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At least 793 records · Page 44Linked to original sources

USGS2014

One-Water Hydrologic Flow Model (MODFLOW-OWHM)

The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, MF-OWHM has the unique set of capabilities to simulate and analyze historical, present, and future conjunctive-use conditions. MF-OWHM is especially useful for the analysis of agricultural water use where few data are available for pumpage, land use, or agricultural information. The features presented in this IHM include additional linkages with SFR, SWR, Drain-Return (DRT), Multi-Node Wells (MNW1 and MNW2), and Unsaturated-Zone Flow (UZF). Thus, MF-OWHM helps to reduce the loss of water during simulation of the hydrosphere and helps to account for “all of the water everywhere and all of the time.” In addition to groundwater, surface-water, and landscape budgets, MF-OWHM provides more options for observations of land subsidence, hydraulic properties, and evapotranspiration (ET) than previous models. Detailed landscape budgets combined with output of estimates of actual evapotranspiration facilitates linkage to remotely sensed observations as input or as additional observations for parameter estimation or water-use analysis. The features of FMP have been extended to allow for temporally variable water-accounting units (farms) that can be linked to land-use models and the specification of both surface-water and groundwater allotments to facilitate sustainability analysis and connectivity to the Groundwater Management Process (GWM). An example model described in this report demonstrates the application of MF-OWHM with the addition of land subsidence and a vertically deforming mesh, delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in demand caused by deficiency in supply, and changes in multi-aquifer pumpage caused by constraints imposed through the Farm Process and the MNW2 Package, and changes in surface water such as runoff, streamflow, and canal flows through SFR and SWR linkages.

Techniques and Methods↗

USGS1982

An automatic optimum kernel-size selection technique for edge enhancement

Edge enhancement is a technique that can be considered, to a first order, a correction for the modulation transfer function of an imaging system. Digital imaging systems sample a continuous function at discrete intervals so that high-frequency information cannot be recorded at the same precision as lower frequency data. Because of this, fine detail or edge information in digital images is lost. Spatial filtering techniques can be used to enhance the fine detail information that does exist in the digital image, but the filter size is dependent on the type of area being processed. A technique has been developed by the authors that uses the horizontal first difference to automatically select the optimum kernel-size that should be used to enhance the edges that are contained in the image.

Remote Sensing of Environment↗

USGS2015

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov . The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Book chapter↗

USGS2018

USA National Phenology Network observational data documentation

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org ) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal ( http://dx.doi.org/10.5066/F78S4N1V ) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.

Open-File Report↗

USGS2005

Remote sensing characterization of the Animas River watershed, southwestern Colorado, by AVIRIS imaging spectroscopy

Visible-wavelength and near-infrared image cubes of the Animas River watershed in southwestern Colorado have been acquired by the Jet Propulsion Laboratory's Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) instrument and processed using the U.S. Geological Survey Tetracorder v3.6a2 implementation. The Tetracorder expert system utilizes a spectral reference library containing more than 400 laboratory and field spectra of end-member minerals, mineral mixtures, vegetation, manmade materials, atmospheric gases, and additional substances to generate maps of mineralogy, vegetation, snow, and other material distributions. Major iron-bearing, clay, mica, carbonate, sulfate, and other minerals were identified, among which are several minerals associated with acid rock drainage, including pyrite, jarosite, alunite, and goethite. Distributions of minerals such as calcite and chlorite indicate a relationship between acid-neutralizing assemblages and stream geochemistry within the watershed. Images denoting material distributions throughout the watershed have been orthorectified against digital terrain models to produce georeferenced image files suitable for inclusion in Geographic Information System databases. Results of this study are of use to land managers, stakeholders, and researchers interested in understanding a number of characteristics of the Animas River watershed.

Scientific Investigations Report↗

USGS2021

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R 2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha −1 . Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.

