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At least 1,063 records · Page 59Linked to original sources
USGS1977

Conversion factors: SI metric and U.S. customary units

The policy of the U.S. Geological Survey is to foster use of the International System of Units (SI) which was defined by the 11th General Conference of Weights and Measures in 1960. This modernized metric system constitutes an international "language" by means of which communications throughout the world's scientific and economic communities may be improved. This publication is designed to familiarize the reader with the SI units of measurement that correspond to the common units frequently used in programs of the Geological Survey. In the near future, SI units will be used exclusively in most publications of the Survey; the conversion factors provided herein will help readers to obtain a "feel" for each unit and to "think metric."

General Information Product↗
USGS1997

Mineral-resource data bases

Data bases are essential for modern scientific research. The new and exciting work being done in the Mineral Resource Program in the U.S. Geological Survey (USGS) usually begins with the question, "Where are the known deposits?" A mineral-resource data base containing this type of information and more can be useful not just to USGS scientists, but to anyone who needs such data. Users of the data bases from outside the USGS include mining and exploration companies, environmental groups, academia, other Federal Agencies, and the general public. At present, the USGS has two large mineral-resource data bases, MRDS (Mineral Resource Data System) and MAS (Minerals Availability System). MRDS was built and is mamtained by the USGS, and MAS was built and maintained by the Bureau of Mines. In 1996, after the Bureau was abolished, MAS was transferred to the USGS. The two data bases were compiled for different purposes and contain very different mformation. For instance, MAS contains information on costs, details of mining methods, and feasibility studies. MRDS has mineralogical and geologic data that are not contained in MAS. Because they are both mineral-resource data bases, however, they contain some information in common, such as location, name(s) of sites, and commodities present. Both data bases are international in scope, and both are quite large. MRDS contains over 110,000 records, while MAS has over 220,000. One reason that MAS has more records is that it contains information on smelters, mill sites, and fossil fuel sites, as well as mineral- resource sites. The USGS is working to combine the information in both data bases. This is a large undertaking that will require some years to complete. In the interim, information from both data bases will still be available

Fact Sheet↗
USGS2006

Velocity, bathymetry, and transverse mixing characteristics of the Ohio River upstream from Cincinnati, Ohio, October 2004–March 2006

Velocity, bathymetry, and transverse (cross-channel) mixing characteristics were studied in a 34-mile study reach of the Ohio River extending from the lower pool of the Captain Anthony Meldahl Lock and Dam, near Willow Grove, Ky, to just downstream from the confluence of the Licking and Ohio Rivers, near Newport, Ky. Information gathered in this study ultimately will be used to parameterize hydrodynamic and water-quality models that are being developed for the study reach. Velocity data were measured at an average cross-section spacing of about 2,200 feet by means of boat-mounted acoustic Doppler current profilers (ADCPs). ADCP data were postprocessed to create text files describing the three-dimensional velocity characteristics in each transect. Bathymetry data were measured at an average transect spacing of about 800 feet by means of a boat-mounted single-beam echosounder. Depth information obtained from the echosounder were postprocessed with water-surface slope and elevation information collected during the surveys to compute stream-bed elevations. The bathymetry data were written to text files formatted as a series of space-delimited x-, y-, and z-coordinates. Two separate dye-tracer studies were done on different days in overlapping stream segments in an 18.3-mile section of the study reach to assess transverse mixing characteristics in the Ohio River. Rhodamine WT dye was injected into the river at a constant rate, and concentrations were measured in downstream cross sections, generally spaced 1 to 2 miles apart. The dye was injected near the Kentucky shoreline during the first study and near the Ohio shoreline during the second study. Dye concentrations were measured along transects in the river by means of calibrated fluorometers equipped with flow-through chambers, automatic temperature compensation, and internal data loggers. The use of flow-through chambers permitted water to be pumped continuously out of the river from selected depths and through the fluorometer for measurement as the boat traversed the river. Time-tagged concentration readings were joined with horizontal coordinate data simultaneously captured from a differentially corrected Global Positioning System (GPS) device to create a plain-text, comma-separated variable file containing spatially tagged dye-concentration data. Plots showing the transverse variation in relative dye concentration indicate that, within the stream segments sampled, complete transverse mixing of the dye did not occur. In addition, the highest concentrations of dye tended to be nearest the side of the river from which the dye was injected. Velocity, bathymetry, and dye-concentration data collected during this study are available for Internet download by means of hyperlinks in this report. Data contained in this report were collected between October 2004 and March 2006.

