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Results for “Journal of Remote Sensing”

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At least 361 records · Page 20Linked to original sources
USGS2025

Multiscale framework for assessing land cover change on barrier islands from extreme storms and restoration

Often found along the estuarine-marine interface, barrier islands and mainland coastal zones are shaped by tides, currents, extreme storms, and relative sea-level rise. These systems provide ecosystem services such as storm surge and wave attenuation, erosion protection to inland areas, habitat for fish and wildlife, recreation, and tourism. Given the importance of these ecosystems coupled with their dynamic nature, information on how these coastal systems are changing can help to inform natural resource management. Remote sensing advancements have led to an abundance of data for monitoring change in coastal settings. This study developed a multiscale framework that can provide trajectory information from screening-level analyses by using existing or custom moderate spatial resolution land cover maps. Using the north-central Gulf Coast as a case study, the trajectory of land cover area for barrier islands and mainland coastal zones was assessed using several geospatial data sets, including: (1) long-term moderate-resolution remote sensing products with an annual (or more frequent) temporal frequency; (2) a restoration database ( e.g. , beach/dune restoration, sediment placement, and dune enhancement); and (3) a tropical storm database. Due to the coarser spatial resolution of data sets used for screening-level analyses, detailed or application-specific analyses are often needed to reduce uncertainty in smaller changes that may not be captured. These may include land cover change analyses ( i.e. this study), periodic land cover maps with higher spatial resolution and more detailed land cover classes, or elevation-related analyses ( e.g. , dune change or inundation change). Using this framework, abrupt changes in land cover on Dauphin Island, Alabama, resulting from extreme storms were detected using moderate spatial resolution screening-level data, while restoration impact analyses may require higher resolution data. Further, land cover change analyses that incorporate change allocation provide robust information for understanding land cover change in dynamic coastal settings.

Alabama, Florida↗
USGS2020

Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements

Surface soil temperature is the soil temperature from the surface to 10 cm in depth. Surface soil temperature plays a significant role in agricultural drought monitoring, ecosystem energy transfer modeling, and global carbon cycle evaluation. Studies have been proposed to estimate surface soil temperature, but surface soil temperature monitoring within forested areas still poses a significant challenge. In this study, we proposed a surface soil temperature retrieval method using combined satellite observations and in-situ measurements for the Great Dismal Swamp (GDS). The GDS is a U.S. protected area managed and protected by the U.S. Fish and Wildlife Service. It is located along the boundary of Virginia and North Carolina, with maple gum, Atlantic white cedar, and pine pocosin as the main forest cover types. Ground-based surface soil temperature measurements were collected for these forest types from May 2015 to April 2017. Both the Land Remote Sensing Satellite (Landsat) Thermal Infrared Sensor (TIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) carry two thermal infrared (TIR) channels. The TIR channels with similar corresponding wavelengths were first fused using an improved fusing model to generate high resolution TIR measurements. Then the enterprise algorithm was applied to calculate land surface temperature (LST) from the fused TIR bands. An improved soil temperature retrieval method was applied to generate surface soil temperature based on LST and vegetation index (VI) within the study area for the three forest types. In-situ measurements were used to build the surface soil temperature retrieval method, and results were then validated. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were integrated separately as VIs in the model to monitor surface soil temperature. The R 2 for retrieved surface soil temperature through satellite observations was 0.76, and the RMSE was 1.96 ℃ ">℃ ℃ when NDVI was integrated in the model; the R 2 was 0.78, and the RMSE was 1.85 ℃ ">℃ ℃ when EVI was used.

North Carolina, Virginia↗
USGS2022

High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape

Groundwater upwellings provide warmer, stable overwinter temperatures for developing salmon embryos, which may be particularly important in cold, braided, gravel-bed sub-Arctic rivers. We used a three-year time series of aerial counts and remote sensing to estimate the distribution of low and high aggregations of spawning fall chum salmon ( Oncorhynchus keta ), classify approximately 0.5 km long river segments by geomorphic channel type, and map thermal variability along a 25.4 km stretch of the Teedriinjik River, Alaska. We used a dynamic multistate occupancy model to estimate detectability, occupancy, and the dynamics of spawning aggregations among river segments. Detectability was higher for large (>150) relative to smaller aggregations. Unoccupied segments were likely to remain so from year to year; low abundance spawning segments were dynamic and rarely remained in that state for multiple years, while ∼20%–35% of high abundance segments remained stable, indicating the presence of high-quality spawning habitat. Spawning habitat use was associated with warmer water temperatures likely caused by groundwater upwellings. We identified spawning habitat characteristics and trends in usage by fall chum salmon, which will inform land management decisions and assist in evaluating impacts of shifting climate conditions and resource management on Arctic salmon populations.