Remote Sensing in Ecology and Conservation↗

USGS2021

The Mars 2020 Perseverance rover mast camera zoom (Mastcam-Z) multispectral, stereoscopic imaging investigation

Mastcam-Z is a multispectral, stereoscopic imaging investigation on the Mars 2020 mission’s Perseverance rover. Mastcam-Z consists of a pair of focusable, 4:1 zoomable cameras that provide broadband red/green/blue and narrowband 400-1000 nm color imaging with fields of view from 25.6° × 19.2° (26 mm focal length at 283 μrad/pixel) to 6.2° × 4.6° (110 mm focal length at 67.4 μrad/pixel). The cameras can resolve (≥ 5 pixels) ∼0.7 mm features at 2 m and ∼3.3 cm features at 100 m distance. Mastcam-Z shares significant heritage with the Mastcam instruments on the Mars Science Laboratory Curiosity rover. Each Mastcam-Z camera consists of zoom, focus, and filter wheel mechanisms and a 1648 × 1214 pixel charge-coupled device detector and electronics. The two Mastcam-Z cameras are mounted with a 24.4 cm stereo baseline and 2.3° total toe-in on a camera plate ∼2 m above the surface on the rover’s Remote Sensing Mast, which provides azimuth and elevation actuation. A separate digital electronics assembly inside the rover provides power, data processing and storage, and the interface to the rover computer. Primary and secondary Mastcam-Z calibration targets mounted on the rover top deck enable tactical reflectance calibration. Mastcam-Z multispectral, stereo, and panoramic images will be used to provide detailed morphology, topography, and geologic context along the rover’s traverse; constrain mineralogic, photometric, and physical properties of surface materials; monitor and characterize atmospheric and astronomical phenomena; and document the rover’s sample extraction and caching locations. Mastcam-Z images will also provide key engineering information to support sample selection and other rover driving and tool/instrument operations decisions.

Space Science Reviews↗

USGS2021

From site to system: Approaches for producing system-wide estimates of fish habitat in large rivers

Worldwide, many productive rivers are dam-regulated and rely on flow management strategies that must balance support of ecological processes with human water use. One component of evaluating this balance is to understand ecological consequences of alternative flow management strategies, which has often been accomplished by coupling population dynamics models with models that relate streamflow to habitat availability and quality. Numerous methods assign habitat availability to locations within a river basin: These include fine-scale field-measured values that are extrapolated to other locations within the basin having similar physical characteristics or equation-driven values created by functions of model-predicted values of physical characteristics. The array of options for creating habitat models is evolving rapidly as high-resolution remote-sensing data becomes more accessible and computational capacity improves. Our objective was to identify trade-offs among approaches that assign habitat relationships to large rivers and to create a decision support tool to supplement choices of extent and granularity. Using a selection of case studies that represent a breadth of scales and diverse trade-offs, we demonstrate the need for a transparent process of data evaluation and assessment to determine the appropriate fit for model scope or context that best supports management needs and recognize sources of uncertainty. The structured approach proposed here aims at improving future model development and refine population dynamics models that inform the management of rivers.

River Research and Applications↗

USGS2009

Palaeoseismology of the Vilariça segment of the Manteigas-Bragança fault in northeastern Portugal

The Manteigas-Bragança fault is a major, 250-km-long, NNE-striking, sinistral strike-slip structure in northern Portugal. This fault has no historical seismicity for large earthquakes, although it may have generated moderate (M5+) earthquakes in 1751 and 1858. Evidence of continued left horizontal displacement is shown by the presence of Cenozoic pull-apart basins as well as late Quaternary stream deflections. To investigate its recent slip history, a number of trenches were excavated at three sites along the Vilariça segment, north and south of the Douro River. At one site at Vale Meão winery, the occurrence of at least two and probably three events in the past 14.5 ka was determined, suggesting an average return period of about 5–7 ka. All three events appear to have occurred as a cluster in the interval between 14.5 and 11 ka, or shortly thereafter, suggesting a return period of less than 2 ka between events within the cluster. In the same area, a small offset rill suggests 2–2.5 m of slip in the most recent event and about 6.1 m after incision below a c . 16 ka alluvial fill event along the Douro River. At another site along the Vilariça River alluvial plain, NE of the Vale Meão site, several trenches were excavated in late Pleistocene and Holocene alluvium, and exposed the fault displacing channel deposits dated to between 18 and 23 ka. In a succession of closely spaced parallel cuts and trenches, the channel riser was traced into and across the fault to resolve c . 6.5 m of displacement after 18 ka and c . 9 m of slip after c . 23 ka. These observations yield a slip rate of 0.3–0.5 mm/a, which is consistent with earlier estimates. Combining the information on timing at Vale Meão winery and displacement at Vilariça argues for earthquakes in the M7+ range, with coseismic displacements of 2–3 m. This demonstrates that there are potential seismic sources in Portugal that are not associated with the 1755 Lisbon earthquake or the Tagus Valley, and, although rare, large events on the Vilariça fault could be quite destructive for the region. This work provides an analogue for the study of active faulting in intracontinental settings and supports the view that earthquakes within intracontinental settings tend to cluster in time. In addition, this study highlights the usefulness and application of multiple field, remote sensing and geochronological techniques for seismic hazard mitigation.

