Engineering topics

Masek, Jeffrey G.

Publications and source records attributed to Masek, Jeffrey G..

At least 19 records

NASA NTRS2018

The Harmonized Landsat and Sentinel-2 Surface Reflectance Data Set

The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a VirtualConstellation (VC) of surface reflectance (SR) data acquired by the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) aboard Landsat 8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, bidirectional reflectance distribution function normalization and spectral bandpass adjustment. Three products are derivedfrom the HLS processing chain: (i) S10: full resolution MSI SR at 10 m, 20 m and 60 m spatial resolutions; (ii)S30: a 30 m MSI Nadir BRDF (Bidirectional Reflectance Distribution Function)-Adjusted Reflectance (NBAR);(iii) L30: a 30 m OLI NBAR. All three products are processed for every Level-1 input products from Landsat 8/OLI (L1T) and Sentinel-2/MSI (L1C). As of version 1.3, the HLS data set covers 10.35 million km2 and spans from first Landsat 8 data (2013); Sentinel-2 data spans from October 2015. The L30 and S30 show a good consistency with coarse spatial resolution products, in particular MODIS Collection 6 MCD09CMG products (overall deviations do not exceed 11%) that are used as a reference for quality assurance. The spatial co-registration of the HLS is improved compared to original Landsat 8 L1T and Sentinel 2A L1C products, for which misregistration issues between multi-temporal data are known. In particular, the resulting computed circular errors at 90% for the HLS product are 6.2 m and 18.8 m, for S10 and L30 products, respectively. The main known issue of the current data set remains the Sentinel-2 cloud mask with many cloud detection omissions. The cross-comparison with MODIS was used to flag products with most evident non-detected clouds. A time series outlier filtering approach is suggested to detect remaining clouds. Finally, several time series are presented to highlight the high potential of the HLS data set for crop monitoring.

Landsat Sentinel-2↗

NASA NTRS2017

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

Many land applications require more frequent observations than can be obtained from a single 'Landsat class' sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Reflectance↗

NASA NTRS2017

Disturbance Distance: Quantifying Forests' Vulnerability to Disturbance Under Current and Future Conditions

Disturbances, both natural and anthropogenic, are critical determinants of forest structure, function, and distribution. The vulnerability of forests to potential changes in disturbance rates remains largely unknown. Here, we developed a framework for quantifying and mapping the vulnerability of forests to changes in disturbance rates. By comparing recent estimates of observed forest disturbance rates over a sample of contiguous US forests to modeled rates of disturbance resulting in forest loss, a novel index of vulnerability, Disturbance Distance, was produced. Sample results indicate that 20% of current US forestland could be lost if disturbance rates were to double, with southwestern forests showing highest vulnerability. Under a future climate scenario, the majority of US forests showed capabilities of withstanding higher rates of disturbance then under the current climate scenario, which may buffer some impacts of intensified forest disturbance.

Dolan, Katelyn A.↗

NASA NTRS2016

The Sentinel-2 MSI Can Increase the Temporal Resolution of 30m Satellite-Derived LAI Estimates

The successful launch of the European Space Agency (ESA) Sentinel-2A (S2-A) on 23 June 2015 with its MultiSpectral Instrument (MSI) provides an important means to augment Earth-observation capabilities following the legacy of Landsat. After the three-month satellite commissioning campaign, the MSI onboard S-2A is performing very well (ESA, 2015). By 3 December 2015, the sensor data records have achieved provisional maturity status and have been accessed in level-1C Top-Of-Atmosphere (TOA) reflectance by the remote sensing community worldwide. Near-nadir observations by the MSI onboard S-2A and the Operational Land Imager (OLI) onboard Landsat 8 were collected during Simultaneous Nadir Overpasses as well as nearly coincident overpasses. This paper presents a processing chain using harmonized S-2A MSI and Landsat 8 OLI sensors to obtain increased temporal resolution in Leaf Area Index (LAI) estimates using the red-edge band B8A of MSI to replace the NIR band B08. Results demonstrate that LAI estimates from the MSI and OLI are comparable, and, given sufficient preprocessing for atmospheric correction and geometric rectification, can be used interchangeably to improve the frequency with which low LAI canopies can be monitored.