Ohio↗
USGS1964

Lake Superior seismic experiment

During the Lake Superior seismic experiment, an International Upper Mantle cooperative program in July 1965, the U. S. Geological Survey provided a total of 8 mobile seismic-recording systems. For the first phase of the experiment the systems were arranged in two groups of 4; one group at the western end of the lake near Duluth and the other was on the Keweenaw Peninsula. During the last three days of the experiment all 8 systems were located at various positions in parts of Wisconsin and Minnesota. Selected sections of 500 seismograms are presented.

Lake Superior↗
USGS1999

Preliminary volcano-hazard assessment for Iliamna Volcano, Alaska

Iliamna Volcano is a 3,053-meter-high, ice- and snow-covered stratovolcano in the southwestern Cook Inlet region about 225 kilometers southwest of Anchorage and about 100 kilometers northwest of Homer. Historical eruptions of Iliamna Volcano have not been positively documented; however, the volcano regularly emits steam and gas, and small, shallow earthquakes are often detected beneath the summit area. The most recent eruptions of the volcano occurred about 300 years ago, and possibly as recently as 90-140 years ago. Prehistoric eruptions have generated plumes of volcanic ash, pyroclastic flows, and lahars that extended to the volcano flanks and beyond. Rock avalanches from the summit area have occurred numerous times in the past. These avalanches flowed several kilometers down the flanks and at least two large avalanches transformed to cohesive lahars. The number and distribution of known volcanic ash deposits from Iliamna Volcano indicate that volcanic ash clouds from prehistoric eruptions were significantly less voluminous and probably less common relative to ash clouds generated by eruptions of other Cook Inlet volcanoes. Plumes of volcanic ash from Iliamna Volcano would be a major hazard to jet aircraft using Anchorage International Airport and other local airports, and depending on wind direction, could drift at least as far as the Kenai Peninsula and beyond. Ashfall from future eruptions could disrupt oil and gas operations and shipping activities in Cook Inlet. Because Iliamna Volcano has not erupted for several hundred years, a future eruption could involve significant amounts of ice and snow that could lead to the formation of large lahars and downstream flooding. The greatest hazards in order of importance are described below and shown on plate 1.

Alaska↗
USGS2021

Afghanistan artisanal and small-scale mining sector

For millennia, extractive activity in Afghanistan (officially the Islamic Republic of Afghanistan, or IRA) has been entirely artisanal or small-scale in scope. Various international governments, organizations, and companies have supported the growth of the sector, and the Government of the Islamic Republic of Afghanistan (GoIRA) views its mineral wealth as vital to the country’s stability and prosperity moving forward (Ministry of Mines and Petroleum 2019a). The development of the sector has been prioritized in multiple national plans, strategies, and roadmaps. Of particular importance is the formalization of the artisanal and small-scale mining (ASM) sector to improve working conditions and enable the government to earn royalties from mineral production.

Report↗
USGS2010

A procedure for radiometric recalibration of Landsat 5 TM reflective-band data

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for the L5 TM imagery used the detectors' response to the internal calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time, causing radiometric calibration errors up to 20%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing level-1 products. The best recalibration results are obtained if the work-order report that was included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2010

Automated masking of cloud and cloud shadow for forest change analysis using Landsat images

Accurate masking of cloud and cloud shadow is a prerequisite for reliable mapping of land surface attributes. Cloud contamination is particularly a problem for land cover change analysis, because unflagged clouds may be mapped as false changes, and the level of such false changes can be comparable to or many times more than that of actual changes, even for images with small percentages of cloud cover. Here we develop an algorithm for automatically flagging clouds and their shadows in Landsat images. This algorithm uses clear view forest pixels as a reference to define cloud boundaries for separating cloud from clear view surfaces in a spectral-temperature space. Shadow locations are predicted according to cloud height estimates and sun illumination geometry, and actual shadow pixels are identified by searching the darkest pixels surrounding the predicted shadow locations. This algorithm produced omission errors of around 1% for the cloud class, although the errors were higher for an image that had very low cloud cover and one acquired in a semiarid environment. While higher values were reported for other error measures, most of the errors were found around the edges of detected clouds and shadows, and many were due to difficulties in flagging thin clouds and the shadow cast by them, both by the developed algorithm and by the image analyst in deriving the reference data. We concluded that this algorithm is especially suitable for forest change analysis, because the commission and omission errors of the derived masks are not likely to significantly bias change analysis results.

