巢湖蓝藻水华时空分布(2000-2015年)

巢湖是我国五大淡水湖之一,近年来水体富营养化严重,蓝藻水华频繁暴发.通过收集2000-2015年晴好天气下2478景MODIS Terra和Aqua影像,利用浮游藻类指数,提取巢湖蓝藻水华时空分布数据.结果显示,巢湖蓝藻水华覆盖面积、暴发频率以及持续时间都在增加,每年最初暴发时间提前.从分布上来看,西巢湖依然严重,中巢湖、东巢湖水华暴发面积较以往大大增加;过去16年内巢湖蓝藻水华暴发频率持续增长,其中2007年最为严重,2008-2010年暴发频率出现缓和,此后又出现增长趋势.这些研究结果有助于掌握蓝藻水华的情况,为巢湖科学治理提供了数据支持.     

基于MODIS数据的甘肃主要水库水体面积变化特征

掌握甘肃主要水库的水体面积变化规律,对"甘肃省国家生态安全屏障综合试验区"建设具有重要参考意义。基于2000—2014年MODIS的8 d合成地表反射率产品MOD09资料,利用WI1水体指数,对甘肃四大水库双塔、昌马、红崖山和刘家峡的水体面积进行监测,并与兰州区域气候中心实时接收的卫星资料目视解译结果进行对比、建立相关关系,进而对上述水库水体面积变化状况进行研究。结果表明:甘肃四大水库8 d合成产品MOD09反演的水体与卫星实时资料目视解译结果均具有很好的相关性,且变化趋势较一致,MOD09产品反演结果能够反映水体实时变化状况,可用于水库水体面积的变化特征研究。近10 a多,甘肃四大水库水体面积表现出春季或秋季较大、夏季最小的年内分布特征,各水库水体面积的年际变化趋势较复杂,疏勒河上的昌马和双塔水库春、夏、秋三季水体面积的年际变化趋势不明显,而红崖山和刘家峡水库水体面积均呈波动增加趋势,这对甘肃中西部农业灌溉极为有利。     

A MODIS time series data based algorithm for mapping forest fire burned area

Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and climate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter (MODIS) time series data in Heilongjiang Province, China. The algorithm is divided into two steps: Firstly, the ‘core’ pixels were extracted to represent the most possible burned pixels based on the comparison of the temporal change of Global Environmental Monitoring Index (GEMI), Burned Area Index (BAI) and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ‘core’ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the highest accuracy of 96.61%.     

An algorithm to classify and monitor seasonal variations in vegetation phenologies and their inter-annual change

The algorithm presented in this paper classifies vegetation from annual Normalized Difference Vegetation Index (NVDI) time series according to the shape of the temporal cycle. Shape is described using the Fourier components’ magnitude and phase. The degree of an NDVI cycle’s similarity to a predefined reference cycle is measured by the similarity in their amplitude ratios and in their phase differences. Tolerable deviations from the ideal ratios and differences can be set by the user depending on individual accuracy requirements. Tolerable vegetation coverage variation within a shape class is another user defined variable. The algorithm is invariant to cycle modifications including temporal shifts, vertical displacements, and intensity variations, modifications that may be caused by differences in climate, soil (-type, -water, -fertility), or topography, but are unrelated to the vegetation type. The output is a highly consistent clustering of NDVI cycles according to their shapes, which can be linked to distinct vegetation types or land use practices. Intra-class coverage variations in the form of continuous fields measured relative to the reference cycle provide additional information about vegetation covers. Based on the same principles, inter-annual vegetation changes can be monitored with the possibility to distinguish between coverage fluctuations and phenological variations/changes.The algorithms are independent from scene statistics and can be used to create spatially and temporally comparable classifications. Their potential is demonstrated using a 250 m MODIS NDVI time series (version 4) from the Middle East.     

Wide‐area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray–Darling River Basin,Australia

Floodplain red gum forests (Eucalyptus camaldulensis plus associated grasses, reeds and sedges) are sites of high biodiversity in otherwise arid regions of southeastern Australia. They depend on periodic floods from rivers, but dams and diversions have reduced flood frequencies and volumes, leading to deterioration of trees and associated biota. There is a need to determine their water requirements so environmental flows can be administered to maintain or restore the forests. Their water requirements include the frequency and extent of overbank flooding, which recharges the floodplain soils with water, as well as the actual amount of water consumed in evapotranspiration (ET). We estimated the flooding requirements and ET for a 38 134 ha area of red gum forest fed by the Murrumbidgee River in Yanga National Park, New South Wales. ET was estimated by three methods: sap flux sensors placed in individual trees; a remote sensing method based on the Enhanced Vegetation Index from MODIS satellite imagery and a water balance method based on differences between river flows into and out of the forest. The methods gave comparable estimates yet covered different spatial and temporal scales. We estimated flood frequency and volume requirements by comparing Normalized Difference Vegetation Index values from Landsat images with flood history from 1995 to 2014, which included both wet periods and dry periods. ET during wet years is about 50% of potential ET but is much less in dry years because of the trees' ability to control stomatal conductance. Based on our analyses plus other studies, red gum trees at this location require environmental flows of 2000 GL yr^?1 every other year, with peak flows of 20 000 ML d^?1, to produce flooding sufficient to keep them in good condition. However, only about 120–200 GL yr^?1 of river water is consumed in ET, with the remainder flowing out of the forest where it enters the Murray River system. Copyright © 2015 John Wiley & Sons, Ltd.     

