A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> When nearly circular clumps of vegetation abound in aerial photographs of mud flats in estuaries in regions of temperate climate the indication is that the marsh is expanding rapidly. <s> BIB001 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> A VARIETY OF MULTIBAND IMAGERY, INCLUDING NINE-LENS MULTIBAND IMAGERY IN THE 400-900 MILLIMICRON RANGE, PANCHROMATIC, EKTARCHROME, AND EKTACHROME-INFRARED PHOTOGRAPHY, HAS BEEN OBTAINED FOR A TIDELANDS AREA IN SAN FRANCISCO BAY. A TECHNIQUE FOR COMPARING THEIR RELATIVE UTILITY FOR SPECIFIC GEOMORPHIC INTERPRETATIONS HAS BEEN DEVELOPED, WHEREBY A SUBJECTIVE FORM OF TRACING ANALYSIS MAY BE CORRELATED WITH A MORE OBJECTIVE (AND QUANTITATIVE) SCHEME OF SELECTED MICRODENSITOMETER TRAVERSES ACROSS THE VARIOUS NEGATIVES AND POSITIVE TRANSPARENCIES. THE RESULTS SUGGEST THAT THE NINE-LENS MULTIBAND IMAGERY IS EXCESSIVE, AND, THAT FOR A SIMILAR USE AS THAT OF THE PHOTOS STUDIED, COULD BE REDUCED TO FOUR-LENS IMAGERY. THE MOST USEFUL FRAMES ARE THE 550-630 MILLIMICRON BANDWIDTH, THE NEAR- INFRARED, THE EKTACHROME COLOR TRANSPARENCY, AND THE EKTACHROME-INFRARED TRANSPARENCY. VARIOUS UTILITIES ARE SUGGESTED FOR EACH TYPE OF IMAGERY, AND INCREASED EXPERIMENTATION BY GEOLOGISTS WITH THE MICRODENSITOMETER IS URGED. /PE/ <s> BIB002 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> This paper summarizes contemporary remote sensing methodology and its application in wetlands. Using color, color infrared, black-and-white, and black-and-white infrared photography, multiband imagery, and infrared imagery, various applications are examined as they relate to wetlands use. Boundary mapping, vegetation differentiation, and plant primary production patterns have all been demonstrated using remote sensing. A new approach is presented for determination of intertidal water movement using infrared imagery in place of more costly time-consuming dye studies. Remote sensing also has been used in wetlands for location and field orientation, comparative analysis, landform analysis, and water pollution analysis. In terms of documenting baseline conditions for future litigation as well as planning purposes, remote sensing techniques afford the most reliable, least expensive and least time-consuming means of accomplishing these tasks. <s> BIB003 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Wetland vegetation at 7 Indiana areas was studied with 1:4,800 color infrared aerial photographs obtained in early September. Scales of 1:8,000, 1:12,000, and 1:20,000 also were tested to determine the minimum scale at which individual species could be consistently identified. A photointerpretive key to vegetation indicated a potential for accurate identification of all dominant species at the 1:4,800 scale. However, loss of textural resolution often prevented recognition of individual species at smaller scales. Variation in fall senescence among species made early September an optimal time for photography intended for species differentiation. J. WILDL. MANAGE. 46(1):61-70 Mapping marsh vegetation through ground sampling can present logistical problems. Aerial photointerpretation is often a desirable alternative in terms of difficulty, timeliness, expense, and accuracy of cover-type delineation. Also, photographs are permanent records of wetland conditions, allowing comparison of marsh parameters over time and serving as valuable sources of data for future studies. Although many workers have used aerial photographs in surveying and classifying freshwater wetlands (Dirschl et al. 1974, Klemas et al. 1974, Carter 1977, Carter et al. 1977, Brown 1978, Carter et al. 1979, Stewart et al. 1980), the small photo scales employed often precluded vegetation analyses in sufficient detail for some research objectives. Our study required specific information on water regimes, shoreline characteristics, and plant communities of Indiana wetlands used by migrant sandhill cranes (Grus canadensis) (Lovvorn and Kirkpatrick 1981). The areas ranged from 10 to over 400 ha in size, and were scattered widely throughout the state. Because of limited time and manpower and he level of detail desired, large-scale color infrared aerial photography was chosen as the best means of obtaining the needed information. This paper describes acquisition and interpretation of the photography, the detail observable at a scale of 1:4,800, and a photointerpretive k y to fall vegetation applicable to wetlands in the north central United States. We thank D. L. Shroufe and L. J. Crawley, Indiana Department of Natural Resources, for providing the aircraft, equipment, and expertise necessary to obtain the photography. R. M. Hoffer helped in planning the missions. This work was supported