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At least 415 records · Page 23Linked to original sources

USGS2018

Evaluating potential distribution of high-risk aquatic invasive species in the water garden and aquarium trade at a global scale based on current established populations

Aquatic non‐native invasive species are commonly traded in the worldwide water garden and aquarium markets, and some of these species pose major threats to the economy, the environment, and human health. Understanding the potential suitable habitat for these species at a global scale and at regional scales can inform risk assessments and predict future potential establishment. Typically, global habitat suitability models are fit for freshwater species with only climate variables, which provides little information about suitable terrestrial conditions for aquatic species. Remotely sensed data including topography and land cover data have the potential to improve our understanding of suitable habitat for aquatic species. In this study, we fit species distribution models using five different model algorithms for three non‐native aquatic invasive species with bioclimatic, topographic, and remotely sensed covariates to evaluate potential suitable habitat beyond simple climate matches. The species examined included a frog (Xenopus laevis), toad (Bombina orientalis), and snail (Pomacea spp.). Using a unique modeling approach for each species including background point selection based on known established populations resulted in robust ensemble habitat suitability models. All models for all species had test area under the receiver operating characteristic curve values greater than 0.70 and percent correctly classified values greater than 0.65. Importantly, we employed multivariate environmental similarity surface maps to evaluate potential extrapolation beyond observed conditions when applying models globally. These global models provide necessary forecasts of where these aquatic invasive species have the potential for establishment outside their native range, a key component in risk analyses.

Risk Analysis↗

USGS2012

Lineament analysis of mineral areas of interest in Afghanistan

During a preliminary mineral resource assessment of Afghanistan (Peters and others, 2007), 24 mineralized areas of interest (AOIs) were highlighted as the focus for future economic development throughout various parts of the country. In addition to located mineral resources of value, development of a viable mining industry in Afghanistan will require the location of suitable groundwater resources for drinking, processing of mineral ores for use or for export, and for agriculture and food production in areas surrounding and supporting future mining enterprises. This report and accompanying GIS datasets describe the results of both automated and manual mapping of lineaments throughout the 24 mineral occurrence AOIs described in detail by Peters and others (2007; 2011). For this study, we define lineaments as "mappable linear or curvilinear features of a surface whose parts align in a straight or slightly curving relationship that may be the expression of a fault or other linear zones of weakness" as derived from remote sensing sources such as optical imagery, radar imagery or digital elevation models (DEMs) (Sabins, 2007). Water wells in bedrock aquifers are generally more productive where boreholes intersect fractures or fracture zones. Lineament identification and analysis have long been used as a reconnaissance tool to identify such favorable conditions for groundwater resources in carbonate bedrock environments (Lattman and Parizek, 1964; Siddiqui and Parizek, 1971). More recently, lineament analysis has been used to identify areas of greater well yields in other bedrock settings, such as crystalline bedrock (Mabee and other, 1994; Moore and others, 2002). Lineaments provide an indication of bedrock areas that warrant further investigation for optimal water well placement. They may also indicate areas of preferential flow and storage of groundwater, and, thus, areas with a greater density of lineaments may indicate greater secondary porosity. Lineaments may indicate structurally trending mineralized areas (for example, Mars and Rowan, 2007), or locations of near-surface water resources, especially when surface vegetation growth coincides with lineaments. The purpose of this report and accompanying GIS data is to provide lineament maps that give one indication of areas that warrant further investigation for optimal bedrock water-well placement within 24 target areas for mineral resources (Peters and others, 2011). These data may also support the identification of faults related to modern seismic hazards (for example, Wheeler and others, 2005; Ruleman and others, 2007), as well as support studies attempting to understand the relationship between tectonic and structural controls on hydrothermal fluid flow, subsequent mineralization, and water-quality issues near mined and unmined mineral deposits (for example, Eppinger and others, 2007).

