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USGS2012

Global petrologic variations on the moon: A ternary-diagram approach.

A ternary-diagram approach for determination of global petrologic variations on the lunar surface is presented that incorporates valuable improvements in our previous method of using geochemical variation diagrams. This new approach uses a ternary diagram that is subdivided into equally spaced segments along each of its three sides and has a triangular area in its center. The segments are assigned distinct colors that cover the range of the visible spectrum. The apexes are assigned the three primary colors, and the center triangle, which represents equal proportions of the three apexes, is assigned the color gray. The apexes are assigned the average Fe and (Th/Ti) c (ratio normalized to chondrites) compositions of KREEP/Mg-suite rocks, mare basalts, and ferroan anorthosites. The composition of each picture element (pixel) within these Apollo orbital gamma ray databases is used to determine its position within the ternary diagram. The color corresponding to this ternary position is then placed on a classification map at that pixel's position within the orbital databases. Error databases produced for the Fe and (Th/Ti) c data were used to exclude pixels having high errors. The resultant classification map shows spatial transitions among petrologic units, allows direct determination of the relative proportions of each end-member composition in a pixel, and increases the geologic interpretability of these data over that of the individual elemental databases. The classification units correspond remarkably well to observed geologic units, when we consider the spatial resolution (100 km) of the gamma ray spectrometer. Our results are as follows: (1) The highlands contain large areas of relatively pure ferroan anorthosite. (2) The average composition of the upper lunar crust is represented by an “anorthositic gabbro” composition, which supports the “magma-ocean” hypothesis for lunar crustal genesis. (3) KREEP/Mg-suite rocks are a minor fraction of the upper lunar crust. (4) Within the farside highlands, areas of KREEP/Mg-suite rocks coincide mostly with areas of crustal thinning, which are probably areas of KREEP basalt extrusions or localized excavations of Mg-suite rocks or KREEP-rich rocks. (5) Portions of the east limb and farside highlands have considerable amounts of a mafic, chondritic Th/Ti component (like mare basalt) whose occurrences coincide with mapped concentrations of light plains that display dark-halo craters; the presence of this component supports the hypothesis that mare volcanism had occurred within this highland region before the end of final heavy bombardment.

Journal of Geophysical Research Solid Earth↗

USGS2014

Wildland fire ash: Production, composition and eco-hydro-geomorphic effects

Fire transforms fuels (i.e. biomass, necromass, soil organic matter) into materials with different chemical and physical properties. One of these materials is ash, which is the particulate residue remaining or deposited on the ground that consists of mineral materials and charred organic components. The quantity and characteristics of ash produced during a wildland fire depend mainly on (1) the total burned fuel (i.e. fuel load), (2) fuel type and (3) its combustion completeness. For a given fuel load and type, a higher combustion completeness will reduce the ash organic carbon content, increasing the relative mineral content, and hence reducing total mass of ash produced. The homogeneity and thickness of the ash layer can vary substantially in space and time and reported average thicknesses range from close to 0 to 50 mm. Ash is a highly mobile material that, after its deposition, may be incorporated into the soil profile, redistributed or removed from a burned site within days or weeks by wind and water erosion to surface depressions, footslopes, streams, lakes, reservoirs and, potentially, into marine deposits. Research on the composition, properties and effects of ash on the burned ecosystem has been conducted on material collected in the field after wildland and prescribed fires as well as on material produced in the laboratory. At low combustion completeness (typically T < 450 °C), ash is organic-rich, with organic carbon as the main component. At high combustion completeness (T > 450 °C), most organic carbon is volatized and the remaining mineral ash has elevated pH when in solution. It is composed mainly of calcium, magnesium, sodium, potassium, silicon and phosphorous in the form of inorganic carbonates, whereas at T > 580 °C the most common forms are oxides. Ash produced under lower combustion completeness is usually darker, coarser, and less dense and has a higher saturated hydraulic conductivity than ash with higher combustion completeness, although physical reactions with CO 2 and when moistened produce further changes in ash characteristics. As a new material present after a wildland fire, ash can have profound effects on ecosystems. It affects biogeochemical cycles, including the C cycle, not only within the burned area, but also globally. Ash incorporated into the soil increases temporarily soil pH and nutrient pools and changes physical properties such as albedo, soil texture and hydraulic properties including water repellency. Ash modifies soil hydrologic behavior by creating a two-layer system: the soil and the ash layer, which can function in different ways depending on (1) ash depth and type, (2) soil type and (3) rainfall characteristics. Key parameters are the ash's water holding capacity, hydraulic conductivity and its potential to clog soil pores. Runoff from burned areas carries soluble nutrients contained in ash, which can lead to problems for potable water supplies. Ash deposition also stimulates soil microbial activity and vegetation growth. Further work is needed to (1) standardize methods for investigating ash and its effects on the ecosystem, (2) characterize ash properties for specific ecosystems and wildland fire types, (3) determine the effects of ash on human and ecosystem health, especially when transported by wind or water, (4) investigate ash's controls on water and soil losses at slope and catchment scales, (5) examine its role in the C cycle, and (6) study its redistribution and fate in the environment.