by the Accelerated Research Program for Migratory Shore and Upland Game Birds, U.S. Fish and Wildlife Service, contract 14-16-0009-79-005 with the Indiana Department of Natural Resources, Division of Fish and Wildlife. <s> BIB004 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Abstract Large-scale colour infrared aerial photographs were obtained for part of a tropical coastal salt-marsh in south-east Queensland, Australia. Print reflectances were classified using a numerical divisive hierarchical procedure and related to field data. Vegetation characteristics such as species, size, dry weight and density were significantly associated with each spectral class al the general (macro) and at the detailed (micro) scales. At the macro scale there were four vegetation types: pure stands of tall Sporobolus virginicus; medium-tall Sporobolus dominant but with some Sarcocornia quinqueftora; a mixed type; and finally a type dominated by Sarcocornia. At the micro scale vegetation types were further differentiated by size and dry weight of the two dominant species. <s> BIB005 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Abstract This study was done to identify the species groups of mangrove forest in aerial photographs, to delineate their distribution and to quantify their coverage. Aerial photographs with a scale of 1:40 000 taken in 1983, were used to delineate mangrove forest from Kemaman to Kuantan. The study was conducted in two phases, interpretation of black-and-white panchromatic photographs, and field survey. Results show that there are three mangrove forest types, namely the Rhizophora type, the Avicennia/Sonneratia type, and the mixed-mangrove type. These can be delineated with 90% correct interpretation. An area of 2214 ha is covered by mangrove forest, of which 2% is the Avicennia/Sonneratia type, 24% the Rhizophora type and 74% the mixed-mangrove type. Avicennia/Sonneratia is found to have the highest stand density with 13 348 trees ha−1, followed by Rhizophora with 6697 and mixed-mangrove forest 1997. Thus, it can be concluded that mangrove forest can be delineated, classified and mapped by using this method of study. <s> BIB006 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Abstract The U.S. Fish and Wildlife Service is conducting an inventory of the wetlands of the United States through its National Wetlands Inventory Project (NWI). After considering alternative remote-sensed data sources, the NWI selected high-altitude aerial photography (1:40 000 to 1:130 000 scale) as its primary data source. Stereoscopic interpretation of this photography is an efficient and cost-effective method for identifying, classifying, and inventorying wetlands on a national, regional, and statewide basis. This paper outlines the NWI procedures and summarizes NWI's experience in inventorying forested wetlands, emphasizing problems encountered and their resolution. <s> BIB007 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> The mangroves in a 2845 km2area in the Southern Gulf of Carpentaria, Australia, were mapped from Landsat TM satellite data. The mangroves were mapped by selecting 10 training set areas in dense mangrove (100% cover), and using the maximum and minimum training set values for green, red, near-infra-red (NIR) and NIR/red to map the remaining mangroves. The accuracy of the map was improved by using ecological information about mangroves—they are found in tidally inundated areas—to derive simple rules in a Geographic Information System, to subdivide the areas labelled ‘ mangrove ’ from image processing of satellite data on the basis of nearness to water (next to water and not adjoining water), ground elevation [higher and lower than 10 m above mean sea level (MSL)] and distance from water (>2 and <2 km). Each zone was cross-checked with 1:50 000 panchromatic aerial photographs. Zones that were still mixed vegetation after applying these simple rules were further subdivided by eye. This process resulted in a map with zones identified as either 100% mangrove or 0% mangrove. The areas that were identified as mangrove were also subdivided on the basis of the three main river systems in the study area. The Norman, Bynoe and Flinders Rivers had 40·86, 10·09 and 5·42 km2of mangroves, respectively. These areas combined with the 9·89 km2of coastal mangrove to give a total of 66·25 km2of mangrove in the study area. <s> BIB008 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Land-cover information for Nigeria was obtained from a countrywide, low-level aerial survey conducted in 1990. A range of spectral vegetation indices (SVIs) and ground surface temperature estimates were calculated for Nigeria using daily data throughout 1990 from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. A