Guidance for benthic habitat mapping: an aerial photographic approach

This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor

Application of remote sensing to state and regional problems

The author has identified the following significant results. The Lowndes County data base is essentially complete with 18 primary variables and 16 proximity variables encoded into the geo-information system. The single purpose, decision tree classifier is now operational. Signatures for the thematic extraction of strip mines from LANDSAT Digital data were obtained by employing both supervised and nonsupervised procedures. Dry, blowing sand areas of beach were also identified from the LANDSAT data. The primary procedure was the analysis of analog data on the I2S signal slicer

Effects of Digitization and JPEG Compression on Land Cover Classification Using Astronaut-Acquired Orbital Photographs

Studies that utilize astronaut-acquired orbital photographs for visual or digital classification require high-quality data to ensure accuracy. The majority of images available must be digitized from film and electronically transferred to scientific users. This study examined the effect of scanning spatial resolution (1200, 2400 pixels per inch [21.2 and 10.6 microns/pixel]), scanning density range option (Auto, Full) and compression ratio (non-lossy [TIFF], and lossy JPEG 10:1, 46:1, 83:1) on digital classification results of an orbital photograph from the NASA - Johnson Space Center archive. Qualitative results suggested that 1200 ppi was acceptable for visual interpretive uses for major land cover types. Moreover, Auto scanning density range was superior to Full density range. Quantitative assessment of the processing steps indicated that, while 2400 ppi scanning spatial resolution resulted in more classified polygons as well as a substantially greater proportion of polygons < 0.2 ha, overall agreement between 1200 ppi and 2400 ppi was quite high. JPEG compression up to approximately 46:1 also did not appear to have a major impact on quantitative classification characteristics. We conclude that both 1200 and 2400 ppi scanning resolutions are acceptable options for this level of land cover classification, as well as a compression ratio at or below approximately 46:1. Auto range density should always be used during scanning because it acquires more of the information from the film. The particular combination of scanning spatial resolution and compression level will require a case-by-case decision and will depend upon memory capabilities, analytical objectives and the spatial properties of the objects in the image

The Assessment of African Protected Areas

In order to achieve goals for reduction in the rate of biodiversity loss, it is vital that geographically flexible conservation funding is focused on the areas where biodiversity is the highest and is most threatened. There is currently a shortage of systematic and repeatable methods for the assessment of priority areas for conservation. Furthermore, existing prioritisations tend to focus on large biogeographical units, defined by regional experts. We propose a continental scale repeatable methodology, using existing geographical databases, for the prioritisation of African protected areas. This information is utilised to develop 6 indicators for each protected area, quantifying its value with regards to amphibian, bird and mammal species diversity, irreplaceability of habitat, and threat from population pressure and agricultural boundary pressure. These indicators are then summarised to show how the protected area performs, for each indicator, in comparison to other protected areas from the same country or the same ecoregion. Results are also synthesised to show the most valuable protected areas for a given taxa. Finally, the prioritisation is presented via the internet in conjunction with phenology, climate, and environmental information specific to each protected area.JRC.H.3-Global environement monitorin

Primary Wood-Using Mills and Forest Resources: Interactions between Wood Demand and Procurement Areas

It is a common belief that the presence of forest industry and associated wood demand will result in forest management of procurement areas. The following essays examined the relationship between mill demand and procurement areas by assessing the likelihood of forest management and the ability to predict future wood output. The first study investigates the likelihood of forest management given proximity to mills using a multivariate probit model, incorporating forest characteristics and primary wood-using mill information collected by the USDA Forest Service Forest Inventory and Analysis and the Timber Products Output (TPO) survey. The second essay explores the use of vector autoregressive methods to forecast county pulpwood output using pulpwood production data collected by TPO. We evaluated a group of forecasting methods in the vector autoregressive family and compared the models forecast accuracy to that of the commonly used step-forward methodology. Results from the first study indicate that mill proximity has a low impact on private forest landowner management decisions. This information may prove useful to industry and state foresters when dealing with increases in demand arising from new markets, such as bioenergy. Forecasts from the second essay highlight the cross-county differences in terms of pulpwood output in response to national demand. While the macroeconomic series helped predict output activity in some counties, a group of counties displayed no correlation between product output and demand measured by the national variables. The results emphasize the need for disaggregated analysis to capture the dynamics of the procurement areas and primary mills