Earth-Science Reviews↗

USGS2012

Teleseismically recorded seismicity before and after the May 7, 1986, Andreanof Islands, Alaska, earthquake

The May 7, 1986, Andreanof Islands earthquake ( M w 8.0) is the largest event to have occurred in that section of the Aleutian arc since the March 9, 1957, Aleutian Islands earthquake ( M w 8.6). Teleseismically well-recorded earthquakes in the region of the 1986 earthquake are relocated with a plate model and with careful attention to the focal depths. The data set is nearly complete for m b ≥4.7 between longitudes 172°W and 179°W for the period 1964 through April 1987 and provides a detailed description of the space-time history of moderate-size earthquakes in the region for that period. Additional insight is provided by source parameters which have been systematically determined for M w ≥5 earthquakes that occurred in the region since 1977 and by a modeling study of the spatial distribution of moment release on the mainshock fault plane. A technically significant component of oblique convergence in the central Aleutian arc results in its breakup into clockwiserotating and westward translating blocks. The western part of the Andreanof block is distinct from and stronger than flanking regions. The greater strength of this block segment and strong coupling along the main thrust zone result in the accumulation of high levels of shear stress, which give rise to great earthquakes near its eastern boundary. The occurrence of the 1986 rupture only 29 years after the 1957 earthquake may indicate that in the central Aleutians M 7+ earthquakes ordinarily do represent the predominant mode of strain release. Segmentation of the main thrust zone into upper and lower planes is supported by spatial and temporal patterns of seismicity and by focal mechanism data. This and other lines of evidence indicate a downdip increase in fault strength and possibly in heterogeneity within the main thrust zone in subduction zone environments. Aftershocks of the 1986 earthquake were bounded to the west by the Andreanof block boundary (Adak Canyon) and to the east by an aseismic segment of the main thrust zone near the subducted extension of the Amlia fracture zone. The aftershock distribution was bounded to the south by a forearc shear zone and to the north by the base of the main thrust zone in the Hawley Ridge segment and by the downdip edge of the upper plane of the main thrust zone in the eastern segment. Aftershocks which occurred near the volcanic line at shallow crustal depths in the upper plate were triggered by the mainshock and manifest a partial decoupling of oblique slip in this region along a west-striking right-lateral fault with low shear strength. Aftershock clustering along the main thrust zone was very similar to the distribution of prior seismicity, suggesting a continuation of long-term processes and the existence of areas with distinct mechanical properties. Interconnecting regions of low seismicity during both the premainshock and aftershock periods coincided with areas of major moment release during the mainshock. Seismicity data prior to the 1986 mainshock gave few clues about the location of the mainshock nucleation point, the mainshock size, and its time of occurrence. However, a large part of the mainshock moment release did coincide with a zone of seismic quiescence monitored by the Adak local seismograph network.