Alaska↗
USGS2013

Survival and home-range size of Northern Spotted Owls in southwestern Oregon

In the Klamath province of southwestern Oregon, Northern Spotted Owls (Strix occidentalis caurina) occur in complex, productive forests that historically supported frequent fires of variable severity. However, little is known about the relationships between Spotted Owl survival and home-range size and the characteristics of fire-prone, mixed-conifer forests of the Klamath province. Thus, the objectives of this study were to estimate monthly survival rates and home-range size in relation to habitat characteristics for Northern Spotted Owls in southwestern Oregon. Home-range size and survival of 15 Northern Spotted Owls was monitored using radiotelemetry in the Ashland Ranger District of the Rogue River–Siskiyou National Forest from September 2006 to October 2008. Habitat classes within Spotted Owl home ranges were characterized using a remote-sensed vegetation map of the study area. Estimates of monthly survival ranged from 0.89 to 1.0 and were positively correlated with the number of late-seral habitat patches and the amount of edge, and negatively correlated with the mean nearest neighbor distance between late-seral habitats. Annual home-range size varied from to 189 to 894 ha ( x = 576; SE = 75), with little difference between breeding and nonbreeding home ranges. Breeding-season home-range size increased with the amount of hard edge, and the amount of old and mature forest combined. Core area, annual and nonbreeding season home-range sizes all increased with increased amounts of hard edge, suggesting that increased fragmentation is associated with larger core and home-range sizes. Although no effect of the amount of late-seral stage forest on either survival or home-range size was detected, these results are the first to concurrently demonstrate increased forest fragmentation with decreased survival and increased home-range size of Northern Spotted Owls.

Oregon↗
USGS2018

Rainbow trout movement behavior and habitat occupancy are influenced by sex and Pacific salmon presence in an Alaska river system

We used spatially continuous field-measured and remotely-sensed aquatic habitat characteristics paired with weekly ground-based telemetry tracking and snorkel surveys to describe movements and habitat occupancy of adult rainbow trout (N = 82) in a runoff-fed, salmon-influenced southcentral Alaska river system. We found that during the ice-free feeding season (June through September) rainbow trout occurrence was associated more with fine-scale (channel unit) characteristics relative to coarse-scale (stream reach) variables. The presence of Pacific salmon (which provide an important seasonal food subsidy), and habitat size were particularly useful predictors. Weekly movement distance differed between pre- and post- spawning salmon arrival, but did not vary by sex. Habitat quality, season, and the arrival of spawning salmon influenced the likelihood of rainbow trout movement, and fish moved farther to seek out higher quality habitats. Because rainbow trout respond to habitat factors at multiple scales and seek out salmon-derived subsidies, it will be important to take a multiscale approach in protecting trout and salmon populations and managing the associated fisheries.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2004

The rise and fall of water hyacinth in Lake Victoria and the Kagera River basin, 1989-2001

Water hyacinth (Eichhornia crassipes (Mart.) Solms) is an invasive aquatic macrophyte associated with major negative economic and ecological impacts to the Lake Victoria region since the plant's establishment in Uganda in the 1980s. Reliable estimates of water hyacinth distribution and extent are required to gauge the severity of the problem through time, relate water hyacinth abundance to environmental factors, identify areas requiring management action, and assess the efficacy of management actions. To provide such estimates and demonstrate the utility of remote sensing for this application, we processed and analyzed remotely sensed imagery to determine the distribution and extent of water hyacinth. Maps were produced and coverage was quantified using a hybrid unsupervised image classification approach with manual editing for each of the riparian countries of Kenya, Tanzania, and Uganda, as well as for numerous gulfs and bays. A similar procedure was carried out for selected lakes in the Rwanda-Tanzania borderlands lakes region in the Kagera River basin. Results confirm the severity of the water hyacinth infestation, especially in the northern parts of the lake. A maximum lake-wide extent of at least 17,374 ha was attained in 1998. Following this, a combination of factors, including conditions associated with the 1997 to 1998 El Nin??o and biocontrol with water hyacinth weevils, appear to have contributed to a major decline in water hyacinth in the most affected parts of the lake. Some lakes in the Kagera basin, such as Lake Mihindi, Rwanda, were severely infested in the late 1990s, but the level of infestation in most of these decreased markedly by the early 2000s.

