Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Abstract Forest ecosystem modelling requires information about canopy chemistry. This is usually obtained through chemical analysis and laboratory spectrometric measurements. The potential of spectrometric remote sensing was investigated with two airborne campaigns organized in 1991 with AVIRIS (Airborne Visible/Infrared Imaging spectrometer) and in 1993 with ISM (Infrared SpectroMeter) over the 'Landes’ forest (south-west France): AVIRIS covers the 400-2500 nm spectral range with 210 bands, whereas the ISM instrument is an airborne profiling spectrometer that operates in the 800-3200 nm spectral range with 128 bands. The study area consists of homogeneous parcels of maritime pines with a wide variety of ages from 2 to 48 years. Simultaneously with the airborne acquisition, foliar samples were collected in the field. These samples were chemically analysed for determining nitrogen, lignin and cellulose contents. Reflectance spectra of dried pine needles were obtained with the help of two laboratory spectro... <s> BIB001 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> The new satellite ocean color sensors offer a means of detecting and monitoring algal blooms in the ocean and coastal zone. Beginning with SeaWiFS (Sea Wide Field-of-view Sensor) in September 1997, these sensors provide coverage every 1 to 2 days with 1-km pixel view at nadir. Atmospheric correction algorithms designed for the coastal zone combined with regional chlorophyll algorithms can provide good and reproducible estimates of chlorophyll, providing the means of monitoring various algal blooms. Harmful algal blooms (HABs) caused by Karenia brevis in the Gulf of Mexico are particularly amenable to remote observation. The Gulf of Mexico has relatively clear water and K. brevis, in bloom conditions, tends to produce a major portion of the phytoplankton biomass. A monitoring program has begun in the Gulf of Mexico that integrates field data from state monitoring programs with satellite imagery, providing an improved capability for the monitoring of K. brevis blooms. <s> BIB002 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> The French Guiana coast, located about 500 km north of the Amazon mouth, is characterized by mangroves and large mud banks migrating northwestwards. These banks are composed of fine clay sediments originating from the Amazon River. In November 1998, field work was carried out on the Mahury River to measure the water colour and the concentration of suspended particles in surface water. An increase of the remote sensing reflectance due to high concentration of mineral particles was observed. The Mahury River survey (November 1998), together with an oceanographic survey onboard the ANTEA vessel (PRECHICO cruise, April 1999), enabled us to identify several classes of remote sensing reflectance spectra characterizing the continental shelf between Cayenne and the Brazil frontier: (1) light blue waters above the shelf break; (2) low salinity dark brown waters above the continental shelf, originating from the Amazon River; (3) green waters above the 20-m isobath; and (4) beige waters close to the coast and in the rivers mouths. The normalized water leaving radiances (nLw) computed from these spectra in the spectral bands of SeaWiFS are examined. The standard OC2 performs poorly in retrieving chlorophyll from the reflectance data because of the relatively high suspended particulate matter concentrations. <s> BIB003 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Nonnative plant species are causing enormous ecological and environmental impacts from local to global scale. Remote sensing images have had mixed success in providing spatial information on land cover characteristics to land managers that increase effective management of invasions into native habitats. However, there has been limited evaluation of the use of hyperspectral data and processing techniques for mapping specific invasive species based on their spectral characteristics. This research evaluated three different methods of processing hyperspectral imagery: minimum noise fraction (MNF), continuum removal, and band ratio indices for mapping iceplant (Carpobrotus edulis) and jubata grass (Cortaderia jubata) in California's coastal habitat. Validation with field sampling data showed high mapping accuracies for all methods for identifying presence or absence of iceplant (97%), with the MNF procedure producing the highest accuracy (55%) when the classes were divided into four different densities of iceplant. <s> BIB004 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Abstract Narrow spectral band reflectance indices of two emergent macrophytes (Typha latifolia and Borrichia frutescens) were found to correspond to changes in water column total ammonia (TA=NH3+NH4+) of a constructed oligohaline (2–5 ppt) subtropical marsh (8 ha) designed as a shrimp farm treatment wetland in south Texas, USA, near the western Gulf of Mexico. A handheld hyperspectral radiometer measured plant leaf reflectance across the visible (VIS, 300–700 nm) and near-infrared (NIR, 700–1100 nm) spectrum during the