Open-File Report↗

USGS2008

Remote-controlled pan, tilt, zoom cameras at Kilauea and Mauna Loa Volcanoes, Hawai'i

Lists of important volcano-monitoring disciplines usually include seismology, geodesy, and gas geochemistry. Visual monitoring - the essence of volcanology - is usually not mentioned. Yet, observations of the outward appearance of a volcano provide data that is equally as important as that provided by the other disciplines. The eye was almost certainly the first volcano monitoring-tool used by early man. Early volcanology was mostly descriptive and was based on careful visual observations of volcanoes. There is still no substitute for the eye of an experienced volcanologist. Today, scientific instruments replace or augment our senses as monitoring tools because instruments are faster and more sensitive, work tirelessly day and night, keep better records, operate in hazardous environments, do not generate lawsuits when damaged or destroyed, and in most cases are cheaper. Furthermore, instruments are capable of detecting phenomena that are outside the reach of our senses. The human eye is now augmented by the camera. Sequences of timed images provide a record of visual phenomena that occur on and above the surface of volcanoes. Photographic monitoring is a fundamental monitoring tool; image sequences can often provide the basis for interpreting other data streams. Monitoring data are most useful when they are generated and are available for analysis in real-time or near real-time. This report describes the current (as of 2006) system for real-time photograph acquisition and transmission from remote sites on Kilauea and Mauna Loa volcanoes to the U.S. Geological Survey Hawaiian Volcano Observatory (HVO). It also describes how the photographs are archived and analyzed. In addition to providing system documentation for HVO, we hope that the report will prove useful as a practical guide to the construction of a high-bandwidth network for the telemetry of real-time data from remote locations.

Hawai'i↗

USGS2004

Global environmental databases from CEOS agencies

The Committee on Earth Observation Satellites (CEOS) is an international organization charged with coordinating international civil spaceborne missions designed to observe and study planet Earth. Comprising 44 space agencies and other national and international organizations, CEOS is recognized as the major international forum for the coordination of Earth observation satellite programs and for the interaction of these programs with users of satellite data worldwide. CEOS was created in 1984 in response to a recommendation from the Economic Summit of Industrialized Nations Working Group on Growth, Technology, and Employment’s Panel of Experts on Satellite Remote Sensing. This group recognized the multidisciplinary nature of satellite Earth observation and the value of coordination across all proposed missions. The CEOS members collect, maintain, apply, and make available data from space missions that encompass the atmospheric, terrestrial, and oceanographic fields. Collectively, these members possess petabytes of Earth observation data critical to understanding the Earth environment. Uses include monitoring oil slicks, evaluating human-induced changes to the atmosphere, determining mineral exploration areas, assessing the environmental effects of volcanic eruptions, measuring the growth of urban areas, determining where landscapes have changed because of urban growth trends, improving the efficiency of fishing as a world food stock, monitoring pest infestation, managing crop production, predicting climate and weather, and numerous other applications vital to industry, national infrastructures, and the world as a whole. The vast amount of satellite obtained, environmental data the CEOS members possess represents a fertile resource for researchers worldwide to exploit.

Conference Paper↗

USGS2018

Clarifying regional hydrologic controls of the Marañón River, Peru through rapid assessment to inform system-wide basin planning approaches

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.

Marañón River↗

USGS2026

Restoring dryland water cycles for precipitation feedback and climate stability; a review