Journal of Geophysical Research Solid Earth↗

USGS2010

The potential influence of changing climate on the persistence of salmonids of the inland west

The Earth's climate warmed steadily during the 20th century, and mean annual air temperatures are estimated to have increased by 0.6°C (Intergovernmental Panel on Climate Change, 2007). Although many cycles of warming and cooling have occurred in the past, the most recent warming period is unique in its rate and magnitude of change (Siegenthaler and others, 2005) and in its association with anthropogenic emissions of greenhouse gases (Intergovernmental Panel on Climate Change , 2007). The climate in the western United States warmed in concert with the global trend but at an accelerated rate (+0.8°C during the 20th century; Saunders and others, 2008). The region could also prove especially sensitive to future changes because the relatively small human population is growing rapidly, as are demands on limited water supplies. Regional hydrological patterns are dominated by seasonal snow accumulation at upper elevations. Most of the region is relatively dry, and both terrestrial and aquatic ecosystems are strongly constrained b y water availability (Barnett and others, 2008; Brown and others, 2008). Stream environments are dynamic and climatically extreme, and salmonid fishes are the dominant elements of the native biodiversity (McPhail and Lindsey, 1986; Waples and others, 2008). Salmonids have broad economic and ecologic importance, but a century of intensive water resource development, nonnative fish stocking, and land use has significantly reduced many populations and several taxa are now protected under the Endangered Species Act (Thurow and others, 1997; Trotter, 2008). Because salmonids require relatively pristine, cold water environments and are often isolated in headwater habitats, members of this group may be especially vulnerable to the effects of a warming climate (Keleher and Rahel, 1996; Rieman and others, 2007; Williams and others, 2009). Warming during the 20th century drove a series of environmental trends that have profound implications for many aspects of salmonid habitat, including disturbance regimes such as wildfire, and unfavorable changes to thermal and hydrologic properties of aquatic systems. Warmer air temperatures have been associated with decreased winter snow accumulations, have accelerated snowmelt, and have advanced the timing of peak runoff by several days to weeks across most of western North America (Stewart and others, 2005; Barnett and others, 2008). Less snow and earlier runoff decrease aquifer recharge, make less water available for groundwater inputs to streams, and are contributing to widespread decreases in summer low flows (Stewart and others, 2005; Rood and others, 2008; Luce and Holden 2009). Interannual variability in stream flow is increasing, as is the persistence of multi-year extreme conditions (McCabe and others, 2004; Pagano and Garen 2005). In many areas of western North America, flood risks have increased in association with warmer temperatures during the 20th century (Hamlet and Lettenmaier, 2005). Streams where midwinter temperatures are near freezing have proven especially sensitive to increased flooding because of associated transitional hydrological patterns (mixtures of rainfall and snowmelt) and propensity for occasional rain-on-snow events to rapidly melt winter snowpack and generate large floods (Hamlet and Lettenmaier, 2005). Stream temperatures in many areas are increasing (Peterson and Kitchell, 2001; Morrison and others, 2002; Bartholow, 2005; Kaushal and others, 2010), due to both air temperature increases and reduced summer flows that make streams more sensitive to warmer air temperatures (Isaak and others, 2010). In recent decades, wildfires have become more common across much of the western United States during periods of more frequent droughts (Westerling and others, 2006; Hoerling and Eischeid, 2007), and local stream temperature can increase in postfire environments (Gresswell, 1999; Dunham and others, 2007). Fire-related temperature increase within streams is commonly a transient phenomenon, lasting only until riparian vegetation has recovered (Gresswell, 1999); however, ongoing climate change could preclude recovery to higher stature, prefire vegetation types in some areas (McKenzie and others, 2004; van Mantgem and Stephenson, 2007), resulting in a loss of critical riparian shading. Additionally, when wildfires occur in steep mountain topographies, the vegetation that stabilize s soils on hillslopes is often killed and landslides become more prevalent (Gresswell, 1999). Landslides int o stream channels form debris flows composed of sediment slurries and dead trees that can scour channels to bedrock and further exacerbate stream heating, delay recovery of riparian areas, or extirpate fish populations (Gresswell, 1999; May and Gresswell, 2003; Dunham and others, 2007). Changes in stream environments will shift habitat distributions, sometimes unpredictably, in both time and space for many salmonid fishes. Water temperature fundamentally influences aquatic ecosystem health because distribution, reproduction, fitness, and survival of