mid-growing season (July–August). Reflectance of the two species and water quality (TA; total phosphorus (TP); salinity, S) were measured along a dynamic nutrient gradient from wetland inlet to outlet. Mean TA concentration was 1.22 mg N l−1 ranging between 0.92 and 1.71 mg N l−1. Salinity fluctuated between 2.5 and 4.5 ppt, while total phosphorus was between 0.01 and 0.86 mg P l−1. T. latifolia, the more dominant wetland cover: (a) reflected 1–5% less in the VIS compared to B. frutescens, (b) generally reflected 7–8% more in the NIR, (c) exhibited an average red-edge (RE) (718 nm) 15 nm greater than B. frutescens, and (d) had an average leaf normalized difference vegetation index [NDVI=(R774−R681)/(R774+R681), where Rλ is reflectance at wavelength λ] of 0.82, versus 0.65 for B. frutescens. A multivariate linear regression equation containing photochemical reflectance index (PRI) and RE for T. latifolia explained 93% of TA variation (P <s> BIB005 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Abstract Remote sensing is an important tool for mapping and monitoring vegetation. Advances in sensor technology continually improve the information content of imagery for airborne, as well as space-borne, systems. This paper investigates whether vegetation associations can be differentiated using hyperspectral reflectance in the visible to shortwave infrared spectral range, and how well species can be separated based on their spectra. For this purpose, the field reflectance spectra of 27 saltmarsh vegetation types of the Dutch Waddenzee wetland were analysed in three steps. Prior to analysis, the spectra were smoothed with an innovative wavelet approach. In the first stage of the analysis, the reflectance spectra of the vegetation types were tested for differences between type classes. It was found that the reflectance spectra of saltmarsh vegetation types are statistically significantly different for various spectral regions. Secondly, it was tested whether this statistical difference could be enhanced by using continuum removal as a normalisation technique. For vegetation spectra, continuum removal improves the statistical difference between vegetation types in the visible spectrum, but weakens the statistical difference of the spectra in the near-infrared and shortwave infrared part of the spectrum. Thirdly, after statistical differences were found, it was determined how distant in spectral space the vegetation type classes were from each other, using the Bhattacharyya (BH) and the Jeffries–Matusita (JM) distance measures. We selected six wavelengths for this, based on the statistical analysis of the first step. The potential of correct classification of the saltmarsh vegetation types using hyperspectral remote sensing is predicted by these distance measures. It is concluded that the reflectance of vegetation types is statistically different. With high quality radiometric calibration of hyperspectral imagery, it is anticipated that vegetation species may be identified from imagery using spectral libraries that were measured in the field during the time of image acquisition. <s> BIB006 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> A new architecture for REMS (Remote-sensing Environmental Monitoring System V1.0) is introduced in this paper. REMS is the first integrated system in China developed to meet the multi-resource, multi-temporal and multi-thematic data processing, analyzing and products distributing, especially to process and monitor inland water resource pollution. The most important components of REMS are presented in this paper including tools for multi-resource data input/output, preprocessing, data visualization and mapping, environment information extraction, conventional image analysis, advanced tools for eco-environment modeling, and integrated interface to connect with general spatial and spectral database and water quality monitoring database. REMS provide professional ability to extract the major characters of water resource such as Chlorophyll content, Total Suspended Matter (TSM), Yellow Substance or CDOM etc. In order to retrieve and predict the blue algae distribution and water quality evolvement, a group of statistical algorithms are also realized to analyses the result and at the same time data assurance measures are also given respectively. Finally, we select the Taihu Lake, JiangShu Province, South China, as the representative research area and some field applications constructed based on REMS are discussed <s> BIB007 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> The extreme flood event of the Elbe and Mulde Rivers in August 2002 caused, with its very sharp rise and decline of the water masses, a manifold of damage to the infrastructure as well as toxic deposits in the flooded areas. The paper gives a summary of the processing of multitemporal and multisensor remote sensing data for the purpose of monitoring this event. Methods and results for several thematic questions are presented and ::: discussed. Procedures for the detection of flooded areas with operational satellite data (Landsat-ETM, IRS) are investigated. Further studies are performed regarding the classification of moisture classes in the flood plain in relation to the high water changes, the accumulation of sediments and silts for different land use classes and the erosive impact of the flood by using data with high spatial resolution from satellite (IKONOS) and from aircraft (Daedalus-Scanner). ::: The time series of multispectral scanner data are very well suited for the spatial analysis of the damage and ecological risk, caused by the flood. The results correlate well with the data from in-situ measurements. At the same time they show how the gathering of samples can be optimized by using remote sensing data. The results can be directly integrated in existing GIS of the public authorities for the assessment and management of extreme ::: flood events. <s> BIB008 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Abstract In this paper, we present a new way of detecting and monitoring flooding through the Autonomous Sciencecraft Experiment (ASE) [Chien, S. T., Debban, C., Yen, R., Sherwood, R. Castano, B., & Cichy, A. G. et al. (2001). ASC Science Study Report, available from http://ASE.jpl.nasa.gov ], which is part of the Space Technology 6 effort under NASA's New Millennium Program. Recent autonomy experiments conducted on Earth Observing 1 (EO-1) using the ASE flight software have demonstrated the ability of several science algorithms to successfully classify key features including flood-induced changes, in hyperspectral images captured by the EO-1 Hyperion instrument. Furthermore, onboard science analysis on the classified images has been performed, and then used to modify an operational plan without interaction from the ground (Sherwood, R., Chien, S., Tran, D., Cichy, B., Castano, R., Davies, A., et al. (2004). Preliminary results of the autonomous sciencecraft experiment. In: Proceedings of the IEEE Aerospace Conference, Big Sky, MT ). These algorithms are used to downlink science data only when change occurs, and to detect features of scientific interests such as flooding, volcanic eruptions, and the formation and breakup of sea ice. The purpose of this paper is to demonstrate the success of ASE and its implications on detecting, mapping, and monitoring transient processes such as flooding autonomously from space. Mapping of water inundation and its change through time is part of our focus in studying transient processes from space. In 2004, hyperspectral data were acquired from the Hyperion instrument for target areas around the world that have a high potential for flooding to develop and test floodwater classifiers. In addition, classifier thresholds were determined from both normal flows and possible flood conditions. The paper introduces the development, testing, and success of the ASE software in detecting and reacting to flooding in near real-time. ASE is now operational and flight-tested, and, thus, ready to use for space-borne reconnaissance. Successful demonstration of the floodwater classifiers includes the capture of a rare flooding event of the Australian Diamantina River during ground testing in February 2004, and the detection of flood-related changes along the Brahmaputra River in Bangladesh and the Yukon River in Alaska during onboard testing on EO-1 in 2005. Both of these detections led to triggered responses onboard the spacecraft, which included acquiring additional Hyperion scenes. These results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. It is hoped that ASE will become a default in future missions to increase the science return by introducing spacecraft autonomy for detection and monitoring of science events, which otherwise would be discovered too late or altogether missed. <s> BIB009 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> In this paper, the potential for identifying discharge and/or flood hydrograph from remotely sensed data is explored. The parameter identification process is based on the minimization of the difference between the solution of the model equations and the observed system response which consists in maximum inundation extent. The river geometry is supposed to be known, effect of the accuracy of these data on the estimation has been tested. Sensitivity of the model to individual parameters is then assessed using an extension of the generalized sensitivity analysis. Synthetic data have been used to test the methodology. Results show that the Nash criterion of the estimated flood hydrograph is higher than 0.9 for all the tested cases. <s> BIB010 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Abstract The relationship between land features and their spectral characteristics is important for the interpretation of remote sensing images. In this study, the spectral characteristics of a submerged plant Vallisneria spiralis with varied coverage was measured with a ground sensor/radiometer, FieldSpec™ Pro JR Spectroradiometer in the laboratory and in the constructed wetland of “Mengqingyuan”, Shanghai, China. The results showed that the reflectance rate of Vallisneria spiralis rose with its increasing coverage, which was exhibited both at the visible band (500–650 nm) and the near infrared band (700–900 