Dungan, Jennifer L.↗

NASA NTRS2016

Landsat 9: Status and Plans

The Landsat 9 mission, currently under development and proceeding towards a targeted launch in late 2020, will be very similar to the Landsat 8 mission, launched in 2013. Like Landsat 8, Landsat 9 is a joint effort between NASA and USGS with two sensors, the Operational Land Imager 2 (OLI-2), essentially a copy of the OLI on Landsat 8 and the Thermal Infrared Sensor 2 (TIRS-2), very similar to the TIRS on Landsat 8. The OLI-2, like OLI, provides 14-bit image data, though for Landsat 9, all 14 bits will be retained and transmitted to the ground. The focal plane modules to be used for OLI-2 were flight spares for OLI and are currently being retested by Ball Aerospace. Results indicate radiometric performance comparable to OLI. The TIRS was a class C instrument, with a 3-year design lifetime, and therefore had limited redundancy. TIRS-2 will be a class B instrument, with a 5-year design lifetime, like OLI (and OLI-2), necessitating design changes to increase redundancy. The stray light and Scene Select Mechanism (SSM) encoder problems observed on orbit with TIRS have also instigated a few design changes to TIRS-2. Stray light analysis and testing have indicated that additional baffles in the TIRS-2 optical system will suppress the out-of-field response. The SSM encoder problems have not been definitively traced to a route cause, though conductive anodic filament growth in the circuit boards is suspected. Improved designs for the encoder are being considered for TIRS-2. The spare Focal Plane Array (FPA) from TIRS is planned for use in TIRS-2; FPA spectral and radiometric performance testing is scheduled for September of this year at NASA's Goddard Space Flight Center.

Landsat↗

NASA NTRS2016

Landsat Program

Landsat initiated the revolution in moderate resolution Earth remote sensing in the 1970s. With seven successful missions over 40+ years, Landsat has documented - and continues to document - the global Earth land surface and its evolution. The Landsat missions and sensors have evolved along with the technology from a demonstration project in the analog world of visual interpretation to an operational mission in the digital world, with incremental improvements along the way in terms of spectral, spatial, radiometric and geometric performance as well as acquisition strategy, data availability, and products.

calibration↗

NASA NTRS2016

Disturbance and the Carbon Balance of US Forests: A Quantitative Review of Impacts from Harvests, Fires, Insects, and Droughts

Disturbances are a major determinant of forest carbon stocks and uptake. They generally reduce land carbon stocks but also initiate a regrowth legacy that contributes substantially to the contemporary rate of carbon stock increase in US forestlands. As managers and policy makers increasingly look to forests for climate protection and mitigation, and because of increasing concern about changes in disturbance intensity and frequency, there is a need for synthesis and integration of current understanding about the role of disturbances and other processes in governing forest carbon cycle dynamics, and the likely future of this and other sinks for atmospheric carbon. This paper aims to address that need by providing a quantitative review of the distribution, extent and carbon impacts of the major disturbances active in the US. We also review recent trends in disturbances, climate, and other global environmental changes and consider their individual and collective contributions to the US carbon budget now and in the likely future. Lastly, we identify some key challenges and opportunities for future research needed to improve current understanding, advance predictive capabilities, and inform forest management in the face of these pressures. Harvest is found to be the most extensive disturbance both in terms of area and carbon impacts, followed by fire, windthrow and bark beetles, and lastly droughts. Collectively these lead to the gross loss of about 200 Tg C y(exp -1) in live biomass annually across the conterminous US. At the same time, the net change in forest carbon stocks is positive (190 Tg C y(exp -1)), indicating not only forest resilience but also an apparently large response to growth enhancements such as fertilization by CO2 and nitrogen. Uncertainty about disturbance legacies, disturbance interactions, likely trends, and global change factors make the future of the US forest carbon sink unclear. While there is scope for management to enhance carbon sinks in US forests, tradeoffs with other values and uses are likely to significantly limit practical implementation. Continued and expanded remote sensing and field-based monitoring capabilities and manipulative experimentation are needed to improve understanding of the US forest carbon sink, and assess how disturbance processes are responding to the pressures of global environmental change. In addition, continued development and application of holistic, decision support tools that consider a range of forest values are needed to enable managers and policy makers to use the best available information for guiding forest resources now and into the future.

