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USGS2024

Assessing the utility of uncrewed aerial system photogrammetrically derived point clouds for land cover classification in the Alaska North Slope

Uncrewed aerial systems (UASs) have been used to collect “pseudo field plot” data in the form of large-scale stereo imagery to supplement and bolster direct field observations to monitor areas in Alaska. These data supplement field data that is difficult to collect in such a vast landscape with a relatively short field season. Dense photogrammetrically derived point clouds are created and are facilitated to extract land cover data using a support vector machine (SVM) classifier in this study. We test our approach using point clouds derived from 1-cm stereo imagery of plots in the Alaska North Slope region and compare the results to field observations. The results show that the overall accuracy of six land cover classes (bare soil, shrub, grass, forb/herb, rock, and litter) is 96.8% from classified patches. Shrub had the highest accuracy (>99%) and forb/herb achieved the lowest (<48%). This study reveals that the approach could be used as reference data to check field observations in remote areas.

Alaska↗
USGS2025

RUSH: Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models

Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments.

Florida, Louisiana, North Carolina↗
USGS2024

Development and evaluation of public-supply community water service area boundaries for the conterminous United States

The water service area dataset, derived from the National Boundary Dataset for public-supply water systems in the United States, offers a detailed resolution surpassing county-level assessments, emphasizing water-centric land use. Crucial for linking populations and infrastructure to system withdrawals, it supports the creation of a national public-supply water-use model, enhancing accuracy in estimating water use and distinguishing between publicly supplied and self-supplied domestic water use. Integrating tabular water system data strengthens the national water-use model by enabling tracking of withdrawal locations, source water, and water quality. Evaluated against U.S. Census-derived population datasets, 16 state-provided water service area datasets, and two national land use datasets, the study covers 22,849 community water systems, excluding most small systems serving fewer than 1000 people. Robust correlations between water service areas (WSAs) and satellite-sourced urban and exurban land use types facilitate tracking changes over time. A comparison of state and national datasets for population and WSAs reveals discrepancies ranging from 5% to 73% in state-level populations and 0% to 167% in state-level WSAs. Significant differences can be attributed to the exclusion of sizable incorporated and unincorporated areas in the state-based datasets. Additional comparisons of major metropolitan areas exhibit differences ranging from 2% to 56%.

conterminous United States↗
USGS2011

Spectral reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting

The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area. The result showed that for a pure snow spectrum, the snow reflectance peaks appeared from visible to 800 nm band locations; there was an obvious absorption valley of snow spectrum near 1030 nm wavelength. Compared with fresh snow, the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300~1300, 1700~1800 and 2200~2300 nm, the lowest was from the compacted snow and frozen ice. For the vegetation and snow mixed spectral characteristics, it was indicated that the spectral reflectance increased for the snow-covered land types(including pine leaf with snow and pine leaf on snow background), due to the influence of snow background in the range of 350~1300 nm. However, the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic. In the end, based on the spectrum analysis of snow, vegetation, and mixed snow/vegetation pixels, the mixed spectral fitting equations were established, and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones(correlation coefficient R2=0.9509).

Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and S↗
USGS2003

Land Use on the Island of Oahu, Hawaii, 1998

A hierarchical land-use classification system for Hawaii was developed, and land use on the island of Oahu was mapped. The land-use classification system emphasizes agriculture, developed (urban), and barren/mining uses. Areas with other land uses (conservation, forest reserve, natural areas, wetlands, water, and barren [sand, rock, or soil] regions, and unmanaged vegetation [native or exotic]) were defined as 'other.' Multiple sources of digital orthophotographs from 1998 and 1999 were used as source data. The 1998 island of Oahu land-use data are provided in digital format at http://water.usgs.gov/lookup/getspatial?oahu_lu98 for use in a Geographic Information System (GIS), at 1:24,000-scale with minimum mapping units of 2 hectares (4.9 acres) area and 30-meters (98.4 feet) feature width. In 1998, a total of 59,195 acres (15.4 percent) of the island of Oahu were classified as agricultural land use; 98,663 acres (25.7 percent) were classified as developed; 1,522 acres (0.4 percent) were classified as barren/mining; and 224,331 acres (58.5 percent) were classified as other. An accuracy assessment identified 98 percent accuracy for all land-use classes. In windward (moister) areas, dense vegetation and canopy cover along with rapid recolonization by vegetation potentially obscured land use from photo-interpretation. While in leeward (drier) areas, sparse vegetative cover and slower vegetation recolonization may have resulted in more frequent recognition of apparent land-use patterns.