supervised classification of the land-cover classes was then performed using a modified discriminant analysis in which predictor variables were selected from the mean, maximum, minimum and standard deviation of the raw waveband AVHRR data, AVHRR derived products and a digital elevation model (DEM). With a 60 per cent threshold coverage by any one of eight major vegetation types the analysis correctly predicted land-cover type with producer accuracies (excluding 'bare ground' with only a few points) of between 48 per cent (cultivation) and 100 per cent (mangrove) (average 74.5 per cent). <s> BIB009 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Four Validation Overflights for Amazon Mosaics (VOAM) aerial video surveys have been carried out in the Brazilian Amazon to provide ground verification for mapping of wetland cover with the Global Rain Forest Mapping (GRFM) Project JERS-1 (Japanese Earth Remote Sensing Satellite) mosaics of the Amazon basin. Surveys in 1995 and 1996, acquired with handheld analog camcorders from small aircraft, were timed to imaging of the GRFM low- and high-water mosaics, and limited to within 600 km of Manaus. For the 1997 and 1999 flights, digital camcorder systems were installed in the Bandeirante survey plane operated by Brazil's National Institute for Space Research. The VOAM97 and VOAM99 surveys circumscribed the Brazilian Amazon, documenting ground conditions at resolutions on the order of 1 m (wide-angle format) and 10 cm (zoom format) for wetlands, forests, savannas, and human-impacted areas. Global Positioning System (GPS) information encoded on the video audio track was extracted by mosaicking software that au... <s> BIB010 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Abstract A study was conducted on the south Texas Gulf Coast to evaluate color-infrared (CIR) aerial photography and CIR true digital imagery combined with unsupervised image analysis techniques to distinguish and map black mangrove [Avicennia germinans (L.) L.] populations. Accuracy assessments performed on computer-classified maps of photographic and digital images of the same study site had both producer's and user's accuracies of 100% for black mangrove. An accuracy assessment performed on a computer-classified map of a digital image only of a second study site had a producer's accuracy of 78.6% and a user's accuracy of 100%. These results indicate that CIR photography and digital imagery combined with image analysis techniques can be used successfully to distinguish and quantify the extent of black mangrove along the south Texas Gulf Coast. <s> BIB011 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Abstract A study was conducted on the South Texas Gulf Coast to evaluate archive aerial color-infrared (CIR) photography combined with supervised image analysis techniques to quantify changes in black mangrove [Avicennia germinans (L.) L.] populations over a 26-year period. Archive CIR film from two study sites (sites 1 and 2) was studied. Photographs of site 1 from 1976, 1988, and 2002 showed that black mangrove populations made up 16.2%, 21.1%, and 29.4% of the study site, respectively. Photographs of site 2 from 1976 and 2002 showed that black mangrove populations made up 0.4% and 2.7% of the study site, respectively. Over the 26-year period, black mangrove had increases in cover of 77% and 467% on sites 1 and 2, respectively. These results indicate that aerial photographs coupled with image analysis techniques can be useful tools to monitor and quantify black mangrove populations over time. <s> BIB012 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Detailed vegetation mapping of wetlands, both natural and restored, can offer valuable infor- mation about vegetation diversity and community structure and provides the means for examining vegetation change over time. We mapped vegetation at six tidal marshes (two natural, four restored) in the San Francisco Estuary, CA, USA, between 2003 and 2004 using detailed vegetation field surveys and high spatial-resolution color-infrared aerial photography. Vegetation classes were determined by performing hierarchical agglomerative clustering on the field data collected from each tidal marsh. Supervised classifi- cation of the CIR photography resulted in vegetation class mapping accuracies ranging from 70 to 92%; 10 out of 12 classification accuracies were above 80%, demonstrating the potential to map emergent wetland vegetation. The number of vegetation classes decreased with salinity, and increased with size and age. In general, landscape diversity, as measured by the Shannon's diversity index, also decreased with salinity, with an exception for the most saline site, a newly restored marsh. Vegetation change between years is evident, but