Landsat's international partners

Science.gov (United States)

Byrnes, Raymond A.

2012-01-01

Since the launch of the first Landsat satellite 40 years ago, International Cooperators (ICs) have formed a key strategic alliance with the U.S. Geological Survey (USGS) to not only engage in Landsat data downlink services but also to enable a foundation for scientific and technical collaboration. The map below shows the locations of all ground stations operated by the United States and IC ground station network for the direct downlink and distribution of Landsat 5 (L5) and Landsat 7 (L7) image data. The circles show the approximate area over which each station has the capability for direct reception of Landsat data. The red circles show the components of the L5 ground station network, the green circles show components of the L7 station network, and the dashed circles show stations with dual (L5 and L7) status. The yellow circles show L5 short-term ("campaign") stations that contribute to the USGS Landsat archive. Ground stations in South Dakota and Australia currently serve as the primary data capture facilities for the USGS Landsat Ground Network (LGN). The Landsat Ground Station (LGS) is located at the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The Alice Springs (ASN) ground station is located at the Geoscience Australia facility in Alice Springs, Australia. These sites receive the image data, via X-band Radio Frequency (RF) link, and the spacecraft housekeeping data, via S-band RF link. LGS also provides tracking services and a command link to the spacecrafts.

Landsat Program

Science.gov (United States)

Markham, Brian L.; Arvidson, Terry; Barsi, Julia A.; Choate, Michael; Kaita, Edward; Levy, Raviv; Lubke, Mark; Masek, Jeffrey G.

2016-01-01

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.

A preliminary study of the feasibility of detecting the floating macrophytes by means of digital processing of MSS/LANDSAT data

Science.gov (United States)

Valeriano, D. D. (Principal Investigator)

1984-01-01

The feasibility of mapping the floating macrophytes (mostly water hyacinth: (Eichornia crassipes) in the Salto Grande reservoir in Americana, SP, by means of digital processing of MSS/LANDSAT data is described. The area occupied by the macrophytes was extracted by exclusion after the merging of two thematic masks representing the area of vegetation free water surface. One of the masks was obtained from a date when the vegetal cover is insignificant, while the other represents a large infestation episode. The utilization of digital processing of MSS/LANDSAT data techniques for the documentation of macrophytes infestation is feasible only when the phenomenon occurs in large areas.

Development of coal partial hydropyrolysis process

Energy Technology Data Exchange (ETDEWEB)

Hideaki Yabe; Takafumi Kawamura; Kohichiroh Gotoh; Akemitsu Akimoto [Nippon Steel Corporation, Chiba (Japan)

2005-07-01

Coal partial hydropyrolysis process aims at co-production of high yield of light oil such as BTX and naphthalene and synthesis gas from a low rank coal under a mild hydropyrolysis condition. The characteristic of this process is in the two-staged entrained hydropyrolysis reactor composed of the reformer and gasifier. This reactor arrangement gives us high heat efficiency of this process. So far, in order to evaluate the process concept a small-scale basic experiment and a 1t/day process development unit study were carried out. The experimental results showed that coal volatiles were partially hydrogenated to increase the light oil and hydrocarbon gases at the condition of partial hydropyrolysis such as pressure of 2-3MPa, temperature of 700-900{sup o}C and hydrogen concentration of 30-50%. This process has a possibility of producing efficiently and economically liquid and gas products as chemicals and fuel for power generation. As a further development in the period of 2003 to 2008, a 20t/day pilot plant study named ECOPRO (efficient co-production with coal flash hydropyrolysis technology) has been started to establish the process technologies for commercialization. 12 refs., 6 figs., 3 tabs.

Landsat 8 Data Modeled as DGGS Data Cubes

Science.gov (United States)

Sherlock, M. J.; Tripathi, G.; Samavati, F.

2016-12-01

In the context of tracking recent global changes in the Earth's landscape, Landsat 8 provides high-resolution multi-wavelength data with a temporal resolution of sixteen days. Such a live dataset can benefit novel applications in environmental monitoring. However, a temporal analysis of this dataset in its native format is a challenging task mostly due to the huge volume of geospatial images and imperfect overlay of different day Landsat 8 images. We propose the creation of data cubes derived from Landsat 8 data, through the use of a Discrete Global Grid System (DGGS). DGGS referencing of Landsat 8 data provides a cell-based representation of the pixel values for a fixed area on earth, indexed by keys. Having the calibrated cell-based Landsat 8 images can speed up temporal analysis and facilitate parallel processing using distributed systems. In our method, the Landsat 8 dataset hosted on Amazon Web Services (AWS) is downloaded using a web crawler and stored on a filesystem. We apply the cell-based DGGS referencing (using Pyxis SDK) to Landsat 8 images which provide a rhombus based tessellation of equal area cells for our use-case. After this step, the cell-images which overlay perfectly on different days, are stacked in the temporal dimension and stored into data cube units. The depth of the cube represents the number of temporal images of the same cell and can be updated when new images are received each day. Harnessing the regular spatio-temporal structure of data cubes, we want to compress, query, transmit and visualize big Landsat 8 data in an efficient way for temporal analysis.

Automated Agricultural Field Extraction from Multi-temporal Web Enabled Landsat Data

Science.gov (United States)

Yan, L.; Roy, D. P.

2012-12-01

Agriculture has caused significant anthropogenic surface change. In many regions agricultural field sizes may be increasing to maximize yields and reduce costs resulting in decreased landscape spatial complexity and increased homogenization of land uses with potential for significant biogeochemical and ecological effects. To date, studies of the incidence, drivers and impacts of changing field sizes have not been undertaken over large areas because of computational constraints and because consistently processed appropriate resolution data have not been available or affordable. The Landsat series of satellites provides near-global coverage, long term, and appropriate spatial resolution (30m) satellite data to document changing field sizes. The recent free availability of all the Landsat data in the U.S. Landsat archive now provides the opportunity to study field size changes in a global and consistent way. Commercial software can be used to extract fields from Landsat data but are inappropriate for large area application because they require considerable human interaction. This paper presents research to develop and validate an automated computational Geographic Object Based Image Analysis methodology to extract agricultural fields and derive field sizes from Web Enabled Landsat Data (WELD) (http://weld.cr.usgs.gov/). WELD weekly products (30m reflectance and brightness temperature) are classified into Satellite Image Automatic Mapper™ (SIAM™) spectral categories and an edge intensity map and a map of the probability of each pixel being agricultural are derived from five years of 52 weeks of WELD and corresponding SIAM™ data. These data are fused to derive candidate agriculture field segments using a variational region-based geometric active contour model. Geometry-based algorithms are used to decompose connected segments belonging to multiple fields into coherent isolated field objects with a divide and conquer strategy to detect and merge partial circle

Exploration for porphyry copper deposits in Pakistan using digital processing of Landsat-1 data

Science.gov (United States)

Schmidt, R. G.

1976-01-01

Rock-type classification by digital-computer processing of Landsat-1 multispectral scanner data has been used to select 23 prospecting targets in the Chagai District, Pakistan, five of which have proved to be large areas of hydrothermally altered porphyry containing pyrite. Empirical maximum and minimum apparent reflectance limits were selected for each multispectral scanner band in each rock type classified, and a relatively unrefined classification table was prepared. Where the values for all four bands fitted within the limits designated for a particular class, a symbol for the presumed rock type was printed by the computer at the appropriate location. Drainage channels, areas of mineralized quartz diorite, areas of pyrite-rich rock, and the approximate limit of propylitic alteration were very well delineated on the computer-generated map of the test area. The classification method was used to evaluate 2,100 sq km in the Mashki Chah region. The results of the experiment show that outcrops of hydrothermally altered and mineralized rock can be identified from Landsat-1 data under favorable conditions.

Requirements, Science, and Measurements for Landsat 10 and Beyond: Perspectives from the Landsat Science Team

Science.gov (United States)

Crawford, C. J.; Masek, J. G.; Roy, D. P.; Woodcock, C. E.; Wulder, M. A.

2017-12-01

The U.S. Geological Survey (USGS) and NASA are currently prioritizing requirements and investing in technology options for a "Landsat 10 and beyond" mission concept as part of the Sustainable Land Imaging (SLI) architecture. Following the successful February 2013 launch of the Landsat 8, the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) have now added over 1 million images to the USGS Landsat archive. The USGS and NASA support and co-lead a Landsat Science Team made up largely of university and government experts to offer independent insight and guidance of program activities and directions. The rapid development of Landsat 9 reflects, in part, strong input from the 2012-2017 USGS Landsat Science Team (LST). During the last two years of the LST's tenure, individual LST members and within LST team working groups have made significant contributions to Landsat 10 and beyond's science traceability and future requirements justification. Central to this input, has been an effort to identify a trade space for enhanced measurement capabilities that maintains mission continuity with eight prior multispectral instruments, and will extend the Landsat Earth observation record beyond 55+ years with an approximate launch date of 2027. The trade space is framed by four fundamental principles in remote sensing theory and practice: (1) temporal resolution, (2) spatial resolution, (3) radiometric resolution, and (4) spectral coverage and resolution. The goal of this communication is to provide a synopsis of past and present 2012-2017 LST contributions to Landsat 10 and beyond measurement science and application priorities. A particular focus will be to document the links between new science and societal benefit areas with potential technical enhancements to the Landsat mission.

Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

Science.gov (United States)

Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric; Masek, Jeffrey G.; Townshend, John R.

2012-01-01

Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

Landsat and water: case studies of the uses and benefits of landsat imagery in water resources

Science.gov (United States)

Serbina, Larisa O.; Miller, Holly M.

2014-01-01

The Landsat program has been collecting and archiving moderate resolution earth imagery since 1972. The number of Landsat users and uses has increased exponentially since the enactment of a free and open data policy in 2008, which made data available free of charge to all users. Benefits from the information Landsat data provides vary from improving environmental quality to protecting public health and safety and informing decision makers such as consumers and producers, government officials and the public at large. Although some studies have been conducted, little is known about the total benefit provided by open access Landsat imagery. This report contains a set of case studies focused on the uses and benefits of Landsat imagery. The purpose of these is to shed more light on the benefits accrued from Landsat imagery and to gain a better understanding of the program’s value. The case studies tell a story of how Landsat imagery is used and what its value is to different private and public entities. Most of the case studies focus on the use of Landsat in water resource management, although some other content areas are included.

Continuous Calibration Improvement in Solar Reflective Bands: Landsat 5 Through Landsat 8

Science.gov (United States)

Mishra, Nischal; Helder, Dennis; Barsi, Julia; Markham, Brian

2016-01-01

Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too.

Landsat-8: Science and product vision for terrestrial global change research

Science.gov (United States)

Roy, David P.; Wulder, M.A.; Loveland, Thomas R.; Woodcock, C.E.; Allen, R. G.; Anderson, M. C.; Helder, D.; Irons, J.R.; Johnson, D.M.; Kennedy, R.; Scambos, T.A.; Schaaf, Crystal B.; Schott, J.R.; Sheng, Y.; Vermote, E. F.; Belward, A.S.; Bindschadler, R.; Cohen, W.B.; Gao, F.; Hipple, J. D.; Hostert, Patrick; Huntington, J.; Justice, C.O.; Kilic, A.; Kovalskyy, Valeriy; Lee, Z. P.; Lymburner, Leo; Masek, J.G.; McCorkel, J.; Shuai, Y.; Trezza, R.; Vogelmann, James; Wynne, R.H.; Zhu, Z.

2014-01-01

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Continuous fields of land cover for the conterminous United States using Landsat data: First results from the Web-Enabled Landsat Data (WELD) project

Science.gov (United States)

Hansen, M.C.; Egorov, Alexey; Roy, David P.; Potapov, P.; Ju, J.; Turubanova, S.; Kommareddy, I.; Loveland, Thomas R.

2011-01-01

Vegetation Continuous Field (VCF) layers of 30 m percent tree cover, bare ground, other vegetation and probability of water were derived for the conterminous United States (CONUS) using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data sets from the Web-Enabled Landsat Data (WELD) project. Turnkey approaches to land cover characterization were enabled due to the systematic WELD Landsat processing, including conversion of digital numbers to calibrated top of atmosphere reflectance and brightness temperature, cloud masking, reprojection into a continental map projection and temporal compositing. Annual, seasonal and monthly WELD composites for 2008 were used as spectral inputs to a bagged regression and classification tree procedure using a large training data set derived from very high spatial resolution imagery and available ancillary data. The results illustrate the ability to perform Landsat land cover characterizations at continental scales that are internally consistent while retaining local spatial and thematic detail.

From Landsat through SLI: Ball Aerospace Instrument Architecture for Earth Surface Monitoring

Science.gov (United States)

Wamsley, P. R.; Gilmore, A. S.; Malone, K. J.; Kampe, T. U.; Good, W. S.

2017-12-01

The Landsat legacy spans more than forty years of moderate resolution, multi-spectral imaging of the Earth's surface. Applications for Landsat data include global environmental change, disaster planning and recovery, crop and natural resource management, and glaciology. In recent years, coastal water science has been greatly enhanced by the outstanding on-orbit performance of Landsat 8. Ball Aerospace designed and built the Operational Land Imager (OLI) instrument on Landsat 8, and is in the process of building OLI 2 for Landsat 9. Both of these instruments have the same design however improved performance is expected from OLI 2 due to greater image bit depth (14 bit on OLI 2 vs 12 bit on OLI). Ball Aerospace is currently working on two novel instrument architectures applicable to Sustainable Land Imaging for Landsat 10 and beyond. With increased budget constraints probable for future missions, technological improvements must be included in future instrument architectures to enable increased capabilities at lower cost. Ball presents the instrument architectures and associated capabilities enabling new science in past, current, and future Landsat missions.

Landsat Science Team meeting: Winter 2015

Science.gov (United States)

Schroeder, Todd A.; Loveland, Thomas; Wulder, Michael A.; Irons, James R.

2015-01-01

The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023.With over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at landsat.usgs.gov/science_LST_Team_ Meetings.php.

Continuity of Landsat observations: Short term considerations

Science.gov (United States)

Wulder, Michael A.; White, Joanne C.; Masek, Jeffery G.; Dwyer, John L.; Roy, David P.

2011-01-01

As of writing in mid-2010, both Landsat-5 and -7 continue to function, with sufficient fuel to enable data collection until the launch of the Landsat Data Continuity Mission (LDCM) scheduled for December of 2012. Failure of one or both of Landsat-5 or -7 may result in a lack of Landsat data for a period of time until the 2012 launch. Although the potential risk of a component failure increases the longer the sensor's design life is exceeded, the possible gap in Landsat data acquisition is reduced with each passing day and the risk of Landsat imagery being unavailable diminishes for all except a handful of applications that are particularly data demanding. Advances in Landsat data compositing and fusion are providing opportunities to address issues associated with Landsat-7 SLC-off imagery and to mitigate a potential acquisition gap through the integration of imagery from different sensors. The latter will likely also provide short-term, regional solutions to application-specific needs for the continuity of Landsat-like observations. Our goal in this communication is not to minimize the community's concerns regarding a gap in Landsat observations, but rather to clarify how the current situation has evolved and provide an up-to-date understanding of the circumstances, implications, and mitigation options related to a potential gap in the Landsat data record.

Thermal Infrared Radiometric Calibration of the Entire Landsat 4, 5, and 7 Archive (1982-2010)

Science.gov (United States)

Schott, John R.; Hook, Simon J.; Barsi, Julia A.; Markham, Brian L.; Miller, Jonathan; Padula, Francis P.; Raqueno, Nina G.

2012-01-01

Landsat's continuing record of the thermal state of the earth's surface represents the only long term (1982 to the present) global record with spatial scales appropriate for human scale studies (i.e., tens of meters). Temperature drives many of the physical and biological processes that impact the global and local environment. As our knowledge of, and interest in, the role of temperature on these processes have grown, the value of Landsat data to monitor trends and process has also grown. The value of the Landsat thermal data archive will continue to grow as we develop more effective ways to study the long term processes and trends affecting the planet. However, in order to take proper advantage of the thermal data, we need to be able to convert the data to surface temperatures. A critical step in this process is to have the entire archive completely and consistently calibrated into absolute radiance so that it can be atmospherically compensated to surface leaving radiance and then to surface radiometric temperature. This paper addresses the methods and procedures that have been used to perform the radiometric calibration of the earliest sizable thermal data set in the archive (Landsat 4 data). The completion of this effort along with the updated calibration of the earlier (1985 1999) Landsat 5 data, also reported here, concludes a comprehensive calibration of the Landsat thermal archive of data from 1982 to the present

LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) is a NASA project to map disturbance, regrowth, and permanent forest conversion...

Landsat eyes help guard the world's forests

Science.gov (United States)

Campbell, Jon

2017-03-03

SummaryThe Landsat program is a joint effort between the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), but the partner agencies have distinct roles. NASA develops remote-sensing instruments and spacecraft, launches satellites, and validates their performance in orbit. The USGS owns and operates Landsat satellites in space and manages their data transmissions, including ground reception, archiving, product generation, and public distribution. In 2008, with support from the U.S. Department of the Interior, the USGS made its Landsat data free to anyone in the world.The current satellites in the Landsat program, Landsat 7 (launched in 1999) and Landsat 8 (launched in 2013), provide complete coverage of the Earth every eight days. A Landsat 9 satellite is scheduled for launch in late 2020.

A fully automatic processing chain to produce Burn Scar Mapping products, using the full Landsat archive over Greece

Science.gov (United States)

Kontoes, Charalampos; Papoutsis, Ioannis; Herekakis, Themistoklis; Michail, Dimitrios; Ieronymidi, Emmanuela

2013-04-01

Remote sensing tools for the accurate, robust and timely assessment of the damages inflicted by forest wildfires provide information that is of paramount importance to public environmental agencies and related stakeholders before, during and after the crisis. The Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens (IAASARS/NOA) has developed a fully automatic single and/or multi date processing chain that takes as input archived Landsat 4, 5 or 7 raw images and produces precise diachronic burnt area polygons and damage assessments over the Greek territory. The methodology consists of three fully automatic stages: 1) the pre-processing stage where the metadata of the raw images are extracted, followed by the application of the LEDAPS software platform for calibration and mask production and the Automated Precise Orthorectification Package, developed by NASA, for image geo-registration and orthorectification, 2) the core-BSM (Burn Scar Mapping) processing stage which incorporates a published classification algorithm based on a series of physical indexes, the application of two filters for noise removal using graph-based techniques and the grouping of pixels classified as burnt to form the appropriate pixels clusters before proceeding to conversion from raster to vector, and 3) the post-processing stage where the products are thematically refined and enriched using auxiliary GIS layers (underlying land cover/use, administrative boundaries, etc.) and human logic/evidence to suppress false alarms and omission errors. The established processing chain has been successfully applied to the entire archive of Landsat imagery over Greece spanning from 1984 to 2012, which has been collected and managed in IAASARS/NOA. The number of full Landsat frames that were subject of process in the framework of the study was 415. These burn scar mapping products are generated for the first time to such a temporal and spatial

Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

Science.gov (United States)

Wilson, Michael J.; Oreopoulos, Lazarous

2011-01-01

The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production

Science.gov (United States)

Leslie, Colin R.; Serbina, Larisa O.; Miller, Holly M.

2017-03-29

Executive SummaryThe use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management.  Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:Estimating Crop Production.—Provides an overview of how Landsat satellite imagery is used to estimate crop production, including the spectral bands most frequently utilized in this application.Monitoring Consumptive Water Use.—Highlights the role of Landsat imagery in monitoring consumptive water use for agricultural production. Globally, a significant amount of agricultural production relies on irrigation, so monitoring water resources is a critical component of agricultural monitoring. National Agricultural Statistics Service—Cropland Data Layer.—Highlights the use of Landsat imagery in developing the annual Cropland Data Layer, a crop-specific land cover classification product that provides information on more than 100 crop categories grown in the United States. Foreign Agricultural Service—Global Agricultural Monitoring.—Highlights Landsat’s role in monitoring global agricultural

Applications of LANDSAT data to the integrated economic development of Mindoro, Phillipines

Science.gov (United States)

Wagner, T. W.; Fernandez, J. C.

1977-01-01

LANDSAT data is seen as providing essential up-to-date resource information for the planning process. LANDSAT data of Mindoro Island in the Philippines was processed to provide thematic maps showing patterns of agriculture, forest cover, terrain, wetlands and water turbidity. A hybrid approach using both supervised and unsupervised classification techniques resulted in 30 different scene classes which were subsequently color-coded and mapped at a scale of 1:250,000. In addition, intensive image analysis is being carried out in evaluating the images. The images, maps, and aerial statistics are being used to provide data to seven technical departments in planning the economic development of Mindoro. Multispectral aircraft imagery was collected to compliment the application of LANDSAT data and validate the classification results.

Landsat Data Continuity Mission (LDCM) Standard Product Generation and Characteristics

Science.gov (United States)

Micijevic, E.; Hayes, R.

2012-12-01

The LDCM's Landsat 8 (L8), planned for launch in February 2013, is the latest satellite in the 40 year history of the Landsat program. The satellite will have two imagers: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The data from both sensors will be processed and combined into the final Level 1 Terrain (L1T) standard product by the Landsat Product Generation System (LPGS) at the USGS Earth Resources Observation and Science (EROS). Landsat 8 products will nominally have 11 image bands; however, products will still be created if OLI only, or TIRS only collections are acquired. The LPGS is designed to create L1T products from Level 0 data by merging OLI and TIRS outputs and performing systematic radiometric and geometric corrections, followed by precision and terrain corrections that include Ground Control Points (GCP), and a Digital Elevation Model (DEM) for topographic accuracy. Scenes that have a quality score of 9 or greater and a percent cloud cover less than 40 will be automatically processed. In addition, any archived scene, regardless of cloud cover, can be requested for processing through USGS EROS clients, GloVis or Earth Explorer. While most data will be processed as Level L1T, some scenes will not have ground control or elevation data necessary for precision or terrain correction, respectively. In these cases, the best level of correction will be applied (Level 1G-systematic or Level 1Gt-systematic terrain). The standard Level 1T products will contain scaled Top of Atmosphere (TOA) reflectance data, only for OLI. The conversion between radiance and reflectance within radiometric processing (L1R) will be performed using the band specific coefficients that are proportional to the respective exoatmospheric solar irradiances and the Earth-Sun distance for the scene's acquisition day. The TIRS data will contain scaled at-sensor radiances and no at-sensor brightness temperature or emissivity conversions are planned. For users that

Landsat-8 Sensor Characterization and Calibration

Directory of Open Access Journals (Sweden)

Brian Markham

2015-02-01

Full Text Available Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI is the reflective band sensor and the Thermal Infrared Sensor (TIRS, the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA and United States Geological Survey (USGS cooperated in the development, launch and operation of the Landsat-8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth’s surface over the now 43-year record. [...

Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data.

Science.gov (United States)

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-09-18

Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate daily synthetic Landsat imagery. This algorithm was designed to avoid the limitations of the conditional spatial temporal data fusion approach (STDFA) including the constant window for disaggregation and the sensor difference. An adaptive window size selection method is proposed in this study to select the best window size and moving steps for the disaggregation of coarse pixels. The linear regression method is used to remove the influence of differences in sensor systems using disaggregated mean coarse reflectance by testing and validation in two study areas located in Xinjiang Province, China. The results show that the MSTDFA algorithm can generate daily synthetic Landsat imagery with a high correlation coefficient (R) ranged from 0.646 to 0.986 between synthetic images and the actual observations. We further show that MSTDFA can be applied to 250 m 16-day MODIS MOD13Q1 products and the Landsat Normalized Different Vegetation Index (NDVI) data by generating a synthetic NDVI image highly similar to actual Landsat NDVI observation with a high R of 0.97.

Near Real-Time Browsable Landsat-8 Imagery

Directory of Open Access Journals (Sweden)

Cheng-Chien Liu

2017-01-01

Full Text Available The successful launch and operation of Landsat-8 extends the remarkable 40-year acquisition of space-based land remote-sensing data. To respond quickly to emergency needs, real-time data are directly downlinked to 17 ground stations across the world on a routine basis. With a size of approximately 1 Gb per scene, however, the standard level-1 product provided by these stations is not able to serve the general public. Users would like to browse the most up-to-date and historical images of their regions of interest (ROI at full-resolution from all kinds of devices without the need for tedious data downloading, decompressing, and processing. This paper reports on the Landsat-8 automatic image processing system (L-8 AIPS that incorporates the function of mask developed by United States Geological Survey (USGS, the pan-sharpening technique of spectral summation intensity modulation, the adaptive contrast enhancement technique, as well as the Openlayers and Google Maps/Earth compatible superoverlay technique. Operation of L-8 AIPS enables the most up-to-date Landsat-8 images of Taiwan to be browsed with a clear contrast enhancement regardless of the cloud condition, and in only one hour’s time after receiving the raw data from the USGS Level 1 Product Generation System (LPGS. For any ROI in Taiwan, all historical Landsat-8 images can also be quickly viewed in time series at full resolution (15 m. The debris flow triggered by Typhoon Soudelor (8 August 2015, as well as the barrier lake formed and the large-scale destruction of vegetation after Typhoon Nepartak (7 July 2016, are given as three examples of successful applications to demonstrate that the gap between the user’s needs and the existing Level-1 product from LPGS can be bridged by providing browsable images in near real-time.

Integrating Landsat-derived disturbance maps with FIA inventory data: Applications for state-Level forest resource assessments

Science.gov (United States)

Sonja Oswalt; Chengquan Huang; Hua Shi; James Vogelmann; Zhiliang Zhu; Samuel N. Goward; John Coulston

2009-01-01

Landsat images have been widely used for assessing forest characteristics and dynamics. Recently, significant progress has been made towards indepth exploration of the rich Landsat archive kept by the U.S. Geological Survey to improve our under standing of forest disturbance and recovery processes. In this study, we used Landsat images to map forest disturbances at...

Exploiting Data Intensive Applications on High Performance Computers to Unlock Australia's Landsat Archive

Science.gov (United States)

Purss, Matthew; Lewis, Adam; Edberg, Roger; Ip, Alex; Sixsmith, Joshua; Frankish, Glenn; Chan, Tai; Evans, Ben; Hurst, Lachlan

2013-04-01

Australia's Earth Observation Program has downlinked and archived satellite data acquired under the NASA Landsat mission for the Australian Government since the establishment of the Australian Landsat Station in 1979. Geoscience Australia maintains this archive and produces image products to aid the delivery of government policy objectives. Due to the labor intensive nature of processing of this data there have been few national-scale datasets created to date. To compile any Earth Observation product the historical approach has been to select the required subset of data and process "scene by scene" on an as-needed basis. As data volumes have increased over time, and the demand for the processed data has also grown, it has become increasingly difficult to rapidly produce these products and achieve satisfactory policy outcomes using these historic processing methods. The result is that we have been "drowning in a sea of uncalibrated data" and scientists, policy makers and the public have not been able to realize the full potential of the Australian Landsat Archive and its value is therefore significantly diminished. To overcome this critical issue, the Australian Space Research Program has funded the "Unlocking the Landsat Archive" (ULA) Project from April 2011 to June 2013 to improve the access and utilization of Australia's archive of Landsat data. The ULA Project is a public-private consortium led by Lockheed Martin Australia (LMA) and involving Geoscience Australia (GA), the Victorian Partnership for Advanced Computing (VPAC), the National Computational Infrastructure (NCI) at the Australian National University (ANU) and the Cooperative Research Centre for Spatial Information (CRC-SI). The outputs from the ULA project will become a fundamental component of Australia's eResearch infrastructure, with the Australian Landsat Archive hosted on the NCI and made openly available under a creative commons license. NCI provides access to researchers through significant HPC

Multispectral processing of ERTS-A (LANDSAT) data for uranium exploration in the Wind River Basin, Wyoming: a visible region ratio to enhance surface alteration associated with roll-type uraium deposits. Final report, June 1974--July 1975

International Nuclear Information System (INIS)

Salmon, B.C.; Pillars, W.W.

1975-07-01

The purpose of this report is to document possible detection capabilities of the LANDSAT multispectral scanner data for use in exploration for uranium roll-type deposits. Spectral reflectivity, mineralogy, iron content, and color paramenters were measured for twenty natural surface samples collected from a semiarid region. The relationships of these properties to LANDSAT response-weighted reflectances and to reflectance ratios are discussed. It was found that the single ratio technique of multispectral processing is likely to be sensitive enough to separate hematitic stain, but not limonitic. A combination of the LANDSAT R/sub 5,4/ and R/sub 7,6/ ratios, and a processing technique sensitive to vegetative cover is recommended for detecting areas of limonitic stain. Digital level slicing of LANDSAT R/sub 5,4/ over the Wind River Basin, after geometric correction, resulted in adequate enhancement of Triassic redbeds and lighter red materials, but not for limonitic areas. No recommendations for prospects in the area were made. Information pertaining to techniques of evaluating laboratory reflectance spectra for remote sensing applications, ratio processing, and planimetric correction of LANDSAT data is presented qualitatively

Identification of soil erosion land surfaces by Landsat data analysis and processing

International Nuclear Information System (INIS)

Lo Curzio, S.

2009-01-01

In this paper, we outline the typical relationship between the spectral reflectance of aileron's on newly-formed land surfaces and the geo morphological features of the land surfaces at issue. These latter represent the products of superficial erosional processes due to the action of the gravity and/or water; thus, such land surfaces are highly representative of the strong soil degradation occurring in a wide area located on the boundary between Molise and Puglia regions (Southern Italy). The results of this study have been reported on thematic maps; on such maps, the detected erosional land surfaces have been mapped on the basis of their typical spectral signature. The study has been performed using Landsat satellite imagery data which have been then validated by means of field survey data. The satellite data have been processed using remote sensing techniques, such as: false colour composite, contrast stretching, principal component analysis and decorrelation stretching. The study has permitted to produce, in a relatively short time and at low expense, a map of the eroded land surfaces. Such a result represents a first and fundamental step in evaluating and monitoring the erosional processes in the study area [it

Tabular data base construction and analysis from thematic classified Landsat imagery of Portland, Oregon

Science.gov (United States)

Bryant, N. A.; George, A. J., Jr.; Hegdahl, R.

1977-01-01

A systematic verification of Landsat data classifications of the Portland, Oregon metropolitan area has been undertaken on the basis of census tract data. The degree of systematic misclassification due to the Bayesian classifier used to process the Landsat data was noted for the various suburban, industrialized and central business districts of the metropolitan area. The Landsat determinations of residential land use were employed to estimate the number of automobile trips generated in the region and to model air pollution hazards.

An automated approach to mapping corn from Landsat imagery

Science.gov (United States)

Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.; Hoffer, R.M.

2004-01-01

Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

Partial oxidation process

International Nuclear Information System (INIS)

Najjar, M.S.

1987-01-01

A process is described for the production of gaseous mixtures comprising H/sub 2/+CO by the partial oxidation of a fuel feedstock comprising a heavy liquid hydrocarbonaceous fuel having a nickel, iron, and vanadium-containing ash or petroleum coke having a nickel, iron, and vanadium-containing ash, or mixtures thereof. The feedstock includes a minimum of 0.5 wt. % of sulfur and the ash includes a minimum of 5.0 wt. % vanadium, a minimum of 0.5 ppm nickel, and a minimum of 0.5 ppm iron. The process comprises: (1) mixing together a copper-containing additive with the fuel feedstock; wherein the weight ratio of copper-containing additive to ash in the fuel feedstock is in the range of about 1.0-10.0, and there is at least 10 parts by weight of copper for each part by weight of vanadium; (2) reacting the mixture from (1) at a temperature in the range of 2200 0 F to 2900 0 F and a pressure in the range of about 5 to 250 atmospheres in a free-flow refactory lined partial oxidation reaction zone with a free-oxygen containing gas in the presence of a temperature moderator and in a reducing atmosphere to produce a hot raw effluent gas stream comprising H/sub 2/+CO and entrained molten slag; and where in the reaction zone and the copper-containing additive combines with at least a portion of the nickel and iron constituents and sulfur found in the feedstock to produce a liquid phase washing agent that collects and transports at least a portion of the vanadium-containing oxide laths and spinels and other ash components and refractory out of the reaction zone; and (3) separating nongaseous materials from the hot raw effluent gas stream

Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images

Science.gov (United States)

Chen, Xuexia; Vogelmann, James E.; Chander, Gyanesh; Ji, Lei; Tolk, Brian; Huang, Chengquan; Rollins, Matthew

2013-01-01

Routine acquisition of Landsat 5 Thematic Mapper (TM) data was discontinued recently and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) has an ongoing problem with the scan line corrector (SLC), thereby creating spatial gaps when covering images obtained during the process. Since temporal and spatial discontinuities of Landsat data are now imminent, it is therefore important to investigate other potential satellite data that can be used to replace Landsat data. We thus cross-compared two near-simultaneous images obtained from Landsat 5 TM and the Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS), both captured on 29 May 2007 over Los Angeles, CA. TM and AWiFS reflectances were compared for the green, red, near-infrared (NIR), and shortwave infrared (SWIR) bands, as well as the normalized difference vegetation index (NDVI) based on manually selected polygons in homogeneous areas. All R2 values of linear regressions were found to be higher than 0.99. The temporally invariant cluster (TIC) method was used to calculate the NDVI correlation between the TM and AWiFS images. The NDVI regression line derived from selected polygons passed through several invariant cluster centres of the TIC density maps and demonstrated that both the scene-dependent polygon regression method and TIC method can generate accurate radiometric normalization. A scene-independent normalization method was also used to normalize the AWiFS data. Image agreement assessment demonstrated that the scene-dependent normalization using homogeneous polygons provided slightly higher accuracy values than those obtained by the scene-independent method. Finally, the non-normalized and relatively normalized ‘Landsat-like’ AWiFS 2007 images were integrated into 1984 to 2010 Landsat time-series stacks (LTSS) for disturbance detection using the Vegetation Change Tracker (VCT) model. Both scene-dependent and scene-independent normalized AWiFS data sets could generate disturbance maps similar to

Reactor modeling and process analysis for partial oxidation of natural gas

NARCIS (Netherlands)

Albrecht, B.A.

2004-01-01

This thesis analyses a novel process of partial oxidation of natural gas and develops a numerical tool for the partial oxidation reactor modeling. The proposed process generates syngas in an integrated plant of a partial oxidation reactor, a syngas turbine and an air separation unit. This is called

NASA 3D Models: Landsat 7

Data.gov (United States)

National Aeronautics and Space Administration — The Landsat Program is a series of Earth-observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Since 1972, Landsat satellites have...

Landsat Data Continuity Mission

Science.gov (United States)

,

2012-01-01

The Landsat Data Continuity Mission (LDCM) is a partnership formed between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit in January 2013. The Landsat era that began in 1972 will become a nearly 41-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archiving, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (30-meter spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of landcover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis at no cost to the user.

Landsat TM data processing for lithological discrimination in the Caraculo area (Namibe Province, SW Angola)

Science.gov (United States)

Alberti, A.; Alessandro, V.; Pieruccini, U.; Pranzini, E.

1993-10-01

Landsat TM data were used for lithological discrimination and mapping in the little-known, semiarid 900 km 2 area around Caraculo station and the middle course of the Rio Giraul (Namibe Province, SW Angola) following two main procedures. The first of these was based on visual evaluation of three-band composites, band-ratio composites and Principal Component Analysis. The second method relied on the extraction of spectral signatures, and their use to obtain automatic classifications. Satisfactory results were reached with the first procedure, thus allowing - with limited support of ground information — the draft of a lithological map, while the second method was not systematically efficient, even for confirmation of data acquired with the first procedure. Image interpretation suggests that an extensive but hithertoun differentiated metasedimentary complex consisting of a heterogeneous supracrustal sequence should be subdivided into at least two units. Field observations proved that one of these is marked by a notable frequency of marbles and the other is characterized by a widespread occurrence of amphibolitic bodies. Moreover, a belt of undetermined (thermally metamorphosed ?) metamorphic rocks is interposed between them. The distinction of so far unidentified units, though restricted to interpretation of processed Landsat TM data, has significant geological implications also in the regional context and will be helpful in guiding future work with conventional geological methods.

Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization

Science.gov (United States)

Vogelmann, James E.; Helder, Dennis; Morfitt, Ron; Choate, Michael J.; Merchant, James W.; Bulley, Henry

2001-01-01

The Thematic Mapper (TM) instruments onboard Landsats 4 and 5 provide high-quality imagery appropriate for many different applications, including land cover mapping, landscape ecology, and change detection. Precise calibration was considered to be critical to the success of the Landsat 7 mission and, thus, issues of calibration were given high priority during the development of the Enhanced Thematic Mapper Plus (ETM+). Data sets from the Landsat 5 TM are not routinely corrected for a number of radiometric and geometric artifacts, including memory effect, gain/bias, and interfocal plane misalignment. In the current investigation, the effects of correcting vs. not correcting these factors were investigated for several applications. Gain/bias calibrations were found to have a greater impact on most applications than did memory effect calibrations. Correcting interfocal plane offsets was found to have a moderate effect on applications. On June 2, 1999, Landsats 5 and 7 data were acquired nearly simultaneously over a study site in the Niobrara, NE area. Field radiometer data acquired at that site were used to facilitate crosscalibrations of Landsats 5 and 7 data. Current findings and results from previous investigations indicate that the internal calibrator of Landsat 5 TM tracked instrument gain well until 1988. After this, the internal calibrator diverged from the data derived from vicarious calibrations. Results from this study also indicate very good agreement between prelaunch measurements and vicarious calibration data for all Landsat 7 reflective bands except Band 4. Values are within about 3.5% of each other, except for Band 4, which differs by 10%. Coefficient of variation (CV) values derived from selected targets in the imagery were also analyzed. The Niobrara Landsat 7 imagery was found to have lower CV values than Landsat 5 data, implying that lower levels of noise characterize Landsat 7 data than current Landsat 5 data. It was also found that following

A Useful Tool for Atmospheric Correction and Surface Temperature Estimation of Landsat Infrared Thermal Data

Science.gov (United States)

Rivalland, Vincent; Tardy, Benjamin; Huc, Mireille; Hagolle, Olivier; Marcq, Sébastien; Boulet, Gilles

2016-04-01

Land Surface temperature (LST) is a critical variable for studying the energy and water budgets at the Earth surface, and is a key component of many aspects of climate research and services. The Landsat program jointly carried out by NASA and USGS has been providing thermal infrared data for 40 years, but no associated LST product has been yet routinely proposed to community. To derive LST values, radiances measured at sensor-level need to be corrected for the atmospheric absorption, the atmospheric emission and the surface emissivity effect. Until now, existing LST products have been generated with multi channel methods such as the Temperature/Emissivity Separation (TES) adapted to ASTER data or the generalized split-window algorithm adapted to MODIS multispectral data. Those approaches are ill-adapted to the Landsat mono-window data specificity. The atmospheric correction methodology usually used for Landsat data requires detailed information about the state of the atmosphere. This information may be obtained from radio-sounding or model atmospheric reanalysis and is supplied to a radiative transfer model in order to estimate atmospheric parameters for a given coordinate. In this work, we present a new automatic tool dedicated to Landsat thermal data correction which improves the common atmospheric correction methodology by introducing the spatial dimension in the process. The python tool developed during this study, named LANDARTs for LANDsat Automatic Retrieval of surface Temperature, is fully automatic and provides atmospheric corrections for a whole Landsat tile. Vertical atmospheric conditions are downloaded from the ERA Interim dataset from ECMWF meteorological organization which provides them at 0.125 degrees resolution, at a global scale and with a 6-hour-time step. The atmospheric correction parameters are estimated on the atmospheric grid using the commercial software MODTRAN, then interpolated to 30m resolution. We detail the processing steps

Retrieval and Mapping of Heavy Metal Concentration in Soil Using Time Series Landsat 8 Imagery

Science.gov (United States)

Fang, Y.; Xu, L.; Peng, J.; Wang, H.; Wong, A.; Clausi, D. A.

2018-04-01

Heavy metal pollution is a critical global environmental problem which has always been a concern. Traditional approach to obtain heavy metal concentration relying on field sampling and lab testing is expensive and time consuming. Although many related studies use spectrometers data to build relational model between heavy metal concentration and spectra information, and then use the model to perform prediction using the hyperspectral imagery, this manner can hardly quickly and accurately map soil metal concentration of an area due to the discrepancies between spectrometers data and remote sensing imagery. Taking the advantage of easy accessibility of Landsat 8 data, this study utilizes Landsat 8 imagery to retrieve soil Cu concentration and mapping its distribution in the study area. To enlarge the spectral information for more accurate retrieval and mapping, 11 single date Landsat 8 imagery from 2013-2017 are selected to form a time series imagery. Three regression methods, partial least square regression (PLSR), artificial neural network (ANN) and support vector regression (SVR) are used to model construction. By comparing these models unbiasedly, the best model are selected to mapping Cu concentration distribution. The produced distribution map shows a good spatial autocorrelation and consistency with the mining area locations.

Landsat Science Team: 2017 Winter Meeting Summary

Science.gov (United States)

Schroeder, Todd A.; Loveland, Thomas; Wulder, Michael A.; Irons, James R.

2017-01-01

The summer meeting of the joint U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) was held July 26-28, 2016, at South Dakota State University (SDSU) in Brookings, SD. LST co-chair Tom Loveland [USGS’s Earth Resources Observation and Science Center (EROS)] and Kevin Kephart [SDSU] welcomed more than 80 participants to the three-day meeting. That attendance at such meetings continues to increase—likely due to the development of new data products and sensor systems—further highlights the growing interest in the Landsat program. The main objectives of this meeting were to provide a status update on Landsat 7 and 8, review team member research activities, and to begin identifying priorities for future Landsat missions.

Recommended practice for process sampling for partial pressure analysis

International Nuclear Information System (INIS)

Blessing, James E.; Ellefson, Robert E.; Raby, Bruce A.; Brucker, Gerardo A.; Waits, Robert K.

2007-01-01

This Recommended Practice describes and recommends various procedures and types of apparatus for obtaining representative samples of process gases from >10 -2 Pa (10 -4 Torr) for partial pressure analysis using a mass spectrometer. The document was prepared by a subcommittee of the Recommended Practices Committee of the American Vacuum Society. The subcommittee was comprised of vacuum users and manufacturers of mass spectrometer partial pressure analyzers who have practical experience in the sampling of process gas atmospheres

The impact of landsat satellite monitoring on conservation biology.

Science.gov (United States)

Leimgruber, Peter; Christen, Catherine A; Laborderie, Alison

2005-07-01

Landsat 7's recent malfunctioning will result in significant gaps in long-term satellite monitoring of Earth, affecting not only the research of the Earth science community but also conservation users of these data. To determine whether or how important Landsat monitoring is for conservation and natural resource management, we reviewed the Landsat program's history with special emphasis on the development of user groups. We also conducted a bibliographic search to determine the extent to which conservation research has been based on Landsat data. Conservation biologists were not an early user group of Landsat data because a) biologists lacked technical capacity--computers and software--to analyze these data; b) Landsat's 1980s commercialization rendered images too costly for biologists' budgets; and c) the broad-scale disciplines of conservation biology and landscape ecology did not develop until the mid-to-late 1980s. All these conditions had changed by the 1990s and Landsat imagery became an important tool for conservation biology. Satellite monitoring and Landsat continuity are mandated by the Land Remote Sensing Act of 1992. This legislation leaves open commercial options. However, past experiments with commercial operations were neither viable nor economical, and severely reduced the quality of monitoring, archiving and data access for academia and the public. Future satellite monitoring programs are essential for conservation and natural resource management, must provide continuity with Landsat, and should be government operated.

Development and implementation of a low cost micro computer system for LANDSAT analysis and geographic data base applications

Science.gov (United States)

Faust, N.; Jordon, L.

1981-01-01

Since the implementation of the GRID and IMGRID computer programs for multivariate spatial analysis in the early 1970's, geographic data analysis subsequently moved from large computers to minicomputers and now to microcomputers with radical reduction in the costs associated with planning analyses. Programs designed to process LANDSAT data to be used as one element in a geographic data base were used once NIMGRID (new IMGRID), a raster oriented geographic information system, was implemented on the microcomputer. Programs for training field selection, supervised and unsupervised classification, and image enhancement were added. Enhancements to the color graphics capabilities of the microsystem allow display of three channels of LANDSAT data in color infrared format. The basic microcomputer hardware needed to perform NIMGRID and most LANDSAT analyses is listed as well as the software available for LANDSAT processing.

Implementation and testing of WELD and automatic spectral rule-based classifications for Landsat ETM+ in South Africa

CSIR Research Space (South Africa)

Wessels, Konrad J

2013-04-01

Full Text Available The Web-enabled Landsat Data (WELD) system was successfully installed in South Africa (SA) and used for pre-processing large amounts of Landsat ETM+ data to composited seasonal mosaics. In pursuit of automated land cover mapping, the overall...

Landsat at 45: How it Changed the Way We See the Earth

Science.gov (United States)

Uri, John

2017-01-01

Landsat were processed by NASA and hardcopies sold to users for a fee, a somewhat tedious process. Since 2008, images have been made available to all interested users by the US Geological Survey (USGS) at no cost via the Internet in near real time. So, how can Landsat help? In short, Landsat looks. And looks. And proves Yogi right. Space-based images from Landsat and other similar satellites offer a unique and critical capability to observe land use over time by providing repetitive observations of the Earth otherwise unavailable. The data provided by the images can be used by scientists and politicians to inform wise decisions in areas such as agriculture, climate, ecosystems and biodiversity, energy, forest management, human health, fire, natural disasters, urban growth and water management. This overview article doesn't allow for examples from each of these disciplines, but details can be found at the following website: https://landsat.gsfc.nasa.gov/how_landsat_helps/. One third of the US economy is influenced by climate, weather and natural hazards, providing strong economic incentives to sustain a healthy space-based Earth observation program. One example, however, may be illustrative of how Landsat and other space-based observations can be helpful in monitoring and documenting some effects of global climate change. It had been noted since the 1970's that permafrost in subarctic areas like Siberia was melting at an accelerating rate. It also became apparent that this led to the formation of hundreds of melt lakes and the liberation of large quantities of methane, a gas that in the short-term has more potent greenhouse effects than carbon dioxide. The methane turned the water in these lakes blue, making them easy to track over time by satellite. Additionally, the newly released methane has been carbon dated to tens of thousands of years ago, meaning that it had remained frozen since the last Ice Age and therefore hadn't been accounted for in models of the Earth

Techniques for land use change detection using Landsat imagery

Science.gov (United States)

Angelici, G. L.; Bryant, N. A.; Friedman, S. Z.

1977-01-01

A variety of procedures were developed for the delineation of areas of land use change using Landsat Multispectral Scanner data and the generation of statistics revealing the nature of the changes involved (i.e., number of acres changed from rural to urban). Techniques of the Image Based Information System were utilized in all stages of the procedure, from logging the Landsat data and registering two frames of imagery, to extracting the changed areas and printing tabulations of land use change in acres. Two alternative methods of delineating land use change are presented while enumerating the steps of the entire process. The Houston, Texas urban area, and the Orlando, Florida urban area, are used as illustrative examples of various procedures.

Landsat 1-5 Multispectral Scanner V1

Data.gov (United States)

National Aeronautics and Space Administration — Abstract: The Landsat Multispectral Scanner (MSS) was a sensor onboard Landsats 1 through 5 and acquired images of the Earth nearly continuously from July 1972 to...

Ambit processes and stochastic partial differential equations

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole; Benth, Fred Espen; Veraart, Almut

Ambit processes are general stochastic processes based on stochastic integrals with respect to Lévy bases. Due to their flexible structure, they have great potential for providing realistic models for various applications such as in turbulence and finance. This papers studies the connection betwe...... ambit processes and solutions to stochastic partial differential equations. We investigate this relationship from two angles: from the Walsh theory of martingale measures and from the viewpoint of the Lévy noise analysis....

Landsat science team meeting: Summer 2015

Science.gov (United States)

Schroeder, Todd; Loveland, Thomas; Wulder, Michael A.; Irons, James R.

2015-01-01

The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023.

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring

Science.gov (United States)

Masek, J. G.; Ju, J.; Claverie, M.; Vermote, E.; Dungan, J. L.; Roger, J. C.; Skakun, S.; Justice, C. O.

2017-12-01

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 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.

Application of LANDSAT to the surveillance and control of lake eutrophication in the Great Lakes Basin

Science.gov (United States)

Rogers, R. H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Preliminary results in Saginaw Bay show that processed LANDSAT data provides a synoptic view of turbidity and circulation patterns that no degree of ground monitoring can provide. Processed imagery was produced to show nine discrete categories of turbidity, as indicated by nine Secchi depths between 0.3 and 3.3 meters. Analysis of lakes near Madison, Wisconsin show that inland lake water can be categorized by LANDSAT as clear, tannin, algal, and red clay. LANDSAT's capability to inventory watershed land use was throughly demonstrated in the Ohio-Kentucky-Indiana regional planning area. Computer tabulations providing area covered by each of 16 land use categories were rapidly and economically produced for each of the 225 watersheds and nine counties.

Partial wave analysis using graphics processing units

Energy Technology Data Exchange (ETDEWEB)

Berger, Niklaus; Liu Beijiang; Wang Jike, E-mail: nberger@ihep.ac.c [Institute of High Energy Physics, Chinese Academy of Sciences, 19B Yuquan Lu, Shijingshan, 100049 Beijing (China)

2010-04-01

Partial wave analysis is an important tool for determining resonance properties in hadron spectroscopy. For large data samples however, the un-binned likelihood fits employed are computationally very expensive. At the Beijing Spectrometer (BES) III experiment, an increase in statistics compared to earlier experiments of up to two orders of magnitude is expected. In order to allow for a timely analysis of these datasets, additional computing power with short turnover times has to be made available. It turns out that graphics processing units (GPUs) originally developed for 3D computer games have an architecture of massively parallel single instruction multiple data floating point units that is almost ideally suited for the algorithms employed in partial wave analysis. We have implemented a framework for tensor manipulation and partial wave fits called GPUPWA. The user writes a program in pure C++ whilst the GPUPWA classes handle computations on the GPU, memory transfers, caching and other technical details. In conjunction with a recent graphics processor, the framework provides a speed-up of the partial wave fit by more than two orders of magnitude compared to legacy FORTRAN code.

BOREAS RSS-7 Landsat TM LAI IMages of the SSA and NSA

Science.gov (United States)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

2000-01-01

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team used Landsat Thematic Mapper (TM) images processed at CCRS to produce images of Leaf Area Index (LAI) for the BOREAS study areas. Two images acquired on 06-Jun and 09-Aug-1991 were used for the SSA, and one image acquired on 09-Jun-1994 was used for the NSA. The LAI images are based on ground measurements and Landsat TM Reduced Simple Ratio (RSR) images. The data are stored in binary image-format files.

Microbial Flora of Partially Processed Periwinkles (Tympantotonus ...

African Journals Online (AJOL)

A survey of microbial flora of partially processed periwinkles (Tympanotonus fuscatus) sold in six markets in Port Harcourt was undertaken for twelve weeks. Results show that all samples of periwinkles were contaminated with Staphylococcus aureus, Bacillus sp., Escherichia coil, Staphepidermidis sp., Micrococcus sp., ...

North American forest disturbance mapped from a decadal Landsat record

Science.gov (United States)

Jeffrey G. Masek; Chengquan Huang; Robert Wolfe; Warren Cohen; Forrest Hall; Jonathan Kutler; Peder. Nelson

2008-01-01

Forest disturbance and recovery are critical ecosystem processes, but the spatial pattern of disturbance has never been mapped across North America. The LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) project has assembled a wall-to-wall record of stand-clearing disturbance (clearcut harvest, fire) for the United States and Canada for the period 1990-...

Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data

Science.gov (United States)

Vogelmann, James; Gallant, Alisa L.; Shi, Hua; Zhu, Zhe

2016-01-01

There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all

Small forest cuttings mapped with Landsat digital data

Science.gov (United States)

Bryant, E.; Dodge, A. G.; Eger, M. J. E.

1979-01-01

The Cooperative Landsat Applications Research Group used computer classification of Landsat digital data to map forest cuttings (clearcuts) in northern New Hampshire. Cuttings as small as 3 hectares were identified. Several ages or conditions of clearcuts could be distinguished. Progress in two methods of duplicating classification categories from one Landsat pass to another are discussed. One method was used in making maps of areas in 1973, 1975, and 1978.

Data-driven simulations of the Landsat Data Continuity Mission (LDCM) platform

Science.gov (United States)

Gerace, Aaron; Gartley, Mike; Schott, John; Raqueño, Nina; Raqueño, Rolando

2011-06-01

The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are two new sensors being developed by the Landsat Data Continuity Mission (LDCM) that will extend over 35 years of archived Landsat data. In a departure from the whiskbroom design used by all previous generations of Landsat, the LDCM system will employ a pushbroom technology. Although the newly adopted modular array, pushbroom architecture has several advantages over the previous whiskbroom design, registration of the multi-spectral data products is a concern. In this paper, the Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool was used to simulate an LDCM collection, which gives the team access to data that would not otherwise be available prior to launch. The DIRSIG model was used to simulate the two-instrument LDCM payload in order to study the geometric and radiometric impacts of the sensor design on the proposed processing chain. The Lake Tahoe area located in eastern California was chosen for this work because of its dramatic change in elevation, which was ideal for studying the geometric effects of the new Landsat sensor design. Multi-modal datasets were used to create the Lake Tahoe site model for use in DIRSIG. National Elevation Dataset (NED) data were used to create the digital elevation map (DEM) required by DIRSIG, QuickBird data were used to identify different material classes in the scene, and ASTER and Hyperion spectral data were used to assign radiometric properties to those classes. In order to model a realistic Landsat orbit in these simulations, orbital parameters were obtained from a Landsat 7 two-line element set and propagated with the SGP4 orbital position model. Line-of-sight vectors defining how the individual detector elements of the OLI and TIRS instruments project through the optics were measured and provided by NASA. Additionally, the relative spectral response functions for the 9 bands of OLI and the 2 bands of TIRS were measured and provided by NASA

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

Science.gov (United States)

Masek, Jeffrey G.; Dungan, Jennifer L.; Ju, Junchang; Roger, Jean-Claude; Claverie, Martin P.; Skakun, Sergii; Vermote, Eric; Justice, Christopher Owen

2017-01-01

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.

The value of earth observations: methods and findings on the value of Landsat imagery

Science.gov (United States)

Miller, Holly M.; Serbina, Larisa O.; Richardson, Leslie A.; Ryker, Sarah J.; Newman, Timothy R.

2016-01-01

Data from Earth observation systems are used extensively in managing and monitoring natural resources, natural hazards, and the impacts of climate change, but the value of such data can be difficult to estimate, particularly when it is available at no cost. Assessing the socioeconomic and scientific value of these data provides a better understanding of the existing and emerging research, science, and applications related to this information and contributes to the decision making process regarding current and future Earth observation systems. Recent USGS research on Landsat data has advanced the literature in this area by using a variety of methods to estimate value. The results of a 2012 survey of Landsat users, a 2013 requirements assessment, and 2013 case studies of applications of Landsat imagery are discussed.

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

Science.gov (United States)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

Use of landsat ETM+ SLC-off segment-based gap-filled imagery for crop type mapping

Science.gov (United States)

Maxwell, S.K.; Craig, M.E.

2008-01-01

Failure of the Scan Line Corrector (SLC) on the Landsat ETM+ sensor has had a major impact on many applications that rely on continuous medium resolution imagery to meet their objectives. The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) program uses Landsat imagery as the primary source of data to produce crop-specific maps for 20 states in the USA. A new method has been developed to fill the image gaps resulting from the SLC failure to support the needs of Landsat users who require coincident spectral data, such as for crop type mapping and monitoring. We tested the new gap-filled method for a CDL crop type mapping project in eastern Nebraska. Scan line gaps were simulated on two Landsat 5 images (spring and late summer 2003) and then gap-filled using landscape boundary models, or segment models, that were derived from 1992 and 2002 Landsat images (used in the gap-fill process). Various date combinations of original and gap-filled images were used to derive crop maps using a supervised classification process. Overall kappa values were slightly higher for crop maps derived from SLC-off gap-filled images compared to crop maps derived from the original imagery (0.3–1.3% higher). Although the age of the segment model used to derive the SLC-off gap-filled product did not negatively impact the overall agreement, differences in individual cover type agreement did increase (−0.8%–1.6% using the 2002 segment model to −5.0–5.1% using the 1992 segment model). Classification agreement also decreased for most of the classes as the size of the segment used in the gap-fill process increased.

Bridging the Divide: Translating Landsat Research Into Usable Science

Science.gov (United States)

Rocchio, L. E.; Davis, A. L.

2006-12-01

Science has long served humankind. Breakthroughs in medicine have increased longevity and advances in technology have made modern-day conveniences possible. Yet, social benefits begotten by the environmental sciences, although critical for the survival of humanity, have not always been as widely recognized or used. To benefit today's rapidly growing population, the divides between environmental research, applied environmental science, and use of this information by decision makers must be bridged. Lessons about the translation from research to usable science can be learned from the four decades of Landsat history, and these lessons can serve as useful models for bridging the gaps between new technology, scientific research, and the use of that research and technology in real-world problem solving. In 1965, William Pecora, then-director of the U.S. Geological Survey, proposed the idea of a remote sensing satellite program to gather facts about natural resources of Earth. For the next seven years, an intense campaign showing the depth and diversity of satellite imagery applications was waged. This led to the 1972 launch of the first civilian land-observing satellite, Landsat 1. By 1975, successful application research based on Landsat 1 imagery prompted then-NASA Administrator Dr. James Fletcher to proclaim that if one space age development would save the world, it would be Landsat and its successor satellites. Thirty-four years of continual Landsat imaging and related-research has lead to the implementation of many socially beneficial applications, such as improved water management techniques, crop insurance fraud reduction, illicit crop inventories, natural disaster relief planning, continent-scale carbon estimates, and extensive cartographic advances. Despite these successes, the challenge of translating Landsat research into realized social benefits remains. Even in this geospatially-savvy era, the utility of Landsat largely escapes policymakers. Here, in an

Detecting Forest Disturbance Events from MODIS and Landsat Time Series for the Conterminous United States

Science.gov (United States)

Zhang, G.; Ganguly, S.; Saatchi, S. S.; Hagen, S. C.; Harris, N.; Yu, Y.; Nemani, R. R.

2013-12-01

Spatial and temporal patterns of forest disturbance and regrowth processes are key for understanding aboveground terrestrial vegetation biomass and carbon stocks at regional-to-continental scales. The NASA Carbon Monitoring System (CMS) program seeks key input datasets, especially information related to impacts due to natural/man-made disturbances in forested landscapes of Conterminous U.S. (CONUS), that would reduce uncertainties in current carbon stock estimation and emission models. This study provides a end-to-end forest disturbance detection framework based on pixel time series analysis from MODIS (Moderate Resolution Imaging Spectroradiometer) and Landsat surface spectral reflectance data. We applied the BFAST (Breaks for Additive Seasonal and Trend) algorithm to the Normalized Difference Vegetation Index (NDVI) data for the time period from 2000 to 2011. A harmonic seasonal model was implemented in BFAST to decompose the time series to seasonal and interannual trend components in order to detect abrupt changes in magnitude and direction of these components. To apply the BFAST for whole CONUS, we built a parallel computing setup for processing massive time-series data using the high performance computing facility of the NASA Earth Exchange (NEX). In the implementation process, we extracted the dominant deforestation events from the magnitude of abrupt changes in both seasonal and interannual components, and estimated dates for corresponding deforestation events. We estimated the recovery rate for deforested regions through regression models developed between NDVI values and time since disturbance for all pixels. A similar implementation of the BFAST algorithm was performed over selected Landsat scenes (all Landsat cloud free data was used to generate NDVI from atmospherically corrected spectral reflectances) to demonstrate the spatial coherence in retrieval layers between MODIS and Landsat. In future, the application of this largely parallel disturbance

Preliminary analysis of the potential of LANDSAT imagery to study desertification. [Xique-Xique, Brazil

Science.gov (United States)

Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Decarvalho, V. C.

1980-01-01

The use of LANDSAT imagery to define and delimit areas under process of desertification was investigated. Imagery for two different years (1973 and 1978) and two different seasons (dry and rainy seasons in 1976), were used to identify terrain morphology and vegetation cover. The analysis of LANDSAT interpretation, combined with geological and soil information obtained from published literature, allowed the identification of eleven ecological units which were classified corresponding to the degree of the Xique Xique region of Rio Sao Francisco.

DEVELOPMENT OF TIME-SERIES HUMAN SETTLEMENT MAPPING SYSTEM USING HISTORICAL LANDSAT ARCHIVE

Directory of Open Access Journals (Sweden)

H. Miyazaki

2016-06-01

Full Text Available Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initiatives using ASTER, Landsat, and TerraSAR-X, next goal has targeted to development of time-series data which can contribute to studies urban development with background context of socioeconomy, disaster risk management, public health, transport and other development issues. We developed an automated algorithm to detect human settlement by classification of built-up and non-built-up in time-series Landsat images. A machine learning algorithm, Local and Global Consistency (LLGC, was applied with improvements for remote sensing data. The algorithm enables to use MCD12Q1, a MODIS-based global land cover map with 500-m resolution, as training data so that any manual process is not required for preparation of training data. In addition, we designed the method to composite multiple results of LLGC into a single output to reduce uncertainty. The LLGC results has a confidence value ranging 0.0 to 1.0 representing probability of built-up and non-built-up. The median value of the confidence for a certain period around a target time was expected to be a robust output of confidence to identify built-up or non-built-up areas against uncertainties in satellite data quality, such as cloud and haze contamination. Four scenes of Landsat data for each target years, 1990, 2000, 2005, and 2010, were chosen among the Landsat archive data with cloud contamination less than 20%.We developed a system with the algorithms on the Data Integration and Analysis System (DIAS in the University of Tokyo and processed 5200 scenes of Landsat data for cities with more than one million people worldwide.

Monitoring water quality from LANDSAT. [satellite observation of Virginia

Science.gov (United States)

Barker, J. L.

1975-01-01

Water quality monitoring possibilities from LANDSAT were demonstrated both for direct readings of reflectances from the water and indirect monitoring of changes in use of land surrounding Swift Creek Reservoir in a joint project with the Virginia State Water Control Board and NASA. Film products were shown to have insufficient resolution and all work was done by digitally processing computer compatible tapes. Land cover maps of the 18,000 hectare Swift Creek Reservoir watershed, prepared for two dates in 1974, are shown. A significant decrease in the pine cover was observed in a 740 hectare construction site within the watershed. A measure of the accuracy of classification was obtained by comparing the LANDSAT results with visual classification at five sites on a U-2 photograph. Such changes in land cover can alert personnel to watch for potential changes in water quality.

LandSAT TM 1994

Data.gov (United States)

Kansas Data Access and Support Center — Before the Landsat commercialization contract was signed between the Department of Commerce and the Earth Observation Satellite Company (EOSAT) on September 27,...

ANALYSIS OF RELATIONSHIP BETWEEN URBAN HEAT ISLAND EFFECT AND LAND USE/COVER TYPE USING LANDSAT 7 ETM+ AND LANDSAT 8 OLI IMAGES

Directory of Open Access Journals (Sweden)

N. Aslan

2016-06-01

Full Text Available The main objectives of this study are (i to calculate Land Surface Temperature (LST from Landsat imageries, (ii to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001 and Landsat 8 OLI (June 17, 2014 imageries, (iii to examine the relationship between LST and different Land Use/Land Cover (LU/LC types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF classifier. Normalized Difference Vegetation Index (NDVI image, ASTER Global Digital Elevation Model (GDEM and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88 % for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6 °C for 2001 and 6.8 °C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r2 = 0.7 and r2 = 0.9 for 2001 and 2014, respectively.

Landsat and water pollution

Science.gov (United States)

Castruccio, P.; Fowler, T.; Loats, H., Jr.

1979-01-01

Report presents data derived from satellite images predicting pollution loads after rainfall. It explains method for converting Landsat images of Eastern United States into cover maps for Baltimore/five county region.

Hydrological balance and water transport processes of partially sealed soils

Science.gov (United States)

Timm, Anne; Wessolek, Gerd

2017-04-01

With increased urbanisation, soil sealing and its drastic effects on hydrological processes have received a lot of attention. Based on safety concerns, there has been a clear focus on urban drainage and prevention of urban floods caused by storm water events. For this reason, any kind of sealing is often seen as impermeable runoff generator that prevents infiltration and evaporation. While many hydrological models, especially storm water models, have been developed, there are only a handful of empirical studies actually measuring the hydrological balance of (partially) sealed surfaces. These challenge the general assumption of negligible infiltration and evaporation and show that these processes take place even for severe sealing such as asphalt. Depending on the material, infiltration from partially sealed surfaces can be equal to that of vegetated ones. Therefore, more detailed knowledge is needed to improve our understanding and models. In Berlin, two partially sealed weighable lysimeters were equipped with multiple temperature and soil moisture sensors in order to study their hydrological balance, as well as water and heat transport processes within the soil profile. This combination of methods affirms previous observations and offers new insights into altered hydrological processes of partially sealed surfaces at a small temporal scale. It could be verified that not all precipitation is transformed into runoff. Even for a relatively high sealing degree of concrete slabs with narrow seams, evaporation and infiltration may exceed runoff. Due to the lack of plant roots, the hydrological balance is mostly governed by precipitation events and evaporation generally occurs directly after rainfall. However, both surfaces allow for upward water transport from the upper underlying soil layers, sometimes resulting in relatively low evaporation rates on days without precipitation. The individual response of the surfaces differs considerably, which illustrates how

Landsat 6 contract signed

Science.gov (United States)

Maggs, William Ward

A new agreement provides $220 million for development and construction of the Landsat 6 remote sensing satellite and its ground systems. The contract, signed on March 31, 1988, by the Department of Commerce (DOC) and the Earth Observation Satellite (EOSAT) Company of Lanham, Md., came just days after approval of DOC's Landsat commercialization plan by subcommittees of the House and Senate appropriations committees.The Landsat 6 spacecraft is due to be launched into orbit on a Titan II rocket in June 1991 from Vandenburg Air Force Base, Calif. The satellite will carry an Enhanced Thematic Mapper (ETM) sensor, an instrument sensitive to electromagnetic radiation in seven ranges or bands of wavelengths. The satellite's payload will also include the Sea Wide Field Sensor (Sea-WiFS), designed to provide information on sea surface temperature and ocean color. The sensor is being developed in a cooperative effort by EOSAT and the National Aeronautics and Space Administration (NASA). A less certain passenger is a proposed 5-m resolution, three-band sensor sensitive to visible light. EOSAT is trying to find both private financing for the device and potential buyers of the high-resolution imagery that it could produce. The company has been actively courting U.S. television networks, which have in the past used imagery from the European Système Probatoire d'Observation de la Terre (SPOT) satellite for news coverage.

River morphodynamics from space: the Landsat frontier

Science.gov (United States)

Schwenk, Jon; Khandelwal, Ankush; Fratkin, Mulu; Kumar, Vipin; Foufoula-Georgiou, Efi

2017-04-01

NASA's Landsat family of satellites have been observing the entire globe since 1984, providing over 30 years of snapshots with an 18 day frequency and 30 meter resolution. These publicly-available Landsat data are particularly exciting to researchers interested in river morphodynamics, who are often limited to use of historical maps, aerial photography, and field surveys with poor and irregular time resolutions and limited spatial extents. Landsat archives show potential for overcoming these limitations, but techniques and tools for accurately and efficiently mining the vault of scenes must first be developed. In this PICO presentation, we detail the problems we encountered while mapping and quantifying planform dynamics of over 1,300 km of the actively-migrating, meandering Ucayali River in Peru from Landsat imagery. We also present methods to overcome these obstacles and introduce the Matlab-based RivMAP (River Morphodynamics from Analysis of Planforms) toolbox that we developed to extract banklines and centerlines, compute widths, curvatures, and angles, identify cutoffs, and quantify planform changes via centerline migration and erosion/accretion over large spatial domains with high temporal resolution. Measurement uncertainties were estimated by analyzing immobile, abandoned oxbow lakes. Our results identify hotspots of planform changes, and combined with limited precipitation, stage, and topography data, we parse three simultaneous controls on river migration: climate, sediment, and meander cutoff. Overall, this study demonstrates the vast potential locked within Landsat archives to identify multi-scale controls on river migration, observe the co-evolution of width, curvature, discharge, and migration, and discover and develop new geomorphic insights.

Anaglyph, Landsat Overlay: Wellington, New Zealand

Science.gov (United States)

2000-01-01

Wellington, the capital city of New Zealand, is located on the shores of Port Nicholson, a natural harbor at the south end of North Island. The city was founded in 1840 by British emigrants and now has a regional population of more than 400,000 residents. As seen here, the natural terrain imposes strong control over the urban growth pattern. Rugged hills generally rising to 300 meters (1,000 feet) help protect the city and harbor from strong winter winds.New Zealand is seismically active and faults are readily seen in the topography. The Wellington Fault forms the straight northwestern (upper left) shoreline of the harbor. Toward the southwest (lower left) the fault crosses through the city, then forms linear canyons in the hills before continuing offshore. Toward the northeast (upper right) the fault forms the sharp mountain front along the northern edge of the heavily populated Hutt Valley.This anaglyph was generated by first draping a Landsat Thematic Mapper image over a topographic map from the Shuttle Radar Topography Mission, then using the topographic data to create two differing perspectives, one for each eye. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.Landsat satellites have provided visible light and infrared images of the Earth continuously since 1972. SRTM topographic data match the 30 meter (99 foot) spatial resolution of most Landsat images and will provide a valuable complement for studying the historic and growing Landsat data archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM project by the United States Geological Survey, Earth Resources Observation Systems (EROS) data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour

Digital color analysis of color-ratio composite LANDSAT scenes. [Nevada

Science.gov (United States)

Raines, G. L.

1977-01-01

A method is presented that can be used to calculate approximate Munsell coordinates of the colors produced by making a color composite from three registered images. Applied to the LANDSAT MSS data of the Goldfield, Nevada, area, this method permits precise and quantitative definition of the limonitic areas originally observed in a LANDSAT color ratio composite. In addition, areas of transported limonite can be discriminated from the limonite in the hydrothermally altered areas of the Goldfield mining district. From the analysis, the numerical distinction between limonitic and nonlimonitic ground is generally less than 3% using the LANDSAT bands and as much as 8% in ratios of LANDSAT MSS bands.

A one year Landsat 8 conterminous United States study of spatial and temporal patterns of cirrus and non-cirrus clouds and implications for the long term Landsat archive.

Science.gov (United States)

Kovalskyy, V.; Roy, D. P.

2014-12-01

The successful February 2013 launch of the Landsat 8 satellite is continuing the 40+ year legacy of the Landsat mission. The payload includes the Operational Land Imager (OLI) that has a new 1370 mm band designed to monitor cirrus clouds and the Thermal Infrared Sensor (TIRS) that together provide 30m low, medium and high confidence cloud detections and 30m low and high confidence cirrus cloud detections. A year of Landsat 8 data over the Conterminous United States (CONUS), composed of 11,296 acquisitions, was analyzed comparing the spatial and temporal incidence of these cloud and cirrus states. This revealed (i) 36.5% of observations were detected with high confidence cloud with spatio-temporal patterns similar to those observed by previous Landsat 7 cloud analyses, (ii) 29.2% were high confidence cirrus, (iii) 20.9% were both high confidence cloud and high confidence cirrus, (iv) 8.3% were detected as high confidence cirrus but not as high confidence cloud. The results illustrate the value of the cirrus band for improved Landsat 8 terrestrial monitoring but imply that the historical CONUS Landsat archive has a similar 8% of undetected cirrus contaminated pixels. The implications for long term Landsat time series records, including the global Web Enabled Landsat Data (WELD) product record, are discussed.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

Science.gov (United States)

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Landsat 7 - A challenge to America

Science.gov (United States)

Colvocoresses, Alden P.

Factors in favor of Landsat 7 are discussed; they include: reasonable cost, a base on which to examine global change, and the need for comprehensive and continuous satellite coverage of the earth at moderate (5-30 m) resolution, in view of various occurrences on the earth's surface, ranging from the Chernobyl disaster to deforestation to the Persian Gulf conflict. Attention is given to proposed parameters for Landsat 7 and suggested actions that should be taken by Congress, the Administration, and the public to implement this space program.

Analysis of land degradation processes on a tiger bush plateau in South West Niger using MODIS and LANDSAT TM/ETM+ data

Science.gov (United States)

Fiorillo, Edoardo; Maselli, Fabio; Tarchiani, Vieri; Vignaroli, Patrizio

2017-10-01

Remote sensing digital image analysis has been applied to monitor land clearing and degradation processes on a plateau covered by tiger bush near Niamey in South West Niger, where signs of severe landscape degradation due to fuelwood supply have been observed in the last decades. A MODIS NDVI dataset (2000-2015) and five LANDSAT images (1986-2012) were used to identify spatial and temporal dynamics and to emphasize areas of greater degradation. The study indicates that the land clearing found by previous investigations in the second part of the 20th century is still ongoing, with a decreasing trend of MODIS NDVI values recorded in the period 2000-2015. This trend appeared to be linked to an increase in bare soil areas that was demonstrated by analysis of LANDSAT SAVI images. The investigation also indicated that rates of degradation are stronger in more deteriorated areas like those located nearer Niamey; degradation patterns also tend to increase from the inner areas to the edges of the plateau. These results attest to the urgency to develop effective environmental preservation policies and find alternative solutions for domestic energy supply.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

Science.gov (United States)

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Estimating the chlorophyll content in the waters of Guanabara Bay from the LANDSAT multispectral scanning digital data

Science.gov (United States)

Dejesusparada, N. (Principal Investigator); Bentancurt, J. J. V.; Herz, B. R.; Molion, L. B.

1980-01-01

Detection of water quality in Guanabara Bay using multispectral scanning digital data taken from LANDSAT satellites was examined. To test these processes, an empirical (statistical) approach was choosen to observe the degree of relationship between LANDSAT data and the in situ data taken simultaneously. The linear and nonlinear regression analyses were taken from among those developed by INPE in 1978. Results indicate that the major regression was in the number six MSS band, atmospheric effects, which indicated a correction coefficient of 0.99 and an average error of 6.59 micrograms liter. This error was similar to that obtained in the laboratory. The chlorophyll content was between 0 and 100 micrograms/liter, as taken from the MSS of LANDSAT.

Color enhancement of landsat agricultural imagery: JPL LACIE image processing support task

Science.gov (United States)

Madura, D. P.; Soha, J. M.; Green, W. B.; Wherry, D. B.; Lewis, S. D.

1978-01-01

Color enhancement techniques were applied to LACIE LANDSAT segments to determine if such enhancement can assist analysis in crop identification. The procedure involved increasing the color range by removing correlation between components. First, a principal component transformation was performed, followed by contrast enhancement to equalize component variances, followed by an inverse transformation to restore familiar color relationships. Filtering was applied to lower order components to reduce color speckle in the enhanced products. Use of single acquisition and multiple acquisition statistics to control the enhancement were compared, and the effects of normalization investigated. Evaluation is left to LACIE personnel.

Estimating the leaf area index (LAI) of black wattle from Landsat ...

African Journals Online (AJOL)

Regression analysis revealed that actual LAI had significant relationships with PAI and NDVI. The results indicate the potential of the Landsat ETM+ satellite imageries to estimate values of important canopy attributes of A. mearnsii that are related to stand productivity that may be used as inputs into process-based models ...

A time-series analysis of flood disaster around Lena river using Landsat TM/ETM+

Science.gov (United States)

Sakai, Toru; Hatta, Shigemi; Okumura, Makoto; Takeuchi, Wataru; Hiyama, Tetsuya; Inoue, Gen

2010-05-01

Landsat satellite has provided a continuous record of earth observation since 1972, gradually improving sensors (i.e. MSS, TM and ETM+). Already processed archives of Landsat image are now available free of charge from the internet. The Landsat image of 30 m spatial resolution with multiple spectral bands between 450 and 2350 nm is appropriate for detailed mapping of natural resource at wide geographical areas. However, one of the biggest concerns in the use of Landsat image is the uncertainty in the timing of acquisitions. Although detection of land cover change usually requires acquisitions before and after the change, the Landsat image is often unavailable because of the long-term intervals (16 days) and variation in atmosphere. Nearly cloud-free image is acquired at least once per year (total of 22 or 23 scenes per year). Therefore, it may be difficult to acquire appropriate images for monitoring natural disturbances caused at short-term intervals (e.g., flood, forest fire and hurricanes). Our objectives are: (1) to examine whether a time-series of Landsat image is available for monitoring a flood disaster, and (2) to evaluate the impact and timing of the flood disaster around Lena river in Siberia. A set of Landsat TM/ETM+ satellite images was used to enable acquisition of cloud-free image, although Landsat ETM+ images include failure of the Scan Line Corrector (SLC) from May 2003. The overlap area of a time series of 20 Landsat TM/ETM+ images (path 120-122, row 17) from April 2007 to August 2007 was clipped (approximately 33 km × 90 km), and the other area was excluded from the analyses. Image classification was performed on each image separately using an unsupervised ISODATA method, and each Landsat TM/ETM+ image was classified into three land cover types: (1) ice, (2) water, and (3) land. From three land cover types, the area of Lena river was estimated. The area of Lena river dramatically changed after spring breakup. The middle part of Lena river around

Perspective View with Landsat Overlay, Costa Rica

Science.gov (United States)

2002-01-01

This perspective view shows the Caribbean coastal plain of Costa Rica, with the Cordillera Central rising in the background and the Pacific Ocean in the distance. The prominent river in the center of the image is the Rio Sucio, which merges with the Rio Sarapiqui at the bottom of the image and eventually joins with Rio San Juan on the Nicaragua border.Like much of Central America, Costa Rica is generally cloud covered so very little satellite imagery is available. The ability of the Shuttle Radar Topography Mission (SRTM) instrument to penetrate clouds and make three-dimensional measurements will allow generation of the first complete high-resolution topographic map of the entire region. These data were used to generate the image.This three-dimensional perspective view was generated using elevation data from SRTM and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices

A COMPARISON OF HAZE REMOVAL ALGORITHMS AND THEIR IMPACTS ON CLASSIFICATION ACCURACY FOR LANDSAT IMAGERY

Directory of Open Access Journals (Sweden)

Yang Xiao

Full Text Available The quality of Landsat images in humid areas is considerably degraded by haze in terms of their spectral response pattern, which limits the possibility of their application in using visible and near-infrared bands. A variety of haze removal algorithms have been proposed to correct these unsatisfactory illumination effects caused by the haze contamination. The purpose of this study was to illustrate the difference of two major algorithms (the improved homomorphic filtering (HF and the virtual cloud point (VCP for their effectiveness in solving spatially varying haze contamination, and to evaluate the impacts of haze removal on land cover classification. A case study with exploiting large quantities of Landsat TM images and climates (clear and haze in the most humid areas in China proved that these haze removal algorithms both perform well in processing Landsat images contaminated by haze. The outcome of the application of VCP appears to be more similar to the reference images compared to HF. Moreover, the Landsat image with VCP haze removal can improve the classification accuracy effectively in comparison to that without haze removal, especially in the cloudy contaminated area

How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?

Directory of Open Access Journals (Sweden)

Warren B. Cohen

2017-03-01

Full Text Available Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms. Many of these algorithms take advantage of the high temporal data volume to mine subtle signals in Landsat time series, but as those signals become subtler, they are more likely to be mixed with noise in Landsat data. This study examines the similarity among seven different algorithms in their ability to map the full range of magnitudes of forest disturbance over six different Landsat scenes distributed across the conterminous US. The maps agreed very well in terms of the amount of undisturbed forest over time; however, for the ~30% of forest mapped as disturbed in a given year by at least one algorithm, there was little agreement about which pixels were affected. Algorithms that targeted higher-magnitude disturbances exhibited higher omission errors but lower commission errors than those targeting a broader range of disturbance magnitudes. These results suggest that a user of any given forest disturbance map should understand the map’s strengths and weaknesses (in terms of omission and commission error rates, with respect to the disturbance targets of interest.

Use of Landsat data to predict the trophic state of Minnesota lakes

Science.gov (United States)

Lillesand, T. M.; Johnson, W. L.; Deuell, R. L.; Lindstrom, O. M.; Meisner, D. E.

1983-01-01

Near-concurrent Landsat Multispectral Scanner (MSS) and ground data were obtained for 60 lakes distributed in two Landsat scene areas. The ground data included measurement of secchi disk depth, chlorophyll-a, total phosphorous, turbidity, color, and total nitrogen, as well as Carlson Trophic State Index (TSI) values derived from the first three parameters. The Landsat data best correlated with the TSI values. Prediction models were developed to classify some 100 'test' lakes appearing in the two analysis scenes on the basis of TSI estimates. Clouds, wind, poor image data, small lake size, and shallow lake depth caused some problems in lake TSI prediction. Overall, however, the Landsat-predicted TSI estimates were judged to be very reliable for the secchi-derived TSI estimation, moderately reliable for prediction of the chlorophyll-a TSI, and unreliable for the phosphorous value. Numerous Landsat data extraction procedures were compared, and the success of the Landsat TSI prediction models was a strong function of the procedure employed.

Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

Science.gov (United States)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

2015-12-01

Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

Science.gov (United States)

Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.

2014-12-01

Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

Science.gov (United States)

Clark, J.

1981-01-01

In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

Simulation assessment of continuous simulating moving bed chromatography process with partial feed and new strategy with partial feed

Directory of Open Access Journals (Sweden)

H. Khan

2009-09-01

Full Text Available Partial Feed simulating moving bed (SMB has proved to be more efficient in binary separation performance (purity, recovery, productivity because of its two additional degrees of freedom, namely feed length and feed time, as compared to classical SMB process. The binary separation of dextran T6 and fructose with linear isotherm is modeled with Aspen Chromatography simulator in a four zone SMB with one column per zone for both normal-feed and Partial Feed. Increase in number of feed length and feed time in the cycle plays a very important role in the separation performance with Partial Feed. In addition, the effect of mode of operation (early or late introduction of increase in number of feed length in the cycle on product purity and recovery is also investigated. Furthermore, the binary separation system is designed with the safety margin method and the optimum operating parameters for simulation are calculated with triangle theory. Finally, a new strategy with Partial Feed is developed, showing improved separation performance relative to the basic four-zone SMB with regard to extract stream purity and recovery. The results of the proposed study can served as a useful summary of Partial Feed operation.

Landsat surface reflectance quality assurance extraction (version 1.7)

Science.gov (United States)

Jones, J.W.; Starbuck, M.J.; Jenkerson, Calli B.

2013-01-01

The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.

Geological interpretation of Landsat TM imagery and aeromagnetic survey data, northern Precordillera region, Argentina

Science.gov (United States)

Chernicoff, C. J.; Nash, C. R.

2002-03-01

This case study demonstrates a methodology for obtaining maximum geoscientific value from reconnaissance (1000 m line spacing) aeromagnetic data through integration with high-resolution satellite imagery. In this study, lithostratigraphic interpretation of optimally processed Landsat TM data at reconnaissance mapping scale (1:100,000) has been carried out as a precursor to geophysical interpretation, providing the basic 'framework' in which to view the imaged geophysical data. The Landsat-derived framework shows the correct positions and vergences of major structures, which characterize this part of the Andean foreland thrust-and-fold belt. Within the structural framework derived from satellite imagery, the locations of major shallow-source aeromagnetic anomalies related to intermediate/mafic extrusive and subvolcanic rocks and the controlling structures of these economically important magmatic events can be correctly interpreted. Results of the study indicate a significant, coherent, and previously unrecognized post-Permian, pre-Miocene volcanic/subvolcanic center, which is probably associated with regional sinistral strike-slip along a reactivated N-S accretionary suture and a pre-existing Precambrian/Paleozoic basement structure. Subsequent west-vergent thick-skinned thrusting associated with uplift of Sierra Valle Fertil Precambrian block has developed a set of distinctive NW-oriented strike-slip faults at the site of the volcanic center. The NW structures cut and rotate late Miocene thin-skinned structures associated with the Precordillera fold-and-thrust belt. Intrusive rocks associated with the inferred Oligocene volcanic center form easily recognizable, partially remanent dipole anomalies, are associated with alteration and Au mineralization (Cerro Guachi, El Pescado, Gnrl. Belgrano mines), and are located along NW-oriented sinistral splay faults. The strike-slip related tectonic/magmatic event is currently regarded as Oligocene in age and may correlate

Fire monitoring capability of the joint Landsat and Sentinel 2 constellation

Science.gov (United States)

Murphy, S.; Wright, R.

2017-12-01

Fires are a global hazard. Landsat and Sentinel 2 can monitor the Earth's surface every 2 - 4 days. This provides an important opportunity to complement the operational (lower resolution) fire monitoring systems. Landsat-class sensors can detect small fires that would be missed by MODIS-classed sensors. All large fires start out as small fires. We analyze fire patterns in California from 1984 to 2017 and compare the performance of Landsat-type and MODIS-type sensors. Had an operational Landsat-Sentinel 2 fire detection system been in place at the time of the Soberanes fire last year (i.e. August 2016), the cost of suppressing of this fire event (US $236 million) could potentially have been reduced by an order of magnitude.

Cloud detection algorithm comparison and validation for operational Landsat data products

Science.gov (United States)

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate

Landsat Remote Sensing Data as an Alternative Approach for ...

African Journals Online (AJOL)

Rungwe Volcanic Province (RVP) is mostly covered by extrusive rocks that overlain the Precambrian basement. The use of Landsat data in this area has revealed the need of effective use of these data in geological mapping programs in Tanzania. Landsat band ratios 5/1, 3/7, 5/7 and 5/4 as well as R: G: B composite ...

Techniques for the creation of land use maps and tabulations from Landsat imagery

Science.gov (United States)

Angelici, G. L.; Bryant, N. A.

1977-01-01

Methods for creating color thematic maps and land use tabulations, employing both Landsat imagery and computer image processing, are discussed. The system, the Multiple Input Land Use System (MILUS) has been tested in the metropolitan section of Dayton, Ohio. Training areas for land use were first digitized by coordinates and then transformed onto an image of white lines on a black background. This image was added to a Landsat image of the same area. Then multispectral classification was performed. A tape of digitized census tract boundaries was computer interfaced to yield an image of tract boundaries on a background registered to the thematic land-use map. Using a data management system, the data were then used to produce figures for the area and percent of land use in each tract. Future work is expected to convert most of the steps into interactive processing. This would greatly reduce the time needed to edit and register the data sets.

Remote sensing of species diversity using Landsat 8 spectral variables

Science.gov (United States)

Madonsela, Sabelo; Cho, Moses Azong; Ramoelo, Abel; Mutanga, Onisimo

2017-11-01

The application of remote sensing in biodiversity estimation has largely relied on the Normalized Difference Vegetation Index (NDVI). The NDVI exploits spectral information from red and near infrared bands of Landsat images and it does not consider canopy background conditions hence it is affected by soil brightness which lowers its sensitivity to vegetation. As such NDVI may be insufficient in explaining tree species diversity. Meanwhile, the Landsat program also collects essential spectral information in the shortwave infrared (SWIR) region which is related to plant properties. The study was intended to: (i) explore the utility of spectral information across Landsat-8 spectrum using the Principal Component Analysis (PCA) and estimate alpha diversity (α-diversity) in the savannah woodland in southern Africa, and (ii) define the species diversity index (Shannon (H‧), Simpson (D2) and species richness (S) - defined as number of species in a community) that best relates to spectral variability on the Landsat-8 Operational Land Imager dataset. We designed 90 m × 90 m field plots (n = 71) and identified all trees with a diameter at breast height (DbH) above 10 cm. H‧, D2 and S were used to quantify tree species diversity within each plot and the corresponding spectral information on all Landsat-8 bands were extracted from each field plot. A stepwise linear regression was applied to determine the relationship between species diversity indices (H‧, D2 and S) and Principal Components (PCs), vegetation indices and Gray Level Co-occurrence Matrix (GLCM) texture layers with calibration (n = 46) and test (n = 23) datasets. The results of regression analysis showed that the Simple Ratio Index derivative had a higher relationship with H‧, D2 and S (r2= 0.36; r2= 0.41; r2= 0.24 respectively) compared to NDVI, EVI, SAVI or their derivatives. Moreover the Landsat-8 derived PCs also had a higher relationship with H‧ and D2 (r2 of 0.36 and 0.35 respectively) than the

What Can We Learn About Glaciers and Ice Sheets From 30 Years of Landsat Imagery?

Science.gov (United States)

Gardner, A. S.; Scambos, T.; Fahnestock, M. A.; Moholdt, G.; Nilsson, J.

2015-12-01

Glacier and ice sheets are known to be rapidly changing and currently account for two thirds of observed sea level rise. Attributing the causes of the rapid decline in land ice requires separation of mass change processes, i.e. accumulation of precipitation, meltwater runoff, and solid ice discharge. Here we examine a 30 year record of Landsat imagery to determine trends in glacier velocity at a global scale in an attempt to identify anomalies in glacier flow that are contributing to changes in land ice mass. The Landsat archive represents a treasure trove of information with hundreds of thousands of images acquired over glaciers and ice sheets during the past 30 years. Gleaning useful and consistent surface displacement information from a multiple sensor archive that is heavily contaminated by cloud, saturated images, poorly resolved sensor geometry, and data gaps has proved challenging. Temporal stacking of displacement fields (Dehecq et al., 2015) and correcting for unresolved topography (Roseanau et al., 2012) have been shown to greatly improve derived velocities. Here we present results from a global processing of the complete Landsat archive for information on glacier surface displacements. We highlight patterns of coherent regional change as well as well as rapid basin-scale changes in glacier flow.

A Cubesat enabled Spatio-Temporal Enhancement Method (CESTEM) utilizing Planet, Landsat and MODIS data

KAUST Repository

Houborg, Rasmus; McCabe, Matthew

2018-01-01

using a multi-scale target sampling scheme that draws Landsat 8 reference data from a series of scenes by using MODIS-consistent surface reflectance time series to quantify relative changes in Landsat-scale reflectances over given Landsat

Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat

Data.gov (United States)

National Aeronautics and Space Administration — The Global Human Built-up And Settlement Extent (HBASE) Dataset from Landsat is a global map of HBASE derived from the Global Land Survey (GLS) Landsat dataset for...

Landsat: A global land-imaging mission

Science.gov (United States)

,

2012-01-01

Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.

LANDSAT-1 data, its use in a soil survey program

Science.gov (United States)

Westin, F. C.; Frazee, C. J.

1975-01-01

The following applications of LANDSAT imagery were investigated: assistance in recognizing soil survey boundaries, low intensity soil surveys, and preparation of a base map for publishing thematic soils maps. The following characteristics of LANDSAT imagery were tested as they apply to the recognition of soil boundaries in South Dakota and western Minnesota: synoptic views due to the large areas covered, near-orthography and lack of distortion, flexibility of selecting the proper season, data recording in four parts of the spectrum, and the use of computer compatible tapes. A low intensity soil survey of Pennington County, South Dakota was completed in 1974. Low intensity inexpensive soil surveys can provide the data needed to evaluate agricultural land for the remaining counties until detailed soil surveys are completed. In using LANDSAT imagery as a base map for publishing thematic soil maps, the first step was to prepare a mosaic with 20 LANDSAT scenes from several late spring passes in 1973.

Landsat as a Political Entity: Meaningful Communication for a National Asset

Science.gov (United States)

Rocchio, L. E.

2010-12-01

Understanding the health of our planet on a global scale is essential to the world’s populace. Earth-observing satellites have long been collecting data that enable a robust comprehension of Earth’s complex and interconnected systems. Despite these important contributions, the fleet of U.S. Earth-observing satellites is aging and operational status for most onboard sensors has not materialized. These satellites are imperative objective viewers of our changing planet as we try to monitor and deal with natural disasters, carbon budgeting, water consumption, and food production. But the satellite building and launching process needed to sustain an operational observatory is extremely political. Landsat, the oldest civilian land-observing satellite, has a long and checkered political past, and it is only because of a handful of political champions that the program has endured. This begs the question: are policymakers aware of the contributions of satellites to our national wellbeing? And if not, can the science community better communicate with the general public at large and policy makers in particular? Here Landsat is examined as a political entity and the six pillars of effective science communication (context, trust, dialogue, clarity, respect, nuance) are used to develop, refine, and analyze a fact sheet and case study that explain the importance of Landsat Earth-observation to our society.

An Analysis LANDSAT-4 Thematic Mapper Geometric Properties

Science.gov (United States)

Walker, R. E.; Zobrist, A. L.; Bryant, N. A.; Gokhman, B.; Friedman, S. Z.; Logan, T. L.

1984-01-01

LANDSAT Thematic Mapper P-data of Washington, D. C., Harrisburg, PA, and Salton Sea, CA are analyzed to determine magnitudes and causes of error in the geometric conformity of the data to known Earth surface geometry. Several tests of data geometry are performed. Intraband and interband correlation and registration are investigated, exclusive of map based ground truth. The magnitudes and statistical trends of pixel offsets between a single band's mirror scans (due to processing procedures) are computed, and the inter-band integrity of registration is analyzed. A line to line correlation analysis is included.

2017 Landsat Science Team Summer Meeting Summary

Science.gov (United States)

Crawford, Christopher J.; Loveland, Thomas R.; Wulder, Michael A.; Irons, James R.

2018-01-01

The summer meeting of the U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) was held June 11-13, 2017, at the USGS’s Earth Resources Observation and Science (EROS) Center near Sioux Falls, SD. This was the final meeting of the Second (2012-2017) LST.1 Frank Kelly [EROS—Center Director] welcomed the attendees and expressed his thanks to the LST members for their contributions. He then introduced video-recorded messages from South Dakota’s U.S. senators, John Thune and Mike Rounds, in which they acknowledged the efforts of the team in advancing the societal impacts of the Landsat Program.

Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin

Science.gov (United States)

Senay, Gabriel; Friedrichs, MacKenzie O.; Singh, Ramesh K.; Velpuri, Naga Manohar

2016-01-01

removal of contaminated pixels, the ability to reliably estimate ET over clouded areas remains an important challenge. Overall, the performance of Landsat 8 based ET compared to available EC datasets and water balance estimates for a complex basin such as the CRB demonstrates the potential of using Landsat 8 for annual water use estimation at a national scale. Future efforts will focus on (a) use of consistent methodology across years, (b) integration of multiple sensors to maximize images used, and (c) employing cloud-computing platforms for large scale processing capabilities.

Monitoring the turbidity and surface temperature changes and effects of the 17 August 1999 earthquake in the Izmit Gulf, Turkey by the Landsat TM/ETM data.

Science.gov (United States)

Tüfekçi, Kenan; Akman, A Unal

2005-09-01

The temporal turbidity and surface temperature changes and effects of the 17 August 1999 earthquake in the Izmit Gulf, Turkey have been investigated using Landsat TM/ETM data. The gulf is in the Mediterranean-Black Sea transition climatic zone and is partially surrounded by green vegetation cover and degraded and densely urbanized-industrialized areas. Landsat TM/ETM data acquired in 1990-1999 confirms increase in turbidity. Turbidity is always low in the southern part and high in the northern part of the gulf, because the more urbanized and industrialized areas are located in the northern part. The Landsat-7 ETM data acquired in the same year (1999) shows seasonal changes in turbidity. Moreover, the two high turbidity and surface temperature anomalies, one of which is parallel to the 17 August 1999 earthquake surface rupture (east-west) and the other which is in the northwest-southeast direction were mapped from Landsat-5 TM data acquired the day (18.08.1999) following the earthquake in the east end of the gulf. On the basis of turbidity implying the sea bottom movement, it is possible to state that a second rupture in the northwest and southeast direction could have occurred at the sea bottom during the earthquake. The distribution of the seismicity centers and the orientation of the lineaments in the area support this finding.

A Harmonized Landsat-Sentinel-2 Surface Reflectance product: a resource for Agricultural Monitoring

Science.gov (United States)

Masek, J. G.; Claverie, M.; Ju, J.; Vermote, E.; Justice, C. O.

2015-12-01

The combination of Landsat and Sentinel-2 data offers a unique opportunity to observe globally the land every 2-3 days at medium (reflectance data from Landsat and Sentinel-2 missions and to deliver them to the community in a combined, seamless form. The HLS will be beneficial for global agricultural monitoring applications that require medium spatial resolution and weekly or more frequent observations. In particular, the provided opportunity to track crop phenology at the scale of individual fields will support detailed mapping of crop type and type-specific vegetation conditions. To create a compatible set of radiometric measurements, the HLS product relies on rigorous pre- and post-launch cross-calibration (Landsat-8 OLI and Sentinel-2 MSI) activities. The processing chain includes the following components: atmospheric correction, cloud/shadow masking, nadir BRDF-adjustment, spectral-adjustment, regridding, and temporal composite. The atmospheric correction and cloud masking is based on the OLI atmospheric correction developed at NASA-GSFC and has been adapted to the MSI data. The BRDF-adjustment is based on a disaggregation technique using MODIS-based BRDF coefficients. The technique has been evaluated using the multi-angular acquisition from the SPOT 4 and 5 (Take5) experiments. The spectral-adjustment relies on a linear regression that has been calibrated and evaluated using synthetic data and surface reflectance processed from a large number of hyperspectral EO-1 Hyperion scenes. Finally, significant effort is placed on product validation and evaluation. The delivered data set will include surface reflectance products at different levels: Using the native gridding, i.e. UTM, 30m for Landsat-8, and UTM, 10-20m for Sentinel-2 Using a common global gridding (Sinusoidal, 30m) Temporal composite (Sinusoidal, 30m, 5-day) During the first year of operation of Sentinel-2A, the HLS will be prototyped over a selection of 30 sites that includes some of the JECAM sites

Users, uses, and value of Landsat satellite imagery: results from the 2012 survey of users

Science.gov (United States)

Miller, Holly M.; Richardson, Leslie A.; Koontz, Stephen R.; Loomis, John; Koontz, Lynne

2013-01-01

Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). Social scientists at the USGS Fort Collins Science Center conducted an extensive survey in early 2012 to explore who uses Landsat imagery, how they use the imagery, and what the value of the imagery is to them. The survey was sent to all users registered with USGS who had accessed Landsat imagery in the year prior to the survey and over 11,000 current Landsat imagery users responded. The results of the survey revealed that respondents from many sectors use Landsat imagery in myriad project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance of and dependence on the imagery, the numerous environmental and societal benefits observed from projects using Landsat imagery, the potential negative impacts on users’ work if Landsat imagery was no longer available, and the substantial aggregated annual economic benefit from the imagery. These results represent only the value of Landsat to users registered with USGS; further research would help to determine what the value of the imagery is to a greater segment of the population, such as downstream users of the imagery and imagery-derived products.

An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band

Directory of Open Access Journals (Sweden)

Jordi Cristóbal

2018-03-01

Full Text Available Land surface temperature (LST is one of the sources of input data for modeling land surface processes. The Landsat satellite series is the only operational mission with more than 30 years of archived thermal infrared imagery from which we can retrieve LST. Unfortunately, stray light artifacts were observed in Landsat-8 TIRS data, mostly affecting Band 11, currently making the split-window technique impractical for retrieving surface temperature without requiring atmospheric data. In this study, a single-channel methodology to retrieve surface temperature from Landsat TM and ETM+ was improved to retrieve LST from Landsat-8 TIRS Band 10 using near-surface air temperature (Ta and integrated atmospheric column water vapor (w as input data. This improved methodology was parameterized and successfully evaluated with simulated data from a global and robust radiosonde database and validated with in situ data from four flux tower sites under different types of vegetation and snow cover in 44 Landsat-8 scenes. Evaluation results using simulated data showed that the inclusion of Ta together with w within a single-channel scheme improves LST retrieval, yielding lower errors and less bias than models based only on w. The new proposed LST retrieval model, developed with both w and Ta, yielded overall errors on the order of 1 K and a bias of −0.5 K validated against in situ data, providing a better performance than other models parameterized using w and Ta or only w models that yielded higher error and bias.

Kerr Reservoir LANDSAT experiment analysis for March 1981

Science.gov (United States)

Lecroy, S. R. (Principal Investigator)

1982-01-01

LANDSAT radiance data were used in an experiment conducted on the waters of Kerr Reservoir to determine if reliable algorithms could be developed that relate water quality parameters to remotely sensed data. A mix of different types of algorithms using the LANDSAT bands was generated to provide a thorough understanding of the relationships among the data involved. Except for secchi depth, the study demonstrated that for the ranges measured, the algorithms that satisfactorily represented the data encompass a mix of linear and nonlinear forms using only one LANDSAT band. Ratioing techniques did not improve the results since the initial design of the experiment minimized the errors against which this procedure is effective. Good correlations were found for total suspended solids, iron, turbidity, and secchi depth. Marginal correlations were discovered for nitrate and tannin + lignin. Quantification maps of Kerr Reservoir are presented for many of the water quality parameters using the developed algorithms.

Geologic mapping using LANDSAT data

Science.gov (United States)

Siegal, B. S.; Abrams, M. J.

1976-01-01

The feasibility of automated classification for lithologic mapping with LANDSAT digital data was evaluated using three classification algorithms. The two supervised algorithms analyzed, a linear discriminant analysis algorithm and a hybrid algorithm which incorporated the Parallelepiped algorithm and the Bayesian maximum likelihood function, were comparable in terms of accuracy; however, classification was only 50 per cent accurate. The linear discriminant analysis algorithm was three times as efficient as the hybrid approach. The unsupervised classification technique, which incorporated the CLUS algorithm, delineated the major lithologic boundaries and, in general, correctly classified the most prominent geologic units. The unsupervised algorithm was not as efficient nor as accurate as the supervised algorithms. Analysis of spectral data for the lithologic units in the 0.4 to 2.5 microns region indicated that a greater separability of the spectral signatures could be obtained using wavelength bands outside the region sensed by LANDSAT.

Assessing the value of Landsat imagery: Results from a 2012 comprehensive user survey

Science.gov (United States)

Miller, H. M.; Richardson, L.; Loomis, J.; Koontz, S.; Koontz, L.

2012-12-01

Landsat satellite imagery has long been recognized as unique among remotely sensed data due to the combination of its extensive archive, global coverage, and relatively high spatial and temporal resolution. Since the imagery became available at no cost in 2008, the number of users registered with the U.S. Geological Survey (USGS) has increased tenfold while the number of scenes downloaded annually has increased a hundredfold. It is clear that the imagery is being used extensively, and understanding the benefits provided by this imagery can help inform decisions involving its provision. However, the value of Landsat imagery is difficult to measure for a variety of reasons, one of which stems from the fact that the imagery has characteristics of a public good and does not have a direct market price to reflect its value to society. Further, there is not a clear understanding of the full range of users of the imagery, as well as how these users are distributed across the many different end uses this data is applied to. To assess the value of Landsat imagery, we conducted a survey of users registered with USGS in early 2012. Over 11,000 current users of Landsat imagery responded to the survey. The value of the imagery was measured both qualitatively and quantitatively. To explore the qualitative value of the imagery, users were asked about the importance of the imagery to their work, their dependence on the imagery, and the impacts on their work if there was no Landsat imagery. The majority of users deemed Landsat imagery important to their work and stated they were dependent on Landsat imagery to do their work. Additionally, if Landsat imagery was no longer available, over half of the users would have to discontinue some of their work. On average, these users would discontinue half of their current work if the imagery was no longer available. The focus of this presentation will be the quantitative results of a double-bounded contingent valuation analysis which reveals

LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003

Data.gov (United States)

National Aeronautics and Space Administration — This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final...

LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final...

Using ecological zones to increase the detail of Landsat classifications

Science.gov (United States)

Fox, L., III; Mayer, K. E.

1981-01-01

Changes in classification detail of forest species descriptions were made for Landsat data on 2.2 million acres in northwestern California. Because basic forest canopy structures may exhibit very similar E-M energy reflectance patterns in different environmental regions, classification labels based on Landsat spectral signatures alone become very generalized when mapping large heterogeneous ecological regions. By adding a seven ecological zone stratification, a 167% improvement in classification detail was made over the results achieved without it. The seven zone stratification is a less costly alternative to the inclusion of complex collateral information, such as terrain data and soil type, into the Landsat data base when making inventories of areas greater than 500,000 acres.

Filling Landsat ETM+ SLC-off gaps using a segmentation model approach

Science.gov (United States)

Maxwell, Susan

2004-01-01

The purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in size from two pixels near the center of the image to 14 pixels along the east and west edges. Even with the scan gaps, the radiometric and geometric qualities of the remaining portions of the image still meet design specifications and therefore contain useful information (see http:// landsat7.usgs.gov for additional information). The U.S. Geological Survey EROS Data Center (EDC) is evaluating several techniques to fill the gaps in SLC-off data to enhance the usability of the imagery (Howard and Lacasse 2004) (PE&RS, August 2004). The method presented here uses a segmentation model approach that allows for same-scene spectral data to be used to fill the gaps. The segment model is generated from a complete satellite image with no missing spectral data (e.g., Landsat 5, Landsat 7 SLCon, SPOT). The model is overlaid on the Landsat SLC-off image, and the missing data within the gaps are then estimated using SLC-off spectral data that intersect the segment boundary. A major advantage of this approach is that the gaps are filled using spectral data derived from the same SLC-off satellite image.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

Science.gov (United States)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Landsat...

Progress Towards a 2012 Landsat Launch

Science.gov (United States)

Irons, Jim; Sabelhaus, Phil; Masek, Jeff; Cook, Bruce; Dabney, Phil; Loveland, Tom

2012-01-01

The Landsat Data Continuity Mission (LDCM) is on schedule for a December 2012 launch date. The mission is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). NASA leads the development and launch of the satellite observatory while leads ground system development. USGS will assume responsibility for operating the satellite and for collecting, archiving, and distributing the LDCM data following launch. When launched the satellite will carry two sensors into orbit. The Operational Land Imager (OLI) will collect data for nine shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will coincidently collect data for two thermal infrared bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it?s manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space Flight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The ground data processing system is in development at the USGS Earth Resources Observation and Science (EROS) Center. The presentation will describe the LDCM satellite system, provide the status of system development, and present prelaunch performance data for OLI and TIRS. The USGS has committed to renaming the satellite as Landsat 8 following launch.

Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio

International Nuclear Information System (INIS)

Bloemer, H.H.L.; Brumfield, J.; Campbell, W.J.

1981-01-01

Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing

An integrtated approach to the use of Landsat TM data for gold exploration in west central Nevada

Science.gov (United States)

Mouat, D. A.; Myers, J. S.; Miller, N. L.

1987-01-01

This paper represents an integration of several Landsat TM image processing techniques with other data to discriminate the lithologies and associated areas of hydrothermal alteration in the vicinity of the Paradise Peak gold mine in west central Nevada. A microprocessor-based image processing system and an IDIMS system were used to analyze data from a 512 X 512 window of a Landsat-5 TM scene collected on June 30, 1984. Image processing techniques included simple band composites, band ratio composites, principal components composites, and baseline-based composites. These techniques were chosen based on their ability to discriminate the spectral characteristics of the products of hydrothermal alteration as well as of the associated regional lithologies. The simple band composite, ratio composite, two principal components composites, and the baseline-based composites separately can define the principal areas of alteration. Combined, they provide a very powerful exploration tool.

Perspective with Landsat Overlay, Mount Kilimanjaro, Tanzania

Science.gov (United States)

2002-01-01

Mount Kilimanjaro (Kilima Njaro or 'shining mountain' in Swahili), the highest point in Africa, reaches 5,895 meters (19,340 feet) above sea level, tall enough to maintain a permanent snow cap despite being just 330 kilometers (210 miles) south of the equator. It is the tallest free-standing mountain on the Earth's land surface world, rising about 4,600 meters (15,000 feet) above the surrounding plain. Kilimanjaro is a triple volcano (has three peaks) that last erupted perhaps more than 100,000 years ago but still exudes volcanic gases. It is accompanied by about 20 other nearby volcanoes, some of which are seen to the west (left) in this view, prominently including Mount Meru, which last erupted only about a century ago. The volcanic mountain slopes are commonly fertile and support thick forests, while the much drier grasslands of the plains are home to elephants, lions, and other savanna wildlife.This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM), a Landsat 7 satellite image, and a false sky. Topographic expression is vertically exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and

Analysis and correction of Landsat 4 and 5 Thematic Mapper Sensor Data

Science.gov (United States)

Bernstein, R.; Hanson, W. A.

1985-01-01

Procedures for the correction and registration and registration of Landsat TM image data are examined. The registration of Landsat-4 TM images of San Francisco to Landsat-5 TM images of the San Francisco using the interactive geometric correction program and the cross-correlation technique is described. The geometric correction program and cross-correlation results are presented. The corrections of the TM data to a map reference and to a cartographic database are discussed; geometric and cartographic analyses are applied to the registration results.

Mapping burned areas using dense time-series of Landsat data

Science.gov (United States)

Hawbaker, Todd J.; Vanderhoof, Melanie; Beal, Yen-Ju G.; Takacs, Joshua; Schmidt, Gail L.; Falgout, Jeff T.; Williams, Brad; Brunner, Nicole M.; Caldwell, Megan K.; Picotte, Joshua J.; Howard, Stephen M.; Stitt, Susan; Dwyer, John L.

2017-01-01

Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables (ECVs), including information about burned area. In this paper, we present an algorithm that identifies burned areas in dense time-series of Landsat data to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm uses gradient boosted regression models to generate burn probability surfaces using band values and spectral indices from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Burn classifications are generated from the burn probability surfaces using pixel-level thresholding in combination with a region growing process. The algorithm can be applied anywhere Landsat and training data are available. For this study, BAECV products were generated for the conterminous United States from 1984 through 2015. These products consist of pixel-level burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability and a burn classification. We compared the BAECV burn classification products to the existing Global Fire Emissions Database (GFED; 1997–2015) and Monitoring Trends in Burn Severity (MTBS; 1984–2013) data. We found that the BAECV products mapped 36% more burned area than the GFED and 116% more burned area than MTBS. Differences between the BAECV products and the GFED were especially high in the West and East where the

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Science.gov (United States)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will

Three-dimensional displays for natural hazards analysis, using classified Landsat Thematic Mapper digital data and large-scale digital elevation models

Science.gov (United States)

Butler, David R.; Walsh, Stephen J.; Brown, Daniel G.

1991-01-01

Methods are described for using Landsat Thematic Mapper digital data and digital elevation models for the display of natural hazard sites in a mountainous region of northwestern Montana, USA. Hazard zones can be easily identified on the three-dimensional images. Proximity of facilities such as highways and building locations to hazard sites can also be easily displayed. A temporal sequence of Landsat TM (or similar) satellite data sets could also be used to display landscape changes associated with dynamic natural hazard processes.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

Science.gov (United States)

Barry T. Wilson; Joseph F. Knight; Ronald E. McRoberts

2018-01-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several...

Heat capacity mapping mission (HCMM) thermal surface water mapping and its correlation to LANDSAT

International Nuclear Information System (INIS)

Colvocoresses, A.P.

1980-03-01

Graphics are presented which show HCMM mapped water-surface temperature in Lake Anna, a 13,000 dendrically-shaped lake which provides cooling for a nuclear power plant in Virginia. The HCMM digital data, produced by NASA were processed by NOAA/NESS into image and line-printer form. A LANDSAT image of the lake illustrates the relationship between MSS band 7 data and the HCMM data as processed by the NASA image processing facility which transforms the data to the same distortion-free hotline oblique Mercator projection. Spatial correlation of the two images is relatively simple by either digital or analog means and the HCMM image has a potential accuracy approaching the 80 m of the original LANDSAT data. While it is difficult to get readings that are not diluted by radiation from cooler adjacent land areas in narrow portions of the lake, digital data indicated by the line-printer display five different temperatures for open-water areas. Where the water surface response was not diluted by land areas, the temperature difference recorded by HCMM corresponds to in situ readings with rsme on the order of 1 C

Evaluation of directional normalization methods for Landsat TM/ETM+ over primary Amazonian lowland forests

Science.gov (United States)

Van doninck, Jasper; Tuomisto, Hanna

2017-06-01

Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross-Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration.

Flood mapping from Sentinel-1 and Landsat-8 data: a case study from river Evros, Greece

Science.gov (United States)

Kyriou, Aggeliki; Nikolakopoulos, Konstantinos

2015-10-01

Floods are suddenly and temporary natural events, affecting areas which are not normally covered by water. The influence of floods plays a significant role both in society and the natural environment, therefore flood mapping is crucial. Remote sensing data can be used to develop flood map in an efficient and effective way. This work is focused on expansion of water bodies overtopping natural levees of the river Evros, invading the surroundings areas and converting them in flooded. Different techniques of flood mapping were used using data from active and passive remote sensing sensors like Sentinlel-1 and Landsat-8 respectively. Space borne pairs obtained from Sentinel-1 were processed in this study. Each pair included an image during the flood, which is called "crisis image" and another one before the event, which is called "archived image". Both images covering the same area were processed producing a map, which shows the spread of the flood. Multispectral data From Landsat-8 were also processed in order to detect and map the flooded areas. Different image processing techniques were applied and the results were compared to the respective results of the radar data processing.

a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

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Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

A Landsat study of water quality in Lake Okeechobee

Science.gov (United States)

Gervin, J. C.; Marshall, M. L.

1976-01-01

This paper uses multiple regression techniques to investigate the relationship between Landsat radiance values and water quality measurements. For a period of over one year, the Central and Southern Florida Flood Control District sampled the water of Lake Okeechobee for chlorophyll, carotenoids, turbidity, and various nutrients at the time of Landsat overpasses. Using an overlay map of the sampling stations, Landsat radiance values were measured from computer compatible tapes using a GE image 100 and averaging over a 22-acre area at each station. These radiance values in four bands were used to form a number of functions (powers, logarithms, exponentials, and ratios), which were then compared with the ground measurements using multiple linear regression techniques. Several dates were used to provide generality and to study possible seasonal variations. Individual correlations were presented for the various water quality parameters and best fit equations were examined for chlorophyll and turbidity. The results and their relationship to past hydrological research were discussed.

An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

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Ainong Li

2015-05-01

Full Text Available Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM images. The model employed Normalized Difference Vegetation Index (NDVI thresholds to approximately divide land targets into eleven groups, due to NDVI’s lower sensitivity to topography and its significant role in indicating land cover type. Within each group of terrestrial targets, corresponding MODIS BRDF (Bidirectional Reflectance Distribution Function products were used to account for land surface’s BRDF effect, and topographic effects are corrected without Lambertian assumption. The methodology was tested with two TM scenes of severely rugged mountain areas acquired under different sun elevation angles. Results demonstrated that reflectance of sun-averted slopes was evidently enhanced, and the overall quality of images was improved with topographic effect being effectively suppressed. Correlation coefficients between Near Infra-Red band reflectance and illumination condition reduced almost to zero, and coefficients of variance also showed some reduction. By comparison with the other two physics-based models (Sandmeier model and Li model, the proposed model showed favorable results on two tested Landsat scenes. With the almost half-century accumulation of Landsat data and the successive launch and operation of Landsat 8, the improved model in this paper can be potentially helpful for the topographic correction of Landsat and Landsat-like data.

Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery

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Samuel Hislop

2018-03-01

Full Text Available Satellite earth observation is being increasingly used to monitor forests across the world. Freely available Landsat data stretching back four decades, coupled with advances in computer processing capabilities, has enabled new time-series techniques for analyzing forest change. Typically, these methods track individual pixel values over time, through the use of various spectral indices. This study examines the utility of eight spectral indices for characterizing fire disturbance and recovery in sclerophyll forests, in order to determine their relative merits in the context of Landsat time-series. Although existing research into Landsat indices is comprehensive, this study presents a new approach, by comparing the distributions of pre and post-fire pixels using Glass’s delta, for evaluating indices without the need of detailed field information. Our results show that in the sclerophyll forests of southeast Australia, common indices, such as the Normalized Difference Vegetation Index (NDVI and the Normalized Burn Ratio (NBR, both accurately capture wildfire disturbance in a pixel-based time-series approach, especially if images from soon after the disturbance are available. However, for tracking forest regrowth and recovery, indices, such as NDVI, which typically capture chlorophyll concentration or canopy ‘greenness’, are not as reliable, with values returning to pre-fire levels in 3–5 years. In comparison, indices that are more sensitive to forest moisture and structure, such as NBR, indicate much longer (8–10 years recovery timeframes. This finding is consistent with studies that were conducted in other forest types. We also demonstrate that additional information regarding forest condition, particularly in relation to recovery, can be extracted from less well known indices, such as NBR2, as well as textural indices incorporating spatial variance. With Landsat time-series gaining in popularity in recent years, it is critical to

Analysis of Coastline Extraction from Landsat-8 OLI Imagery

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Yaolin Liu

2017-10-01

Full Text Available Coastline extraction is a fundamental work for coastal resource management, coastal environmental protection and coastal sustainable development. Due to the free access and long-term record, Landsat series images have the potential to be used for coastline extraction. However, dynamic features of different types of coastlines (e.g., rocky, sandy, artificial, caused by sea level fluctuation from tidal, storm and reclamation, make it difficult to be accurately extracted with coarse spatial resolution, e.g., 30 m, of Landsat images. To access this problem, we analyze the performance of coastline extraction by integrating downscaling, pansharpening and water index approaches in increasing the accuracy of coastline extraction from the latest Landsat-8 Operational Land Imager (OLI imagery. In order to prove the availability of the proposed method, we designed three strategies: (1 Strategy 1 uses the traditional water index method to extract coastline directly from original 30 m Landsat-8 OLI multispectral (MS image; (2 Strategy 2 extracts coastlines from 15 m fused MS images generated by integrating 15 m panchromatic (PAN band and 30 m MS image with ten pansharpening algorithms; (3 Strategy 3 first downscales the PAN band to a finer spatial resolution (e.g., 7.5 m band, and then extracts coastlines from pansharpened MS images generated by integrating downscaled spatial resolution PAN band and 30 m MS image with ten pansharpening algorithms. Using the coastline extracted from ZiYuan-3 (ZY-3 5.8 m MS image as reference, accuracies of coastlines extracted from MS images in three strategies were validated visually and quantitatively. The results show that, compared with coastline extracted directly from 30 m Landsat-8 MS image (strategy 1, strategy 3 achieves the best accuracies with optimal mean net shoreline movement (MNSM of −2.54 m and optimal mean absolute difference (MAD of 11.26 m, followed by coastlines extracted in strategy 2 with optimal MNSM

The Landsat Phenology Study (LaPS): Preliminary CONUS Results for 2008

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Henebry, Geoffrey M.; Roy, David P.; Ju, Junchang; Kovalskyy, Valeriy

2010-05-01

Most studies of land surface phenology (LSP) have used time series derived from moderate spatial resolution satellite sensor data (e.g., AVHRR, MODIS, VEGETATION) because these data are freely available and because they provide an acceptable trade-off between higher, near daily, temporal frequency of observation needed to reduce cloud contamination against lower (500m-5km) spatial resolution. The recent opening of the USGS Landsat archive to web-enabled access presents the opportunity to explore how well Landsat time series can portray LSPs at high spatial resolution. The NASA Web-enabled Landsat data (WELD) project (http://landsat.usgs.gov/WELD.php) has produced 30m composited mosaics for all the conterminous US (CONUS) from Landsat 7 ETM+ data. The composited mosaics are generated on monthly, seasonal, and annual basis and include spectral reflectance, normalized difference vegetation index (NDVI), and the acquisition date of each composited pixel. The WELD compositing approach is designed to select valid land surface observations with minimal cloud, snow, and atmospheric contamination. We extracted 30m pixel time series from the twelve monthly WELD composited mosaics for 2008 at 320 locations across the CONUS where we have ground phenological observations that are heterogeneous with respect to the types of plants observed, the phenophases recorded (predominantly spring green-up) and the ground sampling protocols used. The ground data came from several sources, including the cloned lilac/honeysuckle network, the Phenocam network, five LTER sites (H.J. Andrews, Harvard Forest, Jornada, Konza Prairie, and Sevilleta), and a private woodlot in Maine. Temporal profiles of the 30m WELD Landsat NDVI, the green NDVI (GNDVI), the normalized difference infrared index (NDII) derived from the composited reflectances, are compared to the ground observations. Results show that (i) inclusion of the Landsat acquisition date for each pixel improves the characterization of the LSP

Forest Disturbance Mapping Using Dense Synthetic Landsat/MODIS Time-Series and Permutation-Based Disturbance Index Detection

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David Frantz

2016-03-01

Full Text Available Spatio-temporal information on process-based forest loss is essential for a wide range of applications. Despite remote sensing being the only feasible means of monitoring forest change at regional or greater scales, there is no retrospectively available remote sensor that meets the demand of monitoring forests with the required spatial detail and guaranteed high temporal frequency. As an alternative, we employed the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM to produce a dense synthetic time series by fusing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS nadir Bidirectional Reflectance Distribution Function (BRDF adjusted reflectance. Forest loss was detected by applying a multi-temporal disturbance detection approach implementing a Disturbance Index-based detection strategy. The detection thresholds were permutated with random numbers for the normal distribution in order to generate a multi-dimensional threshold confidence area. As a result, a more robust parameterization and a spatially more coherent detection could be achieved. (i The original Landsat time series; (ii synthetic time series; and a (iii combined hybrid approach were used to identify the timing and extent of disturbances. The identified clearings in the Landsat detection were verified using an annual woodland clearing dataset from Queensland’s Statewide Landcover and Trees Study. Disturbances caused by stand-replacing events were successfully identified. The increased temporal resolution of the synthetic time series indicated promising additional information on disturbance timing. The results of the hybrid detection unified the benefits of both approaches, i.e., the spatial quality and general accuracy of the Landsat detection and the increased temporal information of synthetic time series. Results indicated that a temporal improvement in the detection of the disturbance date could be achieved relative to the irregularly spaced Landsat

Landsat change detection can aid in water quality monitoring

Science.gov (United States)

Macdonald, H. C.; Steele, K. F.; Waite, W. P.; Shinn, M. R.

1977-01-01

Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico

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Jarchow, Christopher J.; Didan, Kamel; Barreto-Muñoz, Armando; Glenn, Edward P.

2018-01-01

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area. PMID:29757265

USING LANDSAT IMAGES IN MAPPING AND MONITORING WATER BODIES IN MĂGURA BASIN

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MEREUȚĂ M.

2015-03-01

Full Text Available The work is part of a wider range of interdisciplinary studies undertaken in Măgura catchment, a right-side tributary of Bahlui River. The Măgura River flows from the massif Great Hill-Hârlău. Before the year 2000 there were 11 lakes, and today are only 4. The purpose of this project is to determine the accuracy of the simple techniques in digital image processing for mapping and monitoring lakes and wetlands. Landsat 7 ETM + and Landsat 8 OLI TIRS data sets are used. The paper highlights the bands’ thematic classification accuracy using minimum technical and digital (software resources. The water bodies’ delineated boundaries of each digital classification procedure were compared with the limits obtained by digitizing the topographical plans (1973 and aerial images (2008. The comparisons show that the Landsat data can be used to map accurately the water bodies. It is a simple method of determining the silting degree, especially for lakes with an area of at least 1 ha. Măgura basin has a high archaeological potential (prehistory up to the modern period, part of the national and international cultural heritage. Creating a GIS database, in order to analyze the human-environment relationship, began by studying the hydrological variables. This factor has an important role in the society’s development, both prehistoric and current.

Modified Optimization Water Index (mowi) for LANDSAT-8 Oli/tirs

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Moradi, M.; Sahebi, M.; Shokri, M.

2017-09-01

Water is one of the most important resources that essential need for human life. Due to population growth and increasing need of human to water, proper management of water resources will be one of the serious challenges of next decades. Remote sensing data is the best way to the management of water resources due time and cost effectiveness over a greater range of temporal and spatial scales. Between many kinds of satellite data, from SAR to optic or from high resolution to low resolution, Landsat imagery is more interesting data for water detection and management of earth surface water. Landsat8 OLI/TIRS is the newest version of Landsat satellite series. In this paper, we investigated the full spectral potential of Landsat8 for water detection. It is developed many kinds of methods for this purpose that index based methods have some advantages than other methods. Pervious indices just use a limited number of spectral band. In this paper, Modified Optimization Water Index (MOWI) defined by consideration of a linear combination of bands that each coefficient of bands calculated by particle swarm algorithm. The result shows that modified optimization water index (MOWI) has a proper performance on different condition like cloud, cloud shadow and mountain shadow.

From stochastic processes to numerical methods: A new scheme for solving reaction subdiffusion fractional partial differential equations

Energy Technology Data Exchange (ETDEWEB)

Angstmann, C.N.; Donnelly, I.C. [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia); Henry, B.I., E-mail: B.Henry@unsw.edu.au [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia); Jacobs, B.A. [School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, Private Bag 3, Wits 2050 (South Africa); DST–NRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-MaSS) (South Africa); Langlands, T.A.M. [Department of Mathematics and Computing, University of Southern Queensland, Toowoomba QLD 4350 (Australia); Nichols, J.A. [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia)

2016-02-15

We have introduced a new explicit numerical method, based on a discrete stochastic process, for solving a class of fractional partial differential equations that model reaction subdiffusion. The scheme is derived from the master equations for the evolution of the probability density of a sum of discrete time random walks. We show that the diffusion limit of the master equations recovers the fractional partial differential equation of interest. This limiting procedure guarantees the consistency of the numerical scheme. The positivity of the solution and stability results are simply obtained, provided that the underlying process is well posed. We also show that the method can be applied to standard reaction–diffusion equations. This work highlights the broader applicability of using discrete stochastic processes to provide numerical schemes for partial differential equations, including fractional partial differential equations.

Comparison of Landsat-8 and Sentinel-2A reflectance and normalized difference vegetation index

Science.gov (United States)

Zhang, H.; Roy, D. P.; Yan, L.; Li, Z.; Huang, H.

2017-12-01

The moderate spatial resolution satellite data from the polar-orbiting Landsat-8 (launched 2013) and Sentinel-2A (launched 2015) sensors provide 10 m to 30 m multi-spectral global coverage with a better than 5-day revisit. Although a national laboratory traceable cross-calibration comparison of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2A MultiSpectral Instrument (MSI) was undertaken pre-launch, there are a number of other sensor differences, notably due to spectral, spatial and angular differences. To examine these in a comprehensive way, Landsat-8 and Sentinel-2A data for approximately 20° × 10° of southern Africa acquired in the summer (January to March) and winter (July to September) of 2016 were compared. Only Landsat-8 and Sentinel-2A observations acquired within one-day apart were considered. The sensor data were registered and then each orbit projected into 30 m fixed global Web Enabled Landsat Data (GWELD) tiles defined in the MODIS sinusoidal equal area projection. Only corresponding sensor observations of each 30 m tile pixel that were flagged as cloud and snow-free, unsaturated, and that had no significant change in their one day separation, were compared. Both the Landsat-8 and Sentinel-2A data were atmospherically corrected using the Landsat Surface Reflectance Code (LaSRC) and were also corrected to nadir BRDF adjusted reflectance (NBAR). Top of atmosphere and surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared OLI and MSI bands, and derived normalized difference vegetation index (NDVI), were compared and their differences quantified using regression analyses. The resulting statistical transformations may be used to improve the consistency between the Landsat-8 OLI and Sentinel-2A MSI data. The importance and sensitivity of the results to correct filtering, atmospheric correction and adjustment to NBAR is demonstrated.

Cádiz bay walers lurbidily varialions from Landsat TM images analysis

OpenAIRE

Gutiérrez Mas, José Manuel; Luna del Barco, A.; Parrado Román, J. M.; Sánchez, E.; Fernández Palacios, A.; Ojeda, J.

1999-01-01

Landsat TM images has been analysed to obtain extent and direction data about turbidity flumes in several hydrodinamic sinoptic situations in Cadiz bay waters. Results are beside data from water samples. Five turbidity levels has been differentiated: very high turbidity, high, middle, low and very low, and three geographic sectors: a) Inner zone, closed to coast and with shoal waters of high and very high turbidity. This sector is very affected by littoral processes (tidals, surge and contine...

Landsat-based monitoring of crop water demand in the San Joaquin Valley

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Johnson, L.; Trout, T.; Wang, D.; Melton, F. S.

2010-12-01

Fresh water resources are becoming increasingly scarce in California due to urbanization, environmental regulation, and groundwater depletion. The strain is projected to worsen under various climate change scenarios and is exacerbated by declining water delivery infrastructure. It is estimated that irrigated agriculture currently commands more than 70% of the state’s water supply, and many growers are striving to improve water use efficiency in order to help maintain the state’s rich agricultural heritage. Remote sensing technology offers the potential to monitor cropland evapotranspiration (ET) regionally, while making farm-based irrigation scheduling more practical, convenient, and possibly more accurate. Landsat5-TM imagery was used in this study to monitor basal crop evapotranspiration (ETcb), which is primarily related to plant transpiration, for several San Joaquin Valley fields throughout the 2008 growing season. A ground-based digital camera was used to measure fractional cover of 48 study fields planted to 18 different crop types (row crops, grains, orchard, and vineyard) of varying maturity over 12 dates coinciding with Landsat overpasses. Landsat L1T terrain-corrected images were atmospherically corrected to surface reflectance by an implementation of the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS), then converted to normalized difference vegetation index (NDVI) on a per-pixel basis. A strong linear relationship between NDVI and fractional cover was observed (r2=0.96), and a resulting conversion equation was used to transform all imagery to fractional cover. Conversion equations previously developed by use of weighting lysimeters were then used to transform fractional cover to basal crop coefficient (Kcb; ratio of crop transpiration plus a small diffusive soil evaporation component to reference ET). Finally, measurements of grass reference ET (ETo) from the California Irrigation Management Information System were used to

Monitoring of urban growth in the state of Hidalgo using Landsat images

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Laura Cano Salinas

2017-03-01

Given this background, this paper is focused on the generation of geographic information for regional urban planning and the overall aim is to examine urban growth rate during the period 2000-2014 in the state of Hidalgo, Mexico and identify potential areas of expansion from Landsat images. The methodology was based on techniques of remote sensing and Geographical Information System (GIS. The inputs used were six Landsat scenes: three for 2000 year and three for 2014. Image processing was performed on ERDAS Imagine® 9.1 and the spatial analysis of urban coverage statewide on ArcGIS 10.0 by ESRI®. First, the radiometric correction was made and we obtained the urban polygons of the 2000 year through of supervised classification. The 2014 urban layer was digitized manually due to the spectral incompatibility between the bands of the Landsat sensor 5 and 7, and the Landsat sensor 8. Then, we build a road density map and the spatial relationship of the urban centers with the road influence area was evaluated. For the year 2000, 103 urban polygons were mapped, whilst for 2014 were identified ten polygons more with a mapped minimum area of 24 ha. The main results indicated that in the state has increased 72.3 km2 urban area from 2000 to 2014. This represents an average growth rate of 1.8% per year. The most widespread municipalities are located in the region of Valle del Mezquital, however, Mineral de la Reforma, Tetepango, Tizayuca and Pachuca showed growth rates of 183.44%, 102% 94% and 68.5% in fourteen years, respectively. According to the road map density, these municipalities are located in areas of greatest influence of infrastructure as the Arco Norte highway in the state. The above findings, lead us to conclude that the Mezquital Valley and the Basin of Mexico are potential areas of urban spreading and it is associated with road development in the Central Mexico.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

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Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Use of LANDSAT data to define soil boundaries in Carroll County, Missouri

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Davidson, S. E.

1981-01-01

Bands 4, 5 and 7 false color composite photographs were prepared using data from LANDSAT scenes acquired during April 1977 and April 1981 on computer compatible tapes, and these color composites were compared with band 7 black and white photographs prepared for the entire county. Delineations of soil boundaries at the soil association level were achieved using LANDSAT spectral reflectance data and slope maps for a portion of Carroll County, Missouri. Forty two spectral reflectance classes from April 1977 LANDSAT data were overlaid on digitized slope maps of nine USGS 7.5 minute series topographic quadrangle slope maps to achieve boundary delineations of the soil associations.

A Partially Observed Markov Decision Process for Dynamic Pricing

OpenAIRE

Yossi Aviv; Amit Pazgal

2005-01-01

In this paper, we develop a stylized partially observed Markov decision process (POMDP) framework to study a dynamic pricing problem faced by sellers of fashion-like goods. We consider a retailer that plans to sell a given stock of items during a finite sales season. The objective of the retailer is to dynamically price the product in a way that maximizes expected revenues. Our model brings together various types of uncertainties about the demand, some of which are resolvable through sales ob...

Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

Science.gov (United States)

Scaramuzza, Pat; Bouchard, M.A.; Dwyer, John L.

2012-01-01

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

Continuous-flow processes for the catalytic partial hydrogenation reaction of alkynes

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Carmen Moreno-Marrodan

2017-04-01

Full Text Available The catalytic partial hydrogenation of substituted alkynes to alkenes is a process of high importance in the manufacture of several market chemicals. The present paper shortly reviews the heterogeneous catalytic systems engineered for this reaction under continuous flow and in the liquid phase. The main contributions appeared in the literature from 1997 up to August 2016 are discussed in terms of reactor design. A comparison with batch and industrial processes is provided whenever possible.

SPOT: How good for geology? A comparison with LANDSAT MSS

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Sesoeren, A.

1986-12-01

Geological interpretation possibilities of SPOT MSS and LANDSAT MSS positive prints enlarged to the same scale were compared, using as a test area part of the Jebel Amour (Algeria). The SPOT imagery offers many advantages, filling the gap between remote sensing from space and aerial photography. The best results by visual interpretation are obtained in combining SPOT for the required details with LANDSAT for the synoptic veiw. Further improvements are expected from the use of SPOT stereo-pairs.

Validation of the USGS Landsat Burned Area Essential Climate Variable (BAECV) across the conterminous United States

Science.gov (United States)

Vanderhoof, Melanie; Fairaux, Nicole; Beal, Yen-Ju G.; Hawbaker, Todd J.

2017-01-01

The Landsat Burned Area Essential Climate Variable (BAECV), developed by the U.S. Geological Survey (USGS), capitalizes on the long temporal availability of Landsat imagery to identify burned areas across the conterminous United States (CONUS) (1984–2015). Adequate validation of such products is critical for their proper usage and interpretation. Validation of coarse-resolution products often relies on independent data derived from moderate-resolution sensors (e.g., Landsat). Validation of Landsat products, in turn, is challenging because there is no corresponding source of high-resolution, multispectral imagery that has been systematically collected in space and time over the entire temporal extent of the Landsat archive. Because of this, comparison between high-resolution images and Landsat science products can help increase user's confidence in the Landsat science products, but may not, alone, be adequate. In this paper, we demonstrate an approach to systematically validate the Landsat-derived BAECV product. Burned area extent was mapped for Landsat image pairs using a manually trained semi-automated algorithm that was manually edited across 28 path/rows and five different years (1988, 1993, 1998, 2003, 2008). Three datasets were independently developed by three analysts and the datasets were integrated on a pixel by pixel basis in which at least one to all three analysts were required to agree a pixel was burned. We found that errors within our Landsat reference dataset could be minimized by using the rendition of the dataset in which pixels were mapped as burned if at least two of the three analysts agreed. BAECV errors of omission and commission for the detection of burned pixels averaged 42% and 33%, respectively for CONUS across all five validation years. Errors of omission and commission were lowest across the western CONUS, for example in the shrub and scrublands of the Arid West (31% and 24%, respectively), and highest in the grasslands and

Improving the mapping of crop types in the Midwestern U.S. by fusing Landsat and MODIS satellite data

Science.gov (United States)

Zhu, Likai; Radeloff, Volker C.; Ives, Anthony R.

2017-06-01

Mapping crop types is of great importance for assessing agricultural production, land-use patterns, and the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat's sensors images are optimized for cropland monitoring. However, accurate mapping of crop types requires frequent cloud-free images during the growing season, which are often not available, and this raises the question of whether Landsat data can be combined with data from other satellites. Here, our goal is to evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one or two images from all cloud-free Landsat observations available for the Arlington Agricultural Research Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used each combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Both the original Landsat and STARFM-predicted images were then classified with a support vector machine (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two original Landsat images of each combination only, 2) classifying the one or two original Landsat images plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images together with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as the input of STARFM did not significantly improve the STARFM predictions compared to using only one, and predictions using Landsat images between July and August as input were most accurate. Including all STARFM-predicted images together with the Landsat images significantly increased average classification error by 4% points (from 21% to 25%) compared to using only Landsat

Fusion of MODIS and landsat-8 surface temperature images: a new approach.

Science.gov (United States)

Hazaymeh, Khaled; Hassan, Quazi K

2015-01-01

Here, our objective was to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS); and implement the developed algorithm over a heterogeneous semi-arid study area in Jordan, Middle East. The STI-FM technique consisted of two major components: (i) establishing a linear relationship between two consecutive MODIS 8-day composite LST images acquired at time 1 and time 2; and (ii) utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat-8 LST image at time 2. It revealed that strong linear relationships (i.e., r2, slopes, and intercepts were in the range 0.93-0.94, 0.94-0.99; and 2.97-20.07) existed between the two consecutive MODIS LST images. We evaluated the synthetic LST images qualitatively and found high visual agreements with the actual Landsat-8 LST images. In addition, we conducted quantitative evaluations of these synthetic images; and found strong agreements with the actual Landsat-8 LST images. For example, r2, root mean square error (RMSE), and absolute average difference (AAD)-values were in the ranges 084-0.90, 0.061-0.080, and 0.003-0.004, respectively.

The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)

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Slonecker, Terry; Jones, Daniel K.; Pellerin, Brian A.

2016-01-01

Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles.

The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM).

Science.gov (United States)

Slonecker, E Terrence; Jones, Daniel K; Pellerin, Brian A

2016-06-30

Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles. Published by Elsevier Ltd.

Updating stand-level forest inventories using airborne laser scanning and Landsat time series data

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Bolton, Douglas K.; White, Joanne C.; Wulder, Michael A.; Coops, Nicholas C.; Hermosilla, Txomin; Yuan, Xiaoping

2018-04-01

Vertical forest structure can be mapped over large areas by combining samples of airborne laser scanning (ALS) data with wall-to-wall spatial data, such as Landsat imagery. Here, we use samples of ALS data and Landsat time-series metrics to produce estimates of top height, basal area, and net stem volume for two timber supply areas near Kamloops, British Columbia, Canada, using an imputation approach. Both single-year and time series metrics were calculated from annual, gap-free Landsat reflectance composites representing 1984-2014. Metrics included long-term means of vegetation indices, as well as measures of the variance and slope of the indices through time. Terrain metrics, generated from a 30 m digital elevation model, were also included as predictors. We found that imputation models improved with the inclusion of Landsat time series metrics when compared to single-year Landsat metrics (relative RMSE decreased from 22.8% to 16.5% for top height, from 32.1% to 23.3% for basal area, and from 45.6% to 34.1% for net stem volume). Landsat metrics that characterized 30-years of stand history resulted in more accurate models (for all three structural attributes) than Landsat metrics that characterized only the most recent 10 or 20 years of stand history. To test model transferability, we compared imputed attributes against ALS-based estimates in nearby forest blocks (>150,000 ha) that were not included in model training or testing. Landsat-imputed attributes correlated strongly to ALS-based estimates in these blocks (R2 = 0.62 and relative RMSE = 13.1% for top height, R2 = 0.75 and relative RMSE = 17.8% for basal area, and R2 = 0.67 and relative RMSE = 26.5% for net stem volume), indicating model transferability. These findings suggest that in areas containing spatially-limited ALS data acquisitions, imputation models, and Landsat time series and terrain metrics can be effectively used to produce wall-to-wall estimates of key inventory attributes, providing an

Perspective View with Landsat Overlay, Lakes Managua and Nicaragua

Science.gov (United States)

2002-01-01

This perspective view shows Lakes Managua and Nicaragua near the Pacific coast of Nicaragua. Lake Managua is the 65-kilometer (40-mile)-long fresh water lake in the foreground of this south-looking view, emptying via the Tipitapa River into the much larger Lake Nicaragua in the distance. The capital city of Managua, with a population of more than 500,000, is located along the southern shore of Lake Managua, the area with the highest population density in Nicaragua.The physical setting of Lake Managua is dominated by the numerous volcanic features aligned in a northwest-southeast axis. The cone-like feature in the foreground is Momotombo, a 1,280-meter (4,199-foot)-high stratovolcano located on the northwest end of the lake. Two water-filled volcanic craters (Apoyegue and Jiloa volcanoes) reside on the Chiltepe Peninsula protruding into the lake from the west. Two volcanoes can also be seen on the island of Ometepe in Lake Nicaragua: El Maderas rising to 1,394 meters (4,573 feet) and the active El Conception at 1,610 meters (5,282 feet).This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar

Using Landsat-derived disturbance history (1972-2010) to predict current forest structure

Science.gov (United States)

Dirk Pflugmacher; Warren B. Cohen; Robert E. Kennedy

2012-01-01

Lidar is currently the most accurate method for remote estimation of forest structure, but it has limited spatial and temporal coverage. Conversely, Landsat data are more widely available, but exhibit a weaker relationship with structure under medium to high leaf area conditions. One potentially valuable means of enhancing the relationship between Landsat reflectance...

IceTrendr: a linear time-series approach to monitoring glacier environments using Landsat

Science.gov (United States)

Nelson, P.; Kennedy, R. E.; Nolin, A. W.; Hughes, J. M.; Braaten, J.

2017-12-01

Arctic glaciers in Alaska and Canada have experienced some of the greatest ice mass loss of any region in recent decades. A challenge to understanding these changing ecosystems, however, is developing globally-consistent, multi-decadal monitoring of glacier ice. We present a toolset and approach that captures, labels, and maps glacier change for use in climate science, hydrology, and Earth science education using Landsat Time Series (LTS). The core step is "temporal segmentation," wherein a yearly LTS is cleaned using pre-processing steps, converted to a snow/ice index, and then simplified into the salient shape of the change trajectory ("temporal signature") using linear segmentation. Such signatures can be characterized as simple `stable' or `transition of glacier ice to rock' to more complex multi-year changes like `transition of glacier ice to debris-covered glacier ice to open water to bare rock to vegetation'. This pilot study demonstrates the potential for interactively mapping, visualizing, and labeling glacier changes. What is truly innovative is that IceTrendr not only maps the changes but also uses expert knowledge to label the changes and such labels can be applied to other glaciers exhibiting statistically similar temporal signatures. Our key findings are that the IceTrendr concept and software can provide important functionality for glaciologists and educators interested in studying glacier changes during the Landsat TM timeframe (1984-present). Issues of concern with using dense Landsat time-series approaches for glacier monitoring include many missing images during the period 1984-1995 and that automated cloud mask are challenged and require the user to manually identify cloud-free images. IceTrendr is much more than just a simple "then and now" approach to glacier mapping. This process is a means of integrating the power of computing, remote sensing, and expert knowledge to "tell the story" of glacier changes.

Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

Science.gov (United States)

Zhu, Zhe

2017-08-01

The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

Electronic spreadsheet to acquire the reflectance from the TM and ETM+ Landsat images

Directory of Open Access Journals (Sweden)

Antonio R. Formaggio

2005-08-01

Full Text Available The reflectance of agricultural cultures and other terrestrial surface "targets" is an intrinsic parameter of these targets, so in many situations, it must be used instead of the values of "gray levels" that is found in the satellite images. In order to get reflectance values, it is necessary to eliminate the atmospheric interference and to make a set of calculations that uses sensor parameters and information regarding the original image. The automation of this procedure has the advantage to speed up the process and to reduce the possibility of errors during calculations. The objective of this paper is to present an electronic spreadsheet that simplifies and automatizes the transformation of the digital numbers of the TM/Landsat-5 and ETM+/Landsat-7 images into reflectance. The method employed for atmospheric correction was the dark object subtraction (DOS. The electronic spreadsheet described here is freely available to users and can be downloaded at the following website: http://www.dsr.inpe.br/Calculo_Reflectancia.xls.

Sun position calculator (SPC) for Landsat imagery with geodetic latitudes

Science.gov (United States)

Seong, Jeong C.

2015-12-01

Landsat imagery comes with sun position information such as azimuth and sun elevation, but they are available only at the center of a scene. To aid in the use of Landsat imagery for various solar radiation applications such as topographic correction, solar power, urban heat island, agriculture, climate and vegetation, it is necessary to calculate the sun position information at every pixel. This research developed a PC application that creates sun position data layers in ArcGIS at every pixel in a Landsat scene. The SPC program is composed of two major routines - converting universal transverse Mercator (UTM) projection coordinates to geographic longitudes and latitudes, and calculating sun position information based on the Meeus' routine. For the latter, an innovative method was also implemented to account for the Earth's flattening on an ellipsoid. The Meeus routine implemented in this research showed about 0.2‧ of mean absolute difference from the National Renewable Energy Laboratory (NREL) Solar Position Algorithm (SPA) routine when solar zenith and azimuth angles were tested with every 30 min data at four city locations (Fairbanks, Atlanta, Sydney and Rio Grande) on June 30, 2014. The Meeus routine was about ten times faster than the SPA routine. Professionals who need the Sun's position information for Landsat imagery will benefit from the SPC application.

Generating Global Leaf Area Index from Landsat: Algorithm Formulation and Demonstration

Science.gov (United States)

Ganguly, Sangram; Nemani, Ramakrishna R.; Zhang, Gong; Hashimoto, Hirofumi; Milesi, Cristina; Michaelis, Andrew; Wang, Weile; Votava, Petr; Samanta, Arindam; Melton, Forrest;

Application of spectrometer cropscan MSR 16R and Landsat imagery for identification the spectral characteristics of land cover

Science.gov (United States)

Tampubolon, Togi; Abdullah, Khiruddin bin; San, Lim Hwee

2013-09-01

The spectral characteristics of land cover are basic references in classifying satellite image for geophysics analysis. It can be obtained from the measurements using spectrometer and satellite image processing. The aims of this study to investigate the spectral characteristics of land cover based on the results of measurement using Spectrometer Cropscan MSR 16R and Landsat satellite imagery. The area of study in this research is in Medan, (Deli Serdang, North Sumatera) Indonesia. The scope of this study is the basic survey from the measurements of spectral land cover which is covered several type of land such as a cultivated and managed terrestrial areas, natural and semi-natural, cultivated aquatic or regularly flooded areas, natural and semi-natural aquatic, artificial surfaces and associated areas, bare areas, artificial waterbodies and natural waterbodies. The measurement and verification were conducted using a spectrometer provided their spectral characteristics and Landsat imagery, respectively. The results of the spectral characteristics of land cover shows that each type of land cover have a unique characteristic. The correlation of spectral land cover based on spectrometer Cropscan MSR 16R and Landsat satellite image are above 90 %. However, the land cover of artificial waterbodiese have a correlation under 40 %. That is because the measurement of spectrometer Cropscan MSR 16R and acquisition of Landsat satellite imagery has a time different.

Space science for applications - The history of Landsat

Science.gov (United States)

Mach, P. E.

1981-01-01

The history of the Landsat project is discussed in terms of three historical phases, each characterized by a dominant problem. From 1964 to 1967, the challenge was to develop interagency cooperation and to achieve consensus on basic plans for the satellite. Between 1968 and 1971, the cooperating agencies had to persuade the Bureau of the Budget to provide funding for the project. Since 1972, the challenge to NASA has been to encourage applications of the Landsat data and plan the shift from an experimental program to an operational one. The tension between experimental and operational goals has run through all these phases, and the conflicts between agencies is detailed, as well as the interaction between technological and political systems.

Combination of Landsat and Sentinel-2 MSI data for initial assessing of burn severity

Science.gov (United States)

Quintano, C.; Fernández-Manso, A.; Fernández-Manso, O.

2018-02-01

Nowadays Earth observation satellites, in particular Landsat, provide a valuable help to forest managers in post-fire operations; being the base of post-fire damage maps that enable to analyze fire impacts and to develop vegetation recovery plans. Sentinel-2A MultiSpectral Instrument (MSI) records data in similar spectral wavelengths that Landsat 8 Operational Land Imager (OLI), and has higher spatial and temporal resolutions. This work compares two types of satellite-based maps for evaluating fire damage in a large wildfire (around 8000 ha) located in Sierra de Gata (central-western Spain) on 6-11 August 2015. 1) burn severity maps based exclusively on Landsat data; specifically, on differenced Normalized Burn Ratio (dNBR) and on its relative versions (Relative dNBR, RdNBR, and Relativized Burn Ratio, RBR) and 2) burn severity maps based on the same indexes but combining pre-fire data from Landsat 8 OLI with post-fire data from Sentinel-2A MSI data. Combination of both Landsat and Sentinel-2 data might reduce the time elapsed since forest fire to the availability of an initial fire damage map. Interpretation of ortho-photograph Pléiades 1 B data (1:10,000) provided us the ground reference data to measure the accuracy of both burn severity maps. Results showed that Landsat based burn severity maps presented an adequate assessment of the damage grade (κ statistic = 0.80) and its spatial distribution in wildfire emergency response. Further using both Landsat and Sentinel-2 MSI data the accuracy of burn severity maps, though slightly lower (κ statistic = 0.70) showed an adequate level for be used by forest managers.

Shape selection in Landsat time series: A tool for monitoring forest dynamics

Science.gov (United States)

Gretchen G. Moisen; Mary C. Meyer; Todd A. Schroeder; Xiyue Liao; Karen G. Schleeweis; Elizabeth A. Freeman; Chris Toney

2016-01-01

We present a new methodology for fitting nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral band or index of choice in temporal Landsat data, our method delivers a smoothed rendition of...

Comparison of Sentinel-2A and Landsat-8 Nadir BRDF Adjusted Reflectance (NBAR) over Southern Africa

Science.gov (United States)

Li, J.; Roy, D. P.; Zhang, H.

2016-12-01

The Landsat satellites have been providing moderate resolution imagery of the Earth's surface for over 40 years with continuity provided by the Landsat 8 and planned Landsat 9 missions. The European Space Agency Sentinel-2 satellite was successfully launched into a polar sun-synchronous orbit in 2015 and carries the Multi Spectral Instrument (MSI) that has Landsat-like bands and acquisition coverage. These new sensors acquire images at view angles ± 7.5° (Landsat) and ± 10.3° (Sentinel-2) from nadir that result in small directional effects in the surface reflectance. When data from adjoining paths, or from long time series are used, a model of the surface anisotropy is required to adjust observations to a uniform nadir view (primarily for visual consistency, vegetation monitoring, or detection of subtle surface changes). Recently a generalized approach was published that provides consistent Landsat view angle corrections to provide nadir BRDF-adjusted reflectance (NBAR). Because the BRDF shapes of different terrestrial surfaces are sufficiently similar over the narrow 15° Landsat field of view, a fixed global set of MODIS BRDF spectral model parameters was shown to be adequate for Landsat NBAR derivation with little sensitivity to the land cover type, condition, or surface disturbance. This poster demonstrates the application of this methodology to Sentinel-2 data over a west-east transect across southern Africa. The reflectance differences between adjacent overlapping paths in the forward and backward scatter directions are quantified for both before and after BRDF correction. Sentinel-2 and Landsat-8 reflectance and NBAR inter-comparison results considering different stages of cloud and saturation filtering, and filtering to reduce surface state differences caused by acquisition time differences, demonstrate the utility of the approach. The relevance and limitations of the corrections for providing consistent moderate resolution reflectance are discussed.

Online Global Land Surface Temperature Estimation from Landsat

Directory of Open Access Journals (Sweden)

David Parastatidis

2017-11-01

Full Text Available This study explores the estimation of land surface temperature (LST for the globe from Landsat 5, 7 and 8 thermal infrared sensors, using different surface emissivity sources. A single channel algorithm is used for consistency among the estimated LST products, whereas the option of using emissivity from different sources provides flexibility for the algorithm’s implementation to any area of interest. The Google Earth Engine (GEE, an advanced earth science data and analysis platform, allows the estimation of LST products for the globe, covering the time period from 1984 to present. To evaluate the method, the estimated LST products were compared against two reference datasets: (a LST products derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer, as higher-level products based on the temperature-emissivity separation approach; (b Landsat LST data that have been independently produced, using different approaches. An overall RMSE (root mean square error of 1.52 °C was observed and it was confirmed that the accuracy of the LST product is dependent on the emissivity; different emissivity sources provided different LST accuracies, depending on the surface cover. The LST products, for the full Landsat 5, 7 and 8 archives, are estimated “on-the-fly” and are available on-line via a web application.

Perspective View with Landsat Overlay, Salt Lake City, Utah

Science.gov (United States)

2002-01-01

Most of the population of Utah lives just west of the Wasatch Mountains in the north central part of the state. This broad east-northeastward view shows that region with the cities of Ogden, Salt Lake City, and Provo seen from left to right. The Great Salt Lake (left) and Utah Lake (right) are quite shallow and appear greenish in this enhanced natural color view. Thousands of years ago ancient Lake Bonneville covered all of the lowlands seen here. Its former shoreline is clearly seen as a wave-cut bench and/or light colored 'bathtub ring' at several places along the base of the mountain front - evidence seen from space of our ever-changing planet.This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM), a Landsat 5 satellite image mosaic, and a false sky. Topographic expression is exaggerated four times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif

Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images

Directory of Open Access Journals (Sweden)

Weili Kou

2015-01-01

Full Text Available Accurate and updated finer resolution maps of rubber plantations and stand ages are needed to understand and assess the impacts of rubber plantations on regional ecosystem processes. This study presented a simple method for mapping rubber plantation areas and their stand ages by integration of PALSAR 50-m mosaic images and multi-temporal Landsat TM/ETM+ images. The L-band PALSAR 50-m mosaic images were used to map forests (including both natural forests and rubber trees and non-forests. For those PALSAR-based forest pixels, we analyzed the multi-temporal Landsat TM/ETM+ images from 2000 to 2009. We first studied phenological signatures of deciduous rubber plantations (defoliation and foliation and natural forests through analysis of surface reflectance, Normal Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, and Land Surface Water Index (LSWI and generated a map of rubber plantations in 2009. We then analyzed phenological signatures of rubber plantations with different stand ages and generated a map, in 2009, of rubber plantation stand ages (≤5, 6–10, >10 years-old based on multi-temporal Landsat images. The resultant maps clearly illustrated how rubber plantations have expanded into the mountains in the study area over the years. The results in this study demonstrate the potential of integrating microwave (e.g., PALSAR and optical remote sensing in the characterization of rubber plantations and their expansion over time.

A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction

OpenAIRE

Chiman Kwan; Bence Budavari; Feng Gao; Xiaolin Zhu

2018-01-01

We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution, whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images to yield high spatial and high temporal resolution images. Our approach consists of two steps. First, a mapping is established between two MODIS images, where one is at an earlier time, t1, and the...

SRTM Perspective View with Landsat Overlay: San Jose, Costa Rica

Science.gov (United States)

2001-01-01

This perspective view shows the capital city of San Jose, Costa Rica, in the right center of the image (gray area). Rising behind it are the volcanoes Irazu, 3402 meters high (11,161 feet) and Turrialba, 3330 meters high (10,925 feet.)Irazu is the highest volcano in Costa Rica and is located in the Irazu Volcano National Park, established in 1955. There have been at least 23 eruptions of Irazu since 1723, the most recent during 1963 to 1965. This activity sent tephra and secondary mudflows into cultivated areas, caused at least 40 deaths, and destroyed 400 houses and some factories.This image was generated in support of the Central American Commission for Environment and Development through an agreement with NASA. The Commission involves eight nations working to develop the Mesoamerican Biological Corridor, an effort to study and preserve some of the most biologically diverse regions of the planet.This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated 2X.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11,2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM

Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS

Directory of Open Access Journals (Sweden)

Said Nawar

2014-11-01

Full Text Available The monitoring of soil salinity levels is necessary for the prevention and mitigation of land degradation in arid environments. To assess the potential of remote sensing in estimating and mapping soil salinity in the El-Tina Plain, Sinai, Egypt, two predictive models were constructed based on the measured soil electrical conductivity (ECe and laboratory soil reflectance spectra resampled to Landsat sensor’s resolution. The models used were partial least squares regression (PLSR and multivariate adaptive regression splines (MARS. The results indicated that a good prediction of the soil salinity can be made based on the MARS model (R2 = 0.73, RMSE = 6.53, and ratio of performance to deviation (RPD = 1.96, which performed better than the PLSR model (R2 = 0.70, RMSE = 6.95, and RPD = 1.82. The models were subsequently applied on a pixel-by-pixel basis to the reflectance values derived from two Landsat images (2006 and 2012 to generate quantitative maps of the soil salinity. The resulting maps were validated successfully for 37 and 26 sampling points for 2006 and 2012, respectively, with R2 = 0.72 and 0.74 for 2006 and 2012, respectively, for the MARS model, and R2 = 0.71 and 0.73 for 2006 and 2012, respectively, for the PLSR model. The results indicated that MARS is a more suitable technique than PLSR for the estimation and mapping of soil salinity, especially in areas with high levels of salinity. The method developed in this paper can be used for other satellite data, like those provided by Landsat 8, and can be applied in other arid and semi-arid environments.

Assessment of Forest Degradation in Vietnam Using Landsat Time Series Data

Directory of Open Access Journals (Sweden)

James E. Vogelmann

2017-07-01

Full Text Available Landsat time series data were used to characterize forest degradation in Lam Dong Province, Vietnam. We conducted three types of image change analyses using Landsat time series data to characterize the land cover changes. Our analyses concentrated on the timeframe of 1973–2014, with much emphasis on the latter part of that range. We conducted a field trip through Lam Dong Province to develop a better understanding of the ground conditions of the region, during which we obtained many photographs of representative forest sites with Global Positioning System locations to assist us in our image interpretations. High-resolution Google Earth imagery and Landsat data of the region were used to validate results. In general, our analyses indicated that many land-use changes have occurred throughout Lam Dong Province, including gradual forest to non-forest transitions. Recent changes are most marked along the relatively narrow interfaces between agricultural and forest areas that occur towards the boundaries of the province. One important observation is that the most highly protected national reserves in the region have not changed much over the entire Landsat timeframe (1972–present. Spectral changes within these regions have not occurred at the same levels as those areas adjacent to the reserves.

Design and implementation of the next generation Landsat satellite communications system

Science.gov (United States)

Mah, Grant R.; O'Brien, Michael; Garon, Howard; Mott, Claire; Ames, Alan; Dearth, Ken

2012-01-01

The next generation Landsat satellite, Landsat 8 (L8), also known as the Landsat Data Continuity Mission (LDCM), uses a highly spectrally efficient modulation and data formatting approach to provide large amounts of downlink (D/L) bandwidth in a limited X-Band spectrum allocation. In addition to purely data throughput and bandwidth considerations, there were a number of additional constraints based on operational considerations for prevention of interference with the NASA Deep-Space Network (DSN) band just above the L8 D/L band, minimization of jitter contributions to prevent impacts to instrument performance, and the need to provide an interface to the Landsat International Cooperator (IC) community. A series of trade studies were conducted to consider either X- or Ka-Band, modulation type, and antenna coverage type, prior to the release of the request for proposal (RFP) for the spacecraft. Through use of the spectrally efficient rate-7/8 Low-Density Parity-Check error-correction coding and novel filtering, an XBand frequency plan was developed that balances all the constraints and considerations, while providing world-class link performance, fitting 384 Mbits/sec of data into the 375 MHz X-Band allocation with bit-error rates better than 10-12 using an earth-coverage antenna.

Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province, Iran

NARCIS (Netherlands)

Mohammdy, M.; Moradi, H.R.; Zeinivand, H.; Temme, A.J.A.M.; Pourghasemi, H.R.; Alizadeh, H.

2014-01-01

The Landsat series of satellites provides a valuable data source for land surface mapping and monitoring. Unfortunately, the scan line corrector (SLC) of the Landsat7 Enhanced Thematic Mapper plus (ETM+) sensor failed on May 13, 2003. This problem resulted in about 22 % of the pixels per scene not

Data fusion of Landsat TM and IRS images in forest classification

Science.gov (United States)

Guangxing Wang; Markus Holopainen; Eero Lukkarinen

2000-01-01

Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...

Continental-Scale Mapping of Adelie Penguin Colonies from Landsat Imagery

Science.gov (United States)

Schwaller, Mathew R.; Southwell, Colin; Emmerson, Louise

2013-01-01

Breeding distribution of the Adlie penguin, Pygoscelis adeliae, was surveyed with Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data in an area covering approximately 330 of longitude along the coastline of Antarctica.An algorithm was designed to minimize radiometric noise and to retrieve Adlie penguin colony location and spatial extent from the ETM+data. In all, 9143 individual pixels were classified as belonging to an Adlie penguin colony class out of the entire dataset of 195 ETM+ scenes, where the dimension of each pixel is 30 m by 30 m,and each scene is approximately 180 km by 180 km. Pixel clustering identified a total of 187 individual Adlie penguin colonies, ranging in size from a single pixel (900 sq m) to a maximum of 875 pixels (0.788 sq km). Colony retrievals have a very low error of commission, on the order of 1% or less, and the error of omission was estimated to be 3% to 4% by population based on comparisons with direct observations from surveys across east Antarctica. Thus, the Landsat retrievals successfully located Adlie penguin colonies that accounted for 96 to 97% of the regional population used as ground truth. Geographic coordinates and the spatial extent of each colony retrieved from the Landsat data are available publically. Regional analysis found several areas where the Landsat retrievals suggest populations that are significantly larger than published estimates. Six Adlie penguin colonies were found that are believed to be previously unreported in the literature.

Spatiotemporal Built-up Land Density Mapping Using Various Spectral Indices in Landsat-7 ETM+ and Landsat-8 OLI/TIRS (Case Study: Surakarta City)

Science.gov (United States)

Risky, Yanuar S.; Aulia, Yogi H.; Widayani, Prima

2017-12-01

Spectral indices variations support for rapid and accurate extracting information such as built-up density. However, the exact determination of spectral waves for built-up density extraction is lacking. This study explains and compares the capabilities of 5 variations of spectral indices in spatiotemporal built-up density mapping using Landsat-7 ETM+ and Landsat-8 OLI/TIRS in Surakarta City on 2002 and 2015. The spectral indices variations used are 3 mid-infrared (MIR) based indices such as the Normalized Difference Built-up Index (NDBI), Urban Index (UI) and Built-up and 2 visible based indices such as VrNIR-BI (visible red) and VgNIR-BI (visible green). Linear regression statistics between ground value samples from Google Earth image in 2002 and 2015 and spectral indices for determining built-up land density. Ground value used amounted to 27 samples for model and 7 samples for accuracy test. The classification of built-up density mapping is divided into 9 classes: unclassified, 0-12.5%, 12.5-25%, 25-37.5%, 37.5-50%, 50-62.5%, 62.5-75%, 75-87.5% and 87.5-100 %. Accuracy of built-up land density mapping in 2002 and 2015 using VrNIR-BI (81,823% and 73.235%), VgNIR-BI (78.934% and 69.028%), NDBI (34.870% and 74.365%), UI (43.273% and 64.398%) and Built-up (59.755% and 72.664%). Based all spectral indices, Surakarta City on 2000-2015 has increased of built-up land density. VgNIR-BI has better capabilities for built-up land density mapping on Landsat-7 ETM + and Landsat-8 OLI/TIRS.

Estimating suitable environments for invasive plant species across large landscapes: A remote sensing strategy using Landsat 7 ETM+

Science.gov (United States)

The key to reducing ecological and economic damage caused by invasive plant species is to locate and eradicate new invasions before they threaten native biodiversity and ecological processes. We used Landsat Enhanced Thematic Mapper Plus imagery to estimate suitable environments for four invasive pl...

Low-cost digital image processing at the University of Oklahoma

Science.gov (United States)

Harrington, J. A., Jr.

1981-01-01

Computer assisted instruction in remote sensing at the University of Oklahoma involves two separate approaches and is dependent upon initial preprocessing of a LANDSAT computer compatible tape using software developed for an IBM 370/158 computer. In-house generated preprocessing algorithms permits students or researchers to select a subset of a LANDSAT scene for subsequent analysis using either general purpose statistical packages or color graphic image processing software developed for Apple II microcomputers. Procedures for preprocessing the data and image analysis using either of the two approaches for low-cost LANDSAT data processing are described.

Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches

Directory of Open Access Journals (Sweden)

Yinghai Ke

2016-03-01

Full Text Available This study presented a MODIS 8-day 1 km evapotranspiration (ET downscaling method based on Landsat 8 data (30 m and machine learning approaches. Eleven indicators including albedo, land surface temperature (LST, and vegetation indices (VIs derived from Landsat 8 data were first upscaled to 1 km resolution. Machine learning algorithms including Support Vector Regression (SVR, Cubist, and Random Forest (RF were used to model the relationship between the Landsat indicators and MODIS 8-day 1 km ET. The models were then used to predict 30 m ET based on Landsat 8 indicators. A total of thirty-two pairs of Landsat 8 images/MODIS ET data were evaluated at four study sites including two in United States and two in South Korea. Among the three models, RF produced the lowest error, with relative Root Mean Square Error (rRMSE less than 20%. Vegetation greenness related indicators such as Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Soil Adjusted Vegetation Index (SAVI, and vegetation moisture related indicators such as Normalized Difference Infrared Index—Landsat 8 OLI band 7 (NDIIb7 and Normalized Difference Water Index (NDWI were the five most important features used in RF model. Temperature-based indicators were less important than vegetation greenness and moisture-related indicators because LST could have considerable variation during each 8-day period. The predicted Landsat downscaled ET had good overall agreement with MODIS ET (average rRMSE = 22% and showed a similar temporal trend as MODIS ET. Compared to the MODIS ET product, the downscaled product demonstrated more spatial details, and had better agreement with in situ ET observations (R2 = 0.56. However, we found that the accuracy of MODIS ET was the main control factor of the accuracy of the downscaled product. Improved coarse-resolution ET estimation would result in better finer-resolution estimation. This study proved the potential of using machine learning

Distinguishing Bark Beetle-infested Vegetation by Tree Species Types and Stress Levels using Landsat Data

Science.gov (United States)

Sivanpillai, R.; Ewers, B. E.; Speckman, H. N.; Miller, S. N.

2015-12-01

In the Western United States, more than 3 million hectares of lodgepole pine forests have been impacted by the Mountain pine beetle outbreak, while another 166,000 hectares of spruce-fir forests have been attacked by Spruce beetle. Following the beetle attack, the trees lose their hydraulic conductivity thus altering their carbon and water fluxes. These trees go through various stages of stress until mortality, described by color changes in their needles prior to losing them. Modeling the impact of these vegetation types require thematically precise land cover data that distinguishes lodgepole pine and spruce-fir forests along with the stage of impact since the ecosystem fluxes are different for these two systems. However, the national and regional-scale land cover datasets derived from remotely sensed data do not have this required thematic precision. We evaluated the feasibility of multispectral data collected by Landsat 8 to distinguish lodgepole pine and spruce fir, and subsequently model the different stages of attack using field data collected in Medicine Bow National Forest (Wyoming, USA). Operational Land Imager, onboard Landsat 8 has more spectral bands and higher radiometric resolution (12 bit) in comparison to sensors onboard earlier Landsat missions which could improve the ability to distinguish these vegetation types and their stress conditions. In addition to these characteristics, its repeat coverage, rigorous radiometric calibration, wide swath width, and no-cost data provide unique advantages to Landsat data for mapping large geographic areas. Initial results from this study highlight the importance of SWIR bands for distinguishing different levels of stress, and the need for ancillary data for distinguishing species types. Insights gained from this study could lead to the generation of land cover maps with higher thematic precision, and improve the ability to model various ecosystem processes as a result of these infestations.

Bayesian Method for Building Frequent Landsat-Like NDVI Datasets by Integrating MODIS and Landsat NDVI

OpenAIRE

Limin Liao; Jinling Song; Jindi Wang; Zhiqiang Xiao; Jian Wang

2016-01-01

Studies related to vegetation dynamics in heterogeneous landscapes often require Normalized Difference Vegetation Index (NDVI) datasets with both high spatial resolution and frequent coverage, which cannot be satisfied by a single sensor due to technical limitations. In this study, we propose a new method called NDVI-Bayesian Spatiotemporal Fusion Model (NDVI-BSFM) for accurately and effectively building frequent high spatial resolution Landsat-like NDVI datasets by integrating Moderate Resol...

Comparative analysis of Worldview-2 and Landsat 8 for coastal saltmarsh mapping accuracy assessment

Science.gov (United States)

Rasel, Sikdar M. M.; Chang, Hsing-Chung; Diti, Israt Jahan; Ralph, Tim; Saintilan, Neil

2016-05-01

Coastal saltmarsh and their constituent components and processes are of an interest scientifically due to their ecological function and services. However, heterogeneity and seasonal dynamic of the coastal wetland system makes it challenging to map saltmarshes with remotely sensed data. This study selected four important saltmarsh species Pragmitis australis, Sporobolus virginicus, Ficiona nodosa and Schoeloplectus sp. as well as a Mangrove and Pine tree species, Avecinia and Casuarina sp respectively. High Spatial Resolution Worldview-2 data and Coarse Spatial resolution Landsat 8 imagery were selected in this study. Among the selected vegetation types some patches ware fragmented and close to the spatial resolution of Worldview-2 data while and some patch were larger than the 30 meter resolution of Landsat 8 data. This study aims to test the effectiveness of different classifier for the imagery with various spatial and spectral resolutions. Three different classification algorithm, Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) and Artificial Neural Network (ANN) were tested and compared with their mapping accuracy of the results derived from both satellite imagery. For Worldview-2 data SVM was giving the higher overall accuracy (92.12%, kappa =0.90) followed by ANN (90.82%, Kappa 0.89) and MLC (90.55%, kappa = 0.88). For Landsat 8 data, MLC (82.04%) showed the highest classification accuracy comparing to SVM (77.31%) and ANN (75.23%). The producer accuracy of the classification results were also presented in the paper.

Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

Science.gov (United States)

Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

Landsat imagery: a unique resource

Science.gov (United States)

Miller, H.; Sexton, N.; Koontz, L.

2011-01-01

Landsat satellites provide high-quality, multi-spectral imagery of the surface of the Earth. These moderate-resolution, remotely sensed images are not just pictures, but contain many layers of data collected at different points along the visible and invisible light spectrum. These data can be manipulated to reveal what the Earth’s surface looks like, including what types of vegetation are present or how a natural disaster has impacted an area (Fig. 1).

Mapping afforestation and its carbon stock using time-series Landsat stacks

Science.gov (United States)

Liu, L.; Wu, Y.

2015-12-01

The Three Norths Shelter Forest Programme (TNSFP) is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land cover and cover changes, but it is still challenging to accurately quantify the plantation and its carbon stock from time-series satellite images. In this paper, the Yulin district, Shaanxi province, representing a typical afforestation area in the TNSFP region, was selected as the study area, and there were twenty-nine Landsat MSS/TM/ETM+ epochs were collected from 1974 to 2012 to reconstruct the forest changes and carbon stock in last 40 years. Firstly, the Landsat ground surface reflectance (GSR) images from 1974 to 2013 were collected and processed based on 6S atmospheric transfer code and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the dense time-series Landsat GSR images based on the integrated forest z-score (IFZ) model, and the afforestation age was successfully retrieved from the Landsat time-series stacks in the last forty years and shown to be consistent with the surveyed tree ages, with a RMSE value of 4.32 years and a determination coefficient (R²) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R² values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in six counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360%. For the forest area since 1974, the forest AGB density increased from 15.72 t

A study of atmospheric diffusion from the LANDSAT imagery. [pollution transport over the ocean

Science.gov (United States)

Dejesusparada, N. (Principal Investigator); Viswanadham, Y.; Torsani, J. A.

1981-01-01

LANDSAT multispectral scanner data of the smoke plumes which originated in eastern Cabo Frio, Brazil and crossed over into the Atlantic Ocean, are analyzed to illustrate how high resolution LANDSAT imagery can aid meteorologists in evaluating specific air pollution events. The eleven LANDSAT images selected are for different months and years. The results show that diffusion is governed primarily by water and air temperature differences. With colder water, low level air is very stable and the vertical diffusion is minimal; but water warmer than the air induces vigorous diffusion. The applicability of three empirical methods for determining the horizontal eddy diffusivity coefficient in the Gaussian plume formula was evaluated with the estimated standard deviation of the crosswind distribution of material in the plume from the LANDSAT imagery. The vertical diffusion coefficient in stable conditions is estimated using Weinstock's formulation. These results form a data base for use in the development and validation of meso scale atmospheric diffusion models.

Perspective view, Landsat overlay San Andreas Fault, Palmdale, California

Science.gov (United States)

2000-01-01

The prominent linear feature straight down the center of this perspective view is the San Andreas Fault. This segment of the fault lies near the city of Palmdale, California (the flat area in the right half of the image) about 60 kilometers (37 miles) north of Los Angeles. The fault is the active tectonic boundary between the North American plate on the right, and the Pacific plate on the left. Relative to each other, the Pacific plate is moving away from the viewer and the North American plate is moving toward the viewer along what geologists call a right lateral strike-slip fault. Two large mountain ranges are visible, the San Gabriel Mountains on the left and the Tehachapi Mountains in the upper right. The Lake Palmdale Reservoir, approximately 1.5 kilometers (0.9 miles) across, sits in the topographic depression created by past movement along the fault. Highway 14 is the prominent linear feature starting at the lower left edge of the image and continuing along the far side of the reservoir. The patterns of residential and agricultural development around Palmdale are seen in the Landsat imagery in the right half of the image. SRTM topographic data will be used by geologists studying fault dynamics and landforms resulting from active tectonics.This type of display adds the important dimension of elevation to the study of land use and environmental processes as observed in satellite images. The perspective view was created by draping a Landsat satellite image over an SRTM elevation model. Topography is exaggerated 1.5 times vertically. The Landsat image was provided by the United States Geological Survey's Earth Resources Observations Systems (EROS) Data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11,2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR

Application of integrated Landsat, geochemical and geophysical data in mineral exploration

International Nuclear Information System (INIS)

Conradsen, K.; Nilsson, G.; Thyrsted, T.; Gronlands Geologiske Undersogelse, Copenhagen, Denmark)

1985-01-01

In South Greenland (20000 sq. km) a remote sensing investigation is executed in connection with uranium exploration. The investigation includes analysis of Landsat data, conversion of geological, geochemical and geophysical data to image format compatible with Landsat images, and analysis of the total set of integrated data. The available geochemical data consisted of samples from 2000 sites, analyzed for U, K, Rb, Sr, Nb, Ga, Y, and Fe. The geophysical data comprised airborne gamma-spectrometric measurements and aeromagnetic data. The interpolation routines consisted of a kriging procedure for the geochemical data and a minimum curvature routine for the geophysical data. The analysis of the integrated data set is at a preliminary stage. As example a composite image showing Landsat channel 7, magnetic values, and Fe values as respectively intensity, hue and saturation is analyzed. It reveals alkaline intrusions and basaltic layers as anomalies while other anomalies cannot be accounted for on the basis of the present geological knowledge. 12 references

Automated mapping of persistent ice and snow cover across the western U.S. with Landsat

Science.gov (United States)

Selkowitz, David J.; Forster, Richard R.

2016-01-01

We implemented an automated approach for mapping persistent ice and snow cover (PISC) across the conterminous western U.S. using all available Landsat TM and ETM+ scenes acquired during the late summer/early fall period between 2010 and 2014. Two separate validation approaches indicate this dataset provides a more accurate representation of glacial ice and perennial snow cover for the region than either the U.S. glacier database derived from US Geological Survey (USGS) Digital Raster Graphics (DRG) maps (based on aerial photography primarily from the 1960s–1980s) or the National Land Cover Database 2011 perennial ice and snow cover class. Our 2010–2014 Landsat-derived dataset indicates 28% less glacier and perennial snow cover than the USGS DRG dataset. There are larger differences between the datasets in some regions, such as the Rocky Mountains of Northwest Wyoming and Southwest Montana, where the Landsat dataset indicates 54% less PISC area. Analysis of Landsat scenes from 1987–1988 and 2008–2010 for three regions using a more conventional, semi-automated approach indicates substantial decreases in glaciers and perennial snow cover that correlate with differences between PISC mapped by the USGS DRG dataset and the automated Landsat-derived dataset. This suggests that most of the differences in PISC between the USGS DRG and the Landsat-derived dataset can be attributed to decreases in PISC, as opposed to differences between mapping techniques. While the dataset produced by the automated Landsat mapping approach is not designed to serve as a conventional glacier inventory that provides glacier outlines and attribute information, it allows for an updated estimate of PISC for the conterminous U.S. as well as for smaller regions. Additionally, the new dataset highlights areas where decreases in PISC have been most significant over the past 25–50 years.

Evaluation of Two Absolute Radiometric Normalization Algorithms for Pre-processing of Landsat Imagery

Institute of Scientific and Technical Information of China (English)

Xu Hanqiu

2006-01-01

In order to evaluate radiometric normalization techniques, two image normalization algorithms for absolute radiometric correction of Landsat imagery were quantitatively compared in this paper, which are the Illumination Correction Model proposed by Markham and Irish and the Illumination and Atmospheric Correction Model developed by the Remote Sensing and GIS Laboratory of the Utah State University. Relative noise, correlation coefficient and slope value were used as the criteria for the evaluation and comparison, which were derived from pseudo-invariant features identified from multitemtween the normalized multitemporal images were significantly reduced when the seasons of multitemporal images were different. However, there was no significant difference between the normalized and unnormalized images with a similar seasonal condition. Furthermore, the correction results of two algorithms are similar when the images are relatively clear with a uniform atmospheric condition. Therefore, the radiometric normalization procedures should be carried out if the multitemporal images have a significant seasonal difference.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

Science.gov (United States)

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Calibration and Validation of Landsat Tree Cover in the Taiga−Tundra Ecotone

Directory of Open Access Journals (Sweden)

Paul Mannix Montesano

2016-06-01

Full Text Available Monitoring current forest characteristics in the taiga−tundra ecotone (TTE at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover >80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010 by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.

Forest management applications of Landsat data in a geographic information system

Science.gov (United States)

Maw, K. D.; Brass, J. A.

1982-01-01

The utility of land-cover data resulting from Landsat MSS classification can be greatly enhanced by use in combination with ancillary data. A demonstration forest management applications data base was constructed for Santa Cruz County, California, to demonstrate geographic information system applications of classified Landsat data. The data base contained detailed soils, digital terrain, land ownership, jurisdictional boundaries, fire events, and generalized land-use data, all registered to a UTM grid base. Applications models were developed from problems typical of fire management and reforestation planning.

A Cubesat enabled Spatio-Temporal Enhancement Method (CESTEM) utilizing Planet, Landsat and MODIS data

KAUST Repository

Houborg, Rasmus

2018-03-19

Satellite sensing in the visible to near-infrared (VNIR) domain has been the backbone of land surface monitoring and characterization for more than four decades. However, a limitation of conventional single-sensor satellite missions is their limited capacity to observe land surface dynamics at the very high spatial and temporal resolutions demanded by a wide range of applications. One solution to this spatio-temporal divide is an observation strategy based on the CubeSat standard, which facilitates constellations of small, inexpensive satellites. Repeatable near-daily image capture in RGB and near-infrared (NIR) bands at 3–4 m resolution has recently become available via a constellation of >130 CubeSats operated commercially by Planet. While the observing capacity afforded by this system is unprecedented, the relatively low radiometric quality and cross-sensor inconsistencies represent key challenges in the realization of their full potential as a game changer in Earth observation. To address this issue, we developed a Cubesat Enabled Spatio-Temporal Enhancement Method (CESTEM) that uses a multi-scale machine-learning technique to correct for radiometric inconsistencies between CubeSat acquisitions. The CESTEM produces Landsat 8 consistent atmospherically corrected surface reflectances in blue, green, red, and NIR bands, but at the spatial scale and temporal frequency of the CubeSat observations. An application of CESTEM over an agricultural dryland system in Saudi Arabia demonstrated CubeSat-based reproduction of Landsat 8 consistent VNIR data with an overall relative mean absolute deviation of 1.6% or better, even when the Landsat 8 and CubeSat acquisitions were temporally displaced by >32 days. The consistently high retrieval accuracies were achieved using a multi-scale target sampling scheme that draws Landsat 8 reference data from a series of scenes by using MODIS-consistent surface reflectance time series to quantify relative changes in Landsat

Remote Sensing of Residue Management in Farms using Landsat 8 Sensor Imagery

Directory of Open Access Journals (Sweden)

M. A Rostami

2017-10-01

Full Text Available Introduction Preserving of crop residues in the field surface after harvesting crops, making difficult farm operations. The farmers for getting rid of crop residues always choose the easiest way, i.e. burning. Burning is one of the common disposal methods for wheat and corn straw in some region of the world. Present study was aimed to investigate the accurate methods for monitoring of residue management after wheat harvesting. With this vision, the potential of Landsat 8 sensor was evaluated for monitoring of residue burning, using satellite spectral indices and Linear Spectral Unmixing Analysis. For this purpose, correlation of ground data with satellite spectral indices and LSUA data were tested by linear regression. Materials and Methods In this study we considered 12 farms where remained plants were burned, 12 green farm, 12 bare farms and 12 farms with full crop residue cover were considered. Spatial coordinates of experimental fields recorded with a GPS and fields map were drawn using ArcGissoftware, version of 10.1. In this study,t wo methods were used to separate burned fields from other farms including Satellite Spectral Indices and Linear Spectral unmixing analysis. In this study, multispectral landsat 8 image was acquired over 2015 year. Landsat 8 products are delivered to the customer as radiometric, sensor, and geometric corrections. Image pixels are unique to Landsat 8 data, and should not be directly compared to imagery from other sensors. Therefore, DN value must be converted to radiance value in order to change the radiance to the reflectance, which is useful when performing spectral analysis techniques, such as transformations, band ratios and the Normalized Difference Vegetation Index (NDVI, etc. In this study, a number of spectral indices and Linear Spectral Unmixing Analysis data were imported/extracted from Landsat 8 image. All satellite image data were analyzed by ENVI software package. The spectral indices used in this

Regional analysis of Landsat data concerning unconformity-vein uranium deposits, Pine Creek Geosyncline, Australia

International Nuclear Information System (INIS)

Raines, G.L.

1982-01-01

Linear features mapped from enhanced Landsat images in zones defining lineaments trending northeast and east-northeast across the uranium area of northern Australia. A model using Landsat data to select areas for uranium exploration is proposed, based on the observed spatial relation of uranium deposits and the newly defined major lineaments

a Landsat Time-Series Stacks Model for Detection of Cropland Change

Science.gov (United States)

Chen, J.; Chen, J.; Zhang, J.

2017-09-01

Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

CALIBRATION/VALIDATION OF LANDSAT-DERIVED OCEAN COLOUR PRODUCTS IN BOSTON HARBOUR

Directory of Open Access Journals (Sweden)

N. Pahlevan

2016-06-01

Full Text Available The Landsat data archive provides a unique opportunity to investigate the long-term evolution of coastal ecosystems at fine spatial scales that cannot be resolved by ocean colour (OC satellite sensors. Recognizing Landsat’s limitations in applications over coastal waters, we have launched a series of field campaigns in Boston Harbor and Massachusetts Bay (MA, USA to validate OC products derived from Landsat-8. We will provide a preliminary demonstration on the calibration/validation of the existing OC algorithms (atmospheric correction and in-water optical properties to enhance monitoring efforts in Boston Harbor. To do so, Landsat optical images were first compared against ocean colour products over high-latitude regions. The in situ cruise data, including optical data (remote sensing reflectance and water samples were analyzed to obtain insights into the optical and biogeochemical properties of near-surface waters. Along with the cruise data, three buoys were deployed in three locations across the Harbor to complement our database of concentrations of chlorophyll a, total suspended solids (TSS, and absorption of colour dissolved organic matter (CDOM. The data collected during the first year of the project are used to develop and/or tune OC algorithms. The data will be combined with historic field data to map in-water constituents back to the early 1990’s. This paper presents preliminary analysis of some of the data collected under Landsat-8 overpasses.

A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes

OpenAIRE

Zhang, Nevin Lianwen; Lee, Stephen S.; Zhang, Weihong

2013-01-01

We present a technique for speeding up the convergence of value iteration for partially observable Markov decisions processes (POMDPs). The underlying idea is similar to that behind modified policy iteration for fully observable Markov decision processes (MDPs). The technique can be easily incorporated into any existing POMDP value iteration algorithms. Experiments have been conducted on several test problems with one POMDP value iteration algorithm called incremental pruning. We find that th...

Valuing geospatial information: Using the contingent valuation method to estimate the economic benefits of Landsat satellite imagery

Science.gov (United States)

Loomis, John; Koontz, Steve; Miller, Holly M.; Richardson, Leslie A.

2015-01-01

While the U.S. government does not charge for downloading Landsat images, the images have value to users. This paper demonstrates a method that can value Landsat and other imagery to users. A survey of downloaders of Landsat images found: (a) established US users have a mean value of $912 USD per scene; (b) new US users and users returning when imagery became free have a mean value of $367 USD per scene. Total US user benefits for the 2.38 million scenes downloaded is $1.8 billion USD. While these benefits indicate a high willingness-to-pay among many Landsat downloaders, it would be economically inefficient for the US government to charge for Landsat imagery. Charging a price of $100 USD a scene would result in an efficiency loss of $37.5 million a year. This economic information should be useful to policy-makers who must decide about the future of this and similar remote sensing programs.

Global Man-made Impervious Surface (GMIS) Dataset From Landsat

Data.gov (United States)

National Aeronautics and Space Administration — The Global Man-made Impervious Surface (GMIS) Dataset From Landsat consists of global estimates of fractional impervious cover derived from the Global Land Survey...

Chesapeake Bay plume dynamics from LANDSAT

Science.gov (United States)

Munday, J. C., Jr.; Fedosh, M. S.

1981-01-01

LANDSAT images with enhancement and density slicing show that the Chesapeake Bay plume usually frequents the Virginia coast south of the Bay mouth. Southwestern (compared to northern) winds spread the plume easterly over a large area. Ebb tide images (compared to flood tide images) show a more dispersed plume. Flooding waters produce high turbidity levels over the shallow northern portion of the Bay mouth.

Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

Burned areas for the conterminous U.S. from 1984 through 2015, an automated approach using dense time-series of Landsat data

Science.gov (United States)

Hawbaker, T. J.; Vanderhoof, M.; Beal, Y. J. G.; Takacs, J. D.; Schmidt, G.; Falgout, J.; Brunner, N. M.; Caldwell, M. K.; Picotte, J. J.; Howard, S. M.; Stitt, S.; Dwyer, J. L.

2016-12-01

Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, many existing fire datasets in the United States are known to be incomplete and that complicates efforts to understand burned area patterns and introduces a large amount of uncertainty in efforts to identify their driving processes and impacts. Because of this, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables. To help meet this need, we developed a novel algorithm that automatically identifies burned areas in temporally-dense time series of Landsat image stacks to produce Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Outputs of the BAECV algorithm, generated for the conterminous United States for 1984 through 2015, consist of burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability, burn classification, and the Julian date of the first Landsat scene a burn was observed. The BAECV products document patterns of fire occurrence that are not well characterized by existing fire datasets in the United States. We anticipate that these data could help to better understand past patterns of fire occurrence, the drivers that created them, and the impacts fires had on natural and human systems.

Partial autocorrelation functions of the fractional ARIMA processes with negative degree of differencing

OpenAIRE

Inoue, Akihiko; Kasahara, Yukio

2004-01-01

Let {Xn : ∈Z} be a fractional ARIMA(p,d,q) process with partial autocorrelation function α(·). In this paper, we prove that if d∈(−1/2,0) then |α(n)|~|d|/n as n→∞. This extends the previous result for the case 0

Passive and partially active fault tolerance for massively parallel stream processing engines

DEFF Research Database (Denmark)

Su, Li; Zhou, Yongluan

2018-01-01

. On the other hand, an active approach usually employs backup nodes to run replicated tasks. Upon failure, the active replica can take over the processing of the failed task with minimal latency. However, both approaches have their own inadequacies in Massively Parallel Stream Processing Engines (MPSPE...... also propose effective and efficient algorithms to optimize a partially active replication plan to maximize the quality of tentative outputs. We implemented PPA on top of Storm, an open-source MPSPE and conducted extensive experiments using both real and synthetic datasets to verify the effectiveness...

Implementing The Automated Phases Of The Partially-Automated Digital Triage Process Model

Directory of Open Access Journals (Sweden)

Gary D Cantrell

2012-12-01

Full Text Available Digital triage is a pre-digital-forensic phase that sometimes takes place as a way of gathering quick intelligence. Although effort has been undertaken to model the digital forensics process, little has been done to date to model digital triage. This work discuses the further development of a model that does attempt to address digital triage the Partially-automated Crime Specific Digital Triage Process model. The model itself will be presented along with a description of how its automated functionality was implemented to facilitate model testing.

Assessment of The trophic state and Chlorophyll-a concentrations using Landsat OLI in Karaoun reservoir, Lebanon

Directory of Open Access Journals (Sweden)

Ali Fadel

2016-12-01

Full Text Available Fadel, A., Faour G. and Slim K. 2016. Assessment of the trophic state and chlorophyll-a concentrations using Landsat OLI in Karaoun reservoir, Lebanon. Lebanese Science Journal, 17(2: 130-145. Harmful algal blooms have become a worldwide environmental problem. A regular and cost-effective monitoring of these blooms is highly needed by lakes managers. Satellite remote sensing imagery like Landsat Operational Land Imager (OLI can be used to assess and monitor chlorophyll-a in water bodies over large areas in a cost-effective way. In this study, the accuracy of Landsat OLI to estimate chlorophyll-a was examined. Four field campaigns and cloud free images of Landsat OLI with 30 m resolution (01 May 2013, 21 August 2013, 10 July 2015, and 11 August 2015 were used in this study to determine the accuracy of Landsat OLI in estimating chlorophyll-a in a 12 km2 freshwater body, Karaoun reservoir. After atmospheric correction of these images, reflectance of single and multiple band combinations were compared to field chlorophyll-a data. Results of field campaigns showed that the trophic state of Karaoun reservoir is still eutrophic to hypereutrophic with high nutrient concentration and low phytoplankton biodiversity, dominated by cyanobacteria species, Microcystis aeruginosa and Aphanizomenon ovalisporum. On single band level, the in situ chlorophyll-a measurement correlated best with band 5 (0.85 - 0.88 µm, with R=0.75 and R2=0.57. Highest correlation (R=0.84 and R2=0.72 was obtained using band combination, B2:B4 band ratio multiplied by B5. Results indicated that Landsat OLI can be used effectively to determine chlorophyll-a concentration in lakes and reservoirs. We recommend the application of Landsat OLI as a satisfactory and cost effective method for monitoring chlorophyll-a in other lakes through-out the world

Monitoring water quality in a hypereutrophic reservoir using Landsat ETM+ and OLI sensors: how transferable are the water quality algorithms?

Science.gov (United States)

Deutsch, Eliza S; Alameddine, Ibrahim; El-Fadel, Mutasem

2018-02-15

The launch of the Landsat 8 in February 2013 extended the life of the Landsat program to over 40 years, increasing the value of using Landsat to monitor long-term changes in the water quality of small lakes and reservoirs, particularly in poorly monitored freshwater systems. Landsat-based water quality hindcasting often incorporate several Landsat sensors in an effort to increase the temporal range of observations; yet the transferability of water quality algorithms across sensors remains poorly examined. In this study, several empirical algorithms were developed to quantify chlorophyll-a, total suspended matter (TSM), and Secchi disk depth (SDD) from surface reflectance measured by Landsat 7 ETM+ and Landsat 8 OLI sensors. Sensor-specific multiple linear regression models were developed by correlating in situ water quality measurements collected from a semi-arid eutrophic reservoir with band ratios from Landsat ETM+ and OLI sensors, along with ancillary data (water temperature and seasonality) representing ecological patterns in algae growth. Overall, ETM+-based models outperformed (adjusted R 2 chlorophyll-a = 0.70, TSM = 0.81, SDD = 0.81) their OLI counterparts (adjusted R 2 chlorophyll-a = 0.50, TSM = 0.58, SDD = 0.63). Inter-sensor differences were most apparent for algorithms utilizing the Blue spectral band. The inclusion of water temperature and seasonality improved the power of TSM and SDD models.

The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report

Science.gov (United States)

Miller, Holly M.; Sexton, Natalie R.; Koontz, Lynne; Loomis, John; Koontz, Stephen R.; Hermans, Caroline

2011-01-01

Moderate-resolution imagery (MRI), such as that provided by the Landsat satellites, provides unique spatial information for use by many people both within and outside of the United States (U.S.). However, exactly who these users are, how they use the imagery, and the value and benefits derived from the information are, to a large extent, unknown. To explore these issues, social scientists at the USGS Fort Collins Science Center conducted a study of U.S.-based MRI users from 2008 through 2010 in two parts: 1) a user identification and 2) a user survey. The objectives for this study were to: 1) identify and classify U.S.-based users of this imagery; 2) better understand how and why MRI, and specifically Landsat, is being used; and 3) qualitatively and quantitatively measure the value and societal benefits of MRI (focusing on Landsat specifically). The results of the survey revealed that respondents from multiple sectors use Landsat imagery in many different ways, as demonstrated by the breadth of project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance placed on the imagery, the numerous benefits received from projects using Landsat imagery, the negative impacts if Landsat imagery was no longer available, and the substantial willingness to pay for replacement imagery in the event of a data gap. The survey collected information from users who are both part of and apart from the known user community. The diversity of the sample delivered results that provide a baseline of knowledge about the users, uses, and value of Landsat imagery. While the results supply a wealth of information on their own, they can also be built upon through further research to generate a more complete picture of the population of Landsat users as a whole.

Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS)

Science.gov (United States)

Micijevic, Esad; Morfitt, Ron

2010-01-01

Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

An Object-Based Approach for Fire History Reconstruction by Using Three Generations of Landsat Sensors

Directory of Open Access Journals (Sweden)

Thomas Katagis

2014-06-01

Full Text Available In this study, the capability of geographic object-based image analysis (GEOBIA in the reconstruction of the recent fire history of a typical Mediterranean area was investigated. More specifically, a semi-automated GEOBIA procedure was developed and tested on archived and newly acquired Landsat Multispectral Scanner (MSS, Thematic Mapper (TM, and Operational Land Imager (OLI images in order to accurately map burned areas in the Mediterranean island of Thasos. The developed GEOBIA ruleset was built with the use of the TM image and then applied to the other two images. This process of transferring the ruleset did not require substantial adjustments or any replacement of the initially selected features used for the classification, thus, displaying reduced complexity in processing the images. As a result, burned area maps of very high accuracy (over 94% overall were produced. In addition to the standard error matrix, the employment of additional measures of agreement between the produced maps and the reference data revealed that “spatial misplacement” was the main source of classification error. It can be concluded that the proposed approach can be potentially used for reconstructing the recent (40-year fire history in the Mediterranean, based on extended time series of Landsat or similar data.

SRTM Perspective View with Landsat Overlay: Costa Rica Coastal Plain

Science.gov (United States)

2001-01-01

This perspective view shows the northern coastal plain of Costa Rica with the Cordillera Central, composed of a number of active and dormant volcanoes, rising in the background. This view looks toward the south over the Rio San Juan, which marks the boundary between Costa Rica and Nicaragua. The smaller river joining Rio San Juan in the center of the image is Rio Sarapiqui, which is navigable upstream as far inland as Puerto Viejo (Old Port) de Sarapiqui at the mountain's base. This river was an important transportation route for those few hardy settlers who first moved into this region, although as recently as 1953 a mere three thatched-roof houses were all that comprised the village of Puerto Viejo.This coastal plain is a sedimentary basin formed about 50 million years ago composed of river alluvium and lahar (mud and ash flow) deposits from the volcanoes of the Cordillera Central. It comprises the province of Heredia (the smallest of Costa Rica's seven) and demonstrates a wide range of climatic conditions, from warm and humid lowlands to cool and damp highlands, and including the mild but seasonally wet and dry Central Valley.This image was generated in support of the Central American Commission for Environment and Development through an agreement with NASA. The Commission involves eight nations working to develop the Mesoamerican Biological Corridor, an effort to study and preserve some of the most biologically diverse regions of the planet.This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated 2X.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat

The use of landsat 7 enhanced thematic mapper plus for mapping leafy spurge

Science.gov (United States)

Mladinich, C.S.; Bustos, M.R.; Stitt, S.; Root, R.; Brown, K.; Anderson, G.L.; Hager, S.

2006-01-01

Euphorbia esula L. (leafy spurge) is an invasive weed that is a major problem in much of the Upper Great Plains region, including parts of Montana, South Dakota, North Dakota, Nebraska, and Wyoming. Infestations in North Dakota alone have had a serious economic impact, estimated at $87 million annually in 1991, to the state's wildlife, tourism, and agricultural economy. Leafy spurge degrades prairie and badland ecosystems by displacing native grasses and forbs. It is a major threat to protected ecosystems in many national parks, national wild lands, and state recreational areas in the region. This study explores the use of Landsat 7 Enhanced Thematic Mapper Plus (Landsat) imagery and derived products as a management tool for mapping leafy spurge in Theodore Roosevelt National Park, in southwestern North Dakota. An unsupervised clustering approach was used to map leafy spurge classes and resulted in overall classification accuracies of approximately 63%. The uses of Landsat imagery did not provide the accuracy required for detailed mapping of small patches of the weed. However, it demonstrated the potential for mapping broad-scale (regional) leafy spurge occurrence. This paper offers recommendations on the suitability of Landsat imagery as a tool for use by resource managers to map and monitor leafy spurge populations over large areas.

Nonlinear Parasitic Capacitance Modelling of High Voltage Power MOSFETs in Partial SOI Process

DEFF Research Database (Denmark)

Fan, Lin; Knott, Arnold; Jørgensen, Ivan Harald Holger

2016-01-01

: off-state, sub-threshold region, and on-state in the linear region. A high voltage power MOSFET is designed in a partial Silicon on Insulator (SOI) process, with the bulk as a separate terminal. 3D plots and contour plots of the capacitances versus bias voltages for the transistor summarize...

Uranium and thorium concentration process during partial fusion and crystallization of granitic magma

International Nuclear Information System (INIS)

Cuney, M.

1982-01-01

Two major processes, frequently difficult to distinguish, lead to uranium and thorium enrichment in igneous rocks and more particularly in granitoids; these are partial melting and fractional crystallization. Mont-Laurier uranothoriferous pegmatoids, Bancroft and Roessing deposits are examples of radioelement concentrations resulting mostly of low grade of melting on essentially metasedimentary formations deposited on a continental margin or intracratonic. Fractional crystallization follows generally partial melting even in migmatitic areas. Conditions prevailing during magma crystallization and in particular oxygen fugacity led either to the formation of uranium preconcentrations in granitoids, or to its partition in the fluid phase expelled from the magma. No important economic uranium deposit appears to be mostly related to fractional crystallization of large plutonic bodies

The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

Science.gov (United States)

Anderson, J. E.

1985-01-01

The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Bringing an ecological view of change to Landsat-based remote sensing

Science.gov (United States)

Kennedy, Robert E.; Andrefouet, Serge; Cohen, Warren; Gomez, Cristina; Griffiths, Patrick; Hais, Martin; Healey, Sean; Helmer, Eileen H.; Hostert, Patrick; Lyons, Mitchell; Meigs, Garrett; Pflugmacher, Dirk; Phinn, Stuart; Powell, Scott; Scarth, Peter; Susmita, Sen; Schroeder, Todd A.; Schneider, Annemarie; Sonnenschein, Ruth; Vogelmann, James; Wulder, Michael A.; Zhu, Zhe

2014-01-01

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, long-term trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

Determining the rate of forest conversion in Mato Grosso, Brazil, using Landsat MSS and AVHRR data

Science.gov (United States)

Nelson, Ross; Horning, Ned; Stone, Thomas A.

1987-01-01

AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and nonforest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. State-wide estimates of forest conversion indicate that between 1981 and 1984, 353,966 ha + or - 77,000 ha (0.4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis) and fire activity (estimated using AVHRR data) was noisy (R-squared = 0.41). The results suggest that AVHRR data may be put to better use as a stratification tool than as a subsidiary variable in list sampling.

Geospatial Method for Computing Supplemental Multi-Decadal U.S. Coastal Land-Use and Land-Cover Classification Products, Using Landsat Data and C-CAP Products

Science.gov (United States)

Spruce, J. P.; Smoot, James; Ellis, Jean; Hilbert, Kent; Swann, Roberta

2012-01-01

This paper discusses the development and implementation of a geospatial data processing method and multi-decadal Landsat time series for computing general coastal U.S. land-use and land-cover (LULC) classifications and change products consisting of seven classes (water, barren, upland herbaceous, non-woody wetland, woody upland, woody wetland, and urban). Use of this approach extends the observational period of the NOAA-generated Coastal Change and Analysis Program (C-CAP) products by almost two decades, assuming the availability of one cloud free Landsat scene from any season for each targeted year. The Mobile Bay region in Alabama was used as a study area to develop, demonstrate, and validate the method that was applied to derive LULC products for nine dates at approximate five year intervals across a 34-year time span, using single dates of data for each classification in which forests were either leaf-on, leaf-off, or mixed senescent conditions. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and C-CAP value-added products. Each classification's overall accuracy was assessed by comparing stratified random locations to available reference data, including higher spatial resolution satellite and aerial imagery, field survey data, and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall Kappa statistics ranging from 0.78 to 0.89. The accuracies are comparable to those from similar, generalized LULC products derived from C-CAP data. The Landsat MSS-based LULC product accuracies are similar to those from Landsat TM or ETM+ data. Accurate classifications were computed for all nine dates, yielding effective results regardless of season. This classification method yielded products that were used to compute LULC change products via additive GIS overlay techniques.

Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

Directory of Open Access Journals (Sweden)

M. Joseph Hughes

2014-05-01

Full Text Available The use of Landsat data to answer ecological questions is greatly increased by the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow. The method uses a neural network approach to determine cloud, cloud shadow, water, snow/ice and clear sky classification memberships of each pixel in a Landsat scene. It then applies a series of spatial procedures to resolve pixels with ambiguous membership by using information, such as the membership values of neighboring pixels and an estimate of cloud shadow locations from cloud and solar geometry. In a comparison with FMask, a high-quality cloud and cloud shadow classification algorithm currently available, SPARCS performs favorably, with substantially lower omission errors for cloud shadow (8.0% and 3.2%, only slightly higher omission errors for clouds (0.9% and 1.3%, respectively and fewer errors of commission (2.6% and 0.3%. Additionally, SPARCS provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of a method for vegetation change detection.

landsat remote sensing data as an alternative approach

African Journals Online (AJOL)

Mgina

The use of Landsat data in this area has revealed the need of effective use of these data in ... and efficient in all aspects of cost. ... Removal of noise and cloud cover effects can well be ... approximatelly1000 km from the business city of Dar es ...

Landsat time series and lidar as predictors of live and dead basal area across five bark beetle-affected forests

Science.gov (United States)

Benjamin C. Bright; Andrew T. Hudak; Robert E. Kennedy; Arjan J. H. Meddens

2014-01-01

Bark beetle-caused tree mortality affects important forest ecosystem processes. Remote sensing methodologies that quantify live and dead basal area (BA) in bark beetle-affected forests can provide valuable information to forest managers and researchers. We compared the utility of light detection and ranging (lidar) and the Landsat-based detection of trends in...

Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine

Science.gov (United States)

Dong, Jinwei; Xiao, Xiangming; Menarguez, Michael A.; Zhang, Geli; Qin, Yuanwei; Thau, David; Biradar, Chandrashekhar; Moore, Berrien

2016-01-01

Area and spatial distribution information of paddy rice are important for understanding of food security, water use, greenhouse gas emission, and disease transmission. Due to climatic warming and increasing food demand, paddy rice has been expanding rapidly in high latitude areas in the last decade, particularly in northeastern (NE) Asia. Current knowledge about paddy rice fields in these cold regions is limited. The phenology- and pixel-based paddy rice mapping (PPPM) algorithm, which identifies the flooding signals in the rice transplanting phase, has been effectively applied in tropical areas, but has not been tested at large scale of cold regions yet. Despite the effects from more snow/ice, paddy rice mapping in high latitude areas is assumed to be more encouraging due to less clouds, lower cropping intensity, and more observations from Landsat sidelaps. Moreover, the enhanced temporal and geographic coverage from Landsat 8 provides an opportunity to acquire phenology information and map paddy rice. This study evaluated the potential of Landsat 8 images on annual paddy rice mapping in NE Asia which was dominated by single cropping system, including Japan, North Korea, South Korea, and NE China. The cloud computing approach was used to process all the available Landsat 8 imagery in 2014 (143 path/rows, ~3290 scenes) with the Google Earth Engine (GEE) platform. The results indicated that the Landsat 8, GEE, and improved PPPM algorithm can effectively support the yearly mapping of paddy rice in NE Asia. The resultant paddy rice map has a high accuracy with the producer (user) accuracy of 73% (92%), based on the validation using very high resolution images and intensive field photos. Geographic characteristics of paddy rice distribution were analyzed from aspects of country, elevation, latitude, and climate. The resultant 30-m paddy rice map is expected to provide unprecedented details about the area, spatial distribution, and landscape pattern of paddy rice fields

The decision tree classifier - Design and potential. [for Landsat-1 data

Science.gov (United States)

Hauska, H.; Swain, P. H.

1975-01-01

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

Burned area detection based on Landsat time series in savannas of southern Burkina Faso

Science.gov (United States)

Liu, Jinxiu; Heiskanen, Janne; Maeda, Eduardo Eiji; Pellikka, Petri K. E.

2018-02-01

West African savannas are subject to regular fires, which have impacts on vegetation structure, biodiversity and carbon balance. An efficient and accurate mapping of burned area associated with seasonal fires can greatly benefit decision making in land management. Since coarse resolution burned area products cannot meet the accuracy needed for fire management and climate modelling at local scales, the medium resolution Landsat data is a promising alternative for local scale studies. In this study, we developed an algorithm for continuous monitoring of annual burned areas using Landsat time series. The algorithm is based on burned pixel detection using harmonic model fitting with Landsat time series and breakpoint identification in the time series data. This approach was tested in a savanna area in southern Burkina Faso using 281 images acquired between October 2000 and April 2016. An overall accuracy of 79.2% was obtained with balanced omission and commission errors. This represents a significant improvement in comparison with MODIS burned area product (67.6%), which had more omission errors than commission errors, indicating underestimation of the total burned area. By observing the spatial distribution of burned areas, we found that the Landsat based method misclassified cropland and cloud shadows as burned areas due to the similar spectral response, and MODIS burned area product omitted small and fragmented burned areas. The proposed algorithm is flexible and robust against decreased data availability caused by clouds and Landsat 7 missing lines, therefore having a high potential for being applied in other landscapes in future studies.

Phenological monitoring of Acadia National Park using Landsat, MODIS and VIIRS observations and fused data

Science.gov (United States)

Liu, Y.; McDonough MacKenzie, C.; Primack, R.; Zhang, X.; Schaaf, C.; Sun, Q.; Wang, Z.

2015-12-01

Monitoring phenology with remotely sensed data has become standard practice in large-plot agriculture but remains an area of research in complex terrain. Landsat data (30m) provides a more appropriate spatial resolution to describe such regions but may only capture a few cloud-free images over a growing period. Daily data from the MODerate resolution Imaging Spectroradiometer(MODIS) and Visible Infrared Imaging Radiometer Suite(VIIRS) offer better temporal acquisitions but at coarse spatial resolutions of 250m to 1km. Thus fused data sets are being employed to provide the temporal and spatial resolutions necessary to accurately monitor vegetation phenology. This study focused on Acadia National Park, Maine, attempts to compare green-up from remote sensing and ground observations over varying topography. Three north-south field transects were established in 2013 on parallel mountains. Along these transects, researchers record the leaf out and flowering phenology for thirty plant species biweekly. These in situ spring phenological observations are compared with the dates detected by Landsat 7, Landsat 8, MODIS, and VIIRS observations, both separately and as fused data, to explore the ability of remotely sensed data to capture the subtle variations due to elevation. Daily Nadir BRDF Adjusted Reflectances(NBAR) from MODIS and VIIRS are fused with Landsat imagery to simulate 30m daily data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM) algorithm. Piecewise logistic functions are fit to the time series to establish spring leaf-out dates. Acadia National Park, a region frequently affected by coastal clouds, is a particularly useful study area as it falls in a Landsat overlap region and thus offers the possibility of acquiring as many as 4 Landsat observations in a 16 day period. With the recent launch of Sentinel 2A, the community will have routine access to such high spatial and temporal data for phenological monitoring.

Machine learning-based Landsat-MODIS data fusion approach for 8-day 30m evapotranspiration monitoring

Science.gov (United States)

Im, J.; Ke, Y.; Park, S.

2016-12-01

Continuous monitoring of evapotranspiration (ET) is important for understanding of hydrological cycles and energy flux dynamics. At regional and local scales, routine ET estimation is a critical for efficient water management, drought impact assessment and ecosystem health monitoring, etc. Remote sensing has long been recognized to be able to provide ET monitoring over large areas. However, no single satellite could provide temporally continuous ET at relatively high spatial resolution due to the trade-off between the spatial and temporal resolution of current satellite sensors. Landsat-series satellites provide optical and thermal imagery at 30-100m resolution, whereas the 16-day revisit cycle hinders the observation of ET dynamics; MODIS provides sources of ET estimation at daily basis, but the 500-1000m ground sampling distance is too coarse for field level applications. In this study, we present a machine learning and STARFM based method for Landsat/MODIS ET fusion. The approach first downscales MODIS 8-day 1km ET (MOD16A2) to 30m based on eleven Landsat-derived indicators such as NDVI, EVI, NDWI etc on the cloud-free Landsat-available days using Random Forest approach. For the days when Landsat data are not available, downscaled ET is synthesized by MODIS and Landsat data fusion with STARFM and STI-FM approaches. The models are evaluated using in situ flux tower measurements at US-ARM and US-Twt AmeriFlux sites the United States. Results show that the downscaled 30m ET have good agreement with MODIS ET (RMSE=0.42-3.4mm/8days, rRMSE=3.2%-26%) and the downscaled ET have higher accuracy than MODIS ET when compared to in-situ measurements.

Impact of partial nitritation degree and C/N ratio on simultaneous Sludge Fermentation, Denitrification and Anammox process.

Science.gov (United States)

Wang, Bo; Peng, Yongzhen; Guo, Yuanyuan; Yuan, Yue; Zhao, Mengyue; Wang, Shuying

2016-11-01

This study presents a novel process (i.e. PN/SFDA) to remove nitrogen from low C/N domestic wastewater. The process mainly involves two reactors, a pre-Sequencing Batch Reactor for partial nitritation (termed as PN-SBR) and an anoxic reactor for integrated Denitrification and Anammox with carbon sources produced from Sludge Fermentation (termed as SFDA). During long-term Runs, NO2(-)/NH4(+) ratio (i.e. NO2(-)-N/NH4(+)-N calculated by mole) in the PN-SBR effluent was gradually increased from 0.2 to 37 by extending aerobic duration, meaning that partial nitritation turning to full nitritation could be achieved. Impact of partial nitritation degree on SFDA process was investigated and the result showed that, NO2(-)/NH4(+) ratios between 2 and 10 were appropriate for the co-existence of denitrification and anammox together in the SFDA reactor, and denitrification instead of anammox contributed greater for nitrogen removal. Further batch tests indicated that anammox collaborated well with denitrification at low C/N (1.0 in this study). Copyright © 2016 Elsevier Ltd. All rights reserved.

Characteristic of nitrous oxide production in partial denitrification process with high nitrite accumulation.

Science.gov (United States)

Du, Rui; Peng, Yongzhen; Cao, Shenbin; Wang, Shuying; Niu, Meng

2016-03-01

Nitrous oxide (N2O) production during the partial denitrification process with nitrate (NO3(-)-N) to nitrite (NO2(-)-N) transformation ratio of 80% was investigated in this study. Results showed that N2O was seldom observed before complete depletion of NO3(-)-N, but it was closely related to the reduction of NO2(-)-N rather than NO3(-)-N. High COD/NO3(-)-N was in favor of N2O production in partial denitrification with high NO2(-)-N accumulation. It was seriously enhanced at constant acidic pH due to the free nitrous acid (FNA) inhibition. However, the N2O production was much lower at initial pH of 5.5 and 6.5 due to the pH increase during denitrification process. Significantly, the pH turning point could be chosen as a controlled parameter to denote the end of NO3(-)-N reduction, which could not only achieve high NO2(-)-N accumulation but also decrease the N2O production significantly for practical application. Copyright © 2015 Elsevier Ltd. All rights reserved.

Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

Directory of Open Access Journals (Sweden)

O. Orhan

2016-06-01

Full Text Available The main purpose of this paper is to investigate multi-temporal land surface temperature (LST and Normalized Difference Vegetation Index (NDVI changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST, Normalized Difference Vegetation Index (NDVI maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

Vegetation burn severity mapping using Landsat-8 and WorldView-2

Science.gov (United States)

Wu, Zhuoting; Middleton, Barry R.; Hetzler, Robert; Vogel, John M.; Dye, Dennis G.

2015-01-01

We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

Distribution of Snow and Maximum Snow Water Equivalent Obtained by LANDSAT Data and Degree Day Method

Science.gov (United States)

Takeda, K.; Ochiai, H.; Takeuchi, S.

1985-01-01

Maximum snow water equivalence and snowcover distribution are estimated using several LANDSAT data taken in snowmelting season over a four year period. The test site is Okutadami-gawa Basin located in the central position of Tohoku-Kanto-Chubu District. The year to year normalization for snowmelt volume computation on the snow line is conducted by year to year correction of degree days using the snowcover percentage within the test basin obtained from LANDSAT data. The maximum snow water equivalent map in the test basin is generated based on the normalized snowmelt volume on the snow line extracted from four LANDSAT data taken in a different year. The snowcover distribution on an arbitrary day in snowmelting of 1982 is estimated from the maximum snow water equivalent map. The estimated snowcover is compared with the snowcover area extracted from NOAA-AVHRR data taken on the same day. The applicability of the snow estimation using LANDSAT data is discussed.

Study on Thixojoining Process Using Partial Remelting Method

Directory of Open Access Journals (Sweden)

M. N. Mohammed

2013-01-01

Full Text Available Cold-work tool steel is considered to be a nonweldable metal due to its high percentage content of carbon and alloy elements. The application of a new process of the semisolid joining of two dissimilar metals is proposed. AISI D2 cold-work tool steel was thixojoined to 304 stainless steel by using a partial remelting method. After thixojoining, microstructural examination including metallographic analysis, energy dispersive spectroscopy (EDS, and Vickers hardness tests was performed. From the results, metallographic analyses along the joint interface between semisolid AISI D2 and stainless steel showed a smooth transition from one to another and neither oxides nor microcracking was observed. Hardness values obtained from the points in the diffusion zone were much higher than those in the 304 stainless steel but lower than those in the AISI D2 tool steel. The study revealed that a new type of nonequilibrium diffusion interfacial structure was constructed at the interface of the two different types of steel. The current work successfully confirmed that avoidance of a dendritic microstructure in the semisolid joined zone and high bonding quality components can be achieved without the need for force or complex equipment when compared to conventional welding processes.

Opening the archive: how free data has enabled the science and monitoring promise of Landsat

Science.gov (United States)

Michael A. Wulder; Jeffrey G. Masek; Warren B. Cohen; Thomas R. Loveland; Curtis E. Woodcock

2012-01-01

Landsat occupies a unique position in the constellation of civilian earth observation satellites, with a long and rich scientific and applications heritage. With nearly 40 years of continuous observation—since launch of the first satellite in 1972—the Landsat program has benefited from insightful technical specification, robust engineering, and the necessary...

Monitoring Springs in the Mojave Desert Using Landsat Time Series Analysis

Science.gov (United States)

Potter, Christopher S.

2018-01-01

The purpose of this study, based on Landsat satellite data was to characterize variations and trends over 30 consecutive years (1985-2016) in perennial vegetation green cover at over 400 confirmed Mojave Desert spring locations. These springs were surveyed between in 2015 and 2016 on lands managed in California by the U.S. Bureau of Land Management (BLM) and on several land trusts within the Barstow, Needles, and Ridgecrest BLM Field Offices. The normalized difference vegetation index (NDVI) from July Landsat images was computed at each spring location and a trend model was first fit to the multi-year NDVI time series using least squares linear regression.Â

Removable partial denture alloys processed by laser-sintering technique.

Science.gov (United States)

Alageel, Omar; Abdallah, Mohamed-Nur; Alsheghri, Ammar; Song, Jun; Caron, Eric; Tamimi, Faleh

2018-04-01

Removable partial dentures (RPDs) are traditionally made using a casting technique. New additive manufacturing processes based on laser sintering has been developed for quick fabrication of RPDs metal frameworks at low cost. The objective of this study was to characterize the mechanical, physical, and biocompatibility properties of RPD cobalt-chromium (Co-Cr) alloys produced by two laser-sintering systems and compare them to those prepared using traditional casting methods. The laser-sintered Co-Cr alloys were processed by the selective laser-sintering method (SLS) and the direct metal laser-sintering (DMLS) method using the Phenix system (L-1) and EOS system (L-2), respectively. L-1 and L-2 techniques were 8 and 3.5 times more precise than the casting (CC) technique (p laser-sintered and cast alloys were biocompatible. In conclusion, laser-sintered alloys are more precise and present better mechanical and fatigue properties than cast alloys for RPDs. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1174-1185, 2018. © 2017 Wiley Periodicals, Inc.

LANDSAT menhaden and thread herring resources investigation. [Gulf of Mexico

Science.gov (United States)

Kemmerer, A. J. (Principal Investigator); Brucks, J. T.; Butler, J. A.; Faller, K. H.; Holley, H. J.; Leming, T. D.; Savastano, K. J.; Vanselous, T. M.

1977-01-01

The author has identified the following significant results. The relationship between the distribution of menhaden and selected oceanographic parameters (water color, turbidity, and possibly chlorophyll concentrations) was established. Similar relationships for thread herring were not established nor were relationships relating to the abundance of either species. Use of aircraft and LANDSAT remote sensing instruments to measure or infer a set of basic oceanographic parameters was evaluated. Parameters which could be accurately inferred included surface water temperature, salinity, and color. Water turbidity (Secchi disk) was evaluated as marginally inferrable from the LANDSAT MSS data and chlorophyll-a concentrations as less than marginal. These evaluations considered the parameters only as experienced in the two test areas using available sensors and statistical techniques.

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

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Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.

2016-01-01

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

Assessment of the Trophic State and Chlorophyll-A Concentrations using Landsat OLI in Karaoun Reservoir Lebanon

International Nuclear Information System (INIS)

Fadel, A.; Faour, GH.; Slim, K.

2016-01-01

Harmful algal blooms have become a worldwide environmental problem. A regular and cost -effective monitoring of these blooms is highly needed by lakes managers. Satellite remote sensing imagery like Landsat Operational Land Imager (OLI) can be used to assess and monitor chlorophyll-a in water bodies over large areas in a cost-effective way. In this study, the accuracy of Landsat OLI to estimate chlorophyll-a was examined. Four field campaigns and cloud free images of Landsat OLI with 30 m resolution (01 May 2013, 21 August 2013, 10 July 2015, and 11 August 2015) were used in this study to determine the accuracy of Landsat OLI in estimating chlorophyll-a in a 12 km2 fresh water body, Karaoun reservoir. After atmospheric correction of these images, reflectance of single and multiple band combinations were compared to field chlorophyll-a data. Results of field campaigns showed that the trophic state of Karaoun reservoir is still eutrophic to hypereutrophic withhigh nutrient concentration andlow phytoplankton biodiversity, dominatedby cyanobacteria species, Microcystis aeruginosa and Aphanizomenon ovalisporum. On single band level, the n situ chlorophyll-a measurement correlated best with band 5 (0.85 -0.88 μm), with R=0.75 and R2=0.57.Highest correlation (R=0.84 and R2=0.72) was obtained using band combination, B2:B4 band ratio multiplied by B5. Results indicated that Landsat OLI can be used effectively to determine chlorophyll-a concentration in lakes and reservoirs. We recommend the application of Landsat OLI as a satisfactory and cost effective method for monitoring chlorophyll-a in other lakes through-out the world. (author)

Centralized mission planning and scheduling system for the Landsat Data Continuity Mission

Science.gov (United States)

Kavelaars, Alicia; Barnoy, Assaf M.; Gregory, Shawna; Garcia, Gonzalo; Talon, Cesar; Greer, Gregory; Williams, Jason; Dulski, Vicki

2014-01-01

Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.

Perspective View with Landsat Overlay, Salt Lake City Olympics Venues, Utah

Science.gov (United States)

2002-01-01

The 2002 Winter Olympics are hosted by Salt Lake City at several venues within the city, in nearby cities, and within the adjacent Wasatch Mountains. This computer generated perspective image provides a northward looking 'view from space' that includes all of these Olympic sites. In the south, next to Utah Lake, Provo hosts the ice hockey competition. In the north, northeast of the Great Salt Lake, Ogden hosts curling, and the nearby Snow Basin ski area hosts the downhill events. In between, southeast of the Great Salt Lake, Salt Lake City hosts the Olympic Village and the various skating events. Further east, across the Wasatch Mountains, the Park City area ski resorts host the bobsled, ski jumping, and snowboarding events. The Winter Olympics are always hosted in mountainous terrain. This view shows the dramatic landscape that makes the Salt Lake City region a world-class center for winter sports.This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and a Landsat 5 satellite image mosaic. Topographic expression is exaggerated four times.For a full-resolution, annotated version of this image, please select Figure 1, below: [figure removed for brevity, see original site] Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60

Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions

Science.gov (United States)

Barry Tyler. Wilson

2015-01-01

This study examined the utility of dense time series of Landsat imagery for small area estimation and mapping of change in forest conditions over time. The study area was a region in north central Wisconsin for which Landsat 7 ETM+ imagery and field measurements from the Forest Inventory and Analysis program are available for the decade of 2003 to 2012. For the periods...

Landsat's role in ecological applications of remote sensing.

Science.gov (United States)

Warren B. Cohen; Samuel N. Goward

2004-01-01

Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by landsat sensors have played the most pivotal role in spatial and temporal scaling. Modern terrestrial ecology relies on...

Category-selective attention interacts with partial awareness processes in a continuous manner: An fMRI study

Directory of Open Access Journals (Sweden)

Shen Tu

2015-12-01

Full Text Available Recently, our team found that category-selective attention could modulate tool processing at the partial awareness level and unconscious face processing in the middle occipital gyrus (MOG. However, the modulation effects in MOG were in opposite directions across the masked tool and masked face conditions in that study: MOG activation decreased in the masked faces condition but increased in the masked tools condition under the consistent compared with the inconsistent cue-selective-attentional modulation. In the present study, in order to confirm that the opposite effects were due to the changed contours of the tools, using the same tool pictures and fMRI technique, we devised another two conditions: variant mirror tool picture condition and invariant tool picture condition. The results showed that, during the variant mirror tool picture condition, activation in the MOG decreased under tool-selective attention compared with face-selective attention. Interestingly, however, during the invariant tool picture condition, activation in the MOG revealed neither positive nor negative changes. Combined with the result of increased MOG activity in the changed different tool condition, the three different effects demonstrated not only that the unconscious component of partial awareness processing (no knowledge of the identity of the tool could be modulated by the category-selective attention in the earlier visual cortex but also that the modulation effect could further interact with the conscious component of partial awareness processing (consciousness of the changing contour of the tool in a continuous manner.

Landsat-based trend analysis of lake dynamics across northern permafrost regions

Science.gov (United States)

Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M.; Arp, Christopher D.; Ulrich, Mathias; Federov, Alexander; Veremeeva, Alexandra

2017-01-01

Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here we present, a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM,ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e. upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.

Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass

Science.gov (United States)

Glenn, Nancy F.; Neuenschwander, Amy; Vierling, Lee A.; Spaete, Lucas; Li, Aihua; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

2016-01-01

The Landsat 8 mission provides new opportunities for quantifying the distribution of above-ground carbon at moderate spatial resolution across the globe, and in particular drylands. Furthermore, coupled with structural information from space-based and airborne laser altimetry, Landsat 8 provides powerful capabilities for large-area, long-term studies that quantify temporal and spatial changes in above-ground biomass and cover. With the planned launch of ICESat-2 in 2017 and thus the potential to couple Landsat 8 and ICESat-2 data, we have unprecedented opportunities to address key challenges in drylands, including quantifying fuel loads, habitat quality, biodiversity, carbon cycling, and desertification.

Mount Ararat, Turkey, Perspective with Landsat Image Overlay

Science.gov (United States)

2004-01-01

This perspective view shows Mount Ararat in easternmost Turkey, which has been the site of several searches for the remains of Noah's Ark. The main peak, known as Great Ararat, is the tallest peak in Turkey, rising to 5165 meters (16,945 feet). This southerly, near horizontal view additionally shows the distinctly conically shaped peak known as 'Little Ararat' on the left. Both peaks are volcanoes that are geologically young, but activity during historic times is uncertain.This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 1.25-times vertical exaggeration to enhance topographic expression. Natural colors of the scene are enhanced by image processing, inclusion of some infrared reflectance (as green) to highlight the vegetation pattern, and inclusion of shading of the elevation model to further highlight the topographic features. Volcanoes pose hazards for people, the most obvious being the threat of eruption. But other hazards are associated with volcanoes too. In 1840 an earthquake shook the Mount Ararat region, causing an unstable part of mountain's north slope to tumble into and destroy a village. Visualizations of satellite imagery when combined with elevation models can be used to reveal such hazards leading to disaster prevention through improved land use planning.But the hazards of volcanoes are balanced in part by the benefits they provide. Over geologic time volcanic materials break down to form fertile soils. Cultivation of these soils has fostered and sustained civilizations, as has occurred in the Mount Ararat region. Likewise, tall volcanic peaks often catch precipitation, providing a water supply to those civilizations. Mount Ararat hosts an icefield and set of glaciers, as seen here in this late summer scene, that are part of this beneficial natural processElevation data used in this image was acquired by the Shuttle Radar Topography Mission

Landsat Image Map Production Methods at the U. S. Geological Survey

Science.gov (United States)

Kidwell, R.D.; Binnie, D.R.; Martin, S.

1987-01-01

To maintain consistently high quality in satellite image map production, the U. S. Geological Survey (USGS) has developed standard procedures for the photographic and digital production of Landsat image mosaics, and for lithographic printing of multispectral imagery. This paper gives a brief review of the photographic, digital, and lithographic procedures currently in use for producing image maps from Landsat data. It is shown that consistency in the printing of image maps is achieved by standardizing the materials and procedures that affect the image detail and color balance of the final product. Densitometric standards are established by printing control targets using the pressplates, inks, pre-press proofs, and paper to be used for printing.

Forest cover of North America in the 1970s mapped using Landsat MSS data

Science.gov (United States)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

LANDSAT-8 OPERATIONAL LAND IMAGER CHANGE DETECTION ANALYSIS

Directory of Open Access Journals (Sweden)

W. Pervez

2017-05-01

Full Text Available This paper investigated the potential utility of Landsat-8 Operational Land Imager (OLI for change detection analysis and mapping application because of its superior technical design to previous Landsat series. The OLI SVM classified data was successfully classified with regard to all six test classes (i.e., bare land, built-up land, mixed trees, bushes, dam water and channel water. OLI support vector machine (SVM classified data for the four seasons (i.e., spring, autumn, winter, and summer was used to change detection results of six cases: (1 winter to spring which resulted reduction in dam water mapping and increases of bushes; (2 winter to summer which resulted reduction in dam water mapping and increase of vegetation; (3 winter to autumn which resulted increase in dam water mapping; (4 spring to summer which resulted reduction of vegetation and shallow water; (5 spring to autumn which resulted decrease of vegetation; and (6 summer to autumn which resulted increase of bushes and vegetation . OLI SVM classified data resulted higher overall accuracy and kappa coefficient and thus found suitable for change detection analysis.

OHIO RIVER WATER QUALITY ASSESSMENT USING LANDSAT-7 DATA

Science.gov (United States)

The objectives of this project were (1) to develop a universal index for measuring Turbidity and Chlorophyll-A from remote sensing data and (2) to correlate satellite image parameters from Landsat-7 data with field measurements of water quality for five parameters: Chlorophyll-A ...

Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series

Directory of Open Access Journals (Sweden)

Valerie J. Pasquarella

2017-07-01

Full Text Available Introduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a significant challenge due to the ephemeral nature of defoliation events. Using the 2016 gypsy moth (Lymantria dispar outbreak in Southern New England as a case study, we present a new approach for near-real-time defoliation monitoring using synthetic images produced from Landsat time series. By comparing predicted and observed images, we assessed changes in vegetation condition multiple times over the course of an outbreak. Initial measures can be made as imagery becomes available, and season-integrated products provide a wall-to-wall assessment of potential defoliation at 30 m resolution. Qualitative and quantitative comparisons suggest our Landsat Time Series (LTS products improve identification of defoliation events relative to existing products and provide a repeatable metric of change in condition. Our synthetic-image approach is an important step toward using the full temporal potential of the Landsat archive for operational monitoring of forest health over large extents, and provides an important new tool for understanding spatial and temporal dynamics of insect defoliators.

Development of a perpendicular vibration-induced electrical discharge machining process for fabrication of partially wavy inner structures

Energy Technology Data Exchange (ETDEWEB)

Lee, Ju Chul; Park, Sang Hu; Min, June Kee; Ha, Man Yeong; Shin, Bo Sung [Pusan National University, Busan (Korea, Republic of); Cho, Jong Rae [Korea Maritime University, Busan (Korea, Republic of)

2016-05-15

Heat transfer enhancement is an important issue in energy systems. To improve the efficiency of a cooling channel used inside injection molds, turbine blades, and high-temperature devices, channels with various shapes, such as wavy, elliptical, and twisted, have been studied. A cooling channel with a partially wavy inner structure has shown outstanding cooling performance despite a small increase in friction factor. However, generating a partially wavy inner structure inside a channel through conventional machining processes is not easy. To address this problem, we developed a new process called Perpendicular vibration-induced electrical discharge machining (PV-EDM). A specific electrode and one- and random-directional vibrating devices controlled by a pneumatic load were designed for the PV-EDM process. Experimental results showed that local shaping on the inner wall of a channel is possible, which confirmed the possibility of application of this process to actual industrial problems.

Assessment of Forest Damage in Croatia using Landsat-8 OLI Images

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Anita Simic Milas

2015-05-01

Full Text Available Background and Purpose: Rapid assessments of forest damage caused by natural disasters such as ice-break, wind, flooding, hurricane, or forest fires are necessary for mitigation and forest management. Forest damage directly impacts carbon uptake and biogeochemical cycles, and thus, has an impact on climate change. It intensifies erosion and flooding, and influences socio-economic well-being of population. Quantification of forest cover change represents a challenge for the scientific community as damaged areas are often in the mountainous and remote regions. Forested area in the western Croatia was considerably damaged by ice-breaking and flooding in 2014. Satellite remote sensing technology has opened up new possibilities for detecting and quantifying forest damage. Several remote sensing tools are available for rapid assessment of forest damage. These include aerial photographic interpretation, and airborne and satellite imagery. This study evaluates the capability of Landsat-8 optical data and a vegetation index for mapping forest damage in Croatia that occurred during the winter of 2014. Materials and Methods: The change detection analysis in this study was based on the Normalized Difference Vegetation Index (NDVI difference approach, where pre- and post- event Landsat-8 images were employed in the ENVI image change workflow. The validation was done by comparing the satellite-generated change detection map with the ground truth data based on field observations and spatial data of forest management units and plans. Results: The overall damage assessment from this study suggests that the total damaged area covers 45,265.32 ha of forest. It is 19.20% less than estimated by Vuletić et al. [3] who found that 56,021.86 ha of forest were affected. Most damage was observed in the mixed, broadleaf and coniferous forest. The change errors of commission and omission were calculated to be 35.73% and 31.60%, respectively. Conclusions: Landsat-8 optical

Temporal validation for landsat-based volume estimation model

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Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan

2015-01-01

Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

REGIONAL GEOLGICAL MAPPING IN TROPICAL ENVIRONMENTS USING LANDSAT TM AND SRTM REMOTE SENSING DATA

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A. Beiranvand Pour

2015-10-01

Full Text Available Landsat Thematic Mapper (TM and Shuttle Radar Topography Mission (SRTM data were used to produce geological maps in tropical environments. Lineament, lithology and landform maps were produced for all states in peninsular Malaysia in this study. Kedah, Perak and Terengganu states have been selected as case studies to demonstrate the results of the data and techniques used. Directional filtering technique was applied to Landsat TM bands 4, 5 and 3 for lineament mapping. The lithology map was produced using Landsat TM bands combination consist of bands 4, 3 and 2. Digital elevation model and landform map were produced using SRTM data in 3 Dimension (3D and 2 Dimension (2D perspective views, respectively. The produced geological maps and the remote sensing data and methods applied in this study are mostly appropriate for hazard risk mapping applications and mineral exploration projects in the peninsular Malaysia and tropical environments.

Geothermal Potential Analysis Using Landsat 8 and Sentinel 2 (Case Study: Mount Ijen)

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Sukojo, B. M.; Mardiana, R.

2017-12-01

Geothermal energy is also a heat energy contained in the earth’s internal. Indonesia has a total geothermal potential of around 27 GWe. The government is eager for the development of geothermal in Indonesia can run well so that geothermal can act as one of the pillars of national energy. However, the geothermal potential has not been fully utilized. One of the geothermal potention is Mount Ijen. Mount Ijen is a strato volcano that has a crater lake with a depth of about 190 m and has a very high degree of acidity and the volume of lake water is very large. With the abundance of potential geothermal potential in Indonesia, it is necessary to have an activity in the form of integrated geoscience studies to be able to maximize the potential content that exists in a geothermal area. One of the studies conducted is to do potential mapping. This research performs image data processing of Landsat 8, Sentinel 2, RBI Map, and preliminary survey data. This research carried out the Vegetation Index, surface temperature and altitude. The equipment used in this research includes image processing software, number processing software, GPS Handheld and Laptop. Surface Temperatures in the Mount Ijen have anomalies with large temperatures ranging between 18° C to 38° C. The best correlation value of altitude and ground surface temperature is -0.89 ie the correlation of January surface temperature. While the correlation value of Landsat 8 and Sentinel 2 vegetation index was 0.81. The land cover confidence matrix scored 80%. Land cover in the research area is dominated by forests by 35% of the research area. There is a potential area of geothermal potential is very high on Mount Ijen with an area of 39.43 hectares located in Wongsorejo District and adjacent to District Sempol.

An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia

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Neil Flood

2013-01-01

Full Text Available Operational monitoring of vegetation and land surface change over large areas can make good use of satellite sensors that measure radiance reflected from the Earth’s surface. Monitoring programs use multiple images for complete spatial coverage over time. Accurate retrievals of vegetation cover and vegetation change estimates can be hampered by variation, in both space and time, in the measured radiance, caused by atmospheric conditions, topography, sensor location, and sun elevation. In order to obtain estimates of cover that are comparable between images, and to retrieve accurate estimates of change, these sources of variation must be removed. In this paper we present a preprocessing scheme for minimising atmospheric, topographic and bi-directional reflectance effects on Landsat-5 TM, Landsat-7 ETM+ and SPOT-5 HRG imagery. The approach involves atmospheric correction to compute surface-leaving radiance, and bi-directional reflectance modelling to remove the effects of topography and angular variation in reflectance. The bi-directional reflectance model has been parameterised for eastern Australia, but the general approach is more widely applicable. The result is surface reflectance standardised to a fixed viewing and illumination geometry. The method can be applied to the entire record for these instruments, without intervention, which is of increasing importance with the increased availability of long term image archives. Validation shows that the corrections improve the estimation of reflectance at any given angular configuration, thus allowing the removal from the reflectance signal of much variation due to factors independent of the land surface. The method has been used to process over 45,000 Landsat-5 TM and Landsat-7 ETM+ scenes and 2,500 SPOT-5 scenes, over eastern Australia, and is now in use in operational monitoring programs.

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

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Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

2010-01-01

Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia

Science.gov (United States)

Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn

2016-06-01

Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

FOREST TREE SPECIES DISTRIBUTION MAPPING USING LANDSAT SATELLITE IMAGERY AND TOPOGRAPHIC VARIABLES WITH THE MAXIMUM ENTROPY METHOD IN MONGOLIA

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S. H. Chiang

2016-06-01

Full Text Available Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface

