Validation of Chlorophyll-a Algorithms in the Coastal Waters of Bay of Bengal Initial Validation Results from OCM-2

In this paper we report chlorophyll measurements made during an ocean colour validation cruise in April 2011 of the research vessel, Sagar Paschimi in the coastal waters of Northern Bay of Bengal. The chlorophyll-a concentration in these waters range from 0.2 to 4.0 mg/m³. Chlorophyll-a concentration from OCM-2 was estimated using the global ocean colour algorithms namely, OC2, OC3, OC4 and Chl-a algorithms respectively. OCM data was processed using the global SeaWiFS Data Analysis System (SeaDAS) in which all the above mentioned algorithms are embedded for estimating the chlorophyll-a concentration. A comparative study was made between and in-situ and satellite derived chlorophyll-a concentration. Although the matchups between in-situ and satellite data from OCM-2 were sparse, it indicates that direct application of the standard SeaWiFS algorithm-the OC4-V4 algorithm—in the coastal waters of the Bay of Bengal will underestimate chlorophyll-a by up to 30%. The results show a good correlation with an R value of 0.61 using OC2 algorithm. However, all the other global algorithms over estimate the chlorophyll-a concentration even in low chlorophyll concentration range. The comparison between in-situ and all the existing chlorophyll algorithms shows the efficiency of these algorithms for quantification of chlorophyll in coastal waters and hence the need to develop regional algorithms and fluorescence based algorithms for better quantification.     

利用MODIS图像反演海岸与海岛的地物光谱反射率

提出一种利用MODIS图像,用查找表反演海岸与海岛地物光谱反射率的方法。该方法首先借助AHMAD辐射传输模型,由MODIS图像的水体像元反演出气溶胶的光学特性;在所选影像为晴空无云条件下,假设一定范围内的海岛与海岸上空的大气和水体上空的大气一样,借助6S辐射传输模型计算基于地物光谱反射率的查找表,然后由MODIS图像的陆地像元的反射率和几何条件加上反演的气溶胶光学厚度,用插值法可求得地物光谱反射率。还给出了厦门地区实际卫星图像的反演结果,并就反演误差进行了分析。     

Coastal Validation of Ultra-high Resolution Wind Vector Retrieval From QuikSCAT in the Gulf of Maine

An experimental 2.5-km ultrahigh-resolution (UHR) wind product provided by NASA's QuikSCAT scatterometer offers the potential for new access to coastal surface wind dynamics at the mesoscale level and below. To give future users the best indication of the value of these data, the UHR wind retrievals must be fully validated in nearshore areas. Comparison with meteorological buoys and standard QuikSCAT products allows detailed investigation of UHR winds. Speed and direction residuals are calculated between all scatterometer products and collocated buoys. An ambiguity selection routine improves wind direction agreement between the UHR winds and the other products. Magnitude residuals follow the patterns of the standard QuikSCAT winds, with a 1–2 m/s positive bias in light winds (below 4 m/s) and high winds (above 16 m/s) and standard deviations consistently below 3 m/s. After application of a land contamination removal algorithm, the UHR product provides extended coverage near the coast. An example of a specific wind event illustrates the potential benefits of improved resolution measurements for examining ocean–atmosphere dynamics.      

Assessment of satellite ocean color products of MERIS,MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)

The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance R_rs(λ) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APD_m) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr⁻¹, whereas the R_rs(λ) uncertainty at 412 nm is the highest (APD_m 47–62%, RMS 0.0027–0.0041 sr⁻¹). The uncertainties of the aerosol optical thickness (AOT) τ_a, diffuse attenuation coefficient for downward irradiance at 490 nm K_d(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of K_d(490), SPM, and Chl-a may decrease significantly to the level of 20–30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task.     

Comparison of Inherent Optical Properties (IOPs) in Open and Coastal Waters of Arabian Sea Using In-Situ Bio-Optical Data

The two main inherent optical properties (IOPs) namely absorption and back scattering coefficients were estimated using a quasi analytical algorithm (QAA) for open and coastal ocean waters of Arabian Sea. Absorption due to gelbstoff and back scattering due to the particulate matter were calculated using the quasi analytical algorithm for all the in-situ measured reflectance spectra collected in the Arabian Sea. A comparative study was made to study the spectral variability of reflectance spectra in open as well as coastal waters of Arabian Sea. Spectral analysis was made for the absorption and back scattering coefficients calculated using the QAA for both open and coastal waters. The absorption coefficient in the open ocean waters vary from a minimum value of 0.029 to a maximum value of 0.445 and it varies from a minimum value of 0.081 to a maximum value of 4.000 for the coastal waters of Arabian Sea. Absorption due to gelbstoff or the CDOM a_g(λ), calculated for the Arabian Sea waters show a variation of 0.000202 to 0.112437 for open ocean waters and it varies from 0.002848 to 2.8936 for coastal waters of Arabian Sea. Particulate back scattering coefficient for open ocean waters vary from 0.0000307 to 0.006575 whereas b_bp(λ) vary from 0.000167 to 0.026014 for coastal ocean waters. The minimum slope for the open ocean waters is 0.989 and maximum value of 2.147 (average value of 1.7) was observed; whereas a minimum value of 0.046 and a maximum value of 1.201 (average value of 0.6) were observed from the in-situ spectra for coastal waters of Veraval. The slope ‘Y’ estimated from the model is 1.957 for open ocean waters and 0.515 for coastal waters collected in the Arabian Sea.     

Landscape Dynamics in North East Region of India (Meghalaya State) Using Spatial Decision Tree Model

Abstract

India has figured with two hotspots ‐ the Western Ghats and the Eastern Himalayas ‐ in an identification of 8 ‘hottest’ biodiversity hotspots (Myers et. al. 2000). The Meghalaya state (study area) in North Eastern India lies within the “Indo‐Burma” area, which is one of the 8 ‘hottest’ biodiversity hotspots. Timber extraction, the age‐old practice of shifting cultivation and mining has been a major cause of extensive changes in this landscape. Human induced disturbance differs from natural disturbance especially in extension, severity and frequency. Spatial presentation of landscape dynamics can be used to infer disturbance regimes horizontally. Disturbance regimes are mostly dominated by landuse practices in Meghalaya and these landuse practices are important contributors for overall interpretation of ecological processes operating within the landscape. In this scenario, the development of models to study landscape dynamics using remote sensing and GIS would be of great importance to ecologists. In this paper, we make an attempt to characterize landscape dynamics using a decision tree based approach. The varying impacts of human interventions reflected in three zones at landscape level have been brought out in the present study. The physiographic zones of Meghalaya (viz. Garo hills, Khasi hills and Jaintia hills) manifest different landscape characteristics and present varying degree of degradation status. Garo hills, experiences maximum shifting cultivation and has shown highest dynamism in the study area followed by Jaintia and Khasi hills. Characterization of landscape dynamics is important in the perspective of decision makers and policy makers in order to prioritize conservation strategies, so that urgent and necessary action can be taken.     

FVCOM与ROMS在美国东海岸洋流模拟的对比研究

ROMS与FVCOM是在美国东海地区应用较为普遍的两种海洋模型,常采用模拟粒子轨迹的手段解决沿海海洋问题。在实际应用前,对模型在洋流模拟上精度的验证是至关重要的。本文使用2004至2010年在美国东海岸部署的drifter,通过与模型模拟轨迹对比的方法对第三代FVCOM海洋模型(GOM3)与ROMS(GOMOFS)模型的表层洋流模拟能力进行评定,采用分离率与距离比两种精度指标,得出ROMS模型的表层洋流模拟能力优于FVCOM模型。     

黑河流域遥感物候产品验证与分析

植被物候遥感产品对全球变化响应、农业生产管理、生态学的应用等多领域研究具有重要意义。但现有植被物候遥感产品还有较多问题,主要包括一方面使用不同参数的时间序列数据以及不同提取算法导致的产品结果差异较大,另一方面在地面验证中地面观测数据与遥感反演数据的物理含义不一致导致的验证方法的系统性误差。本文以黑河流域为研究区,对比验证基于EVI(Enhanced Vegetation Index)时间序列数据提取的MLCD(MODIS global land cover dynamics product)植被遥感物候产品和基于LAI(Leaf Area Index)时间序列数据提取的UMPM(product by universal multi-life-cycle phenology monitoring method)植被遥感物候产品的有效性及精度等。同时,通过验证分析进一步评估基于EVI和LAI时间序列提取的物候特征的差异及特点,探讨由于地面观测植被物候与遥感提取植被物候的物理意义的不一致问题导致的直接验证结果偏差。结果表明:UMPM产品有效性整体高于MLCD产品,但在以草地和灌木为主的稀疏植被区,由于LAI取值精度的原因,UMPM产品存在较多缺失数据,且时空稳定性较低;基于玉米地面观测数据表明,EVI对植被开始生长的信号比LAI更加敏感,更适合提取生长起点,但植被指数易饱和,峰值起点普遍提前,基于LAI提取的峰值起点更加合理。由于地面观测的物候期在后期更加关注果实生长,遥感观测仅关注叶片的生长,遥感定义的峰值终点和生长终点与玉米的乳熟期和成熟期差异较大。     

Identification of Groundwater Potential Zones of a Tropical River Basin (Kerala,India) Using Remote Sensing and GIS Techniques

The present work accentuated the expediency of remote sensing and geographic information system (GIS) applications in groundwater studies, especially in the identification of groundwater potential zones in Ithikkara River Basin (IRB), Kerala, India. The information on geology, geomorphology, lineaments, slope and land use/land cover was gathered from Landsat ETM + data and Survey of India (SOI) toposheets of scale 1:50,000 in addition, GIS platform was used for the integration of various themes. The composite map generated was further classified according to the spatial variation of the groundwater potential. Four categories of groundwater potential zones namely poor, moderate, good and very good were identified and delineated. The hydrogeomorphological units like valley fills and alluvial plain and are potential zones for groundwater exploration and development and valley fills associated with lineaments is highly promising area for groundwater extraction. The spatial variation of the potential indicates that groundwater occurrence is controlled by geology, structures, slope and landforms.     

海岛(礁)DEM成果质量检验关键技术研究

在人机交互质量检验技术的基础上,提出了解决海岛(礁)DEM成果质量检验问题的3个关键技术。首先,提出了目录组织模型用于质量检验的自动化检查方法,该模型支持对各个单位汇交的成果数据组织、数据命名和数据格式等方面进行检查,实现了对空间参照系、逻辑一致性等质量元素较为全面的检查,提高了大规模批量海岛(礁)DEM成果的检验效率;其次,提出了桩点法统计高程中误差,以取代外业现场打点检查DEM高程精度的检测方法,解决了海岛(礁)无法布设足够外业检查点的技术难题;最后,开发了质量等级评定工具,实现了DEM成果质量检验评价结果的电子化统一管理。通过对3000多幅海岛(礁)DEM成果质量检验的工作证实,该技术提升了质量检验能力和效率,保证了测绘成果检验的正确性和科学性。     

雪热力模型(SNTHERM)在冰沟流域的模拟和敏感性试验

采用基于质能平衡的积雪过程模型—雪热力模型(Snow Thermal Model, SNTHERM.89）来描述和模拟2008年中国甘肃省黑河实验冰沟流域的积雪过程与积雪特性参数,并将模型模拟的雪水当量与高级微波扫描辐射计(AMSR-E）的雪水当量产品进行了对比。模型验证结果表明,SNTHERM模型能准确模拟黑河冰沟流域的积雪变化过程和积雪特性,对积雪的演变特征作出合理的描述,表明SNTHERM在中国黑河冰沟流域有较好的适用性。对SNTHERM模型进行不同驱动气象参数和初始输入参数的敏感性分析的结果表明,积雪特性参数对辐射通量最敏感;各积雪特性参数对各自的初始输入比较敏感,密度则对初始输入的雪深、密度和颗粒大小都比较敏感,表明在需要准确模拟密度的情况下以及进行雪水当量同化工作时,初始输入的雪层深度、密度和颗粒都必须比较准确。     

基于光谱混合分析的毛乌素沙地油蒿群落覆盖度提取

油蒿群落覆盖度是判断毛乌素沙地荒漠化程度严重与否的直接指标,其信息的准确获取有助于更为合理的荒漠化监测与评价。本研究以Landsat ETM 为数据源,深入探讨了光谱混合分析过程中影像预处理、端元选取、光谱混合模型选择及光谱混合分析结果分析等关键问题,给出了恰当的解决方案,进而进行了油蒿群落覆盖度的提取,并通过野外实测数据对提取结果进行了验证。验证结果表明:基于光谱混合分析技术提取的油蒿群落分量与实测油蒿群落覆盖度线性相关显著,相关系数为0.88,因而研究区的油蒿群落覆盖度可以通过油蒿群落分量的线性变换得到。因此,光谱混合分析是提取毛乌素沙地油蒿群落覆盖度的有效技术。     

Palaeo-path investigation of the lower Ajay River (India) using archaeological evidence and applied remote sensing

Numerous palaeochannels, oxbow lakes and elongated sediment fills in Eastern India, particularly along the lower Ajay River, provide a record of channel shifting during the Late Quaternary. Proper characterization of these features is useful for discussing the dynamic evolution of the river system in the Ajay-Damodar Interfluve region. Remote sensing data, archaeological evidence and sedimentology aid in reconstructing the geomorphic history of the lower Ajay River. Archaeological studies help in calculating the rate and direction of channel migration. The channel migration rate varies from 0.32 to 3.41 m/year in the study area. Bouguer gravity anomalies suggest that the rate of channel migration may be controlled by the density variations of the basement rocks. Furthermore, neotectonics activity played a significant role in the migration of Ajay River towards north-east direction.     

Application of Landsat data in determining the range biomass in Jodhpur district,Westren Rajasthan (India)

The range biomass in three different soil types of Jodhpur district has been estimated from the computer print out of Landsat imagery. The total biomass in the younger alluvial soil varies from 36.1 to 35910.0 kg; in pipar soils it ranges between 23.2 to 21541.2 kg, and in Chirai soils total biomass varies from 26.6 to 6852.7 kg.     

Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data

The hard-rock hilly Aravalli terrain of Rajasthan province of India suffers with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. In the present study, detailed analysis of meteorological and hydrological data of the Aravalli region has been carried out for the years 1984–2003. Standardised Precipitation Index (SPI) has been used to quantify the precipitation deficit. Standardised Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) and Vegetation Health Index (VHI) have been computed using NDVI values obtained from Global Vegetation Index (GVI) and thermal channel data of NOAA AVHRR satellite. Detailed analyses of spatial and temporal drought dynamics during monsoon and non-monsoon seasons have been carried out through drought index maps generated in Geographic Information Systems (GIS) environment. Analysis and interpretation of these maps reveal that negative SPI anomalies not always correspond to drought. In the Aravalli region, aquifer-stress shifts its position time to time, and in certain pockets it is more frequent. In comparison to hydrological stress, vegetative stress in the Aravalli region is found to be slower to begin but quicker to withdraw.     

Artificial Neural Network (ANN) Based Inversion of Benthic Substrate Bottom Type and Bathymetry in Optically Shallow Waters - Initial Model Results

Ocean-colour remote sensing in optically shallow waters is influenced by contribution from the water column depth as well as by the substrate type. Therefore, it is required to include the contribution from the water column and substrate bottom type for bathymetry estimation. In this report we demonstrate the use of Artificial Neural Network (ANN) based approach to spectrally distinguish various benthic bottom types and estimate depth of substrate bottom simultaneously in optically shallow waters. We have used in-water radiative transfer simulation modeling to generate simulated top-of-the-water column reflectance the four major benthic bottom types viz. sea grass, coral sand, green algae and red algae using Hydrolight simulation model. The simulated remote sensing reflectance, for the four benthic bottom types having benthic bottom depth up to 30 m were generated for moderately clear waters. A multi-layer perceptron (MLP) type neural network was trained using the simulated data. ANN based approach was used for classification of the benthic bottom type and simultaneous inversion of bathymetry. Simulated data was inverted to yield benthic bottom type classification with an accuracy of ~98% for the four benthic substrate types and the substrate depth were estimated with an error of 0% for sea grass, 1% for coral sand and 1–3% for green and red algae up to 25 m, whereas for substrate bottom deeper than 25 m depth the classification errors increased by 2–5% for three substrate bottom types except sea grass bottom type. The initial results are promising which needs validation using the in-situ measured remote sensing reflectance spectra for implementing further on satellite data.     

基于被动微波遥感的青藏高原雪深反演及其结果评价

采用修正的张氏雪深反演算法，用ＳＳＭ／Ｉ３７ＧＨz和19GHz水平极化亮温值计算了青藏高原及其毗邻地区的积雪深度，对其精度进行了评价，并对误差来源进行了分析，结果显示，此算法能够较好地反映研究区的雪深分布，但局部地区误差较大，总体上雪深被高估，其误差主要来源于冻土，深霜层，植被以及雪层中液态水含量，雪粒的形状和粒径的变化带来的影响，SSM／I数据较低的分辨率和研究区复杂的地形使反演的雪深与观测的雪深缺少可比性，给精度的评价带来影响。     

Fluviomorphological investigations in the flood plain area of river satluj in the North East of Ludhiana (Punjab State) using photo-interpretation techniques

Various geomorph.ological features associated with fluvial processes of the river Satluj are mapped using photo-interpretation techniques with a view to assess the environmental status of the area in the north-east of Ludhiana (Punjab State). Features mapped include braided river channels, oxbow lakes and meander scrolls. The younger alluvium supports good vegetation and cultivation because of -shallow depth of water level; though prone to annual floods in the lower levels and major floods in the higher levels. It is saved from these hazards by providing bunding on both sides of river isolated sand deposit patches have been demarcated in the older alluvium. Shifting of the main river channel towards north is noticed as it has gradually shifted from its earlier course which lies towards south.     

Delineation of groundwater potential zone in hard rock terrain of India using remote sensing,geographical information system (GIS) and analytic hierarchy process (AHP) techniques

The present study has been undertaken to delineate the groundwater potential zones in the hard rock terrain of Palamu district, Jharkhand using the advanced applications of remote sensing, geographical information systems and analytic hierarchy process techniques. The integration and analyses of various thematic databases viz., geomorphology, lithology, soil, slope, lineament density, weathered zone thickness, drainage density and rainfall proved useful in the delineation of GWP zones. The study indicates that only 136?km² of the study area exhibit excellent groundwater potential, 248?km² has very good groundwater potential, whereas 36.89 and 38.23% are under poor and very poor groundwater potential zones, respectively. Hence, only a total of 11.6% of the area (490?km²) is classified as high to excellent groundwater potential. The final groundwater prospect map obtained was classified as excellent potential, very good potential, good potential, moderate potential, poor potential and very poor potential zone.