the differences across sites in composition and pattern were larger than change within sites over two growing seasons. <s> BIB013 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high- and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR) data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove ecosystem mapping, as well as the numerous methods and techniques used for data analyses, and to further discuss their potential and limitations. <s> BIB014 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> The Australian Great Artesian Basin (GAB) supports a unique and diverse range of ecologically significant groundwater-fed wetland ecosystems termed GAB springs. The springs are of great national and international importance for their ecological, scientific and economic values, and are culturally significant to indigenous Australians. The ecological sustainability of the springs has become uncertain in recent times due to increased mining operations and associated groundwater extractions from the GAB. The impacts of existing water extractions from the time of European settlement, pastoral activities and more recently mining are largely unknown. This situation is compounded by the likelihood of future increasing demand of water extractions for mining operations. The GAB springs are spatially disparate ecosystems located within the arid interior of South Australia, akin to islands in their ecological setting. The springs exhibit a diverse range of geomorphology, hydrogeology, surface expressions and vegetation community composition over a wide range of spatial scales. A suite of remote sensing technologies were used to capture the range of scales of the spring wetlands and their surface expressions. This multi-sensor approach enabled definition of the spatial and temporal responses of dominant plant species, communities and entire wetlands. To validate the suite of satellite and airborne imagery several comprehensive field campaigns were conducted, capturing the variation in spring vegetation communities and surface expressions. This paper provides a review highlighting the sensor synergies that can be drawn from research conducted from the Australian National Water Commission flagship research program, Allocating Water and Maintaining Springs in the Great Artesian Basin, which has developed new spatial and temporal tools for monitoring indicators of GAB spring response to water allocations and land use (Lewis et al., 2013). The main objectives of this study included: mapping the location and elevation of western GAB springs using high-precision DGPS; development of protocols for ground-based image validation data; develop techniques for detection and monitoring of the surface characteristics of spring-fed wetlands and surrounding environments using fine spatial and spectral resolution imagery; define the short and long-term temporal dynamics of the springs of indicative vegetation types and entire wetlands; use these remote sensing techniques to provide objective and quantitative information about the spring environments and ecological processes. The sensors and image analyses employed to address these objectives included: MODIS NDVI time series (annual and seasonal traces of entire wetlands and dominant vegetation types); very high resolution multispectral satellite (detailed delineation of wetland extents using NDVI thresholds) and airborne hyperspectral imagery (detailed discrimination of spring plant communities and surrounding substrate using spectral matching algorithms); supported by concurrent colour digital aerial photography and collection of near-concurrent in-situ ecological and spectral data for image calibration and validation purposes. The main focus of this review paper is to draw synergies from the image analyses and research findings that can uniquely be provided using this suite of image data in combination, over differing temporal and spatial scales, to provide new understanding of the drivers and ecological processes underpinning the springs. The multi-sensor approach revealed for the first time the spatial and temporal responses of these unique ecosystems to changing climatic conditions, land use change and groundwater extractions. Our results reveal that long-term variation is an inherent signature of the wetlands, with distinct phenological responses for differing vegetation species being driven by seasonal temperature and rainfall. In addition the springs were found to change over short time periods (2-3 years) in response to rainfall and land use change, expressed as changing trajectories of outflow channels and inter-connectivity between springs. This research provides a baseline definition of the long-term natural variation within these groundwater-fed ecosystems