Remote-Sensing Detection of Invasive Chinese Tallow (Triadica sebifera) in a Floodplain Environment

Chinese tallow (Tradica sebifera) is an established invasive species in many southern woodlands in the United States. Its ability to adapt and spread quickly into disturbed areas has made it an invasive species of much concern to land managers. Riparian/floodplain environments have been affected by tallow as much as upland areas and entail a high degree of Chinese tallow invasion. Remote sensing is a tool that may provide a means of detecting, or classifying, Chinese tallow. There have been very few studies that have attempted to map Chinese tallow in a floodplain environment. This research focused on mapping Chinese tallow on a single river meander bend. The purpose of this study was to determine which of the nonparametric detection methods considered, such as Multivariate Regression Splines (MARS), Stochastic Gradient Boosting (SGB) and the Random Forest (RF) models, as well as common spectral-extraction algorithms, were able to most accurately detect Chinese tallow in a floodplain forest based on remote-sensing data. In addition, it was the purpose of this study to attempt to determine factors affecting tallow growth and spread, and to map the spatial distribution of tallow in the study area. Fieldwork was conducted in 2010 and 2014 to acquire Chinese tallow presence/absence information to be used for classification model training and testing. A hyperspectral Hyperion satellite image from summer 2010 constituted the primary remote-sensing data source, as well as airborne LiDAR data. The three nonparametric models tested were used to predict Chinese tallow occurrences in the study area. A variety of input variables were employed in the modeling process, including: Hyperion image bands, dimensionality-reduced Minimum Noise Fraction (MNF) images, vegetation indices, and topographic and soil variables. An endmember-based approach was also used to classify tallow presence but was not very successful. Results show that the most accurate dataset-combination trials involving both SGB and MARS yield high overall classification accuracy, 92.85%, whereas the most accurate RF dataset-combination trial provides lower overall classification accuracy, at 80%. Both spatial and aspatial statistical analyses were performed on the classification results. Significance testing indicates that the most accurate RF classification is not statistically significantly different from the most accurate SGB and MARS classifications. However, other error matrix significance testing finds the most accurate RF classification to be statistically significantly different from the most accurate SGB and MARS Chinese tallow classifications. A hot-spot analysis revealed that homogenous areas classified as tallow or as non-tallow can be detected and identified. Results from this study are promising in many areas of the meander bend, such as the transition zone where tallow is prevalent but less so in areas that have more established forest. Some methods tested were successful in detecting tallow and their use may aid land managers in the managing Chinese tallow growth and spread

Discrimination of unique biological communities in the Mississippi lignite belt

Small scale hardcopy LANDSAT prints were manually interpreted and color infrared aerial photography was obtained in an effort to identify and map large contiguous areas of old growth hardwood stands within Mississippi's lignite belt which do not exhibit signs of recent disturbance by agriculture, grazing, timber harvesting, fire, or any natural catastrophe, and which may, therefore, contain unique or historical ecological habitat types. An information system using land cover classes derived from digital LANDSAT data and containing information on geology, hydrology, soils, and cultural activities was developed. Using computer-assisted land cover classifications, all hardwood remnants in the study area which are subject to possible disturbance from surface mining were determined. Twelve rare plants were also identified by botanists

Estuarine Mapping and Eco-Geomorphological Characterization for Potential Application in Conservation and Management: Three Study Cases along the Iberian Coast