ectothermic organisms are inextricably linked to the thermal regime of the environment. Historically, research has focused on defining lethal thermal limits of salmonids (Eaton and others, 1995; Selong and others, 2001; Todd and others, 2008); however, water temperature is known to be important in biological processes at a variety of spatial scales and levels of biological organization (Rahel and Olden, 2008; McCullough and others, 2009). For instance, trout are affected directly by water temperature through feeding, metabolism, and growth rates, and indirectly by factors such as prey availability and species interactions (Wehrly and others, 2007; Rahel and Olden, 2008). Where cold water temperatures currently limit habitat suitability and distributions of some species (for example, at the highest and most northerly distributional extents; Nakano and others, 1996; Coleman and Fausch, 2007), a warming climate may gradually increase the quality and extent of suitable habitat. Over time, previously constrained populations are expected to expand into these new habitats and increase in number. Some evidence suggests this may already be happening in Alaska, where streams in recently deglaciated areas are being colonized by emigrants from nearby salmon and char populations (Milner and others, 2000). Unfortunately, many of the sensitive salmonid species that are often the focus of western managers are unlikely to benefit from future water temperature increases. Warmer stream temperatures will facilitate invasion by nonnative species that are broadly established in downstream areas into upstream areas where they will compete with native species (Rieman and others, 2006; Rahel and Olden, 2008; Fausch and others, 2009). In other cases, warmer stream temperatures will render thermally suitable habitats unsuitable in downstream areas and effect net losses of habitat because upstream distributions are often constrained by streams that are too small or steep (Hari and others, 2006; Isaak and others, 2010). Both scenarios are realistic for fish species like bull trout ( Salvelinus confluentus ) (Rieman and others, 2006; Rieman and others, 2007), the various subspecies of cutthroat trout ( Oncorhynchus clarkii ) (Williams and others, 2009), Gila trout ( Oncorhynchus gilae gilae ) (Kennedy and others, 2008), and Apache trout ( Oncorhynchus gilae apache ) (Rinne and Minckley, 1985; Carmichael and others, 1993). As native species are increasingly confined to smaller and more isolated habitats by a gradually warming climate, the effects of wildfires (whether related to lethal changes in water quality during a fire, channel debris flows, or chronic postfire warming ) could have greater proportional effects on remaining habitats (for example, Brown and others, 2001; Rieman and others, 2007). If these changes were accompanied by additional hydrologic alterations associated with changes to the magnitude, frequency, duration, timing, and rate of change of discharge patterns (Jager and others, 1999; Henderson and others, 2000), populations may begin to lose some of their historic resilience and become ever more susceptible to local extirpations. As dramatic and extensive as climatic and environmental trends are for salmonid habitats, global climate models (GCMs) project that many of these trends will continue and even accelerate until at least the middle of the 21st century (Intergovernmental Panel on Climate Change, 2007). Current projections suggest mean annual air temperatures will increase by an additional 1–3°C, and early indications are that climate trajectory is at the higher end of this range (Pittock, 2006; Raupach and others, 2007). Although predicted changes vary considerably, even the most conservative estimates suggest a warming rate that will be twice that observed during the 20th century. Projections for the midcentury are most certainly due to the effects of greenhouse gases already emitted or predicted in the short term, uncertainties of the effects of longer-term greenhouse gas emissions, short-term climate cycles, and process errors associated with climate models (Cox and Stephenson, 2007). Projections of changes in total precipitation are less certain than those for air temperatures, but most GCMs project relatively small changes in the Northwest, with the exception of slightly drier summer periods (Mote and others, 2008; Karl and others, 2009). In the Southwest, however, significant decreases (such as 15–30 percent ) are projected during most periods of the year, and this area is one of the few for which Intergovernmental Panel on Climate Change (2007) precipitation projections have a high level of certainty (Hoerling and Eischeid, 2007; Karl and others, 2009). Clearly, managers of native salmonids in the wester n United States should consider adjusting management strategies to accommodate a warmer and possibly drier future (Williams and others, 2009). Tools are needed to forecast where important changes may occur and how conservation efforts should be prioritized. In this Open-File Report, we document our initial efforts in this regard for 10 species and subspecies of inland trout and Montana Arctic grayling ( Thymallus arcticus ) across the western United States.

