USGS Science⌕ Search

SEARCH · USGS Science

Results for “Spatial Statistics”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 865 records · Page 48Linked to original sources
USGS2003

A Framework for Long-term Ecological Monitoring in Olympic National Park: Prototype for the Coniferous Forest Biome

This report is the result of a five-year collaboration between scientists of the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, Olympic Field Station, and the natural resources staff of Olympic National Park to develop a comprehensive strategy for monitoring natural resources of Olympic National Park. Olympic National Park is the National Park Serviceʼs prototype monitoring park, representing parks in the coniferous forest biome. Under the umbrella of the National Park Serviceʼs prototype parks program, U.S. Geological Survey and Olympic National Park staffs are obligated to: develop strategies and designs for monitoring the long-term health and integrity of national park ecosystems with a significant coniferous forest component. design exportable monitoring protocols that can be used by other parks within the coniferous forest biome (i.e., parks having similar environments), and create a demonstration area and ʻcenter of excellenceʼ for assisting other parks in developing ecological monitoring programs. Olympic National Park is part of the North Coast and Cascades Network, a network of seven Pacific Northwestern park units created recently by the National Park Serviceʼs Inventory and Monitoring Program to extend the monitoring of ʻvital signsʼ of park health to all National Park Service units. It is our intent and hope that the monitoring strategies and conceptual models described here will meet the overall purpose of the prototype parks monitoring program in proving useful not only to Olympic National Park, but also to parks within the North Coast and Cascades Network and elsewhere. Part I contains the conceptual design and sampling framework for the prototype long-term monitoring program in Olympic National Park. In this section, we explore key elements of monitoring design that help to ensure the spatial, ecological, and temporal integration of monitoring program elements and discuss approaches used to design an ecosystem-based monitoring program. Basic monitoring components include ecosystem drivers, (e.g., climate, atmospheric inputs, human pressures), indicators of ecosystem integrity (e.g., biogeochemical indicators), known threats (e.g., impacts of introduced mountain goats), and focal or ʻkeyʼ species (e.g., rare or listed species, Roosevelt elk). Monitoring system drivers and key indicators of ecosystem integrity provide the long-term baseline needed to judge what constitutes ʻunnaturalʼ variation in park resources and provide the earliest possible warning of unacceptable change. Monitoring effects of known threats and the status of focal species will provide information useful to park managers for dealing with current park issues. In Part I we describe the process of identifying potential indicators of ecological condition and present conceptual models of park ecosystems. In addition we report results from several workshops held in conjunction with Olympic National Park aimed at identifying potential indicators of change in the parkʼs ecosystem. First, we describe the responses of Olympic National Park staff to the generic question, “What is the most important resource to monitor in Olympic National Park and why?” followed by the responses from resource and land managers from areas adjoining the park. We also catalogue the responses of various expert groups that we asked to help identify the most appropriate system drivers and indicators of change in the Olympic National Park ecosystems. Results of the workshops provided the justification for selecting basic indicators of ecosystem integrity, effects of current threats to park resources, and focal resources of parks to detect both the currently evident and unforeseeable changes in park resources. We conclude Part I by exploring several generic statistical issues relevant to monitoring natural resources in Olympic National Park. Specifically we discuss trade-offs associated with sampling extensively versus sampling intensively in smaller geographic regions and describe a conceptual framework to guide development of a generic sampling frame for monitoring. We recommend partitioning Olympic National Park into three zones of decreasing accessibility to maximize monitoring efficiency. We present examples of how the generic sampling frame could be used to help ensure spatial integration of individual monitoring projects. Part II of the report is a record of the potential monitoring questions and indicators identified to date in our workshops. The presentation is organized according to the major system drivers, components, and processes identified in the intermediate-level working model of the Olympic National Park ecosystem. For each component of the park system, we develop the need and justification for monitoring, articulate park management issues, and describe key resources and ecosystem functions. We also present a pictorial conceptual model of each ecological subsystem, identify monitoring questions, and list potential indicators for each monitoring question. We conclude each section by identifying linkages of indicators to other ecological subsystems in our general ecosystem model, spatial and temporal contexts for monitoring (where and how often to monitor), and research and development needs. Part II represents the most current detailed listing of potential indicators—the material for subsequent discussions of monitoring priorities and selection of indicators for protocol development. Collectively, the sections of this report contain a comprehensive list of the important monitoring questions and potential indicators as well as recommendations for designing an integrated monitoring program. In Part I, Chapter 6 we provide recommendations on how to proceed with the important next steps in the design process: establishing priorities among the many possible monitoring questions and indicators, and beginning to research and design effective long-term monitoring protocols.