Manteigas - Braganca fault↗

USGS2019

Demonstrating the value of Earth observations—methods, practical applications, and solutions—group on Earth observations side event proceedings

Executive Summary The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO). This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes. During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes. The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without. A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point: Effect of increasing temperatures on human health; Flooding—Mitigating, managing, and avoiding impacts to safety and property damage; Harmful algal blooms—Effects on human health, recreation, and tourism; Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the economy; and Effects of natural hazards on transportation systems—Effects on mobility, safety, and the economy. During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Open-File Report↗

USGS2011

Field Reconnaissance Geologic Mapping of the Columbia Hills, Mars: Results from MER Spirit and MRO HiRISE Observations

Chemical, mineralogic, and lithologic ground truth was acquired for the first time on Mars in terrain units mapped using orbital Mars Reconnaissance Orbiter's High Resolution Imaging Science Experiment (MRO HiRISE) image data. Examination of several dozen outcrops shows that Mars is geologically complex at meter length scales, the record of its geologic history is well exposed, stratigraphic units may be identified and correlated across significant areas on the ground, and outcrops and geologic relationships between materials may be analyzed with techniques commonly employed in terrestrial field geology. Despite their burial during the course of Martian geologic time by widespread epiclastic materials, mobile fines, and fall deposits, the selective exhumation of deep and well-preserved geologic units has exposed undisturbed outcrops, stratigraphic sections, and structural information much as they are preserved and exposed on Earth. A rich geologic record awaits skilled future field investigators on Mars. The correlation of ground observations and orbital images enables construction of a corresponding geologic reconnaissance map. Most of the outcrops visited are interpreted to be pyroclastic, impactite, and epiclastic deposits overlying an unexposed substrate, probably related to a modified Gusev crater central peak. Fluids have altered chemistry and mineralogy of these protoliths in degrees that vary substantially within the same map unit. Examination of the rocks exposed above and below the major unconformity between the plains lavas and the Columbia Hills directly confirms the general conclusion from remote sensing in previous studies over past years that the early history of Mars was a time of more intense deposition and modification of the surface. Although the availability of fluids and the chemical and mineral activity declined from this early period, significant later volcanism and fluid convection enabled additional, if localized, chemical activity.

Journal of Geophysical Research E: Planets↗

USGS2005

Elevations and Distances

Photographs and other images of the Earth taken from the air and from space show a great deal about the planet's landforms, vegetation, and resources. Aerial and satellite images, known as remotely sensed images, permit accurate mapping of land cover and make landscape features understandable on regional, continental, and even global scales. Transient phenomena, such as seasonal vegetation vigor and contaminant discharges, can be studied by comparing images acquired at different times. The U.S. Geological Survey (USGS), which began using aerial photographs for mapping in the 1930's, archives photographs from its mapping projects and from those of some other Federal agencies. In addition, many images from such space programs as Landsat, begun in 1972, are held by the USGS. Most satellite scenes can be obtained only in digital form for use in computer-based image processing and geographic information systems, but in some cases are also available as photographic products.