Water-Resources Investigations Report↗
USGS2026

Linking distribution and return-on-investment models to optimize woody management for prairie grouse in Nebraska

Grasslands in Nebraska, USA, face threats from agricultural conversion, urban development, and woody encroachment, all of which negatively affect prairie grouse ( Tympanuchus spp.) populations. To optimize conservation planning, Nebraska wildlife agencies developed probabilistic area-based surveys for greater prairie-chicken ( T. cupido ) and sharp-tailed grouse ( T. phasianellus ) to sample landscapes across a range of environmental conditions. This design improves historical surveys and enables the development of distribution models that quantitatively define habitat associations and support scenario-based conservation planning. Using survey data collected during 2020–2022, we modeled prairie grouse occurrence and abundance as functions of land cover, topography, and climate using Bayesian logistic and zero-inflated negative binomial models with regularized horseshoe priors. We then conducted a maximum potential return-on-investment analysis of woody cover treatments, assuming sustained treatment success, relative to projected impacts of woody encroachment on prairie grouse populations by 2050. Among modeled associations were a positive association with grasslands having low woody cover and a negative association with grasslands having high woody cover. Across the 3-year period, median estimated annual populations were 142,380 for greater prairie-chicken (range of 95% CIs across years = 68,821–277,615) and 64,154 for sharp-tailed grouse (range of 95% CIs across years = 27,550–146,559). Under projected woody encroachment, mean predicted population declines were 10% for greater prairie-chicken (range of 95% CIs = 7–14%) and 6% for sharp-tailed grouse (range of 95% CIs = 5–7%). Areas with high prairie grouse density and low treatment costs in 2021, and high projected woody encroachment and population loss by 2050, offered the greatest return on investment for woody management. Return on investment was greatest in the northwestern Shortgrass Prairie ecoregion (northwestern Nebraska) for sharp-tailed grouse and the eastern Sandhills ecoregion (central Nebraska) for both species. These models underscore the value of evidence-based, quantitative approaches for prioritizing conservation actions on working lands. Scenario-based modeling could be extended to guide other treatments, such as optimizing restoration (e.g., Conservation Reserve Program) or incentivizing grassland persistence in areas with predicted climate resilience.

Nebraska↗
USGS2005

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.

Remote Sensing of Environment↗
USGS2015

Land-cover change in the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative, 1973 to 2000

This report summarizes baseline land-cover change information for four time intervals from between 1973 and 2000 for the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (LCC). The study used sample data from the USGS Land Cover Trends dataset to develop estimates of change for 10 land-cover classes in the LCC. The results show that an estimated 17.7 percent of the LCC land cover had a change during the 27-year period. Cyclic forest dynamics&mdash;of timber harvest and regrowth&mdash;are the most extensive types of land conversion. Agricultural land had an estimated net decline of 3.5 percent as cropland and pasture were urbanized and developed and converted to forest use. Urban and other developed land covers expanded from 2.0 percent of the LCC in 1973 to 3.1 percent in 2000. The report also highlights causes and challenges of land-cover change.

Gulf Coastal Plains, Ozarks↗
USGS2014

Assessing landscape constraints on species abundance: Does the neighborhood limit species response to local habitat conservation programs?

Landscapes in agricultural systems continue to undergo significant change, and the loss of biodiversity is an ever-increasing threat. Although habitat restoration is beneficial, management actions do not always result in the desired outcome. Managers must understand why management actions fail; yet, past studies have focused on assessing habitat attributes at a single spatial scale, and often fail to consider the importance of ecological mechanisms that act across spatial scales. We located survey sites across southern Nebraska, USA and conducted point counts to estimate Ring-necked Pheasant abundance, an economically important species to the region, while simultaneously quantifying landscape effects using a geographic information system. To identify suitable areas for allocating limited management resources, we assessed land cover relationships to our counts using a Bayesian binomial-Poisson hierarchical model to construct predictive Species Distribution Models of relative abundance. Our results indicated that landscape scale land cover variables severely constrained or, alternatively, facilitated the positive effects of local land management for Ring-necked Pheasants.