Information and Technology Report↗
USGS2025

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗
USGS2010

Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: The Argentine ant at Haleakala National Park, Hawaii

Mechanistic models for predicting species’ distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456-521 degree-days), were just above the developmental requirements identified from earlier laboratory studies (445 degree-days above 15.98C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about the potential spread of invasive species.

Hawaii↗
USGS2005

Fractured-aquifer hydrogeology from geophysical logs; the passaic formation, New Jersey

The Passaic Formation consists of gradational sequences of mudstone, siltstone, and sandstone, and is a principal aquifer in central New Jersey. Ground‐water flow is primarily controlled by fractures interspersed throughout these sedimentary rocks and characterizing these fractures in terms of type, orientation, spatial distribution, frequency, and transmissivity is fundamental towards understanding local fluid‐transport processes. To obtain this information, a comprehensive suite of geophysical logs was collected in 10 wells roughly 46 m in depth and located within a .05 km 2 area in Hopewell Township, New Jersey. A seemingly complex, heterogeneous network of fractures identified with an acoustic televiewer was statistically reduced to two principal subsets corresponding to two distinct fracture types: (1) bedding‐plane partings and (2) high‐angle fractures. Bedding‐plane partings are the most numerous and have an average strike of N84°W and dip of 20° N. The high‐angle fractures are oriented subparallel to these features, with an average strike of N79° E and dip of 71° S, making the two fracture types roughly orthogonal. Their intersections form linear features that also retain this approximately east‐west strike. Inspection of fluid temperature and conductance logs in conjunction with flow meter measurements obtained during pumping allows the transmissive fractures to be distinguished from the general fracture population. These results show that, within the resolution capabilities of the logging tools, approximately 51 (or 18 percent) of the 280 total fractures are water producing. The bedding‐plane partings exhibit transmissivities that average roughly 5 m 2 /day and that generally diminish in magnitude and frequency with depth. The high‐angle fractures have average transmissivities that are about half those of the bedding‐plane partings and show no apparent dependence upon depth. The geophysical logging results allow us to infer a distinct hydrogeologic structure within this aquifer that is defined by fracture type and orientation. Fluid flow near the surface is controlled primarily by the highly transmissive, subhorizontal bedding‐plane partings. As depth increases, the high‐angle fractures apparently become more dominant hydrologically.

Ground Water↗
USGS2016

An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach

We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.

Remote Sensing↗
USGS2020

Climate change: Flowering time may be shifting in surprising ways

Climate change is known to affect regional weather patterns and phenology; however, we lack under-standing of how climate drives phenological change across local spatial gradients. This spatial variation is critical for determining whether subpopulations and metacommunities are changing in unison or diverging in phenology. Divergent responses could reduce synchrony both within species (disrupting gene flow among subpopulations) and among species (disrupting interspecific interactions in communities). We also lack understanding of phenological change in environments where life history events are frequently aseasonal, such as the tropical, arid,and semi-arid ecosystems that cover vast areas.Using a 33-year-long dataset spanning a 1,267-m semi-arid elevational gradient in the southwestern United States, we test whether flowering phenology diverged among subpopulations within species and among five communities comprising 590 species. Applying circular statistics to test for changes in year-round flowering, we show flowering has become earlier for all communities except at the highest elevations. However, flowering times shifted at different rates across elevations likely because of elevation-specific changes in temperature and precipitation, indicating diverging phenologies of neighboring communities. Subpopulations of individual species also diverged at mid-elevation but converged in phenology at high elevation. These changes in flowering phenology among communities and subpopulations are undetectable when data are pooled across the gradient. Furthermore, we show that nonlinear changes in flowering times over the 33-year record are obscured by traditional calculations of long-term trends. These findings reveal greater spatiotemporal complexity in phenological responses than previously recognized and indicate climate is driving phenological reshuffling acrosslocal spatial gradients.

Current Biology↗
USGS2005

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Environmental Management↗
USGS2007

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts.

Arizona↗
USGS2016

Surface-air mercury fluxes across Western North America: A synthesis of spatial trends and controlling variables

Mercury (Hg) emission and deposition can occur to and from soils, and are an important component of the global atmospheric Hg budget. This paper focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.