as well as their short-term responses to land use changes and water extractions. These outcomes provide an ideal platform for developing models to predict responses of these ecosystems to present local anthropogenic changes in the region and to global climate change. <s> BIB015 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> This research focuses on improving image analysis using multi-spectral aerial photography and unsupervised classification with a high number of classes. A range of class numbers (15 to 240) were explored using an automated process for classification and validation using the kappa statistic as a measure of classification accuracy. The classification model was kept simple so that the different data treatments could be directly compared under an otherwise standardised method, acknowledging that a typical landcover analysis work-flow would normally build upon this data-preparation phase using a range of available post-classification refinement procedures. Although the accuracy of the unsupervised classification achieved in this simplified model was only moderate, this research has shown that unsupervised classification accuracy improves with increasing numbers of classes and with addition of two processing variants (addition of a normalised difference vegetation index and principal components transformation),... <s> BIB016 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> tAlthough wetlands play a key role in controlling flooding and nonpoint source pollution, sequesteringcarbon and providing an abundance of ecological services, the inventory and characterization of wetlandhabitats are most often limited to small areas. This explains why the understanding of their ecologicalfunctioning is still insufficient for a reliable functional assessment on areas larger than a few hectares.While LiDAR data and multispectral Earth Observation (EO) images are often used separately to mapwetland habitats, their combined use is currently being assessed for different habitat types. The aim ofthis study is to evaluate the combination of multispectral and multiseasonal imagery and LiDAR data toprecisely map the distribution of wetland habitats. The image classification was performed combiningan object-based approach and decision-tree modeling. Four multispectral images with high (SPOT-5)and very high spatial resolution (Quickbird, KOMPSAT-2, aerial photographs) were classified separately.Another classification was then applied integrating summer and winter multispectral image data andthree layers derived from LiDAR data: vegetation height, microtopography and intensity return. Thecomparison of classification results shows that some habitats are better identified on the winter image andothers on the summer image (overall accuracies = 58.5 and 57.6%). They also point out that classificationaccuracy is highly improved (overall accuracy = 86.5%) when combining LiDAR data and multispectralimages. Moreover, this study highlights the advantage of integrating vegetation height, microtopographyand intensity parameters in the classification process. This article demonstrates that information providedby the synergetic use of multispectral images and LiDAR data can help in wetland functional assessment© 2014 Elsevier B.V. All rights reserved. <s> BIB017 </s> A Review of Wetland Remote Sensing <s> Aerial Photographs for Wetland Studies <s> Optical remote sensing data have been considered to display signal saturation phenomena in regions of high aboveground biomass (AGB) and multi-storied forest canopies. However, some recent studies using texture indices derived from optical remote sensing data via the Fourier-based textural ordination (FOTO) approach have provided promising results without saturation problems for some tropical forests, which tend to underestimate AGB predictions. This study was applied to the temperate mixed forest of the Liangshui National Nature Reserve in Northeastern China and demonstrated the capability of FOTO texture indices to obtain a higher prediction quality of forest AGB. Based on high spatial resolution aerial photos (1.0 m spatial resolution) acquired in September 2009, the relationship between FOTO texture indices and field-derived biomass measurements was calibrated using a support vector regression (SVR) algorithm. Ten-fold cross-validation was used to construct a robust prediction model, which avoided the over-fitting problem. By further comparison the performance of the model estimates for greater coverage, the predicted results were compared with a reference biomass map derived from LiDAR metrics. This study showed that the FOTO indices accounted for 88.3% of the variance in ground-based AGB; the root mean square error (RMSE) was 34.35 t/ha, and RMSE normalized by the mean value of the estimates was 22.31%. This novel texture-based method has great potential for forest AGB estimation in other temperate regions. <s> BIB018