Nebraska↗
USGS2017

Groundwater levels, geochemistry, and water budget of the Tsala Apopka Lake system, west-central Florida, 2004–12

Tsala Apopka Lake is a complex system of lakes and wetlands, with intervening uplands, located in Citrus County in west-central Florida. It is located within the 2,100 square mile watershed of the Withlacoochee River, which drains north and northwest towards the Gulf of Mexico. The lake system is managed by the Southwest Florida Water Management District as three distinct “pools,” which from upstream to downstream are referred to as the Floral City Pool, Inverness Pool, and Hernando Pool. Each pool contains a mixture of deep-water lakes that remain wet year round, ephemeral (seasonal) ponds and wetlands, and dry uplands. Many of the major deep-water lakes are interconnected by canals. Flow from the Withlacoochee River, when conditions allow, can be diverted into the lake system. Flow thorough the canals can be used to control the distribution of water between the three pools. Flow in the canals is controlled using structures, such as gates and weirs. Hydrogeologic units in the study area include a surficial aquifer consisting of Quaternary-age sediments, a discontinuous intermediate confining unit consisting of Miocene- and Pliocene-age sediments, and the underlying Upper Floridan aquifer, which consists of Eocene- and Oligocene-age carbonates. The fine-grained quartz sands that constitute the surficial aquifer are generally thin, typically less than 25 feet thick, within the vicinity of Tsala Apopka Lake. A thin, discontinuous, sandy clay layer forms the intermediate confining unit. The Upper Floridan aquifer is generally unconfined in the vicinity of Tsala Apopka Lake because the intermediate confining unit is discontinuous and breached by numerous karst features. In the study area, the Upper Floridan aquifer includes the upper Avon Park Formation and Ocala Limestone. The Ocala Limestone is the primary source of drinking water and spring flow in the area. The objectives of this study are to document the interaction of Tsala Apopka Lake, the surficial aquifer, and the Upper Floridan aquifer; and to estimate an annual water budget for each pool and for the entire lake system for 2004–12. The hydrologic interactions were evaluated using hydraulic head and geochemical data. Geochemical data, including major ion, isotope, and age-tracer data, were used to evaluate sources of water and to distinguish flow paths. Hydrologic connection of the surficial environment (lakes, ponds, wetlands, and the surficial aquifer) was quantified on the basis of a conceptualized annual water-budget model. The model included the change in surface water and groundwater storage, precipitation, evapotranspiration, surface-water inflow and outflow, and net groundwater exchange with the underlying Upper Floridan aquifer. The control volume for each pool extended to the base of the surficial aquifer and covered an area defined to exceed the maximum inundated area for each pool during 2004–12 by 0.5 foot. Net groundwater flow was computed as a lumped value and was either positive or negative, with a negative value indicating downward or lateral leakage from the control volume and a positive value indicating upward leakage to the control volume. The annual water budget for Tsala Apopka Lake was calculated using a combination of field observations and remotely sensed data for each of three pools and for the composite three pool area. A digital elevation model at a 5-foot grid spacing and bathymetric survey data were used to define the land-surface elevation and volume of each pool and to calculate the changes in inundated area with change in lake stage. Continuous lake-stage and groundwater-level data were used to define the change in storage for each pool. The rainfall data used in the water-budget calculations were based on daily radar reflectance data and measured rainfall from weather stations. Evapotranspiration was computed as a function of reference evapotranspiration, adjusted to actual evapotranspiration using a monthly land-cover coefficient (based on evapotranspiration measurements at stations located in representative landscapes). Surface-water inflows and outflows were determined using stage data collected at a series of streamgages installed primarily at the water-control structures. Discharge was measured under varying flow regimes and ratings were developed for the water-control structures. The discharge data collected during the study period were used to calibrate a surface-water flow model for 2004–12. Flows predicted by the model were used in the water-budget analysis. Net groundwater flow was determined as the residual term in the water-budget equation. The results of the water-budget analysis indicate that rainfall was the largest input of water to Tsala Apopka Lake, whereas evapotranspiration was the largest output. For the 2004–12 analysis period, surface-water inflow accounted for 11 percent of the inputs, net groundwater inflow accounted for 1 percent of inputs (annual periods with positive net groundwater flow were included as inputs, while annual periods with negative net groundwater flow were counted as outputs), and rainfall accounted for the remaining 88 percent. For the same period, the outputs consisted of 2 percent surface-water outflow, 12 percent net groundwater outflow, and 86 percent evapotranspiration. Net groundwater inflows and surface-water/groundwater storage were negligible during the water-budget period but could be important components of the budget in individual years. The net groundwater flow was negative (downward) for 8 out of the 9 years modeled (2004–12), indicating that the Tsala Apopka Lake study area was primarily a recharge area for the underlying Upper Floridan aquifer during this time period. Groundwater-level elevation in paired wells (adjacent wells completed in the surficial aquifer and Upper Floridan aquifer) typically was higher in the surficial aquifer than the Upper Floridan aquifer. However, hydraulic head data indicate that the surficial aquifer often has discharge potential to the surface-water system, especially in the low lying areas near the major lakes. Surficial-aquifer water levels were often higher than lake stages, especially during wet periods, which is likely an indication of aquifer-to-lake seepage in these areas. East of the major lakes, hydraulic head data were nearly equal in the surficial aquifer and Upper Floridan aquifer, which is an indication that the Upper Floridan aquifer is unconfined. Based on deuterium and oxygen stable isotope data collected in December 2011 and December 2012, there was no evidence of recharge to the Upper Floridan aquifer from the wetlands east of the major lakes; aquifer isotopic ratios did not indicate an enriched source, which is typical of lake and wetland sources. West of the major lakes, there was evidence of enriched isotopic ratios in water samples from the Upper Floridan aquifer. Differences in hydraulic head at paired wells in the surficial aquifer and Upper Floridan aquifer indicated that the surficial aquifer has the potential to recharge the Upper Floridan aquifer in the western part of the pools and west of the major lakes.