Drylands across the globe are experiencing intensifying water scarcity, land degradation, and hydroclimatic extremes. This review integrates evidence from multidecadal field studies, hydrologic monitoring, geomorphic and ecological assessments, remote sensing, and land–atmosphere science to evaluate how restoration influences key components of the terrestrial water cycle. Low-tech natural infrastructure in dryland streams (NIDS)—including check dams, leaky weirs, one-rock dams, and gabions—has emerged as a promising but under-synthesized nature-based solution for restoring hydrologic function in these environments. We describe the mechanisms through which these interventions modify runoff detention, infiltration, sediment and alluvial storage, shallow-groundwater recharge, vegetation recovery, and surface-energy partitioning, and we summarize outcomes across diverse dryland settings. Findings consistently show increased water residence time, enhanced soil-moisture storage, expanded riparian vegetation, extended flow duration, and shifts toward greater latent-heat flux—producing localized cooling and strengthened ecohydrological feedbacks. Building on these localized effects, we articulate a hypothesis that links the spatial extent of restoration, the density of NIDS per unit drainage area, and the magnitude of the latent-to-sensible-heat contrast generated by wetter post-rainfall conditions. Specifically, we hypothesize that when NIDS are implemented at densities permitted by topography and across areas large enough to maintain elevated soil moisture after storm events, the resulting increases in latent heat flux, surface cooling, and boundary-layer moistening may enhance moisture convergence and boundary-layer development, potentially increasing the likelihood or stability of convective precipitation, analogous to how reductions in these processes have contributed to regional drought intensification. These land–atmosphere feedbacks remain untested at scale but represent an important research Frontier. By integrating hydrologic, geomorphic, ecological, and atmospheric perspectives, this review provides a comprehensive framework for considering how low-tech, landscape-scale interventions can strengthen watershed resilience and contribute to climate-relevant nature-based solutions.

Arizona↗

USGS1995

K1-95-HW: Cruise report 1995 - Preliminary results, phase III: Sediment chemistry and biological sampling survey

Mamala Bay, off the south shore of the island of Oahu, has been used as a repository of dredged material primarily from Pearl and Honolulu Harbors for over a century. The U.S. Geological Survey, U.S. Army Corps of Engineers, and the U.S. Environmental Protection Agency are conducting an integrated study on the distribution and character of dredged materials as well as the effects of dredged material on the marine environment. A three phase study is providing information to evaluate the effects on seafloor substrate and the benthic fauna. The studies include geophysical profiling and imaging, bottom photography, sampling, chemical and physical analyses of sediment, and evaluations of the benthic population, population density, and adverse impacts to the benthic fauna. Phase 1, conducted in 1993, inventoried the seafloor via remote sensing. Sidescan sonar and subbottom profilers characterized the seafloor in and around the disposal sites, and the resulting products reveal the character and extent of the dredged material. These data were used to plan Phase 2 in 1994, a sampling program that employed subbottom profilers, video and still photography, and seafloor sampling to ground truth the sonar mosaic and identify the seafloor substrates responsible for the various acoustic signatures on the sonar images and subbottom profiles. Box coring provided the samples necessary to distinguish dredged material from native sediment, and for the chemical analyses used to determine contaminant concentrations. Phase 3 studies conducted in June of 1995 consisted of box core sampling for chemical and biological analyses. Specific studies include: infaunal taxonomy and population density, bioassay/bioaccumulation, sediment chemistry, and post-disposal resuspension and transport. The 1995 survey, conducted June 14 through 17, resulted in the collection of 39 box cores from 20 different stations. Multiple box cores were composited at 7 different locations occupied in 1994, to provide the material required for the 7 bioassay and bioaccumulation analyses currently underway (Figure 1). Seventeen of the 20 stations occupied provided the biological samples for the benthic infaunal identification and population density study conducted by Dr. Julie Brock of the University of Hawaii, and the sediment chemistry analyses conducted (and completed) by Quanterra Environmental Laboratories (Figure 1). Seven of the 20 stations occupied in 1995 were occupied in 1994, and provide the data for direct comparison of sediment chemistry at the same sites from two consecutive years. The sum total of the data collected from all three phases of the monitoring program will provide the U.S. Army Corps of Engineers and the U.S. Environmental Protection Agency with the information required to make informed decisions as to the management of the South Oahu disposal site in Mamala Bay.