International Journal of Remote Sensing↗
USGS2016

Ichthyophonus parasite phylogeny based on ITS rDNA structure prediction and alignment identifies six clades, with a single dominant marine type

Despite their widespread, global impact in both wild and cultured fishes, little is known of the diversity, transmission patterns, and phylogeography of parasites generally identified as Ichthyophonus. This study constructed a phylogeny based on the structural alignment of internal transcribed spacer (ITS) rDNA sequences to compare Ichthyophonus isolates from fish hosts in the Atlantic and Pacific oceans, and several rivers and aquaculture sites in North America, Europe, and Japan. Structure of the Ichthyophonus ITS1–5.8S–ITS2 transcript exhibited several homologies with other eukaryotes, and 6 distinct clades were identified within Ichthyophonus. A single clade contained a majority (71 of 98) of parasite isolations. This ubiquitous Ichthyophonus type occurred in 13 marine and anadromous hosts and was associated with epizootics in Atlantic herring, Chinook salmon, and American shad. A second clade contained all isolates from aquaculture, despite great geographic separation of the freshwater hosts. Each of the 4 remaining clades contained isolates from single host species. This study is the first to evaluate the genetic relationships among Ichthyophonus species across a significant portion of their host and geographic range. Additionally, parasite infection prevalence is reported in 16 fish species.

Diseases of Aquatic Organisms↗
USGS2013

Adaptive harvest management for the Svalbard population of pink-footed geese: cooperator report

This document describes progress to date on the development of a harvest‐management strategy for maintaining pink‐footed goose abundance near their target level by providing for sustainable harvests in Norway and Denmark. Many goose populations in western Europe have increased dramatically in recent decades. The Svalbard population of pink‐footed geese (Anser brachyrhynchus) is a good example, increasing from about 10 thousand individuals in the early 1960’s to roughly 80 thousand today. Although these geese are a highly valued resource, the growing numbers of geese are causing agricultural conflicts in wintering and staging areas. The African‐Eurasian Waterbird Agreement (AEWA; http://www.unep‐aewa.org/) calls for means to manage populations which cause conflicts with certain human economic activities. We compiled relevant demographic and weather data and specified an annual‐cycle model for pink-footed geese that reconciles the different dates of monitoring activities and the timing of harvest-management decisions. We then developed dynamic models for survival and reproductive processes and parameterized them using available data. By combining varying hypotheses about survival and reproduction, we developed a suite of nine models that represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent, and the extent to which spring temperatures are important. These nine models varied significantly in their predictions of the harvest required to stabilize current population size, ranging from a low of about 500 to a high of about 17 thousand. For comparison, the harvest in Norway and Denmark was about 11 thousand in 2011 and the population increased from 70 to 80 thousand. We relied on the passive form of adaptive management in formulating a harvest strategy. In passive adaptive management, alternative population models and their associated weights of evidence are explicitly considered in the development of an optimal harvest strategy. Unlike active adaptive management, however, there is no explicit consideration of how harvest management actions could reduce uncertainty as to the most appropriate model of population dynamics. In optimizing a harvest strategy, we assumed equal probabilities for all nine models and assumed relatively course control over harvest. We used a management objective that seeks to maximize sustainable harvest, but avoids harvest decisions that are expected to result in a subsequent population size different than the population goal of 60 thousand. Optimal harvest strategies were calculated using stochastic dynamic programming, and Monte Carlo simulations were used to investigate expected strategy performance. The optimal passive adaptive‐management strategy is expected to maintain mean population size near 60 thousand, regardless of the most appropriate model. However, mean harvest rates and harvests varied substantially depending on the most appropriate model of population dynamics. With an average number of days above freezing in May in Svalbard, optimal harvest rates (i.e., the proportion of the population to be harvested in autumn) increase rapidly once there are more than about 50 thousand birds in the population. Generally, optimal harvests were on the order of 10 – 20 thousand for population sizes > 60 thousand, and 0 – 5 thousand for population sizes < 60 thousand. For the observations of young of 15.4 thousand and adults of 54.6 thousand in autumn 2010, and 10 days above freezing in May 2011 (a relatively warm spring compared to the average of about 7), the optimal harvest rate in autumn of 2011 would have been 0.16, or a harvest of about 14 thousand. Based on the optimal strategy, hunting‐season closures would be required as the number of adults in the autumn population falls below about 52 thousand, regardless of the number of young in the population. As the number of adults and young decrease, the number of warm days in May required to keep the hunting season open increases. We also investigated the ability of the optimal strategy to stabilize the population at around 60 thousand birds, assuming varying values of the maximum harvest rate that could be implemented. Harvest strategies that contained a maximum harvest rate of 0.16 (equivalent to a harvest of about 17 thousand) were effective at stabilizing the population at 60 thousand within 4‐5 years, regardless of climate scenario. Harvest strategies with a maximum harvest rate of 0.12 (harvest ≈ 13 thousand) were also able to stabilize the population near 60 thousand, although it took more time. Harvest strategies with a maximum harvest rate of 0.08 (harvest ≈ 8 thousand) were unsuccessful at stabilizing the population at 60 thousand. Continued monitoring of the pink‐footed goose population on an annual basis is critical to an informed harvest management strategy. At a minimum, the ground census in November should be continued to determine population size and proportion of young. Continued estimates of harvest from Norway and Denmark are also necessary to help judge the credibility of the alternative population models. However, an adaptive management process that relies on periodic updating of model weights will depend on acquiring either estimates of the realized harvest rate of adults or the age composition of the harvest. We also recommend that a census conducted during spring migration be operationalized, and that estimates of survival based on mark‐recapture data be updated. Finally, the International Working Group has expressed a desire to adopt a three‐year cycle of decision making related to the regulation of pink‐footed goose harvests. The idea is that once a target harvest level is adopted, it would remain in place for three years, after which time population status would be assessed and a potentially new management action chosen. We have developed a preliminary framework to implement a three‐year cycle using stochastic dynamic programming, and we hope to have it fully operational later this year . We note, however, that application of this 3‐year framework will still require annual resource monitoring and assessments to facilitate learning, and to allow managers the opportunity to respond to any unforeseen change in resource conditions.

Report↗
USGS2021

The Independent Volcanic Eruption Source Parameter Archive (IVESPA, version 1.0): A new observational database to support explosive eruptive column model validation and development

Eruptive column models are powerful tools for investigating the transport of volcanic gas and ash, reconstructing past explosive eruptions, and simulating future hazards. However, the evaluation of these models is challenging as it requires independent estimates of the main model inputs (e.g. mass eruption rate) and outputs (e.g. column height). There exists no database of independently estimated eruption source parameters (ESPs) that is extensive, standardized, maintained, and consensus-based. This paper introduces the Independent Volcanic Eruption Source Parameter Archive (IVESPA, ivespa.co.uk), a community effort endorsed by the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) Commission on Tephra Hazard Modelling. We compiled data for 134 explosive eruptive events, spanning the 1902-2016 period, with independent estimates of: i) total erupted mass of fall deposits; ii) duration; iii) eruption column height; and iv) atmospheric conditions. Crucially, we distinguish plume top versus umbrella spreading height, and the height of ash versus sulphur dioxide injection. All parameter values provided have been vetted independently by at least two experts. Uncertainties are quantified systematically, including flags to describe the degree of interpretation of the literature required for each estimate. IVESPA also includes a range of additional parameters such as total grain size distribution, eruption style, morphology of the plume (weak versus strong), and mass contribution from pyroclastic density currents, where available. We discuss the future developments and potential applications of IVESPA and make recommendations for reporting ESPs to maximize their usability across different applications. IVESPA covers an unprecedented range of ESPs and can therefore be used to evaluate and develop eruptive column models across a wide range of conditions using a standardized dataset.

Journal of Volcanology and Geothermal Research↗
USGS1999

Chemical weathering in a tropical watershed, Luquillo Mountains, Puerto Rico III: Quartz dissolution rates

The paucity of weathering rates for quartz in the natural environment stems both from the slow rate at which quartz dissolves and the difficulty in differentiating solute Si contributed by quartz from that derived from other silicate minerals. This study, a first effort in quantifying natural rates of quartz dissolution, takes advantage of extremely rapid tropical weathering, simple regolith mineralogy, and detailed information on hydrologic and chemical transport. Quartz abundances and grain sizes are relatively constant with depth in a thick saprolite. Limited quartz dissolution is indicated by solution rounding of primary angularity and by the formation of etch pits. A low correlation of surface area (0.14 and 0.42 m2 g-1) with grain size indicates that internal microfractures and pitting are the principal contributors to total surface area. Pore water silica concentration increases linearly with depth. On a molar basis, between one and three quarters of pore water silica is derived from quartz with the remainder contributed from biotite weathering. Average solute Si remains thermodynamically undersaturated with respect to recently revised estimates of quartz solubility (<180 ??M) but exceeds estimated critical saturation concentrations controlling the initiation of etch pit formation (>17-81 ??M). Etch pitting is more abundant on grains in the upper saprolite and is associated with pore waters lower in dissolved silica. Rate constants describing quartz dissolution increase with decreasing depth (from 10-14.5-10-15.1 mol m-2 s-1), which correlate with both greater thermodynamic undersaturation and increasing etch pit densities. Unlike for many aluminosilicates, the calculated natural weathering rates of quartz fall slightly below the rate constants previously reported for experimental studies (10-12.4-10-14.2 mol m-2 s-1). This agreement reflects the structural simplicity of quartz, dilute solutes, and near-hydrologic saturation.

Geochimica et Cosmochimica Acta↗
USGS2005

Quality management system, U.S. Geological Survey National Water Quality Laboratory

A quality management system (QMS) is a document that describes the quality policy, system, and practices of an organization. The document may include by reference other publications relating to the laboratory's arrangements. The U.S. Geological Survey QMS describes the policies, objectives, principles, organizational authority, responsibilities, accountability, and implementation plan of the National Water Quality Laboratory (NWQL) for ensuring quality in its work processes, products, and services. It includes all operations associated with its internal management and extends as far as practicable toward the field-sampling component and the data user. The quality system described in the QMS is the framework for planning, implementing, and assessing work performed by the NWQL and for carrying out required quality assurance and quality control for compliance with the standards set by the National Environmental Laboratory Accreditation Conference. All personnel associated with the NWQL, including Federal and non-Federal employees, are bound by the requirements set forth in the policies, processes, and standard operating procedures included or referenced in this document.

Open-File Report↗
USGS2017

Time-causal decomposition of geomagnetic time series into secular variation, solar quiet, and disturbance signals

A theoretical basis and prototype numerical algorithm are provided that decompose regular time series of geomagnetic observations into three components: secular variation; solar quiet, and disturbance. Respectively, these three components correspond roughly to slow changes in the Earth’s internal magnetic field, periodic daily variations caused by quasi-stationary (with respect to the sun) electrical current systems in the Earth’s magnetosphere, and episodic perturbations to the geomagnetic baseline that are typically driven by fluctuations in a solar wind that interacts electromagnetically with the Earth’s magnetosphere. In contrast to similar algorithms applied to geomagnetic data in the past, this one addresses the issue of real time data acquisition directly by applying a time-causal, exponential smoother with “seasonal corrections” to the data as soon as they become available.

Open-File Report↗
USGS2007

Generalized potentiometric surface of the Arikaree aquifer, Pine Ridge Indian Reservation and Bennett County, South Dakota

INTRODUCTION The Pine Ridge Indian Reservation and Bennett County are located in southwest South Dakota. The Pine Ridge Indian Reservation includes all of Shannon County and the part of Jackson County south of the White River. Extensive Indian trust lands are in Bennett County. For purposes of this map, the Pine Ridge Indian Reservation and all of Bennett County are included in the study area (sheet 1). Ground water from wells and springs is the predominant source of public and domestic supply within the study area. The Arikaree aquifer is the largest source of ground water throughout this area. The Oglala Sioux Tribe is developing a ground-water management plan designed to “preserve, protect and maintain the quality of ground water for living and future members and non-members of the Oglala Sioux Indian Tribe within the internal and external boundaries of the Pine Ridge Reservation” (Michael Catches Enemy, Oglala Sioux Tribe Natural Resources Regulatory Agency, oral commun., 2007). Hydrologic information about the Arikaree aquifer is important to managing this resource. In 1998, the U.S. Geological Survey (USGS) began working in cooperation with the Oglala Sioux Tribe to develop a potentiometric map of the Arikaree aquifer in Jackson and Shannon Counties, with a primary component of that effort being a well inventory in those counties. In 2003, the study area was expanded to include Bennett County.

South Dakota↗
USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗
USGS2016

Landsat International Cooperators and Global Archive Consolidation

Landsat missions have always been an important component of U.S. foreign policy, as well as science and technology policy. The Landsat program’s longstanding network of International Cooperators (ICs), which operates numerous International Ground Stations (IGS) around the world, embodies the United States’ policy of peaceful use of outer space and the worldwide dissemination of civil space technology for public benefit. Thus, the ICs provide an essential dimension to the Landsat mission. In 2010, the Landsat Global Archive Consolidation (LGAC) initiative began, with goals to consolidate the Landsat data archives of all IGSs, make the data more accessible to the global Landsat user community, and significantly increase the frequency of observations over a given area of interest to contribute to the understanding of a changing Earth.

Fact Sheet↗