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USGS2021

Rapid monitoring of the abundance and spread of exotic annual grasses in the western United States using remote sensing and machine learning

Exotic annual grasses (EAG) are one of the most damaging agents of change in western North America. Despite known socio-environmental effects of EAG there remains a need to enhance monitoring capabilities for better informing conservation and management practices. Here, we integrate field observations, remote sensing and climate data with machine-learning techniques to estimate and assess patterns of historical (1985–2019; R 2 = 0.86 ± 0.05; MAE = 6.7 ± 1.4%), present (2020), and future (2025–2040) EAG abundance (30-m) across much of the western United States. Trend analysis revealed that ∼8% and 1% of the landscape experienced significant rises and declines in historical EAG cover, respectively, with hotspots of invasion generally occurring near roads and along low-to-mid elevation gradients with warmer and drier conditions. Accurate simulations of the response of EAG to changing environmental conditions, disturbances and management treatments indicate that ecosystem resistance to invasion is largely controlled by long-term EAG abundance (surrogate for seed bank), time since and frequency of wildfire, and plant community interactions. Ecological thresholds associated with enhanced probabilities of wildfire occurrence and invasion rates indicate that relatively little (10%) EAG cover is needed to heighten these risks. Climate change is expected to push 8% of the landscape across invasion thresholds by 2040, impacting 6% of existing sage-grouse habitat, and we identify where fuel breaks may be placed to reduce wildfire risks and invasion. Spatially detailed, timely, and accurate depictions of past, present, and future EAG abundance are vital for the protection of life and property and the continued stewardship of sagebrush ecosystems.

California, Colorado, Idaho, Nevada, Oregon, Utah,↗

USGS2022

Comparison of Digital Terrain Models from two photoclinometry methods

We evaluate the horizontal resolution and vertical precision for digital topographic models (DTMs) of the Moon derived from image radiance information, a process known as photoclinometry (PC) or shape-from-shading (SfS). We use the implementations in two available planetary image processing software systems, single image PC in the U.S. Geological Survey Integrated Software for Imagers and Spectrometers (ISIS) system, and multi-image SfS in the Ames Stereo Pipeline (ASP), and test results obtained with and without use of a starting solution from stereo, with single and multiple images, and for varying illumination conditions. To obtain the higher quality reference DTMs against which the products can be evaluated, we derived DTMs by stereoanalysis of Lunar Reconnaissance Orbiter Narrow-Angle Camera (LROC NAC) images at their native pixel spacing of ∼0.5 m, then produced a 16-m/post stereo DTM from images downsampled to 4 m/pixel and refined it with images at 16 m/pixel. When used with a single image, both algorithms improved resolution (by a factor of 1.4 for PC and 2.4 for SfS compared to stereo). An albedo map produced in ISIS by ratioing the image to a simulation based on the stereo DTM was well correlated with one output by SfS. The albedo correction was crucial for PC with ∼60° incidence but not at ∼80°. DTMs produced by PC and SfS without a starting stereo DTM had larger errors but good detail, and could be useful for many applications. In SfS, it was necessary to increase smoothing to get a usable DTM when the weighting on an a priori DTM was reduced. Multi-image SfS including modeling of spatially varying albedo reduced vertical errors by factors of 1.5 or more compared to single-image SfS.

International Archives of the Photogrammetry, Remo↗

USGS1993

Identification of requirements and sources for global digital topographic data

Many of the physical processes being studied by global change researchers are affects by land surface topography and consequently topographic data are an important requirement for these investigations. Remotely sensed data, especially those that will be collected by the instruments of the Earth Observing System, require significant correction to remove topographic effects. Although some requirements are met by existing topographic data, there are serious data shortages that will affect global change science. The interdisciplinary and multi temporal natural of global change research requires that remotely sensed data be processed using a consistent, highly accurate global topographic database so that information extracted from these data for different areas and times can be compared quantitively. Cartographic and remote sensing sources for the generation of new topographic data exist or are planned and will be helpful for fulfilling these requirements. More consistent use of accuracy statement terminology by data users and producers is necessary to better compare the requirements with existing or future data sets.

Pecora 12 Symposium↗

USGS2018

Hierarchical multi-population viability analysis

Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long-term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi-population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub-models. We present a case study in which we customized this model for historical population monitoring data (1985–2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi-pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical multi-population viability analysis bridges the gap between site-level field observations and population-level processes, making effective use of existing datasets to support management decisions with robust estimates of population dynamics, extinction risks, and uncertainties.

Ecology↗

USGS2026

Lava flow emplacement dynamics during the Mauna Loa 2022 eruption

On November 27, 2022, Mauna Loa erupted for the first time in 38 years, threatening a major highway on the Island of Hawaiʻi. The opening phases of the eruption were focused at the volcano’s summit, before magma propagated into the upper Northeast Rift Zone to erupt at four fissure segments that localized at fissure 3 by December 2. This fissure produced a braided ʻaʻā flow that traversed the steep north flank at >1 km/hr, before slowing as slopes shallowed. Effusion rates peaked in the early hours of the eruption and then steadied at around 100 m3/s at fissure 3. Lava effusion became variable and dropped abruptly on December 7. The eruption ended on December 10 with a final flow length of 18 km. We tracked lava effusion rates, flow advance, channel dynamics, and 3-D flow field development with field and remote sensing observations throughout this eruption to inform lava flow forecasts and investigate ʻaʻā flow dynamics. Flows were mapped using optical and infrared imagery, uncrewed aircraft systems, and airborne single-pass InSAR. Video- and time-lapse cameras were deployed to record lava fountaining and channelized flow at frequent intervals, supplemented by field measurements. Analyses of these data built a detailed record of effusion rates and associated flow dynamics. We combine these high frequency observations of the proximal flow field with broader thermal and 3-D mapping of the evolution in the medial and distal flow field to examine ʻaʻā flow dynamics from source to toe. Within the steep, medial section of the flow field, channel blockages caused back-ups and overflows as the eruption progressed. Disrupted lava supply to the distal flow field and low slopes resulted in stalling, widening, and thickening at the toe. Overall, 142 million m3 of lava covered 36 km2 over 13 days. Our results inform the controls on development and evolution of lava flow fields, with implications for forecasting primary flow advance and secondary flow field growth.

Hawaii↗

USGS2018

Evaluating and monitoring forest fuel treatments using remote sensing applications in Arizona, U.S.A.

The practice of fire suppression across the western United States over the past century has led to dense forests, and when coupled with drought has contributed to an increase in large and destructive wildfires. Forest management efforts aimed at reducing flammable fuels through various fuel treatments can help to restore frequent fire regimes and increase forest resilience. Our research examines how different fuel treatments influenced burn severity and post-fire vegetative stand dynamics on the San Carlos Apache Reservation, in east-central Arizona, U.S.A. Our methods included the use of multitemporal remote sensing data and cloud computing to evaluate burn severity and post-fire vegetation conditions as well as statistical analyses. We investigated how forest thinning, commercial harvesting, prescribed burning, and resource benefit burning (managed wildfire) related to satellite measured burn severity (the difference Normalized Burn Ratio – dNBR) following the 2013 Creek Fire and used spectral measures of post-fire stand dynamics to track changes in land surface characteristics (i.e., brightness, greenness and wetness). We found strong negative relationships between dNBR and post-fire greenness and wetness, and a positive non-linear relationship between dNBR and brightness, with greater variability at higher severities. Fire severity and post-fire surface changes also differed by treatment type. Our results showed harvested and thinned sites that were not treated with prescribed fire had the highest severity fire. When harvesting was followed by a prescribed burn, the sites experienced lower burn severity and reduced post-fire changes in vegetation greenness and wetness. Areas that had previously experienced resource benefit burns had the lowest burn severities and the highest post-fire greenness measurements compared to all other treatments, except for where the prescribed burn had occurred. These results suggest that fire treatments may be most effective at reducing the probability of hazardous fire and increasing post-fire recovery. This research demonstrates the utility of remote sensing and spatial data t o inform forest management, and how various fuel treatments can influence burn severity and post-fire vegetation response within ponderosa pine forests across the southwestern U.S.

Arizona↗

USGS2025

Numerical simulation of sound-side barrier-island inundation and breaching during Hurricane Dorian (2019)

Hurricane-induced morphological changes and associated community hazards along sandy, barrier-island coastlines have been studied primarily from the perspective of ocean-side attack by storm-driven ocean surge and large waves. Thus, our understanding of long-term barrier island morphological change focuses on beach erosion, overwash, and inlet formation. In contrast, outwash events with inundation from the sound side, such as one that occurred in Cape Lookout National Seashore, North Carolina, USA during Hurricane Dorian (September 2019), are understudied. Studying such events can improve understanding of barrier island response and stability for a broader range of conditions. Here, we model the hydrodynamics and morphological evolution of a barrier island using a coupled wave-current-sediment transport modeling system. Wind-driven surge in Pamlico Sound led to overtopping from the sound side, which eroded outwash channels and transported sediment seaward into the nearshore. Simulations reproduce the channel features observed with aerial imagery and provide information not available from the remote-sensing observations, including channel depths (>2 m) and the fate of the eroded sand. We found that >99% of the eroded sand was deposited in the nearshore, within 1,000 m of the shoreline in depths <10 m, suggesting that the deposited sediment remains available for littoral transport and beach recovery. Simulations with combinations of coarse or fine sediment and vegetated or unvegetated landcover indicate that channel position did not vary with grain size or vegetation, while volume of erosion and channel morphology were more responsive to variations in grain size and less responsive to presence of vegetation.

North Carolina↗

USGS2009

What is a picture worth? A history of remote sensing

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m. Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.

Hydrological Sciences Bulletin↗

USGS2015

Relative importance of phosphorus, invasive mussels and climate for patterns in chlorophyll a and primary production in Lakes Michigan and Huron

1. Lakes Michigan and Huron, which are undergoing oligotrophication after reduction of phosphorus loading, invasion by dreissenid mussels and variation in climate, provide an opportunity to conduct large-scale evaluation of the relative importance of these changes for lake productivity. We used remote sensing, field data and an information-theoretic approach to identify factors that showed statistical relationships with observed changes in chlorophyll a (chla) and primary production (PP). 2. Spring phosphorus (TP), annual mean chla and PP have all declined significantly in both lakes since the late 1990s. Additionally, monthly mean values of chla have decreased in many but not all months, indicating altered seasonal patterns. The most striking change has been the decrease in chla concentration during the spring bloom. 3. Mean chlorophyll a concentration was 17% higher in Lake Michigan than in Lake Huron, and total production for 2008 in Lake Michigan (9.5 tg year 1 ) was 10% greater than in Lake Huron (7.8 tg year 1 ), even though Lake Michigan is slightly smaller (by 3%) than Lake Huron. Differences between the lakes in the early 1970s evidently persisted to 2008. 4. Invasive mussels influenced temporal trends in spring chla and annual primary production. However, TP had a greater effect on chla and primary production than did the mussels, and TP varied independently from them. Two climatic variables (precipitation and air temperature in the basins) influenced annual chla and annual PP, while the extent of ice cover influenced TP but not chla or primary production. Our results demonstrate that observed temporal patterns in chla and PP are the result of complex interactions of P, climate and invasive mussels.

Freshwater Biology↗

USGS2008

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

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

Environmental & Engineering Geoscience↗

USGS2013

National Satellite Land Remote Sensing Data Archive

The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

Fact Sheet↗

USGS2021

Rangeland fractional components across the western United States from 1985 to 2018

Monitoring temporal dynamics of rangelands to detect and understand change in vegetation cover and composition provides a wealth of information to improve management and sustainability. Remote sensing allows the evaluation of both abrupt and gradual rangeland change at unprecedented spatial and temporal extents. Here, we describe the production of the National Land Cover Database (NLCD) Back in Time (BIT) dataset which quantified the percent cover of rangeland components (bare ground, herbaceous, annual herbaceous, litter, shrub, and sagebrush ( Artemisia spp. Nutt.) across the western United States using Landsat imagery from 1985 to 2018. We evaluate the relationships of component trends with climate drivers at an ecoregion scale, describe the nature of landscape change, and demonstrate several case studies related to changes in grazing management, prescribed burns, and vegetation treatments. Our results showed the net cover of shrub, sagebrush, and litter significantly ( p < 0.01) decreased, bare ground and herbaceous cover had no significant change, and annual herbaceous cover significantly ( p < 0.05) increased. Change was ubiquitous, with a mean of 92% of pixels with some change and 38% of pixels with significant change ( p < 0.10). However, most change was gradual, well over half of pixels have a range of less than 10%, and most change occurred outside of known disturbances. The BIT data facilitate a comprehensive assessment of rangeland condition, evaluation of past management actions, understanding of system variability, and opportunities for future planning.

Arizona, California, Colorado, Idaho, Kansas, Mont↗

USGS2012

Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km 2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

Biogeosciences↗

USGS2016

Validation of the ASTER Global Digital Elevation Model version 3 over the conterminous United States

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

The International Archives of the Photogrammetry, ↗

USGS2018

A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras

We use simulated images to demonstrate a novel technique for mitigating geometric distortions caused by platform motion (“jitter”) as two-dimensional image sensors are exposed and read out line by line (“rolling shutter”). The results indicate that the Europa Imaging System (EIS) on NASA’s Europa Clipper can likely meet its scientific goals requiring 0.1-pixel precision. We are therefore adapting the software used to demonstrate and test rolling shutter jitter correction to become part of the standard processing pipeline for EIS. The correction method will also apply to other rolling-shutter cameras, provided they have the operational flexibility to read out selected “check lines” at chosen times during the systematic readout of the frame area

The International Archives of the Photogrammetry, ↗

USGS2017

Community tools for cartographic and photogrammetric processing of Mars Express HRSC images

The High Resolution Stereo Camera (HRSC) on the Mars Express orbiter (Neukum et al. 2004) is a multi-line pushbroom scanner that can obtain stereo and color coverage of targets in a single overpass, with pixel scales as small as 10 m at periapsis. Since commencing operations in 2004 it has imaged ~ 77 % of Mars at 20 m/pixel or better. The instrument team uses the Video Image Communication And Retrieval (VICAR) software to produce and archive a range of data products from uncalibrated and radiometrically calibrated images to controlled digital topographic models (DTMs) and orthoimages and regional mosaics of DTM and orthophoto data (Gwinner et al. 2009; 2010b; 2016). Alternatives to this highly effective standard processing pipeline are nevertheless of interest to researchers who do not have access to the full VICAR suite and may wish to make topographic products or perform other (e. g., spectrophotometric) analyses prior to the release of the highest level products. We have therefore developed software to ingest HRSC images and model their geometry in the USGS Integrated Software for Imagers and Spectrometers (ISIS3), which can be used for data preparation, geodetic control, and analysis, and the commercial photogrammetric software SOCET SET (® BAE Systems; Miller and Walker 1993; 1995) which can be used for independent production of DTMs and orthoimages. The initial implementation of this capability utilized the then-current ISIS2 system and the generic pushbroom sensor model of SOCET SET, and was described in the DTM comparison of independent photogrammetric processing by different elements of the HRSC team (Heipke et al. 2007). A major drawback of this prototype was that neither software system then allowed for pushbroom images in which the exposure time changes from line to line. Except at periapsis, HRSC makes such timing changes every few hundred lines to accommodate changes of altitude and velocity in its elliptical orbit. As a result, it was necessary to split observations into blocks of constant exposure time, greatly increasing the effort needed to control the images and collect DTMs. Here, we describe a substantially improved HRSC processing capability that incorporates sensor models with varying line timing in the current ISIS3 system (Sides 2017) and SOCET SET. This enormously reduces the work effort for processing most images and eliminates the artifacts that arose from segmenting them. In addition, the software takes advantage of the continuously evolving capabilities of ISIS3 and the improved image matching module NGATE (Next Generation Automatic Terrain Extraction, incorporating area and feature based algorithms, multi-image and multi-direction matching) of SOCET SET, thus greatly reducing the need for manual editing of DTM errors. We have also developed a procedure for geodetically controlling the images to Mars Orbiter Laser Altimeter (MOLA) data by registering a preliminary stereo topographic model to MOLA by using the point cloud alignment ( pc_align ) function of the NASA Ames Stereo Pipeline (ASP; Moratto et al. 2010). This effectively converts inter-image tiepoints into ground control points in the MOLA coordinate system. The result is improved absolute accuracy and a significant reduction in work effort relative to manual measurement of ground control. The ISIS and ASP software used are freely available; SOCET SET, is a commercial product. By the end of 2017 we expect to have ported our SOCET SET HRSC sensor model to the Community Sensor Model (CSM; Community Sensor Model Working Group 2010; Hare and Kirk 2017) standard utilized by the successor photogrammetric system SOCET GXP that is currently offered by BAE. In early 2018, we are also working with BAE to release the CSM source code under a BSD or MIT open source license.