Hawai'i↗

USGS2017

The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA

A synthesis of field, biostratigraphic, detrital zircon geochronologic, and remote sensing data across north-central Nevada, United States, defines a thick, regionally extensive sheet of Middle–Upper Ordovician Valmy Formation quartzite that structurally overlies deformed early Paleozoic units of the Roberts Mountains allochthon. Late Paleozoic regional unconformities that record tectonic disruptions have been recognized in the foreland of central and eastern Nevada and locally within the Roberts Mountains allochthon; these identify multiple, regional tectonic events between the Devonian–Mississippian initiation of the Antler orogeny and the Permian–Triassic Sonoma orogeny. However, few studies have documented the regional kinematic history of the Robert Mountains allochthon sensu stricto. In the Independence Mountains of northern Nevada, emplacement of the Roberts Mountains allochthon is restricted to the Mississippian. In the Tuscarora Mountains, the range west and southwest of the Independence Mountains, several deformation events have been identified, and emplacement of the thrust sheet containing the Valmy Formation is restricted to the Late Pennsylvanian–Early Permian. These structural and temporal relations, reflected in the Antler foreland basin adjacent to the Roberts Mountains allochthon and overlap sequences, suggest that the Roberts Mountains allochthon is a composite stratigraphic terrane assembled along the Cordilleran margin during two or more late Paleozoic contractional events. Valmy Formation deposits likely represent the development of coalescing submarine fans below or within bypass channels in a deep slope or rise environment. Petrographic characteristics, biostratigraphy, and detrital zircon U-Pb age populations of the Valmy Formation link it to coeval slope and rise turbidites of the Vinini Formation and shelfal Eureka Quartzite; Valmy Formation detrital zircon age populations are dissimilar to the rift-to-drift facies of the Neoproterozoic–Cambrian Prospect Mountain Quartzite. Throughout north-central Nevada, the Valmy Formation is in fault contact with units of the Roberts Mountains allochthon, including the Devonian–Mississippian Slaven Chert, Silurian–Devonian Elder Sandstone, and Cambrian(?)–Ordovician Vinini Formation, which were deformed prior to, or during, emplacement of the thrust sheet containing Valmy Formation quartzite. Our mapping and data synthesis, guided by regional quartz maps based on remote sensing (Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER]) data, delineate similar structural relationships discontinuously for >200 km along strike of the Roberts Mountains allochthon. Exploration for concealed gold deposits within reach of drilling requires knowledge of the relative thicknesses of the Roberts Mountains allochthon and the Valmy Formation. Overall thicknesses of deformed Roberts Mountains allochthon units between the Valmy Formation and underlying carbonate rocks, which host large, world-class Carlin-type gold deposits, vary by hundreds of meters, but are generally less than 700 m in three of the areas studied here. Recognition of windows through and klippen of the Roberts Mountains allochthon is essential for identification of areas where deposits may be at or near the surface. Correspondingly, most ongoing exploration for Carlin-type gold deposits subjacent to the Roberts Mountains allochthon targets concealed deposits. The model proposed in this study is applicable to determining depth to rocks prospective for undiscovered deposits.

Nevada↗

USGS2018

Spatiotemporal analysis of Landsat-8 and Sentinel-2 data to support monitoring of dryland ecosystems