Geomorphological changes in recent decades in three estuaries along the Iberian coast were analysed using aerial orthophotographs. A hierarchical classification scheme, based on a literature review representing 26 estuarine eco-geomorphological features relevant to estuarine dynamics and functioning, is described. The estuaries selected were San Vicente de la Barquera (N Spain), Guadiana River (SW border between Spain and Portugal) and the Ebro River Delta mouth (NE Spain). For these systems, a 60-year time series of high-resolution maps was developed, analysing the changes in feature surfaces. The main subsystems analysed were beach, dunes, saltmarshes and the drainage network. The results of the cartographies showed general behaviour common to all transitional systems, relationships among main subsystems and processes inherent to each one. This work illustrates how beaches and dunes serve as a protective barrier for the tidal flats, acting as a sediment buffer for the entire system. The subsystems are connected by the drainage network responsible for the exchange of matter and energy between them. Furthermore, an accuracy assessment was performed in one of the study zones to identify the limitations of mapping with aerial photographs. The results explain the changes with time but also the processes and relationships between the estuarine features at a long-term scale. This work adds an important perspective towards a general understanding of their dependence on intrinsic and boundary conditions

System requirement report for Level 2 – national management institutions, for the Bureau of Fisheries and Aquatic Resources in the Philippines

This report presents the findings from a thorough literature review, workshops, and group and individual interviews conducted by STREAM in the Philippines in November and December 2003. The ambitious scope of the report combined with the limited time frame and funding available to compile it necessitated the extensive use of secondary data, including both published and unpublished material written by staff of the agencies / organisations involved, with very limited editing of material used. All possible efforts were made to generate information in participation with the government institutions responsible for managing the fisheries, and all contributors (as well as many other stakeholders) were provided with multiple opportunities to comment on the report content. The contributors are listed on the front page of the report. (Pdf contains 56 pages)

Arctic shrub expansion revealed by Landsat-derived multitemporal vegetation cover fractions in the Western Canadian Arctic

Warming induced shifts in tundra vegetation composition and structure, including circumpolar expansion of shrubs, modifies ecosystem structure and functioning with potentially global consequences due to feedback mechanisms between vegetation and climate. Satellite-derived vegetation indices indicate widespread greening of the surface, often associated with regional evidence of shrub expansion obtained from long-term ecological monitoring and repeated orthophotos. However, explicitly quantifying shrub expansion across large scales using satellite observations requires characterising the fine-scale mosaic of Arctic vegetation types beyond index-based approaches. Although previous studies have illustrated the potential of estimating fractional cover of various Plant Functional Types (PFTs) from satellite imagery, limited availability of reference data across space and time has constrained deriving fraction cover time series capable of detecting shrub expansion. We applied regression-based unmixing using synthetic training data to build multitemporal machine learning models in order to estimate fractional cover of shrubs and other surface components in the Mackenzie Delta Region for six time intervals between 1984 and 2020. We trained Kernel Ridge Regression (KRR) and Random Forest Regression (RFR) models using Landsat-derived spectral-temporal-metrics and synthetic training data generated from pure class spectra obtained directly from the imagery. Independent validation using very-high-resolution imagery suggested that KRR outperforms RFR, estimating shrub cover with a MAE of 10.6 and remaining surface components with MAEs between 3.0 and 11.2. Canopy-forming shrubs were well modelled across all cover densities, coniferous tree cover tended to be overestimated and differentiating between herbaceous and lichen cover was challenging. Shrub cover expanded by on average + 2.2 per decade for the entire study area and + 4.2 per decade within the low Arctic tundra, while relative changes were strongest in the northernmost regions. In conjunction with shrub expansion, we observed herbaceous plant and lichen cover decline. Our results corroborate the perception of the replacement and homogenisation of Arctic vegetation communities facilitated by the competitive advantage of shrub species under a warming climate. The proposed method allows for multidecadal quantitative estimates of fractional cover at 30 m resolution, initiating new opportunities for mapping past and present fractional cover of tundra PFTs and can help advance our understanding of Arctic shrub expansion within the vast and heterogeneous tundra biome