Florida↗
USGS2016

Cumulative drought and land-use impacts on perennial vegetation across a North American dryland region

Question The decline and loss of perennial vegetation in dryland ecosystems due to global change pressures can alter ecosystem properties and initiate land degradation processes. We tracked changes of perennial vegetation using remote sensing to address the question of how prolonged drought and land-use intensification have affected perennial vegetation cover across a desert region in the early 21st century? Location Mojave Desert, southeastern California, southern Nevada, southwestern Utah and northwestern Arizona, USA. Methods We coupled the Moderate-Resolution Imaging Spectroradiometer Enhanced Vegetation Index (MODIS-EVI) with ground-based measurements of perennial vegetation cover taken in about 2000 and about 2010. Using the difference between these years, we determined perennial vegetation changes in the early 21st century and related these shifts to climate, soil and landscape properties, and patterns of land use. Results We found a good fit between MODIS-EVI and perennial vegetation cover (2000: R 2 = 0.83 and 2010: R 2 = 0.74). The southwestern, far southeastern and central Mojave Desert had large declines in perennial vegetation cover in the early 21st century, while the northeastern and southeastern portions of the desert had increases. These changes were explained by 10-yr precipitation anomalies, particularly in the cool season and during extreme dry or wet years. Areas heavily impacted by visitor use or wildfire lost perennial vegetation cover, and vegetation in protected areas increased to a greater degree than in unprotected areas. Conclusions We find that we can extrapolate previously documented declines of perennial plant cover to an entire desert, and demonstrate that prolonged water shortages coupled with land-use intensification create identifiable patterns of vegetation change in dryland regions.