Drylands are the habitat and source of livelihood for about two fifths of the world’s population and are highly susceptible to climate and anthropogenic change. To understand the vulnerability of drylands to changing environmental conditions, land managers need to effectively monitor rates of past change and remote sensing offers a cost-effective means to assess and manage these vast landscapes. Here, we present a novel approach to accurately monitor land-surface phenology in drylands of the Western United States using a regression tree modeling framework that combined information collected by the Operational Land Imager (OLI) onboard Landsat 8 and the Multispectral Instrument (MSI) onboard Sentinel-2. This highly-automatable approach allowed us to precisely characterize seasonal variations in spectral vegetation indices with substantial agreement between observed and predicted values (R 2 = 0.98; Mean Absolute Error = 0.01). Derived phenology curves agreed with independent eMODIS phenological signatures of major land cover types (average r -value = 0.86), cheatgrass cover (average r -value = 0.96), and growing season proxies for vegetation productivity (R 2 = 0.88), although a systematic bias towards earlier maturity and senescence indicates enhanced monitoring capabilities associated with the use of harmonized Landsat-8 Sentinel-2 data. Overall, our results demonstrate that observations made by the MSI and OLI can be used in conjunction to accurately characterize land-surface phenology and exclusion of imagery from either sensor drastically reduces our ability to monitor dryland environments. Given the declines in MODIS performance and forthcoming decommission with no equivalent replacement planned, data fusion approaches that integrate observations from multispectral sensors will be needed to effectively monitor dryland ecosystems. While the synthetic image stacks are expected to be locally useful, the technical approach can serve a wide variety of applications such as invasive species and drought monitoring, habitat mapping, production of phenology metrics, and land-cover change modeling.

Remote Sensing↗

USGS2017

Optical and biochemical properties of a southwest Florida whiting event

“Whiting” in oceanography is a term used to describe a sharply defined patch of water that contains high levels of suspended, fine-grained calcium carbonate (CaCO 3 ). Whitings have been reported in many oceanic and lake environments, and recently have been reported in southwest Florida coastal waters. Here, field and laboratory measurements were used to study optical, biological, and chemical properties of whiting waters off southwest Florida. No significant difference was found in chlorophyll a concentrations between whiting and outside waters (non-whiting water), but average particle backscattering coefficients in whiting waters were double those in outside waters, and remote sensing reflectance in whiting waters was higher at all wavelengths (400–700 nm). While other potential causes cannot be completely ruled out, particle composition and biochemical differences between sampled whiting water, contiguous water, and outside water indicate a biologically precipitated mode of whiting formation. Taxonomic examination of marine phytoplankton samples collected during a whiting event revealed a community dominated by autotrophic picoplankton and a small (<10 μm), centric diatom species, identified as Thalassiosira sp. through the use of scanning electron microscopy. Amorphous to fully formed crystals of CaCO 3 were observed along the girdle bands of Thalassiosira sp. cells and autotrophic picoplankton cells. Although carbonate parameters differed from whiting and contiguous to outside water, more sampling is needed to determine if these results are statistically significant.

Florida↗

USGS2020

National Land Imaging Program

Changes taking place across the Earth’s land surface have the potential to affect people, economies, and the environment on a daily basis. Our Nation’s economic security and environmental vitality rely on continuous monitoring of the Earth’s continents, islands, and coastal regions to record, study, and understand land change at local, regional, and global scales. The U.S. Geological Survey’s National Land Imaging Program helps meet this need by ensuring the continuous availability of moderate-resolution satellite imagery and other remotely sensed and geospatial data.

Fact Sheet↗

USGS2009

NASA and USGS invest in invasive species modeling to evaluate habitat for Africanized Honey Bees

Invasive non-native species, such as plants, animals, and pathogens, have long been an interest to the U.S. Geological Survey (USGS) and NASA. Invasive species cause harm to our economy (around $120 B/year), the environment (e.g., replacing native biodiversity, forest pathogens negatively affecting carbon storage), and human health (e.g., plague, West Nile virus). Five years ago, the USGS and NASA formed a partnership to improve ecological forecasting capabilities for the early detection and containment of the highest priority invasive species. Scientists from NASA Goddard Space Flight Center (GSFC) and the Fort Collins Science Center developed a longterm strategy to integrate remote sensing capabilities, high-performance computing capabilities and new spatial modeling techniques to advance the science of ecological invasions [Schnase et al., 2002].