General Information Product↗

USGS1997

Aerial Photographs and Satellite Images

General Information Product↗

USGS2025

Object detection-assisted workflow facilitates cryptic snake monitoring

Camera traps are an important tool used to study rare and cryptic animals, including snakes. Time-lapse photography can be particularly useful for studying snakes that often fail to trigger a camera's infrared motion sensor due to their ectothermic nature. However, the large datasets produced by time-lapse photography require labor-intensive classification, limiting their use in large-scale studies. While many artificial intelligence-based object detection models are effective at identifying mammals in images, their ability to detect snakes is unproven. Here, we used camera data to evaluate the efficacy of an object detection model to rapidly and accurately detect snakes. We classified images manually to the species level and compared this with a hybrid review workflow where the model removed blank images followed by a manual review. Using a ≥0.05 model confidence threshold, our hybrid review workflow correctly identified 94.5% of blank images, completed image classification 6× faster, and detected large (>66 cm) snakes as well as manual review. Conversely, the hybrid review method often failed to detect all instances of a snake in a string of images and detected fewer small (<66 cm) snakes than manual review. However, most relevant ecological information requires only a single detection in a sequence of images, and study design changes could likely improve the detection of smaller snakes. Our findings suggest that an object detection-assisted hybrid workflow can greatly reduce time spent manually classifying data-heavy time-lapse snake studies and facilitate ecological monitoring for large snakes.

Florida↗

USGS2009

Assessing the landscape context and conversion risk of protected areas using satellite data products

Since the establishment of the first national park (Yellowstone National Park in 1872) and the first wildlife refuge (Pelican Island in 1903), dramatic changes have occurred in both ecological and cultural landscapes across the U.S. The ability of these protected areas to maintain current levels of biodiversity depend, at least in part, on the integrity of the surrounding landscape. Our objective was to quantify and compare the extent and pattern of natural land cover, risk of conversion, and relationships with demographic and economic variables in counties near National Park Service units and U.S. Fish and Wildlife Service refuges with those counties distant from either type of protected area in the coterminous United States. Our results indicate that landscapes in counties within 10 km of both parks and refuges and those within 10 km of just parks were more natural, more intact, and more protected than those in counties within 10 km of just refuges and counties greater than 10 km from either protected area system. However, they also had greater human population density and change in population, indicating potential conversion risk since the percent of landscape protected averaged < 5% in both groups and human population dynamics are primary drivers of change in many landscapes. Conversion outweighed protection by at least two times (Conservation Risk Index > 2) in 76% of counties near both parks and refuges, 81% of counties near just parks, 91% of counties near just refuges, and 93% of distant counties. Thirteen percent of counties in the coterminous U.S. had moderate to high amounts of natural land cover (> 60%), low protection (< 20%), and the greatest change in population (> 20%). Although these areas are not the most critically endangered, they represent the greatest conservation opportunity, need, and urgency. Our approach is based on national level metrics that are simple, general, informative, and can be understood by broad audiences and by policy makers and managers to assess the health of lands surrounding parks and refuges. Regular monitoring of these metrics with satellite data products in counties surrounding protected areas provides a consistent, national level assessment of management opportunities and potentially adverse changes on adjacent lands.

Remote Sensing of Environment↗

USGS2005

Cubic map algebra functions for spatio-temporal analysis

We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

Cartography and Geographic Information Science↗

USGS1981

Studying the Earth from space

Space age technology contains a key to increased knowledge about the Earth's resources; this key is remote sensing detecting the nature or condition of something without actually touching it. An early and still most useful form of remote sensing is photography which records the scene, as man sees it, on film sensitive to that part of the electromagnetic spectrum called visible energy. Electromagnetic energy travels in waves of various lengths; most are invisible to the human eye. Wavelengths progressively longer than those that the eye can see are infrared and microwave. Wavelengths progressively shorter than the eye can see are ultraviolet, X-rays, and gamma rays.

General Information Product↗

USGS2013

The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation

The development of new tools that provide timely, detailed-spatial-resolution drought information is essential for improving drought preparedness and response. This paper presents a new method for monitoring drought-induced vegetation stress called the Vegetation Drought Response Index (VegDRI). VegDRI integrates traditional climate-based drought indicators and satellite-derived vegetation index metrics with other biophysical information to produce a 1 km map of drought conditions that can be produced in near-real time. The initial VegDRI map results for a 2002 case study conducted across seven states in the north-central United States illustrates the utility of VegDRI for improved large-area drought monitoring.

GIScience and Remote Sensing↗