Science of the Total Environment↗
USGS2007

Natal location influences movement and survival of a spatially structured population of snail kites

Despite the accepted importance of the need to better understand how natal location affects movement decisions and survival of animals, robust estimates of movement and survival in relation to the natal location are lacking. Our study focuses on movement and survival related to the natal location of snail kites in Florida and shows that kites, in addition to exhibiting a high level of site tenacity to breeding regions, also exhibit particular attraction to their natal region. More specifically, we found that estimates of movement from post-dispersal regions were greater toward natal regions than toward non-natal regions (differences were significant for three of four regions). We also found that estimates of natal philopatry were greater than estimates of philopatry to non-natal regions (differences were statistically significant for two of four regions). A previous study indicated an effect of natal region on juvenile survival; in this study, we show an effect of natal region on adult survival. Estimates of adult survival varied among kites that were hatched in different regions. Adults experienced mortality rates characteristic of the region occupied at the time when survival was measured, but because there is a greater probability that kites will return to their natal region than to any other regions, their survival was ultimately influenced by their natal region. In most years, kites hatched in southern regions had greater survival probabilities than did kites hatched in northern regions. However, during a multiregional drought, one of the northern regions served as a refuge from drought, and during this perturbation, survival was greater for birds hatched in the north. Our study shows that natal location may be important in influencing the ecological dynamics of kites but also highlights the importance of considering temporal variation in habitat conditions of spatially structured systems when attempting to evaluate the conservation value of habitats.

Oecologia↗
USGS2020

Sample-size considerations for a study of shorebird nest survival in the 1002 Area, Arctic National Wildlife Refuge, Alaska

Authorization of lease sales for oil development in the 1002 Area of the Arctic National Wildlife Refuge has highlighted gaps in information about biological communities in the area. The U.S. Fish and Wildlife Service, which is planning a study to evaluate spatial variation in the nest survival of tundra-breeding shorebirds to identify hotspots with high nest survival, sought advice from the U.S. Geological Survey on how to predict which sampling designs might be successful in achieving the study goals. I used previously obtained data on nest survival from Alaska’s North Slope to develop a simulation study that explored the statistical consequences of various sampling designs in the context of expected ranges of values of biological parameters. Of all sampling parameters, the number of nests per plot had the strongest influence on the ability to detect hotspots, followed by number of years of monitoring and the age at which nests were found. The benefit of sampling 98 plots instead of 68 was relatively small. Ages of nests cannot be predicted a priori, so I developed a field reference chart to identify when further nest-searching would be useful for a given plot. This simulation study used the best available information, but values of biological parameters will become better defined following subsequent data collection in the 1002 Area. Data from upcoming field seasons could be used to refine this analysis and improve estimation of the expected results of the field study, thus maximizing the likelihood that data from the 1002 Area nest survival study will meet the monitoring goals.

Alaska↗
USGS2002

Grizzly bear denning and potential conflict areas in the Greater Yellowstone Ecosystem

Increasing winter use of steep, high-elevation terrain by backcountry recreationists has elevated concern about disturbance of denning grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). To help identify areas where such conflicts might occur, we developed a spatially explicit model to predict potential denning areas in the GYE. Using a scan area of 630 m around each location, we assigned site attributes to 344 den locations of radio-trackedg rizzly bears from 1975-99. Attributesi dentified as predictorsf or the analysis included elevation, slope, an index of solar radiation, and forest cover. We used the Mahalanobis distance statistic to model the similarity between sites used by denning bears and each cell in the data layers. We used the final Mahalanobis distance model to produce maps of the study area. Potential denning habitat, based upon the model, is abundantw ithin the GYE. Ourr esultsc an be used by land managementa gencies to identifyp otentialc onflict sites and minimize effects of regulated activities on denning grizzly bears. We illustrate how the Gallatin National Forest (GNF) used the model to examine the overlap between potential snowmobile use areas and potential denning habitat as part of a Biological Assessment submitted to the U.S. Fish and Wildlife Service.

Wyoming↗
USGS2009

Variability of the Southern California wave climate and implications for sediment transport

We analyzed wave and wind data from 18 buoys in the Southern California Bight to characterize the spatial and temporal variability of the regional wave climate. Point Conception shelters most of the Bight from being directly impacted by North Pacific weather. The wave height inside the sheltered zone and to the east of the Channel Islands is less than half the wave height in the open ocean to the west. Within the sheltered Bight, storm waves (by proxy of being greater than the 95th percentile wave height for more than 6 hours) are mainly from the west, but long period swells (T p >15 seconds) are mainly from the south-southwest. There are on average two to four storms during each winter month (November-March) and fewer than two storms per month for the rest of the year. The Channel Islands selectively block the westerly swells and make the wave climate in the Santa Barbara Channel different from the rest of the sheltered Bight. A statistically significant wave-height minimum exists in the area offshore Dana Point and Oceanside. The multiyear (2-23 years) wave-data records from all 18 buoys show negligible temporal trend, positive or negative. Like the wave climate, the long-term probability of sediment transport on the continental shelves of the Bight displays large difference between the sheltered and open-ocean (near Point Conception) sites. The return period of incipient sediment motion on the sheltered shelf breaks (one to five months) is at least two orders of magnitude longer than that on the Point Conception shelf break (0.6 day). Similar to the spatial distribution of wave heights, there is a systematic return-period maximum on the shelf off Dana Point and Oceanside. ?? 2009 The Geological Society of America.