Arizona, California, Colorado, Idaho, Montana, Nev↗

USGS1981

Significant results from using earth observation satellites for mineral and energy resource exploration

A large number of Earth-observation satellites orbit our world several times each day, providing new information about the land and sea surfaces and the overlying thin layer of atmosphere that makes our planet unique. Meteorological satellites have had the longest history of experimental use and most are now considered operational. The geologic information collected by the Landsat, Polar Orbiting Geophysical Observatory (POGO), Magsat, Heat Capacity Mapping Mission (HCMM) and Seasat land and ocean observation systems is being thoroughly tested, and some of these systems are now approaching operational use. Landsat multispectral images provide views of large areas of the Earth under uniform lighting conditions and can be obtained at a variety of scales and formats. Not only do the Landsat data provide highly useful images showing surficial materials and structures such as folds and faults, but also measurements and computer-derived ratios of the brightness of different rock types, alteration zones, and mineral associations. These data have led to the finding of a variety of new ore deposits. In addition, the combination of Landsat digital data and aeromagnetic data has extended the use of Landsat as an exploration tool which can be used to readily relate surface features to subsurface anomalies. Magsat data, now being collected, are helping refine information on major crustal anomalies that were first recognized during the analysis of POGO data. The more nearly circular orbit, lower altitude, and increased sophistication of its vector magnetometer enable Magsat to provide more precise information than POGO. Information of this type is required to develop crustal models. Although Magsat is designed to operate for only 4–8 months, the number of orbits that it should be able to make will be sufficient to accomplish its mission and to record a major magnetic storm expected in 1980. HCMM is a two-band visible to near-IR (0.55–1.1 μm) and thermal infrared (10.2–12.5 μm) system designed to measure reflected solar energy, determine the heat capacity of rocks and to monitor soil moisture, thermal effluents, plant canopy temperatures and snow cover. Launched in April 1978, it is in sun-synchronous, circular orbit at an altitude of 620 km. It is a relatively low-resolution system with an instantaneous field of view (IFOV) of 500–600 m and a swath width of 716 km. However, the system is designed to detect objects in the range of 260°–340° K with a sensitivity (NEδT) of 0.4°K at 280°. Recording the thermal radiation of urban heat islands and high thermal inertia of quartzite strata in the Appalachian region are two examples of its land applications. Launched in June 1978, Seasat operated for only 100 days, but successfully acquired much information over both sea and land. The collection of synthetic aperture radar (SAR) imagery and radar altimetry was particularly important to geologists. Although there are difficulties in processing and distributing these data in a timely manner, initial evaluations indicate that the radar imagery supplements Landsat data by increasing the spectral range and offering a different look angle. The radar altimeter provides accurate profiles over narrow strips of land (1 km wide) and has demonstrated usefulness in measuring icecap surfaces (Greenland, Iceland, and Antarctica). The Salar of Uyuni in southern Bolivia served as a calibration site for the altimeter and has enabled investigators to develop a land-based smoothing algorithm that is believed to increase the accuracy of the system to 10 cm. Data from the altimeter are currently being used to measure subsidence resulting from ground water withdrawal in the Phoenix-Tucson area.