利用MODIS图像反演海岸带气溶胶光学特性

针对中国沿海地区海洋表面高反射率和强吸收性气溶胶粒子多的特点,提出了利用卫星图像反演该区域气溶胶光学特性的新算法。以MODIS图像为例进行研究,首先利用气溶胶观测站对中国海岸带气溶胶粒子的长期观测数据统计出气溶胶粒子模式;再应用线性分层离散坐标法对这些气溶胶模式计算出不同气溶胶光学厚度和不同几何条件下的表观反射率组成的查找表;然后利用MODIS长波段的图像和查找表完成浑浊水域上空的大气气溶胶光学特性的反演;最后采用清洁日地基观测结果对该算法的正确性和适用性进行了验证。     

国内外7种常用南极被动微波海冰密集度产品的比较与评估

围绕国内外机构发布的南极被动微波海冰密集度产品（PM-SIC）的差异和精度问题,应用MODIS和Sentinel-1反演的海冰密集度,对德国不莱梅大学（产品UB-AMSR2/ASI）、美国冰雪数据中心（产品NSIDC-SSMIS/NT、NSIDC-SSMIS/CDR、NSIDC-AMSR2/NT2）、欧洲气象卫星应用组织海洋与海冰卫星应用中心（产品OSI-SAF/BR-BST）、国家卫星海洋应用中心（产品NSOAS-SMR/NT）和国家卫星气象中心（产品NSMC-MWRI/NT2）发布的7种南极海冰密集度产品进行比较与评估。结果表明：（1）NSIDC-SSMIS/NT与NSIDC-SSMIS/CDR海冰密集度具有较高的一致性（平均偏差为−0.08%,相关系数为0.99）,NSOAS-SMR/NT与NSIDC-AMSR2/NT2间的差异最大（平均偏差为−14.41%,相关系数为0.81）;（2）7种PM-SIC的变化趋势一致,NSOAS-SMR/NT和NSMC-MWRI/NT2与其他PM-SIC的偏差具有明显的季节性差异;（3）NSOAS-SMR/NT和NSMC-MWRI/NT2与其他PM-SIC均在印度洋扇区、别林斯高晋海和阿蒙森海扇区绝对偏差较大,在罗斯海扇区差异最小。偏差较大的区域主要分布在海冰边缘区及近陆地海域,在高密集度区域差异较小;（4）应用MODIS与Sentinel-1反演的海冰密集度对7种PM-SIC验证表明,NSMC-MWRI/NT2与验证数据的一致性最高。NSOAS-SMR/NT、UB-AMSR2/ASI和OSI-SAF/BR-BST海冰密集度偏低,而NSMC-MWRI/NT2、NSIDC-AMSR2/NT2、NSIDC-SSMIS/CDR和NSIDC-SSMIS/NT海冰密集度偏高。不同海冰密集度产品的比较与评估可为发展遥感反演算法、研制和应用高质量的海冰密集度产品,更好地监测南极海冰动态变化提供依据和参考。     

多源遥感数据时空融合模型应用分析

多源遥感数据时空融合模型是解决目前遥感数据获取能力不足问题的重要方法之一,当前主要融合方法的研究,集中于平原区域,缺乏复杂条件下的多源遥感数据融合技术的应用研究。针对我国南方复杂条件,本文对比研究了多源遥感数据时空融合模型在我国南方复杂条件下的应用能力。针对LORENZO模型、LIU模型、统计回归模型、STARFM和ESTARFM 5种主流多源遥感数据时空融合模型,采用Landsat-ETM+和MODIS数据,以江苏省南京市的小块区域为实验区,利用5种模型生产融合影像,以真实Landsat-ETM+数据为模板,定性和定量评价融合效果的好坏。结果表明：除LORENZO模型外,其余4种模型获得的融合影像与真实影像之间都具有较高的相关性,相关系数均高于0.6,其中,ESTARFM模型的融合影像与真实影像间的相关性最高,融合效果最好,其次为STARFM模型,再次为LIU模型和统计模型法。在融合过程中采用距离、时间和光谱等信息越多,融合效果越好,在复杂地区的适用能力越强,融合影像更能反映地物的细节特征。     

Monitoring the impact of backflow and dredging on water clarity using MODIS images of Poyang Lake,China

Backflow from the Yangtze River to Poyang Lake occurs frequently due to their different flood seasons. Based on the reasons for and time period of backflow, this study estimated the spatial‐temporal extent and the change of water clarity influenced by sediments within the backflow and northern Poyang Lake using time‐series Moderate Resolution Imaging Spectroradiometer (MODIS) images. The results revealed that the sediments from backflows together with dredging activities in the northern Poyang Lake not only affected the northern Poyang Lake, but also influenced the central and southern Poyang Lake and the Poyang Lake national nature reserve, and resulted in great decline of water clarity in the regions influenced, which could seriously affect the lake ecosystem. The results indicated that MODIS images have potential for monitoring the distribution of sediments from backflows and dredging activities. However, the potential is limited because of the frequent cloud cover in the study area and the characteristics of backflow itself. The dredging activity combined with backflows might have great negative impacts on the Poyang Lake ecosystem, and it would be worthwhile to explore the possible impacts in order to develop scientific knowledge to support the decisions, which need to be made by the responsible authorities for deciding how to rationally manage this unique lake ecosystem Copyright © 2008 John Wiley & Sons, Ltd.