Applied Vegetation Science↗
USGS2016

Effect of land cover change on snow free surface albedo across the continental United States

Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30 m-×-30 m) land cover change data and moderate resolution (~ 500 m-×-500 m) albedo data. The land cover change data spanned 10 years (2001 − 2011) and the albedo data included observations every eight days for 13 years (2001 − 2013). Empirical testing was based on autoregressive time series analysis of snow free albedo for verified locations of land cover change. Approximately one-third of the autoregressive analyses for woody to herbaceous or forest to shrub change classes were not significant, indicating that albedo did not change significantly as a result of land cover change at these locations. In addition, ~ 80% of mean differences in albedo arising from land cover change were less than ± 0.02, a nominal benchmark for precision of albedo measurements that is related to significant changes in radiative forcing. Under snow free conditions, we found that land cover change does not guarantee a significant albedo response, and that the differences in mean albedo response for the majority of land cover change locations were small.

Global and Planetary Change↗
USGS2007

Modeled impact of anthropogenic land cover change on climate

Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

Journal of Climate↗
USGS2009

A 125 year history of topographic mapping and GIS in the U.S. Geological Survey 1884-2009, part 2: 1980-2009

The United States Geological Survey (USGS) entered the mainstream of developments in computer-assisted technology for mapping during the 1970s. The introduction by USGS of digital line graphs (DLGs), digital elevation models (DEMs), and land use data analysis (LUDA) nationwide land-cover data provided a base for the rapid expansion of the use of GIS in the 1980s. Whereas USGS had developed the topologically structured DLG data and the Geographic Information Retrieval and Analysis System (GIRAS) for land-cover data, the Map Overlay Statistical System (MOSS), a nontopologically structured GIS software package developed by Autometric, Inc., under contract to the U.S. Fish and Wildlife Service, dominated the use of GIS by federal agencies in the 1970s. Thus, USGS data was used in MOSS, but the topological structure, which later became a requirement for GIS vector datasets, was not used in early GIS applications. The introduction of Esri's ARC/INFO in 1982 changed that, and by the end of the 1980s, topological structure for vector data was essential, and ARC/INFO was the dominant GIS software package used by federal agencies.

ArcNews↗
USGS2019

Performances of WorldView-3, Sentinel-2, and Landsat-8 data in mapping impervious surface

Many efforts have been made to map developed impervious surface from remotely sensed information in the last two decades. The U.S. Geological Survey (USGS) developed the National Land Cover Database (NLCD) to provide consistent land cover and change products for the Nation since 2001. Percent impervious surface area (ISA), one of the products in NLCD as a continuous field and estimated with Landsat imagery, represents the fraction of human-made impervious area in a 30 m resolution grid. ISA is used to map urban land cover types and extents for the United States. However, it is still a challenge to quantify highly heterogeneous features in many urban areas using remotely sensed data with spatial and spectral resolutions similar to Landsat and to determine the impacts of remotely sensed data characteristics on ISA mapping.

California, Texas↗
USGS2002

Multispectral image sharpening using a shift-invariant wavelet transform and adaptive processing of multiresolution edges

Enhanced false color images from mid-IR, near-IR (NIR), and visible bands of the Landsat thematic mapper (TM) are commonly used for visually interpreting land cover type. Described here is a technique for sharpening or fusion of NIR with higher resolution panchromatic (Pan) that uses a shift-invariant implementation of the discrete wavelet transform (SIDWT) and a reported pixel-based selection rule to combine coefficients. There can be contrast reversals (e.g., at soil-vegetation boundaries between NIR and visible band images) and consequently degraded sharpening and edge artifacts. To improve performance for these conditions, I used a local area-based correlation technique originally reported for comparing image-pyramid-derived edges for the adaptive processing of wavelet-derived edge data. Also, using the redundant data of the SIDWT improves edge data generation. There is additional improvement because sharpened subband imagery is used with the edge-correlation process. A reported technique for sharpening three-band spectral imagery used forward and inverse intensity, hue, and saturation transforms and wavelet-based sharpening of intensity. This technique had limitations with opposite contrast data, and in this study sharpening was applied to single-band multispectral-Pan image pairs. Sharpening used simulated 30-m NIR imagery produced by degrading the spatial resolution of a higher resolution reference. Performance, evaluated by comparison between sharpened and reference image, was improved when sharpened subband data were used with the edge correlation.

Conference Paper↗