Advances in Space Research↗

USGS2012

A seismic refraction survey of the Imperial Valley Region, California

The U.S. Geological Survey conducted an extensive seismic refraction survey in the Imperial Valley region of California in 1979. The Imperial Valley is located in the Salton Trough, an active rift between the Pacific and North American plates. Forty shots fired at seven shot points were recorded by 100 portable seismic instruments at typical spacing of 0.5–1 km. More than 1300 recording locations were occupied, and more than 3000 usable seismograms were obtained. We analyzed five profiles using a standard ray‐tracing program, constructed a contour map of reduced travel times from our most widely recorded shot point, and modeled an existing gravity profile across the Salton Trough. Results are itemized: (1) All models have in common a sedimentary layer ( V p = 1.8–5.0 km/s), a “transition zone” ( V p = 5.0–5.65 km/s), a basement ( V p = 5.65 km/s in the Imperial Valley, 5.9 km/s on the bordering mesas), and subbasement ( V p = 7.2 km/s). (2) The sedimentary layer ranges in thickness along the axis of the Salton Trough from 3.7 km (Salton Sea) to 4.8 km (U.S.‐Mexican border). On the bordering mesas it is quite variable in thickness. (3) The “transition” zone is about 1 km thick in most places. In the Imperial Valley there are no marked velocity discontinuities in this zone between the sedimentary layer and basement. On the bordering mesas, however, there is a discontinuity at the top of this zone. (4) There are apparently two types of basement. On the bordering mesas, basement is crystalline igneous and metamorphic rocks. In the Imperial Valley, basement is mostly lower‐greenshist‐facies sedimentary rocks, based primarily on the smooth transition in character from sediment to basement arrivals, the low value of basement velocity, and the fact that deep (4 km) wells in the valley penetrate only the upper part of the known Cenozoic stratigraphic column for the Salton Trough. (5) The subbasement, or intermediate crustal layer, ranges in depth along the axis of the Salton Trough from 16 km (Salton Sea) to 10 km (U.S.‐Mexican border). Gravity modeling requires that this layer deepen and/or pinch out beneath the bordering mesas and mountain ranges. Based on its high velocity and the presence of intrusive basaltic rocks in the sedimentary section in the Imperial Valley, the subbasement is thought to be a mafic intrusive complex similar to oceanic middle crust. (6) Several structures are seen that affect basement, transition zone, and deeper parts of the sedimentary layer. They include a scarp along the Imperial fault, as much as 1 km down to the northeast, and a scarp passing roughly along the topographic boundary between the Imperial Valley and the bordering mesa to the west, as much as 3½ km down to the east. We interpret the latter scarp to be the suture, or rift boundary, between the older crystalline basement on the mesa and the younger metasedimentary basement in the Imperial Valley. (7) On a contour map of reduced travel time from our most widely recorded shot point, subtle patches of early arrivals among otherwise late arrivals in the central Imperial Valley correlate well with known geothermal resource areas having reservoir temperatures of more than 150°C. Apparently the Salton Trough is a location where new crust is being generated. As the rift opens, mafic intrusive rocks fill it from below as sedimentary rocks fill it from above. Rifting and intrusion produce high heat flow that metamorphoses the sedimentary rocks to shallow depth (metasedimentary basement in the Imperial Valley) and thus consolidates the new crust.