Journal of Aquatic Plant Management↗
USGS2025

Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements

Evapotranspiration (ET) describes the sum of water transfer from the ground surface through soil evaporation and water loss from leaf stomata into the atmosphere − critical factors linking the global water and carbon cycles. Myriad ET models based on remote sensing data provide spatially continuous estimates of ET; however, leaf photosynthetic information is critical to ensure accurate ET estimates, which are difficult to measure from space. Remotely sensed sun-induced chlorophyll fluorescence (SIF) provides a proxy of stomatal conductance activity with high performance in predicting plant transpiration, which can account for a large proportion of terrestrial and riverine ET. This study aims to improve estimates of tree water use in semi-arid to arid environments. In this study, a fixed stomatal conductance model and three SIF-driven canopy conductance (g sc ) models were applied to model potential ET (PET). The models estimated PET using the Penman-Monteith equation with: (1) a constant leaf stomatal conductance; (2) a transpiration-driven g sc model; (3) a g sc model based on electron-transfer rate and vapor pressure deficit, and a (4) Ball-Berry stomatal conductance model. A machine learning model was then applied to scale PET to actual ET (AET) using remote sensing and climate data. Accordingly, four AET models were cross-validated with in-situ measured AET at 52 sites, including 21 eddy covariance flux tower sites, and 31 sap-flow measurement sites (semi-arid and plantation area), for various plant functional types in Australia. This study demonstrated that SIF effectively captured seasonal variations of g sc , finding that AET models with SIF-driven g sc models correlated well with in-situ measured AET (R 2 = 0.64). Modelled AET with dynamic variations of g sc generated lower prediction error (0.85 mm day −1 ), while the AET model with fixed stomatal conductance tended to overestimate AET in floodplains and underestimate it in evergreen broadleaf forests, indicating using fixed stomatal conductance results in unstable performance when modelling AET. This study demonstrated that SIF-driven AET models improved broadscale estimation of ET. Our findings provide vital broadscale hydrological data to assist catchment and regional water management, particularly over unmonitored areas at risk of future climate-driven reductions in rainfall.

Journal of Hydrology↗
USGS2012

Analysis of ERS 1 synthetic aperture radar data of frozen lakes in northern Montana and implications for climate studies

Lakes that freeze each winter are good indicators of regional climate change if key parameters, such as freeze-up and breakup date and maximum ice thickness, are measured over a decade-scale time frame. Synthetic aperture radar (SAR) satellite data have proven to be especially useful for measurement of climatologically significant parameters characteristic of frozen lakes. In this paper, five lakes in Glacier National Park, Montana, have been studied both in the field and using Earth Remote-Sensing Satellite (ERS) 1 SAR data during the 1992-1993 winter. The lakes are characterized by clear ice, sometimes with tubular or rounded bubbles, and often with a layer of snow ice on top of the clear ice. They are also often snow covered. Freeze-up is detected quite easily using ERS 1 SAR data as soon as a thin layer of ice forms. The effect of snow ice on the backscatter is thought to be significant but is, as yet, undetermined. On the five lakes studied, relative backscatter was found to increase with ice thickness until a maximum was reached in February. Breakup, an often ill-defined occurrence, is difficult to detect because surface water causes the SAR signal to be absorbed, thus masking the ice below. Comparison of the bubble structure of thaw lakes in northern Alaska with lakes in northern Montana has shown that the ice structure is quite different, and this difference may contribute to differential SAR signature evolution in the lakes of the two areas.

Journal of Geophysical Research↗
USGS2023

Barrier island reconfiguration leads to rapid erosion and relocation of a rural Alaska community

