% increase in shrimp pond development. If these rates of change prevail into the future, mangroves in Ecuador will reach parity with shrimp ponds in 1984 and completely disappear by mid-1990. Recognizing the significance of this loss to shellfish and fish production along the coast, Ecuadorian scientists at CLIRSEN have subsequently initiated a nationwide mangrove mapping program to create a historical base for future mangrove management strategies.     

两种应用场景下NDVI时间序列数据拟合方法研究

植被覆盖指数（NDVI）时间序列数据集包含地表植被的长势、生长周期、时空变化等信息,其拟合重建结果可应用于物候信息提取、生态质量评价、人类活动扰动识别、覆被变化动态监测等方面。基于TIMESAT软件,选取物候参数提取和扰动识别2个应用场景,结合地面站点数据和Jacknife法模拟数据,对比分析非对称高斯函数拟合法（AG法）、双Logistic函数拟合法（D-L法）和Savitzky-Golay滤波法（S-G法）3种方法的拟合效果。结果表明：（1）3种方法拟合重建后提取的生长开始时间（SOS）、生长结束时间（EOS）、生长周期（LOS）等物候参数接近站点数据,AG法和D-L法保持NDVI时序曲线整体变化特征的能力较强,提取的SOS和EOS更接近站点数据;（2）人类活动扰动识别应用场景中,S-G法在滤波时能够最大限度地保留时序曲线细节变化,恢复速率相关系数达到0.618,回归估计标准差低于AG法和D-L法,因此识别精度最优。     

植物病虫害的遥感探测

本文概述了应用遥感技术探测植物病虫害的原理、途径、优缺点与发展过程.着重报导了最近在安徽省孤山林场开展的从TM图象提取森林松毛虫害的成功试验,并展望了应用遥感技术提高植物病虫害防治水平的前景.     

基于星载雷达的洪水灾害淹没范围获取方法探讨

探讨了以星载雷达监测所获得的数据为数据源,提取洪水灾害淹没范围的基本原理和方法,并以１９９５年５月洞庭湖遭受洪水时所获得的ＪＥＲＳ－１ＳＡＲ数据为例,说明了该方法的应用及其有效性。     

高分辨率卫星遥感数据在白衣庵滑坡调查研究中的应用

利用Quickbird-2卫星遥感数据对白依庵滑坡进行了调查研究。首先选取321和432波段进行彩色合成,并且与pan波段进行了分辨率融合,对融合后的图像进行正射校正作为遥感解译底图。从遥感影像上提取了白依庵滑坡的各要素,进行了稳定性评价和危害性分析,并提出了防治措施建议。根据研究结果可知,在现阶段利用Quickbird-2高分辨率卫星遥感数据进行滑坡研究具有无比的优越性、实用性和经济性。     

Relative density of finds for assessing similarity-based maps of orchid occurrence

Similarity-based mapping of the expected distribution of 10 orchid species was conducted in a study area covering 300 km² in south-eastern Estonia. The observation track and species finds were recorded during fieldwork. Absence locations were generated on the line of observation track. Both presence and absence sites having an in-between distance of at least 100 m were used as training data. Expected presence/absence of a species was calculated according to similarity between the predictable location and selected observations (examples) of presence and absence sites. For each species, the machine learning system identified the best predictive sets by selecting the most useful variables out of 136 map and remote sensing features. Similarity-based estimations were evaluated both by training fit and by independent verification data. Reliability of the predictive maps was expressed also by usefulness ratios—the densities of validation find sites (1) in the predicted presence area relative to the density of those in the predicted absence area, and (2) relative to the share of the observation track in the predicted presence area and in the predicted absence area. The predictive mapping was most efficient for Dactylorhiza incarnata, D. russowii, Epipactis palustris, and Goodyera repens. We conclude that the profound coverage of observations on any larger area is unrealistic and the reliability of similarity-based predictive maps depends on the representativity of existing records relative to the diversity of the study area. The investigation showed that the studied species are much more common in nature than the records in the national database indicate.     

密云水库流域植被覆盖度变化对输沙量的影响

封闭流域中,泥沙的产生是多种因素相互作用,相互制约的结果,而在这些众多的环境影响因素中,植被是土壤侵蚀中最重要的环境控制因子,目前,植被覆盖度变化对输沙量的影响一直是区域生态环境研究中比较热门的话题。文章使用遥感(Remote Sensing(RS))、地理信息系统(Geographic Information System(GIS))与统计分析相结合的方法评价了密云水库流域内2个子流域出口处2002年至2005年植被覆盖度变化对输沙量的影响。密云水库流域多为山地,其降雨具有明显的季节性。本文的主要目的在于分析2002年至2005年植被覆盖度变化对流域输沙量的影响,并分析了植被覆盖度变化对气候改变及人类活动的综合影响,结果表明:在密云水库流域内,输沙量是降雨情况和人为因素引起的地表植被覆盖度变化情况的综合反映,人口增长、经济发展和城市化是密云水库流域内引起土地利用变化和地表植被覆盖度变化的主要驱动力。并且,输沙量可以被看作是一个很好的指标来定量分离出生物生理和人为的影响,并从中能够找出在流域生态系统中获得显著结果关键的临界点。研究结果对制定流域的合理开发和管理计划将有所帮助。     

A three-component model of phytoplankton size class for the Atlantic Ocean

A three-component model was developed which calculates the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) to the overall chlorophyll-a concentration in the Atlantic Ocean. The model is an extension of the Sathyendranath et al. (2001) approach, based on the assumption that small cells dominate at low chlorophyll-a concentrations and large cells at high chlorophyll-a concentrations. Diagnostic pigments were used to infer cell size using an established technique adapted to account for small picoeukaroytes in ultra-oligotrophic environments. Atlantic Meridional Transect (AMT) pigment data taken between 1997 and 2004 were split into two datasets; 1935 measurements were used to parameterise the model, and a further 241 surface measurements, spatially and temporally matched to chlorophyll-a derived from SeaWiFS satellite data, were set aside to validate the model. Comparison with an independent global pigment dataset (256 measurements) also supports the broader-scale application of the model. The effect of optical depth on the model parameters was also investigated and explicitly incorporated into the model. It is envisaged that future applications would include validating multi-plankton biogeochemical models and improving primary-production estimates by accounting for community composition.     

一种基于Landsat 8 OLI影像的水体信息提取方法研究

提出一种基于Landsat 8 OLI影像提取水体信息的斜率比值法（SR）,比对不同方法、不同类型水体和不同季节影像的数据,结果表明：SR法相比归一化差异水体指数法（NDWI）和改进的归一化差异水体指数法（MNDWI）,水体信息提取精度更高,且对阈值精确度的要求低,阈值一般设定为2.0;SR法适用于清澈水体、浑浊水体、浅水河滩等水体,对河流干流和较大支流的提取精度达到99%,细小支流、沟渠的提取精度为66%,面积较小的水体提取精度为65%;在冬季太阳高度角较低时,SR也能较好地去除阴影。     

基于MODIS数据的林火识别方法研究

森林火灾是一种世界性的重要自然灾害。遥感、地理信息系统(简称GIS)、网络等现代高新技术的出现和发展。为人类研究防灾减灾的工作提供了更为方便的条件。该文在分析MODIS数据各波段特性、对地表亮温法和亮温一植被指数法火点识别的精度进行比较的基础上,结合CIS技术,利用地面信息,采用亮温一植被指数法,建立了基于MODIS数据的林火识别模型。经实验验证,该方法总体判识精度优于80％,能较好地满足林火检测需求,同时还可以获得燃烧植被的类型。