nm). Water quality influenced the reflectance rate with the primary differences between the laboratory and field experiments mainly occurring at the near-infrared band (700–900 nm). A regression analysis was carried out respectively between the coverage of Vallisneria spiralis and the reflectance rate at the wavelengths of Quick Bird 4 bands where the coverage responded to the strongest. These results of regression analyses showed a clear linear relationship, by which the coverage of Vallisneria spiralis could be quantitatively deduced from the reflectance rate measured in situ. The implications in terms of the ability of hyperspectral remote sensing to distinguish and monitor the distribution and dynamics of submerged vegetation on a large scale are discussed. <s> BIB011 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates. The processing integrates photogrammetric and quantitative remote sensing approaches. We carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012. Poor weather conditions during the campaign complicated the data processing, but this is one of the challenges that are faced in operational applications. The <s> BIB012 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. WATER RESOURCE AND FLOOD MANAGEMENT <s> Abstract Lakes Chivero and Manyame are amongst Zimbabwe’s most polluted inland water bodies. MEdium Resolution Imaging Spectrometry level 1b full resolution imagery for 2011 and 2012 were used to derive chlorophyll-a (chl_a) and phycocyanin (blue-green algae) concentrations using a semi-empirical band ratio model; total suspended matter (TSM) concentrations were derived from the MERIS processor. In-situ measured chl_a was used to validate the remotely sensed values. Results indicate that remote sensing measurements are comparable with in situ measurements. A strong positive correlation ( R 2 = 0.91; MAE = 2.75 mg/m 3 (8.5%)) and p R 2 = 0.9458; p R 2 = 0.7344; p R 2 = 9047; p <s> BIB013
Water is one of the most important resources available on Earth as is vital for survival of humanity. For this reason, managing the water resource efficiently, analyzing and monitoring the quality of water has attracted a lot of attention from the researchers BIB001 - BIB004 . Hyperspectral remote sensing technology has found enormous applications in water resource management. Accurate estimates of water resource parameters are possible by analyzing spatial, spectral and temporal variations in water bodies. Xingtang et al. BIB007 systematically introduced their research on key technologies related to robust hyperspectral water resource monitoring system in China. This work was used by Li  to estimate the suspended matter concentrations of Meiliang Bay of Taihu Lake using the CHRIS data as shown in Figure 8 . The efficacy of flood detection and monitoring system is limited by their incapacity to get important information about water conditions from airborne and ground observatories in a timely manner. Recent improvements in remote sensing technology has improved the early flood warning system and vastly reduced the time of detection and reaction to flood events to a few hours BIB009 . US geological survey and NASA are incorporating space borne observations of rainfall resources, rivers and land topography into early warning systems with potential global applications  . Glaber and Reinartz BIB008 studied the optimal procedure for detection of flooded areas with remote sensing data. They investigated the erosive impact of floods, moisture content in flood plain areas, accumulation of sediments. Roux and Dartus BIB010 explored the flood hydrographs and estimated the river discharge from remotely sensed data. They optimized their model to minimize the error between system response and their proposed model to estimate the river discharge. Honkavaara et al. BIB012 presented various challenges regarding data processing faced by hyperspectral sensors in adverse meteorological conditions and proposed radiometric correction to minimize the effects of radiometric variations in varying illumination conditions. Hyperspectral remote sensing provides efficient and reliable information about water quality parameters which contain biochemical, hydro-physical and biological attributes BIB013 -  . HSI enable us to measure chlorophyll, turbidity and chemical oxygen demand and phosphorous in water resources. Chlorophyll content in water is extensively studied by hyperspectral remote sensing, which gives an estimate of algal level and hence water quality. Studies have been carried out for evaluation of ammonia changes for wetland BIB005 , classifying different parameters of lakes  , estuaries BIB003 and analyzing algal blooms BIB002 . Wetland mapping has played a significant role in order to enhance the quality of our ecosystem BIB006 . Hyperspectral imagery has helped in detailed understanding of vegetation characteristics of ecosystem. Extensive research studies have been carried out using remote sensing to explore the significance of acquiring timely data for monitoring and mapping aquatic vegetation BIB011 , which is said to be an important aspect in ecosystem reconstruction and restoration.