Filters: partyWithName: Melanie K Vanderhoof (X)
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The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions. Outputs of the BAECV algorithm consist of pixel-level burn probabilities for each Landsat scene, and annual burn probability, burn classification, and burn date composites. These products were generated for the conterminous United States for 1984 through 2015. These data are also available for download at https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1.1_2017/...
Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface-water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface-water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface-water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine...
Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions, and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011-2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, 3, and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery,...
The Upper Missouri River headwaters (UMH) basin (36 400 km2 ) depends on its river corridors to support irrigated agriculture and world-class trout fisheries. We evaluated trends (1984–2016) in riparian wetness, an indicator of the riparian condition, in peak irrigation months (June, July and August) for 158 km2 of riparian area across the basin using the Landsat normalized difference wetness index (NDWI). We found that 8 of the 19 riparian reaches across the basin showed a significant drying trend over this period, including all three basin outlet reaches along the Jefferson, Madison and Gallatin rivers. The influence of upstream climate was quantified using per reach random forest regressions. Much of the interannual...
Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version...
Geographically Isolated Wetlands (GIWs) occur along gradients of hydrologic and ecological connectivity and isolation, even within wetland types (e.g., forested, emergent marshes) and functional classes (e.g., ephemeral systems, permanent systems, etc.). Within a given watershed, the relative positions of wetlands and open-waters along these gradients influence the type and magnitude of their chemical, physical, and biological effects on downgradient waters. In addition, the ways in which GIWs connect to the broader hydrological landscape, and the effects of such connectivity on downgradient waters, depends largely upon climate, geology, and relief, the heterogeneity of which expands with increasing scale. Developing...
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Geographically isolated wetlands, depressional wetlands, perimeter,
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Fire history metrics enable rapidly increasing amounts of burned area data to be collapsed into a handful of data layers that can be used efficiently by diverse stakeholders. In this effort the U.S. Geological Survey's Landsat Burned Area Product Landsat Burned Area product was used to identify burned area across CONUS over a 39-year period (1984-2022). The Landsat BA product was consolidated into a suite of annual BA products, which in-turn were used to calculate a series of contemporary fire history metrics (30 m resolution). Fire history metrics included: (1) fire frequency (FRQ), (2) time since last burn (TSLB) and (3) year of last burn (YLB), (4) longest fire-free interval (LFFI), and (5) average fire interval...
Categories: Data;
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OGC WFS Layer,
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Tags: Landsat,
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United States,
burned area,
fire frequency,
Wetland conservation in the Upper Mississippi River Basin (UMRB) is a priority for Federal, State, NGO, and Tribal land managers to support migratory bird habitat in Minnesota and Iowa. These wetlands, known as depressional wetlands, also provide ecosystem services associated with flood water storage and enhancing down-stream water quality by storing and processing nutrients. Understanding how conservation efforts and management strategies can impact both wildlife habitat and water quality/quantity issues in the UMRB is critical for helping this region adapt to future precipitation patterns. High intensity rainfall events can cause depressional wetlands to overflow and connect with Mississippi River tributaries....
Categories: Project;
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Tags: 2022,
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Data Visualization & Tools,
Data Visualization & Tools,
Midwest,
Forested areas in the Western U.S. that are impacted by disturbances such as fire and drought have increased in recent decades. This trend is likely to continue, with the increase in frequency and extent of wildfire activity being especially concerning. Resource managers need reliable scientific information to better understand wildfire occurrence, which can vary substantially across landscapes and throughout time. However, few scientific models capture this variability, and projections of future potential changes in fire occurrence can include some uncertainty. This uncertainty can limit our ability to anticipate potential wildfire impacts on society and ecological systems. Another method to help managers prepare...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2020,
CASC,
Completed,
Drought,
Drought,
Post-fire shifts in vegetation composition will have broad ecological impacts. However, information characterizing post-fire recovery patterns and their drivers are lacking over large spatial extents. In this analysis we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of post-fire, dual season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field-measured patterns of re-vegetation, and (3) identify seasonally-specific drivers of post-fire rates of NDVI recovery. Rates of post-fire...