Special Paper of the Geological Society of America↗
USGS2006

Relationships between reef fish communities and remotely sensed rugosity measurements in Biscayne National Park, Florida, USA

The realization that coral reef ecosystem management must occur across multiple spatial scales and habitat types has led scientists and resource managers to seek variables that are easily measured over large areas and correlate well with reef resources. Here we investigate the utility of new technology in airborne laser surveying (NASA Experimental Advanced Airborne Research Lidar (EAARL)) in assessing topographical complexity (rugosity) to predict reef fish community structure on shallow (<10 m deep) patch reefs. Marine portions of Biscayne National Park, Florida, USA, were surveyed remotely using the EAARL, and reef fish populations were visually surveyed on 10 patch reefs at independent, randomly selected stations ( n = 10–13 per reef). Rugosity at each station was assessed in situ by divers using the traditional chain-transect method (10-m scale), and remotely using the EAARL submarine topography data at multiple spatial scales (2, 5, and 10 m). The rugosity and biological datasets were analyzed together to elucidate the predictive power of EAARL rugosity in describing the variance in reef fish community variables and to assess the correlation between chain-transect and EAARL rugosity. EAARL rugosity was not well correlated with chain-transect rugosity, or with species richness of fishes (although statistically significant, the amount of variance explained by the model was very low). Variance in reef fish community attributes was better explained in reef-by-reef variability than by physical variables. However, once the reef-by-reef variability was taken into account in a two-way analysis of variance, the importance of rugosity could be seen on individual reefs. Fish species richness and abundance were statistically higher at high rugosity stations compared to medium and low rugosity stations, as predicted by prior ecological research. The EAARL shows promise as an important mapping tool for reef resource managers as they strive to inventory and protect coral reef resources.

Florida↗
USGS2009

Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium

A Global Irrigated Area Map (GIAM) has been produced for the end of the last millennium using multiple satellite sensor, secondary, Google Earth and groundtruth data. The data included: (a) Advanced Very High Resolution Radiometer (AVHRR) 3-band and Normalized Difference Vegetation Index (NDVI) 10 km monthly time-series for 1997-1999, (b) Syste me pour l'Observation de la Terre Vegetation (SPOT VGT) NDVI 1 km monthly time series for 1999, (c) East Anglia University Climate Research Unit (CRU) rainfall 50km monthly time series for 1961-2000, (d) Global 30 Arc-Second Elevation Data Set (GTOPO30) 1 km digital elevation data of the World, (e) Japanese Earth Resources Satellite-1 Synthetic Aperture Radar (JERS-1 SAR) data for the rain forests during two seasons in 1996 and (f) University of Maryland Global Tree Cover 1 km data for 1992-1993. A single mega-file data-cube (MFDC) of the World with 159 layers, akin to hyperspectral data, was composed by re-sampling different data types into a common 1 km resolution. The MFDC was segmented based on elevation, temperature and precipitation zones. Classification was performed on the segments. Quantitative spectral matching techniques (SMTs) used in hyperspectral data analysis were adopted to group class spectra derived from unsupervised classification and match them with ideal or target spectra. A rigorous class identification and labelling process involved the use of: (a) space-time spiral curve (ST-SC) plots, (b) brightness-greenness-wetness (BGW) plots, (c) time series NDVI plots, (d) Google Earth very-high-resolution imagery (VHRI) 'zoom-in views' in over 11 000 locations, (e) groundtruth data broadly sourced from the degree confluence project (3 864 sample locations) and from the GIAM project (1 790 sample locations), (f) high-resolution Landsat-ETM+ Geocover 150m mosaic of the World and (g) secondary data (e.g. national and global land use and land cover data). Mixed classes were resolved based on decision tree algorithms and spatial modelling, and when that did not work, the problem class was used to mask and re-classify the MDFC, and the class identification and labelling protocol repeated. The sub-pixel area (SPA) calculations were performed by multiplying full-pixel areas (FPAs) with irrigated area fractions (IAFs) for every class. A 28 class GIAM was produced and the area statistics reported as: (a) annualized irrigated areas (AIAs), which consider intensity of irrigation (i.e. sum of irrigated areas from different seasons in a year plus continuous year-round irrigation or gross irrigated areas), and (b) total area available for irrigation (TAAI), which does not consider intensity of irrigation (i.e. irrigated areas at any given point of time plus the areas left fallow but 'equipped for irrigation' at the same point of time or net irrigated areas). The AIA of the World at the end of the last millennium was 467 million hectares (Mha), which is sum of the non-overlapping areas of: (a) 252 Mha from season one, (b) 174 Mha from season two and (c) 41 Mha from continuous year-round crops. The TAAI at the end of the last millennium was 399 Mha. The distribution of irrigated areas is highly skewed amongst continents and countries. Asia accounts for 79% (370 Mha) of all AIAs, followed by Europe (7%) and North America (7%). Three continents, South America (4%), Africa (2%) and Australia (1%), have a very low proportion of the global irrigation. The GIAM had an accuracy of 79-91%, with errors of omission not exceeding 21%, and the errors of commission not exceeding 23%. The GIAM statistics were also compared with: (a) the United Nations Food and Agricultural Organization (FAO) and University of Frankfurt (UF) derived irrigated areas and (b) national census data for India. The relationships and causes of differences are discussed in detail. The GIAM products are made available through a web portal (http://www.iwmigiam.org). ?? 2009 Taylor & Francis.