Coastal erosion is one of the foremost hazards that circumpolar communities face. Climate change and warming temperatures are anticipated to accelerate coastal change, increasing risk to coastal communities. Most erosion hazard studies for Alaska communities only consider linear erosion and do not anticipate coastal morphologic changes. This study showcases the possibility and consequence of accelerated erosion by examining a shift from stability to rapid erosion that forced the rural Alaska Native village of Meshik (now Port Heiden) to abandon the original town site and relocate inland. A combination of remote sensing, coastal surveys, and community-based monitoring are used to map coastal morphologic changes and identify erosion drivers. The community’s shoreline was stable until a protective barrier island eroded away. The exposure to open ocean waves, coupled with unconsolidated, low-density sediments, led to rapid erosion rates averaging of 5.8 ± 0.6 m/y from the 1970s to 2020s. The sudden and rapid erosion put great stress on Meshik and resulted in the loss of homes, erosion of a safe boat harbor, and pollution of the beach and bay. Erosion of the barrier island coincided with a period of greater storm activity and sea ice decline, but the exact cause for its erosion could not be determined. Many polar communities are built on or behind barriers and are on easily erodible soils such as sands and thawing permafrost. This study highlights the need to study, monitor, and predict morphologic change and regime shifts that can bring catastrophic impacts to coastal communities.

Alaska↗
USGS2013

Vegetation impoverishment despite greening: a case study from central Senegal

Recent remote sensing studies have documented a greening trend in the semi-arid Sahel and Sudan zones of West Africa since the early 1980s, which challenges the mainstream paradigm of irreversible land degradation in this region. What the greening trend means on the ground, however, has not yet been explored. This research focuses on a region in central Senegal to examine changes in woody vegetation abundance and composition in selected sites by means of a botanical inventory of woody vegetation species, repeat photography, and perceptions of local land users. Despite the greening, an impoverishment of the woody vegetation cover was observed in the studied sites, indicated by an overall reduction in woody species richness, a loss of large trees, an increasing dominance of shrubs, and a shift towards more arid-tolerant, Sahelian species since 1983. Thus, interpretation of the satellite-derived greening trend as an improvement or recovery is not always justified. The case of central Senegal represents only one of several possible pathways of greening throughout the region, all of which result in similar satellite-derived greening signals.

Journal of Arid Environments↗
USGS2010

The thermal signature of volcanic eruptions on Io and Earth,

We investigate a spectrum-based technique to identify the style of active volcanic eruptions on Jupiter's moon Io. Thermal remote sensing of Io has had to rely primarily on low-spatial-resolution data, similar to low-spatial-resolution satellite data applied to detecting and charting the temporal evolution of terrestrial hot spots. These terrestrial analyses use data from sensors designed to monitor the weather and sea surface temperature. On Io, such low-spatial-resolution data are used to classify eruption styles (modes of emplacement) by means of several criteria related to the temporal evolution of the infrared spectrum associated with the eruptive activity at each hot spot, which we term “thermal signature.” We find that the ratio of the emission at 2 and 5 µm, and how this ratio changes with time, is often diagnostic of eruption style, even in low-spatial-resolution data. Tests using thermal data for terrestrial “ground truth” cases show that our classification system is valid on Earth. The results of our analysis can be used to aid in the design of future space-based instruments that can be used for volcano monitoring on Io, as well as Earth.

Journal of Volcanology and Geothermal Research↗
USGS2017

Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software

Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.

International Journal of Applied Earth Observation↗
USGS1997

Multispectral thermal infrared mapping of sulfur dioxide plumes: A case study from the East Rift Zone of Kilauea Volcano, Hawaii

The synoptic perspective and rapid mode of data acquisition provided by remote sensing are well suited for the study of volcanic SO 2 plumes. In this paper we describe a plume-mapping procedure that is based on image data acquired with NASA's airborne thermal infrared multispectral scanner (TIMS) and apply the procedure to TIMS data collected over the East Rift Zone of Kilauea Volcano, Hawaii, on September 30, 1988. These image data covered the Pu‘u ‘O ‘o and Kupaianaha vents and a skylight in the lava tube that was draining the Kupaianaha lava pond. Our estimate of the SO 2 emission rate from Pu‘u ‘O ‘o (17–20 kg s −1 ) is roughly twice the average of estimates derived from correlation spectrometer (COSPEC) measurements collected 10 days prior to the TIMS overflight (10 kg s −1 ). The agreement between the TIMS and COSPEC results improves when we compare SO 2 burden estimates, which are relatively independent of wind speed. We demonstrate the feasibility of mapping Pu‘u ‘O ‘o - scale SO 2 plumes from space in anticipation of the 1998 launch of the advanced spaceborne thermal emission and reflectance radiometer (ASTER).