The International Archives of the Photogrammetry, ↗

USGS2008

Radargrammetry on three planets

Synthetic Aperture Radar (SAR) can provide useful images in situations where passive optical imaging cannot, either because the microwaves used can penetrate atmospheric clouds, because active imaging can "see in the dark," or both. We have participated in the NASA Magellan mission to Venus in the 1990s and the current NASA-ESA Cassini-Huygens mission to Saturn and Titan, which have used SAR to see through the clouds of Venus and Titan, respectively, and have developed software and techniques for the production of digital topographic models (DTMs) from radar stereopairs. We are currently preparing for similar radargrammetric analysis of data from the Mini-RF instrument to be carried to the Moon on both the ISRO Chandrayaan-1 and NASA Lunar Reconnaissance Orbiter (LRO) missions later in 2008. These instruments are intended to image the permanently shadowed areas at the lunar poles and even see below the surface to detect possible water ice deposits. In this paper, we describe our approach to radargrammetric topographic mapping, based on the use of the USGS ISIS software system to ingest and prepare data, and the commercial stereoanalysis software SOCET SET (® BAE Systems), augmented with custom sensor models we have implemented, for DTM production and editing. We describe the commonalities and differences between the various data sets, and some of the lessons learned, both radargrammetric and geoscientific.

The International Archives of the Photogrammetry, ↗

USGS2008

Cartography for lunar exploration: 2008 status and mission plans

The initial spacecraft exploration of the Moon in the 1960s-70s yielded extensive data, primarily in the form of film and television images, which were used to produce a large number of hardcopy maps by conventional techniques. A second era of exploration, beginning in the early 1990s, has produced digital data including global multispectral imagery and altimetry, from which a new generation of digital map products tied to a rapidly evolving global control network has been made. Efforts are also underway to scan the earlier hardcopy maps for online distribution and to digitize the film images so that modern processing techniques can be used to make high-resolution digital terrain models (DTMs) and image mosaics consistent with the current global control. The pace of lunar exploration is accelerating dramatically, with as many as eight new missions already launched or planned for the current decade. These missions, of which the most important for cartography are SMART-1 (Europe), Kaguya/SELENE (Japan), Chang'e-1 (China), Chandrayaan-1 (India), and Lunar Reconnaissance Orbiter (USA), will return a volume of data exceeding that of all previous lunar and planetary missions combined. Framing and scanner camera images, including multispectral and stereo data, hyperspectral images, synthetic aperture radar (SAR) images, and laser altimetry will all be collected, including, in most cases, multiple data sets of each type. Substantial advances in international standardization and cooperation, development of new and more efficient data processing methods, and availability of resources for processing and archiving will all be needed if the next generation of missions are to fulfill their potential for high-precision mapping of the Moon in support of subsequent exploration and scientific investigation.

The International Archives of the Photogrammetry, ↗