Aerial photography allows the rapid collection of a large amount of data and a unique overview of an area. Aerial photography has been the principal remote sensing technology used to analyze ground surface events. The development of satellite remote sensing during the 1970s and 1980s has pushed the aerial-imagery analyses to a new level BIB014 . Only 17 papers were found before the 1990s that used aerial photography as the only information source to study wetland in the wetland remote sensing dataset. Johannessen BIB001 used aerial photographs of Nehalem Bay from 1939 and 1960 to compare the marsh boundaries in different aerial photographs with the U.S. Coast Survey chart from 1875 for seven estuaries. The paper's idea was provoked by the circular pattern that appeared in the photographs; it was the earliest paper on wetland remote sensing. The author concluded that the appearance of abundant circular clumps of vegetation in the aerial photographs of estuarine mud flats in temperate regions was proof of the rapid expansion of marshes. Subsequently, Pestrong BIB002 used nine-lens multiband imagery within the range of 400-900 nm and other images in a tideland area of San Francisco Bay in the United States to develop a technique comparing their relative utility for specific geomorphic interpretations. The author argued that the nine-lens multiband imagery is excessive and can be mitigated to four bands (550-630 nm, near-infrared, Ektachrome color transparency, and Ektachrome-infrared transparency). In the next few years, aerial photography was used in wetland mapping BIB003  and the visual interpretation method was developed. Wetland land cover classification and plant identification are often challenging due to the complexity of the wetland landscapes and the influence of biophysical variables, such as water levels, salt content, phenological vegetation variations, and density [36] , but many studies have explored more methods to obtain accurate results. Scarpace et al.  used properly calibrated digitized aerial photography imagery to identify the wetland vegetation in Sheboygan Marsh of the United States by employing the visual interpretation method. To estimate the accuracy of the results, random points were selected; the accuracy was determined to be 56%-60%. The vegetation types could be clearly identified by color-infrared (CIR) aerial photographs because of the strongly reflecting plants in near-infrared wavebands to which CIR aerial photograph is sensitive BIB005 . Based on a comparison with other scales of aerial photographs in seven Indiana wetlands, Lovvorn and Kirkpatrick BIB004 found that 1:4800 scale CIR aerial photographs have potential for the accurate identification of all dominant species and that early September is an optimal time for species identification using color photographs because of the variation in fall senescence among species. Dale et al. BIB005 used CIR aerial photographs to identify the vegetation types in a subtropical coastal salt marsh in southeastern Queensland, Australia, by employing a polythetic divisive procedure. Based on a comparison of their results with unsupervised and supervised classifications, they found that the intrinsic visible variation on a photograph has an advantage over the other two classification methods. At last, four clearly separate salt marsh vegetation types were identified in the photos at macro-level; eight types were recognizable at micro-level. Ibrahim and Hashim BIB006 identified species groups of mangrove forest in 1:40,000-scale aerial photographs and determined three mangrove forest types with a 90% correct interpretation. Tiner BIB007 used high-altitude aerial photography with 1:40,000 to 1:130,000 scales as the primary data sources and visual stereoscopic photo interpretation for the identification, classification, and inventory of forested wetlands on a national basis in the United States. The author concluded that CIR aerial photography from the early spring is best for detecting deciduous forested wetlands in temperate regions. Besides the visual interpretation techniques for wetland mapping, automated classification methods (unsupervised classification and supervised classification) were also carried out. Supervised classification was used for high-resolution multispectral imagery from the Compact Airborne Spectrographic Imager (CASI) to classify mangroves from Turks and Caicos. Six mangrove classes were identified with an overall accuracy of 78.2%. The authors concluded that CASI imagery can be used to assess mangrove areas with a greater level of detail and accuracy