Journal of Geophysical Research B: Solid Earth↗
USGS1997

Estimation of directional surface wave spectra from a towed research catamaran

During the High-Resolution Remote Sensing Main Experiment (1993), wave height was estimated from a moving catamaran using pitch-rate and roll-rate sensors, a three-axis accelerometer, and a capacitive wave wire. The wave spectrum in the frequency band ranging roughly from 0.08 to 0.3 Hz was verified by independent buoy measurements. To estimate the directional frequency spectrum from a wave-wire array, the Data-Adaptive Spectral Estimator is extended to include the Doppler shifting effects of a moving platform. The method is applied to data obtained from a fixed platform during the Risø Air–Sea Experiment (1994) and to data obtained from a moving platform during the Coastal Ocean Processes Experiment (1995). Both results show that the propagation direction of the peak wind waves compares well with the measured wind direction. When swells and local wind waves are not aligned, the method can resolve the difference of propagation directions. Using the fixed platform data a numerical test is conducted that shows that the method is able to distinguish two wave systems propagating at the same frequency but in two different directions.

Journal of Atmospheric and Oceanic Technology↗
USGS2002

Basis and methods of NASA airborne topographic mapper lidar surveys for coastal studies

This paper provides an overview of the basic principles of airborne laser altimetry for surveys of coastal topography, and describes the methods used in the acquisition and processing of NASA Airborne Topographic Mapper (ATM) surveys that cover much of the conterminous US coastline. This form of remote sensing, also known as "topographic lidar", has undergone extremely rapid development during the last two decades, and has the potential to contribute within a wide range of coastal scientific investigations. Various airborne laser surveying (ALS) applications that are relevant to coastal studies are being pursued by researchers in a range of Earth science disciplines. Examples include the mapping of "bald earth" land surfaces below even moderately dense vegetation in studies of geologic framework and hydrology, and determination of the vegetation canopy structure, a key variable in mapping wildlife habitats. ALS has also proven to be an excellent method for the regional mapping of geomorphic change along barrier island beaches and other sandy coasts due to storms or long-term sedimentary processes. Coastal scientists are adopting ALS as a basic method in the study of an array of additional coastal topics. ALS can provide useful information in the analysis of shoreline change, the prediction and assessment of landslides along seacliffs and headlands, examination of subsidence causing coastal land loss, and in predicting storm surge and tsunami inundation.

Journal of Coastal Research↗
USGS2011

Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA

This paper quantifies current fire severity distributions for 19 different fire-regime types in Yosemite National Park, California, USA. Landsat Thematic Mapper remote sensing data are used to map burn severity for 99 fires (cumulatively over 97 000 ha) that burned in Yosemite over a 20-year period. These maps are used to quantify the frequency distributions of fire severity by fire-regime type. A classification is created for the resultant distributions and they are discussed within the context of four vegetation zones: the foothill shrub and woodland zone; the lower montane forest zone; the upper montane forest zone and the subalpine forest zone. The severity distributions can form a building block from which to discuss current fire regimes across the Sierra Nevada in California. This work establishes a framework for comparing the effects of current fires on our landscapes with our notions of how fires historically burned, and how current fire severity distributions differ from our desired future conditions. As this process is refined, a new set of information will be available to researchers and land managers to help understand how fire regimes have changed from the past and how we might attempt to manage them in the future.

California↗
USGS2025

Mobile radar provides insights into hydrologic responses in burn areas

Background Wildfires often occur in mountainous terrain, regions that pose substantial challenges to operational meteorological and hydrologic observing networks. Aims A mobile, post-fire hydrometeorological observatory comprising remote-sensing and in situ instrumentation was developed and deployed in a burnt area to provide unique insights into rainfall-induced post-fire hazards. Methods Mobile radar-based rainfall estimates were produced throughout the burn area at 75-m resolution and compared with rain gauge accumulations and basin response variables. Key results The mobile radar was capable of resolving details in intra-basin rain fields as well as detecting storms approaching the burn area with accuracy equivalent to rain gauges. Runoff responses were complex and dependent on spatiotemporal patterns and magnitude of rainfall intensity over the burn area. Conclusions The complement of the mobile radar with the near-field, non-contact instruments measuring the hydrologic response provided valuable information in regions that are difficult to access and are not routinely monitored by conventional observing networks. Implications Post-fire observatories equipped with mobile radars deployed on burn areas provide real-time data, early alerting capabilities and visualizations to potentially guide impact-based decision support for local authorities.

Colorado↗
USGS2016

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

International Journal of Digital Earth↗