The Earth Observer↗

USGS2011

Lidar vegetation mapping in national parks: Gulf Coast Network

Airborne lidar (Light Detection and Ranging) is an active remote sensing technique used to collect accurate elevation data over large areas. Lidar provides an extremely high level of regional topographic detail, which makes this technology an essential component of U.S. Geological Survey (USGS) science strategy. The USGS Coastal and Marine Geology Program (CMGP) has collaborated with the National Aeronautics and Space Administration (NASA) and the National Park Service (NPS) to acquire dense topographic lidar data in a variety of coastal environments.

Louisiana↗

USGS2021

UAV-based estimate of snow cover dynamics: Optimizing semi-arid forest structure for snow persistence

Seasonal snow cover in the dry forests of the American West provides essential water resources to both human and natural systems. The structure of trees and their arrangement across the landscape are important drivers of snow cover distribution across these forests, varying widely in both space and time. We used unmanned aerial vehicle (UAV) multispectral imagery and Structure-from-Motion (SfM) models to quantify rapidly melting snow cover dynamics and examine the effects of forest structure shading on persistent snow cover in a recently thinned ponderosa pine forest. Using repeat UAV multispectral imagery (n = 11 dates) across the 76 ha forest, we first developed a rapid and effective method for identifying persistent snow cover with 90.2% overall accuracy. The SfM model correctly identified 98% (n = 1280) of the trees, when compared with terrestrial laser scanner validation data. Using the SfM-derived forest structure variables, we then found that canopy shading associated with the vertical and horizontal metrics was a significant driver of persistent snow cover patches ( R 2 = 0.70). The results indicate that UAV image-derived forest structure metrics can be used to accurately predict snow patch size and persistence. Our results provide insight into the importance of forest structure, specifically canopy shading, in the amount and distribution of persistent seasonal snow cover in a typical dry forest environment. An operational understanding of forest structure effects on snow cover will help drive forest management that can target snow cover dynamics in addition to forest health.

Arizona↗

USGS2014

Evaluation of Landsat-7 SLC-off image products for forest change detection

Since July 2003, Landsat-7 ETM+ has been operating without the scan line corrector (SLC), which compensates for the forward motion of the satellite in the imagery acquired. Data collected in SLC-off mode have gaps in a systematic wedge-shaped pattern outside of the central 22 km swath of the imagery; however, the spatial and spectral quality of the remaining portions of the imagery are not diminished. To explore the continued use of Landsat-7 ETM+ SLC-off imagery to characterize change in forested environments, we compare the change detection results generated from a reference image pair (a 1999 Landsat-7 ETM+ image and a 2003 Landsat-5 TM image) with change detection results generated from the same 1999 Landsat-7 ETM+ image coupled with three different 2003 Landsat-7 SLC-off products: unremediated SLC-off (i.e., with gaps); histogram-based gap-filled; and segment-based gap-filled. The results are compared on both a pixel and polygon basis; on a pixel basis, the unremediated SLC-off product missed 35% of the change identified by the reference data, and the histogram- and segment-based gap-filled products missed 23% and 21% of the change, respectively. When using forest inventory polygons as a context for change (to reduce commission error), the amount of change missed was 31%, 14%, and 12% for the each of the unremediated, histogram-based gap-filled, and segment-based gap-filled products, respectively. Our results indicate that over the time period considered, and given the types and spatial distribution of change events within our study area, the gap-filled products can provide a useful data source for change detection in forested environments. The selection of which product to use is, however, very dependent on the nature of the application and the spatial configuration of change events. ?? 2008 Government of Canada.