Williams, Christopher A.↗

NASA NTRS2016

The Vegetation Greenness Trend in Canada and US Alaska from 1984-2012 Landsat Data

To assess the North American high-latitude vegetation response to the rising temperature, we derived NDVI end for 91.2% of the non-water, non-snow land area of Canada and Alaska using the peak-summer Landsat surface reflectance data of 19842012. Our analysis indicated that 29.4% and 2.9 of the land area of Canada and Alaska showed statistically significant positive (greening) and negative (browning) trends respectively, at significance level p b 0.01, after burned forest areas were masked out. The area with greening trend dominated over that with browning trend for all land cover types. The greening occurred primarily in the tundra of western Alaska, along the north coast of Canada and in northeastern Canada; the most intensive and extensive greening occurred in Quebec and Labrador. The browning occurred mostly in the boreal forests of eastern Alaska. The Landsat-based greenness trend is broadly similar to the 8-km GIMMS AVHRR-based trend for all vegetation zones. However, for tundra, the Landsat data indicated much less extensive greening in Alaska North Slope and much more extensive greening in Quebec and Labrador, and substantially less extensive browning trend in the boreal forests that were free of fire disturbances. These differences call for further validation of the Landsat reflectance and the AVHRR NDVI datasets. Correlation study with local environmental factors, such as topography, glacial history and soil condition, will be needed to understand the heterogeneous greenness change at the Landsat scale.

Ju, Junchang↗

NASA NTRS2015

Regional Rates of Young US Forest Growth Estimated From Annual Landsat Disturbance History and IKONOS Stereo Imagery

Forests of the Contiguous United States (CONUS) have been found to be a large contributor to the global atmospheric carbon sink. The magnitude and nature of this sink is still uncertain and recent studies have sought to define the dynamics that control its strength and longevity. The Landsat series of satellites has been a vital resource to understand the long-term changes in land cover that can impact ecosystem function and terrestrial carbonstock. We combine annual Landsat forest disturbance history from 1985 to 2011 with single date IKONOS stereoimagery to estimate the change in young forest canopy height and above ground live dry biomass accumulation for selected sites in the CONUS. Our approach follows an approximately linear growth rate following clearing over short intervals and does not estimate the distinct non-linear growth rate over longer intervals.We produced canopy height models by differencing digital surface models estimated from IKONOS stereo pairs with national elevation data (NED). Correlations between height and biomass were established independently using airborne LiDAR, and then applied to the IKONOS-estimated canopy height models. Graphing current biomass against time since disturbance provided biomass accumulation rates. For 20 study sites distributed across five regions of the CONUS, 19 showed statistically significant recovery trends (p is less than 0.001) with canopy growth from 0.26 m yr-1to 0.73 m yr-1. Above ground live dry biomass (AGB) density accumulation ranged from 1.31 t/ha yr-1 to 12.47 t/ha yr-1. Mean forest AGB accumulationwas 6.31 t/ha yr-1 among all sites with significant growth trends. We evaluated the accuracy of our estimates by comparing to field estimated site index curves of growth, airborne LiDAR data, and independent model predictions of C accumulation. Growth estimates found with this approach are consistent with site index curves and total biomass estimates fall within the range of field estimates. This is aviable approach to estimate forest biomass accumulation in regions with clear-cut harvest disturbances.

Neigh, Christopher S. R.↗

NASA NTRS2014

Deciphering the Precision of Stereo IKONOS Canopy Height Models for U.S. Forests with G-LiHT Airborne LiDAR

Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR) data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs) and height data derived from Goddard's airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT) with three types of IKONOS stereo derived digital surface models (DSMs) that estimate CHMs by subtracting National Elevation Data (NED) digital terrain models (DTMs). We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1) G-LiHT DTMs were highly correlated with NED DTMs with R (sup 2) greater than 0.98 and root mean square errors (RMSEs) less than 2.96 m; (2) when using one visually identifiable ground control point (GCP) from NED, G-LiHT DSMs and IKONOS DSMs had R (sup 2) greater than 0.84 and RMSEs of 2.7 to 4.1 m; and (3) one GCP CHMs for two study sites had R (sup 2) greater than 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

IKONOS↗

NASA NTRS2014

An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface Reflectance and MODIS-based A Priori Anisotropy Knowledge

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "MODIS-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a "pre-MODIS era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT reflects a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from MODIS observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir reflectance ratios as a bridge between the Landsat and MODIS scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach respectively with that from the "concurrent" approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the "pre-MODIS era" LUT approach is highly consistent (R(exp 2) = 0.988, the scene-averaged low RMSE = 0.009 and bias = −0.005) with that generated by the earlier "concurrent" approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the "pre-MODIS" LUT and "concurrent" approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.