International Journal of Remote Sensing↗
USGS1989

Accretion and canal impacts in a rapidly subsiding wetland II: Feldspar marker horizon technique

Recent (6–12 month) marsh sediment accretion and accumulation rates were measured with feldspar marker horizons in the vicinity of natural waterways and man-made canals with spoil banks in the rapidly subsiding environment of coastal Louisiana. Annual accretion rates in a Spartina alterniflora salt marsh in the Mississippi deltaic plain averaged 6 mm in marsh adjacent to canals compared to 10 mm in marsh adjacent to natural waterways. The rates, however, were not statistically significantly different. The average rate of sediment accretion in the same salt marsh region for a transect perpendicular to a canal (13 mm yr −1 ) was significantly greater than the rate measured for a transect perpendicular to a natural waterway (7 mm yr −1 ). Measurements of soil bulk density and organic matter content from the two transects were also different. This spatial variability in accretion rates is probably related to (1) spoil bank influences on local hydrology; and (2) a locally high rate of sediment input from lateral erosion associated with pond enlargement. In a brackish Spartina patens marsh on Louisiana’s Chenier plain, vertical accretion rates were the same along natural and canal waterways (3–4 mm yr −1 ) in a hydrologically restricted marsh region. However, the accretion rates for both waterways were significantly lower than the rates along a nonhydrologically restricted natural waterway nearby (11 mm yr −1 ). The vertical accretion of matter displayed semi-annual differences in the brackish marsh environment.

Louisiana↗
USGS2024

Intercomparison of same-day remote sensing data for measuring winter cover crop biophysical traits

Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and WorldView-2 same-day paired satellite imagery and handheld multispectral proximal sensors on two days during the 2012–2013 winter cover crop season. We compared two processing levels from three satellites with spatially aggregated proximal data for red and green spectral bands as well as the normalized difference vegetation index (NDVI). We then compared NDVI estimated fractional green cover to in-situ photographs, and we derived cover crop biomass estimates from NDVI using existing calibration equations. We used slope and intercept contrasts to test whether estimates of biomass and fractional green cover differed statistically between sensors and processing levels. Compared to top-of-atmosphere imagery, surface reflectance imagery were more closely correlated with proximal sensors, with intercepts closer to zero, regression slopes nearer to the 1:1 line, and less variance between measured values. Additionally, surface reflectance NDVI derived from satellites showed strong agreement with passive handheld multispectral proximal sensor-sensor estimated fractional green cover and biomass (adj. R 2 = 0.96 and 0.95; RMSE = 4.76% and 259 kg ha−1, respectively). Although active handheld multispectral proximal sensor-sensor derived fractional green cover and biomass estimates showed high accuracies (R 2 = 0.96 and 0.96, respectively), they also demonstrated large intercept offsets (−25.5 and 4.51, respectively). Our results suggest that many passive multispectral remote sensing platforms may be used interchangeably to assess cover crop biophysical traits whereas SPOT 5 required an adjustment in NDVI intercept. Active sensors may require separate calibrations or intercept correction prior to combination with passive sensor data. Although surface reflectance products were highly correlated with proximal sensors, the standardized cloud mask failed to completely capture cloud shadows in Landsat 7, which dampened the signal of NIR and red bands in shadowed pixels.

Maryland↗
USGS1991

Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic

The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors

Photogrammetric Engineering and Remote Sensing↗