California↗

USGS2021

Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud

Executive Summary Global food and water security analysis and management require precise and accurate global cropland-extent maps. Existing maps have limitations, in that they are (1) mapped using coarse-resolution remote-sensing data, resulting in the lack of precise mapping location of croplands and their accuracies; (2) derived by collecting and collating national statistical data that are often subjective, leading to substantial uncertainties in cropland-area estimates, as well as their locations; and (3) extracted from one or more classes of a land use–land cover product in which cropland classes are not the focus of mapping, leading to their mixing with other classes and creating significant errors of omission and commission. These limitations can be overcome by producing high-resolution cropland-extent maps using satellite-sensor data, such as Landsat 30-m resolution or higher. The most fundamental cropland product is the high-resolution cropland-extent map because all higher level cropland products, such as crop-watering method (that is, whether crops are irrigated or rainfed), crop types, cropping intensities, cropland fallows, crop productivity, and crop-water productivity, are dependent on a precise and accurate cropland-extent product. Given these realities, the overarching goal of this study was to produce a Landsat satellite-derived global cropland-extent product at 30-m resolution. The work, which involved a paradigm shift in how global cropland-extent maps are produced, involved the following five key steps: (1) petabyte-scale computing that involved multiyear, 8- to 16-day, time-series Landsat 30-m resolution data for the global land surface; (2) composition of analysis-ready data (ARD) cubes; (3) creation of a large global-reference data hub for machine learning; (4) use of multiple machine-learning algorithms (MLAs) by writing software and computing in the cloud; and (5) Google Earth Engine (GEE) cloud computing. The five key steps involved nine distinct phases. First, the world was segmented into 74 agroecological zones (AEZs). Second, Landsat 8- to 16-day data were used to time-composite 10-band (blue, green, red, near-infrared, short-wave infrared band 1, short-wave infrared band 2, thermal infrared, enhanced vegetation index, normalized difference water index, and normalized difference vegetation index) Landsat 30-m resolution data cubes for every 2- to 4-month time period during 3- to 4-year periods (stated as nominal-year 2015 or, simply, 2015), along with two additional 30-m resolution bands (Shuttle Radar Topography Mission elevation, and slope) in each of the 74 AEZs. Third, more than 100,000 reference-training data samples were collected using ground data (some of which were collected using a mobile application), as well as submeter- to 5-m-resolution, very high-resolution imagery sourced from other reliable sources. Fourth, reference-training data were used to create a knowledge base for separating cropland from noncropland. Fifth, MLAs such as the pixel-based supervised random forest and support-vector machines were written on the GEE using Python and JavaScript. Sixth, object-based recursive hierarchical segmentation algorithm was used, in addition to MLAs, to overcome uncertainties. Seventh, MLAs used the knowledge base to classify and separate cropland from noncropland. Eighth, accuracy assessment was conducted by generating error matrices for each of the 74 AEZs using 19,171 independent validation-data samples. Ninth, cropland areas were computed for all countries of the world and compared with United Nation’s (UN’s) Food and Agricultural Organization (FAO) and other national statistics. The outcome was a Landsat-derived global cropland-extent product at 30-m resolution (GCEP30), which has an overall accuracy of 91.7 percent. For the cropland class, producer’s accuracy was 83.4 percent, and user’s accuracy was 78.3 percent. GCEP30 calculated (using direct pixel count) the global net-cropland area (GNCA) for the year 2015 as 1.873 billion hectares (~12.6 percent of the Earth’s terrestrial area). The continental cropland distribution as a percentage of GNCA was Asia, 33 percent; Europe, 25.5 percent; Africa, 16.7 percent; North America, 14.4 percent; South America, 8.1 percent; and Australia and Oceania, 2.4 percent. The worldwide cropland areas in GCEP30 for 2015 were higher by 236 to 299 million hectares (Mha) compared to national statistics reported elsewhere for the same year (for example, in Food and Agriculture Organization’s corporate statistical database [FAOSTAT] and in the monthly irrigated and rainfed crop areas [MIRCA] database). The global cropland area reported for 2015 increased by 344 Mha (22.5 percent), compared to the year 2000. During