Albedo algorithm↗

NASA NTRS2013

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing U.S. land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha/yr of forests were disturbed annually, representing 1.09%/yr of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, while variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic since the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy.

Masek, Jeffrey G.↗

NASA NTRS2013

High-Resolution Satellite Data Open for Government Research

U.S. satellite commercial imagery (CI) with resolution less than 1 meter is a common geospatial reference used by the public through Web applications, mobile devices, and the news media. However, CI use in the scientific community has not kept pace, even though those who are performing U.S. government research have access to these data at no cost.Previously, studies using multiple CI acquisitions from IKONOS-2, Quickbird-2, GeoEye-1, WorldView-1, and WorldView-2 would have been cost prohibitive. Now, with near-global submeter coverage and online distribution, opportunities abound for future scientific studies. This archive is already quite extensive (examples are shown in Figure 1) and is being used in many novel applications.

Data↗

NASA NTRS2013

Use of In Situ and Airborne Multiangle Data to Assess MODIS and Landsat-Based Estimates of Directional Reflectance and Albedo

The quantification of uncertainty in satellite-derived global surface albedo products is a critical aspect in producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A challenge in validating albedo measurements acquired from space is the ability to overcome the spatial scaling errors that can produce disagreements between satellite and field-measured values. Here, we present the results from an accuracy assessment of MODIS and Landsat-TM albedo retrievals, based on collocated comparisons with tower and airborne Cloud Absorption Radiometer (CAR) measurements collected during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC). The initial focus was on evaluating intersensor consistency through comparisons of intrinsic bidirectional reflectance estimates. Local and regional assessments were then performed to obtain estimates of the resulting scaling uncertainties, and to establish the accuracy of albedo reconstructions during extended periods of precipitation. In general, the satellite derived estimates met the accuracy requirements established for the high-quality MODIS operational albedos at 500 m (the greater of 0.02 units or +/-10% of surface measured values). However, results reveal a high degree of variability in the root-mean-square error (RMSE) and bias of MODIS visible (0.3-0.7 μm) and Landsat-TM shortwave (0.3-5.0 μm) albedos; where, in some cases, retrieval uncertainties were found to be in excess of 15%. Results suggest that an overall improvement in MODIS shortwave albedo retrieval accuracy of 7.8%, based on comparisons between MODIS and CAR albedos, resulted from the removal of sub-grid scale mismatch errors when directly scaling-up the tower measurements to the MODIS satellite footprint.

biosphere↗

NASA NTRS2012

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

Gao, Feng↗

NASA NTRS2012

Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and Challenges

The compilation of global Landsat data-sets and the ever-lowering costs of computing now make it feasible to monitor the Earth's land cover at Landsat resolutions of 30 m. In this article, we describe the methods to create global products of forest cover and cover change at Landsat resolutions. Nevertheless, there are many challenges in ensuring the creation of high-quality products. And we propose various ways in which the challenges can be overcome. Among the challenges are the need for atmospheric correction, incorrect calibration coefficients in some of the data-sets, the different phenologies between compilations, the need for terrain correction, the lack of consistent reference data for training and accuracy assessment, and the need for highly automated characterization and change detection. We propose and evaluate the creation and use of surface reflectance products, improved selection of scenes to reduce phenological differences, terrain illumination correction, automated training selection, and the use of information extraction procedures robust to errors in training data along with several other issues. At several stages we use Moderate Resolution Spectroradiometer data and products to assist our analysis. A global working prototype product of forest cover and forest cover change is included.

Global↗

NASA NTRS2012

Landsat Data Continuity Mission - Launch Fever

The year 2013 will be an exciting period for those that study the Earth land surface from space, particularly those that observe and characterize land cover, land use, and the change of cover and use over time. Two new satellite observatories will be launched next year that will enhance capabilities for observing the global land surface. The United States plans to launch the Landsat Data Continuity Mission (LDCM) in January. That event will be followed later in the year by the European Space Agency (ESA) launch of the first Sentinel 2 satellite. Considered together, the two satellites will increase the frequency of opportunities for viewing the land surface at a scale where human impact and influence can be differentiated from natural change. Data from the two satellites will provide images for similar spectral bands and for comparable spatial resolutions with rigorous attention to calibration that will facilitate cross comparisons. This presentation will provide an overview of the LDCM satellite system and report its readiness for the January launch.

Irons, James R.↗

NASA NTRS2012

Landsat Science: 40 Years of Innovation and Opportunity

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Cook, Bruce D.↗