Aquatic features critical to watershed hydrology range widely in size from narrow, shallow streams to large, deep lakes. In this study we evaluated wetland, lake, and river systems across the Prairie Pothole Region to explore where pan-sharpened high-resolution (PSHR) imagery, relative to Landsat imagery, could provide additional data on surface water distribution and movement, missed by Landsat. We used the monthly Global Surface Water (GSW) Landsat product as well as surface water derived from Landsat imagery using a matched filtering algorithm (MF Landsat) to help consider how including partially inundated Landsat pixels as water influenced our findings. The PSHR outputs (and MF Landsat) were able to identify...
Abstract Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster-based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional...
Categories: Publication;
Types: Citation
Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We...
Starting in 2022, processing switched to the Collection 2 Landsat ARD data. Landsat Burned Area Products for 2022 based on Landsat Collection 2 data are available at: Hawbaker, T.J., Vanderhoof, M.K., Schimdt, G.L., and Picotte, J.P., 2023. The Landsat Collection 2 Burned Area Products for the conterminous United States, U.S. Geological Survey Data Release, https://doi.org/10.5066/P9F26LY6 The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference...
High-frequency observations of surface water at fine spatial scales are critical to effectively manage aquatic habitat, flood risk and water quality. We developed inundation algorithms for Sentinel-1 and Sentinel-2 across 12 sites within the conterminous United States (CONUS) covering >536,000 km2 and representing diverse hydrologic and vegetation landscapes. These algorithms were trained on data from 13,412 points spread throughout the 12 sites. Each scene in the 5-year (2017-2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables not only from Sentinel-1 and Sentinel-2, but also variables derived from topographic and weather datasets. The Sentinel-1 model...
Wildfires and prescribed fires are frequent but under-mapped across wetlands of the southeastern United States . High annual precipitation supports rapid post-fire recovery of wetland vegetation, while associated cloud cover limits clear-sky observations. In addition, the low burn severity of prescribed fires and spectral confusion between fluctuating water levels and burned areas have resulted in wetland burned area being chronically under-estimated across the region. In this analysis, we first quantify the increase in clear-sky observations by using Sentinel-2 in addition to Landsat 8. We then present an approach using the Sentinel-2 archive (2016-2019) to train a wetland burned area algorithm at 20 m resolution....
Postfire shifts in vegetation composition will have broad ecological impacts. However, information characterizing postfire recovery patterns and their drivers are lacking over large spatial extents. In this analysis, we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of postfire, dual‐season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field‐measured patterns of re‐vegetation, and (3) identify seasonally specific drivers of postfire rates of NDVI recovery. Rates of postfire NDVI...
Categories: Publication;
Types: Citation
High-frequency observations of surface water at fine spatial scales are critical to effectively manage aquatic habitat, flood risk and water quality. We developed inundation algorithms for Sentinel-1 and Sentinel-2 across 12 sites within the conterminous United States (CONUS) covering >536,000 km2 and representing diverse hydrologic and vegetation landscapes. These algorithms were trained on data from 13,412 points spread throughout the 12 sites. Each scene in the 5-year (2017-2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables not only from Sentinel-1 and Sentinel-2, but also variables derived from topographic and weather datasets. The Sentinel-1 model...
Landsat Normalised Difference Vegetation Index (NDVI) is commonly used to monitor post-fire green-up; however, most studies do not distinguish new growth of conifer from deciduous or herbaceous species, despite potential consequences for local climate, carbon and wildlife. We found that dual season (growing and snow cover) NDVI improved our ability to distinguish conifer tree presence and density. We then examined the post-fire pattern (1984–2017) in Landsat NDVI for fires that occurred a minimum of 20 years ago (1986–1997). Points were classified into four categories depending on whether NDVI, 20 years post-fire, had returned to pre-fire values in only the growing season, only under snow cover, in both seasons...
Degradation of streams and associated riparian habitat across the Missouri River Headwaters Basin has motivated several stream restoration projects across the watershed. Many of these projects install a series of beaver dam analogues (BDAs) to aggrade incised streams, elevate local water tables, and create natural surface water storage by reconnecting streams with their floodplains. Satellite imagery can provide a spatially continuous mechanism to monitor the effects of these in-stream structures on stream surface area. However, remote sensing-based approaches to map narrow (e.g., <5 m wide) linear features such as streams have been under-developed relative to efforts to map other types of aquatic systems, such...
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