than with satellite sensors  . Furthermore, CIR photographs have been used to identify a special wetland plant. Everitt et al.  used supervised classification techniques to classify CIR photographs and distinguish wild taro along Rio Grande River in Southwest Texas and obtained classification results with higher accuracy (producer and user accuracies ranging from 83.3% to 100%). Unsupervised and supervised image analysis techniques were used for archived aerial CIR photographs to monitor black mangrove on South Texas Gulf Coast of the United States and provided accurate results BIB011 BIB012 . Tuxen et al. BIB013 used supervised classification of CIR photographs to map the composition changes of the wetland vegetation in San Francisco Estuary, USA. The mapping accuracies ranged from 70% to 92%. Martin et al. BIB016 improved the image analysis for lower delta of Waikato River situated on west coast of the North Island of New Zealand using multispectral aerial photography and unsupervised classification with a high number of classes. Their results showed that the unsupervised classification accuracy can be improved with an increasing number of spectral classes, although it is likely that they did not achieve the upper accuracy limit with their maximum class size of 240 classes. The highest unsupervised classification accuracy achieved was a kappa value of 0.45 when 240 classes were used. Aerial photography has an advantage in terms of spatial resolution and data acquisition time; however, wetland studies use these data typically in narrow coastal areas or along rivers because of the generally small cover areas. In most cases, aerial photographs are combined with other satellite images to study wetland on a regional or national scale. Matthews  mapped wood bison habitat in an area of 3383.5 km 2 in the vicinity of the Mills and Mink lakes in the Northwest Territory of Canada using Landsat 5 Thematic Mapper (TM) as data sources and CIR photographs (1:20,000 scale) and ground surveys as reference data. Visual interpretation and automated classification methods were employed to classify the study region into ten habitat cover types, with an overall accuracy of 91%, and the two important winter forage habitats, sedge meadow and willow savanna, with an accuracy of 95% and 75%, respectively. Long and Skewes BIB008 used 1:50,000 panchromatic aerial photographs to check the mangrove map from Landsat TM satellite data in Southern Gulf of Carpentaria. Aerial video surveys have also been used to provide ground verification for mapping of wetland cover in Amazon Basin BIB010 . Aerial surveys can also be used as supplementary data for the land cover mapping in large areas based on coarse spatial resolution imagery (e.g., Advanced Very High Resolution Radiometer, AVHRR) BIB009 . White BIB015 used multi-sensors to capture the variation in spring wetland vegetation communities and surface expressions in Australian Great Artesian Basin. Airborne hyperspectral imagery was selected as reference data to discriminate the spring plant communities and surrounding substrate in detail. The combination of multispectral and multi-seasonal imagery (Quickbird, Korea Multi-Purpose Satellite-2 (KOMPSAT-2), aerial photographs) and Light Detection and Ranging (LiDAR) data were used by Rapinel et al. BIB017 to precisely map the distribution of wetland habitats in northeastern Brittany near the Mont-Saint-Michel Bay, France. They argued that the classification accuracy can be highly improved (overall accuracy = 86.5%) when combining LiDAR data and multispectral images. To overcome the signal saturation phenomena in regions of high aboveground biomass and multi-storied forest canopies using optical remote sensing data, Meng et al. BIB018 used texture indices derived from optical remote sensing data via Fourier-based textural ordination (FOTO) to map aboveground biomass in temperate forest of Northeastern China. Based on aerial photos with high spatial resolution, they calibrated the relationship between FOTO indices and field-derived biomass measurements and found that FOTO indices account for 88.3% of the variance in ground-based aboveground biomass. Aerial photography techniques have been widely used in wetland studies because of their excellent advantages in terms of spatial resolution, cost and time, especially when satellite remote sensing techniques were in an early stage. Because of the challenges of data acquisition in large areas by flight, aerial photography has usually been used for the wetland mapping of small areas. After the launch of satellites, especially the launch of Landsat TM, aerial photography was mainly used for assessment of the classification procedures or biomass derived from lower-resolution remote sensing methods.