Canadian Journal of Remote Sensing↗

USGS2024

Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys

Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine learning processing to detect and classify wildlife from imagery in near real-time, we evaluated deep learning methods that address hardware limitations and the need for processing efficiencies to support the envisioned in-flight workflow. We developed an annotated dataset for a suite of marine birds from high-resolution digital aerial imagery collected over open water environments to train the models. The proposed 3-stage workflow for automated, in-flight data processing includes: 1) image filtering based on the probability of any bird occurrence, 2) bird instance detection, and 3) bird instance classification. For image filtering, we compared the performance of a binary classifier with Mask Region-based Convolutional Neural Network (Mask R-CNN) as a means of sub-setting large volumes of imagery based on the probability of at least one bird occurrence in an image. On both the validation and test datasets, the binary classifier achieved higher performance than Mask R-CNN for predicting bird occurrence at the image-level. We recommend the binary classifier over Mask R-CNN for workflow first-stage filtering. For bird instance detection, we leveraged Mask R-CNN as our detection framework and proposed an iterative refinement method to bootstrap our predicted detections from loose ground-truth annotations. We also discuss future work to address the taxonomic classification phase of the envisioned workflow.

Massachusetts, Wisconsin↗

USGS2013

Phenology-based, remote sensing of post-burn disturbance windows in rangelands

Wildland fire activity has increased in many parts of the world in recent decades. Ecological disturbance by fire can accelerate ecosystem degradation processes such as erosion due to combustion of vegetation that otherwise provides protective cover to the soil surface. This study employed a novel ecological indicator based on remote sensing of vegetation greenness dynamics (phenology) to estimate variability in the window of time between fire and the reemergence of green vegetation. The indicator was applied as a proxy for short-term, post-fire disturbance windows in rangelands; where a disturbance window is defined as the time required for an ecological or geomorphic process that is altered to return to pre-disturbance levels. We examined variability in the indicator determined for time series of MODIS and AVHRR NDVI remote sensing data for a database of ∼100 historical wildland fires, with associated post-fire reseeding treatments, that burned 1990–2003 in cold desert shrub steppe of the Great Basin and Columbia Plateau of the western USA. The indicator-based estimates of disturbance window length were examined relative to the day of the year that fires burned and seeding treatments to consider effects of contemporary variability in fire regime and management activities in this environment. A key finding was that contemporary changes of increased length of the annual fire season could have indirect effects on ecosystem degradation, as early season fires appeared to result in longer time that soils remained relatively bare of the protective cover of vegetation after fires. Also important was that reemergence of vegetation did not occur more quickly after fire in sites treated with post-fire seeding, which is a strategy commonly employed to accelerate post-fire vegetation recovery and stabilize soil. Future work with the indicator could examine other ecological factors that are dynamic in space and time following disturbance – such as nutrient cycling, carbon storage, microbial community composition, or soil hydrology – as a function of disturbance windows, possibly using simulation modeling and historical wildfire information.

California;Idaho;Nevada;Oregon;Utah;Washington↗

USGS2008

Remote sensing and GIS approach for water-well site selection, southwest Iran

The Pabdeh-Lali Anticline of northern Khuzestan province is located in southwestern Iran and occupies 790 km2. This structure is situated in the Zagros folded belt. As a result of well-developed karst systems in the anticlinal axis, the water supply potential is high and is drained by many peripheral springs. However, there is a scarcity of water for agriculture and population centers on the anticlinal flanks, which imposes a severe problem in terms of area development. This study combines remotely sensed (RS) data and a geographical information system (GIS) into a RSGIS technique to delineate new areas for groundwater development and specific sites for drilling productive water wells. Toward these goals, RS data were used to develop GIS layers for lithology, structural geology, topographic slope, elevation, and drainage density. Field measurements were made to create spring-location and groundwater-quality GIS layers. Subsequently, expert choice and relational methods were used in a GIS environment to conjunctively analyze all layers to delineate preferable regions and 43 individual sites in which to drill water wells. Results indicate that the most preferred areas are, in preferential order, within recent alluvial deposits, the Bakhtiyari Conglomerates, and the Aghajari Sandstone. The Asmari Limestone and other units have much lower potential for groundwater supplies. Potential usefulness of the RSGIS method was indicated when six out of nine producing wells recently drilled by the Khozestan Water and Power Authority (which had no knowledge of this study) were located in areas preferentially selected by this technique.

Environmental & Engineering Geoscience↗