Retrospective mapping of burnt areas in Central Siberia using a modification of the normalised difference water index

The boreal forest contains almost half the total carbon pool of world forest ecosystems, and so has a very significant role in global biogeochemical cycles. The flux of greenhouse gases in and out of these forests is influenced strongly by disturbances such as diseases, logging and predominantly fire. It is important to quantify these disturbances to enable the modelling of major greenhouse gases. However, because of the remoteness and vastness of the boreal forest, little data is available on the type, extent, frequency and severity of these disturbances in Siberia. For burnt areas, two of the more responsive wavelengths are the short wave infra-red (SWIR) and the near infra-red (NIR). These produce a vegetation index, the normalised difference SWIR (NDSWIR) capable of detecting retrospective disturbances. Here we combine the NDSWIR from MODIS imagery acquired in the summer of 2003 with thermal anomaly data from 1992 to 2003 to detect and date areas which burnt at some point between 1992 and 2003. The semi-automated method is called SWIR and Thermal ANomalies for Detecting Disturbances (STANDD) and is complemented by an Normalised Difference Vegetation Index (NDVI) differencing method using MODIS 2002 and 2003 imagery to ensure reliable detection of area burnt in the year of image acquisition (i.e. 2003). The area of this study covers approximately 3 million km² stretching from Lake Baikal in the south to the Laptev Sea in the north, above the Arctic Circle. Landsat ETM+ images were used to validate the shape and areal extent of the burnt areas resulting in an 81% overall accuracy with a kappa coefficient of agreement of 0.63.     

Sea-air flux of CO2 in the Caribbean Sea estimated using in situ and remote sensing data

Empirical relationships between sea surface carbon dioxide fugacity (fCO₂^sw) and sea surface temperature (SST) were applied to datasets of remotely sensed SST to create fCO₂^sw fields in the Caribbean Sea. SST datasets from different sensors were used, as well as the SST fields created by optimum interpolation of bias corrected AVHRR data. Empirical relationships were derived using shipboard fCO₂^sw data, in situ SST data, and SST data from the remote sensing platforms. The results show that the application of a relationship based on shipboard SST data, on fields of remotely sensed SST yields biased fCO₂^sw values. This bias is reduced if the fCO₂^sw-SST relationships are derived using the same SST data that are used to create the SST fields. The fCO₂^sw fields found to best reproduce observed fCO₂^sw are used in combination with wind speed data from QuikSCAT to create weekly maps of the sea-air CO₂ flux in the Caribbean Sea in 2002. The region to the SW of Cuba was a source of CO₂ to the atmosphere throughout 2002, and the region to the NE was a sink during winter and spring and a source during summer and fall. The net uptake of CO₂ in the region was doubled when potential skin layer effects on fCO₂^sw were taken into account.     

MODIS动态监测黄河宁蒙河段凌情的技术与方法

黄河宁夏河段和内蒙古河段（以下简称宁蒙河段）的凌情是我国大江大河中的一种特殊水文现象，由于凌情引发的凌汛灾害危害巨大，防凌历来是防汛部门的重要任务。在分析黄河宁蒙河道特点、MODIS卫星遥感数据特点和该河段所在区域天气状况的基础上，提出了MODIS遥感动态监测宁蒙河段凌情的技术与方法，研究和应用表明MODIS卫星遥感技术能够实现宁蒙河段凌情实时动态监测，在动态监测封开河长度、壅水漫滩等方面效果显著。     

Mapping surface temperature in large lakes with MODIS data

Satellite sensor MODIS on two platforms can produce Sea Surface Temperature over certain regions about three to four times per day. Our objective was to test if the MODIS SST product can be applied for lakes whose surface areas are large enough to be observed at the MODIS spatial resolution and to compare the satellite-derived lake surface temperatures with in situ measurements. Surface temperatures for Lakes Vänern and Vättern in Sweden, two of the largest European lakes, are extracted from the MODIS/Terra images for period 2001-2003. The results are analyzed on different quality levels, as all MODIS L2 products are equipped with an additional quality flag. We present temperature development over 2001-2003, and show the capability of the MODIS SST product to couple the known thermodynamical features in the lakes under study, where temperature varies greatly with space and time. These results can complement lake monitoring programs anywhere.     

Intra-seasonal NDVI change projections in semi-arid Africa

Early warning systems (EWS) tend to focus on the identification of slow onset disasters such famine and epidemic disease. Since hazardous environmental conditions often precede disastrous outcomes by many months, effective monitoring via satellite and in situ observations can successfully guide mitigation activities. Accurate short term forecasts of NDVI could increase lead times, making early warning earlier. This paper presents a simple empirical model for making 1 to 4 month NDVI projections. These statistical projections are based on parameterized satellite rainfall estimates (RFE) and relative humidity demand (RHD). A quasi-global, 1 month ahead, 1° study demonstrates reasonable accuracies in many semi-arid regions. In Africa, a 0.1° cross-validated skill assessment quantifies the technique's applicability at 1 to 4 month forecast intervals. These results suggest that useful projections can be made over many semi-arid, food insecure regions of Africa, with plausible extensions to drought prone areas of Asia, Australia and South America.     

古尔班通古特沙漠梭梭林地NDVI的时间效应-基于物候变化和MODIS图像的研究

遥感图像信息提取研究是遥感研究中的一个关键问题,也是遥感研究的热点和难点之一。使用2000~2010年MODIS-NDVI 16 d合成数据和物候记录,借助GIS空间分析和统计分析方法,重构了古尔班通古特沙漠梭梭林地Mean NDVI时间序列特征曲线。分析物候与Mean NDVI时间序列表明,梭梭林地内的短命植物生长期早于梭梭。研究梭梭林地Mean NDVI时间序列曲线发现,曲线中存在一个明显区别于其他地物的特征点,该点可以作为梭梭林地信息“诊断点”。根据“诊断点”特征构建了梭梭林地特征指数模型(HFFI),进而反演了古尔班通古特沙漠梭梭林地信息,并利用地面实际观测资料进行验证,结果表明分类精度达到83%。     

IRS-P6 LISS-3和Landsat-5 TM两种多光谱传感器影像数据的对比分析

随着载有各种新型传感器的卫星相继发射升空,不同传感器之间的相互比较成了一个研究热点。首先从传感器的轨道特征、光谱范围等方面对IRS-P6 LISS-3和Landsat-5 TM进行了机理方面的对比分析,选取3对同日过空的遥感影像,研究了IRS-P6 LISS-3和Landsat-5 TM遥感数据在可见光-近红外、短红外各对应光谱波段之间的关系,建立TM和LISS-3各波段之间的相互转换公式,与Chander等提出的转换公式进行对比分析。结果表明:实际TM和模拟TM多光谱数据之间具有较强的相关关系,决定系数R²均大于0.97;模拟TM与实际TM的水体指数(MNDWI)和归一化植被指数(NDVI)空间散点分布和实际LISS-3与实际TM的空间散点分布相比,具有更强的相关关系,其决定系数R²有一定提高,散点分布趋于对称。因此,所求的关系转换方程具有较高的精度和有效性,效果优于Chander等提出的转换公式。     

遥感数据时空融合技术在农作物监测中的适应性研究

受卫星回访周期及云的影响,大范围研究区同一时期的Landsat卫星数据很难获取,因而国内外学者提出了遥感影像时空融合技术。以石河子为实验区,利用STARFM(Spatial and Temporal Adaptive Reflectance Fusion Model)模型融合生成了高时空分辨率TM影像,对不同作物类型真实反射率与融合影像反射率作相关性分析,分析了遥感数据时空融合技术在新疆农作物监测中的适用性。结果表明:利用STARFM模型模拟得到的融合影像与真实影像间的相关性较高,但当地物类型发生变化时,融合影像与真实影像间将存在明显的差异。地物类型变化作物融合影像反射率与真实影像反射率间的相关性较小。     

径流过程分维数与其主要影响因素的定量研究

为研究分维数与其主要影响因素的定量关系,收集泾河张家山水文站的径流资料和该流域长武、环县、崆峒气象站日降雨数据以及ＮＤＶＩ遥感影像,分别选取降水不均匀系数为代表降水年内分配不均匀程度的指标和ＮＤＶＩ为反映人类活动对流域植被覆盖影响的指标,经过归一化处理后,使用ＭＴＡＬＡＢ软件得出以年为单位的泾河径流过程分维数与该流域降水不均匀系数和ＮＤＶＩ的定量关系式。结果表明分维数与降水不均匀系数呈正相关（Ｒ＝０．５５７１）,而与ＮＤＶＩ呈负相关（Ｒ＝０．２２７８）。说明降水年内分配越不均匀,植被覆盖越小,径流过程越复杂,分维数就越大,符合平常认知;泾河流域的降水对径流过程的影响较流域植被覆盖更大。     

2000—2014年辽宁省植被动态演变特征分析

基于MODIS － NDVI 数据,辅以线性回归法与分段线性回归法,并借助ArcGIS 软件,对辽宁 省2000—2014 年植被覆盖的动态演变过程进行分析。结果表明: ( 1) 时间上,辽宁省植被NDVI 在年 际尺度上呈现出明显的增大趋势,2005 年出现突变,多年平均NDVI 值为0. 496; 春季、夏季、秋季 以及植被生长季NDVI 突变年份分别为2006 年、2005 年、2009 年和2004 年,秋季波动变化的突变点 明显滞后; 植被生长最旺盛的季节为夏季,且集中于8 月。( 2) 空间上,辽宁省植被覆盖具有明显的 地域性差异,呈现出东部高、中西部低的分布特征; 辽宁省植被覆盖优良区与辽东山地的界限基本吻 合,植被覆盖贫乏区主要集中在朝阳市和阜新市的东北部地区。( 3) 辽宁省植被覆盖程度呈山地阴坡 高于阳坡的形态,并且植被覆盖程度最好的坡向为北偏西方向。( 4) 2000—2014 年辽宁省植被覆盖度 整体以维持现状和轻微改善为主,保持不变的区域集中于中东部地区,辽阳市与沈阳市一带有轻微退 化现象,辽西北地区改善情况较为明显。