the same period (2000–2015), the world’s population increased by 20 percent. Whereas some of these areal increases are real increases in cropland areas, others are due to the types of data, methods, and approaches used. Using the highest known resolution (compared to previous coarse-resolution global products) enabled this study to capture fragmented croplands. Coarse-resolution data compute areas on the basis of subpixels, which, for a large proportion of certain land use–land cover classes, will show only a certain percentage of the total pixel area as actual area. Subpixel areas can lead to substantial uncertainties in area computation, as determining the exact fraction of cropland areas within a coarse-resolution pixel is resource intensive and subject to errors. Other innovations in GCEP30 include reference-data hubs, machine learning, and cloud computing. Cropland areas in 214 countries, territories, departments, and regions were calculated for the year 2015 using GCEP30, on the basis of UN’s global administrative unit layers (GAUL) boundaries. The 10 leading countries in terms of cropland area (as a percentage of the GNCA) were India (9.6 percent), United States (8.95 percent), China (8.82 percent), Russia (8.32 percent), Brazil (3.42 percent), Ukraine (2.32 percent), Canada (2.29 percent), Argentina (2.05 percent), Indonesia (2 percent), and Nigeria (1.91 percent). Together, these 10 countries occupy 50 percent of the global cropland, and they have 52 percent of the global population. Their combined cropland area increased by 2 percent between 2000 and 2015, compared to the substantial increase in population of 517 million (15.5 percent). Together, India, United States, China, and Russia encompass 36 percent of the total area. In the United States and Canada, from 2000 to 2015, cropland decreased by about 2 percent, whereas their populations increased by 14 and 13 percent, respectively. The additional food requirements in these 10 countries, which are caused by increased populations, as well as increasing nutritional demands, are met by production increases in existing cropland or through virtual food trade, or both. More than 18 countries, territories, departments, or regions had 60 percent or more of their geographic area as cropland: Republic of Moldova, San Marino, and Hungary had more than 80 percent of the country’s area as cropland; Denmark, Ukraine, Ireland, and Bangladesh, 70 to 80 percent; and Uruguay, Netherlands, United Kingdom, Spain, Lithuania, Poland, Gaza Strip, Czechia, Italy, India, and Azerbaijan, 60 to 70 percent. Europe and South Asia can be considered agricultural capitals of the world, on the basis of their percentages of geographic area as cropland. United States, China, and Russia, which all have high cropland areas, are ranked second, third, and fourth in the world; India is ranked first. However, the amount of cropland as a percentage of the country’s geographic area is relatively very low for United States (18.3 percent), China (17.7 percent), and Russia (9.5 percent), whereas it is 60.5 percent for India. Most African and South American countries, territories, departments, or regions have less than 15 percent of their geographic area as cropland. China and India together house 36 percent of the world’s population; however, between 2000 and 2015, the amount of China’s cropland area fell by 18.9 percent, owing to urban expansion and the abandonment of farmlands caused by demographic changes (that is, the movement of population from villages to cities). In contrast, China’s population grew by 10 percent. The amount of India’s cropland increased by 8.5 percent, whereas its population grew by 20 percent. This study showed that, out of the 10 leading cropland countries, Ukraine, Nigeria, Russia, and Indonesia showed an 18 to 31 percent increase in cropland areas, on the basis of GCEP30 by the year 2015, compared to 2000. Nigeria’s cropland area increased by 25 percent, and its population increased by 31 percent in the same period. In these countries, food security is maintained by cropland expansion, productivity increases, and virtual food trade. Nevertheless, this trend of increasing net-cropland area and productivity will likely become difficult to maintain, owing to diminishing arable lands and plateauing of 50 years of continual yield increases, requiring policymakers to explore novel and data-supported approaches to solving future food security issues. The GCEP30 product, which can be browsed at full resolution at www.croplands.org , has been released for public download and use through U.S. Geological Survey (USGS)–National Aeronautics and Space Administration (NASA) Land Processes Distributed Active Archive Center (see https://lpdaac.usgs.gov/news/release-of-gfsad-30-meter-cropland-extent-products/ ).

Professional Paper↗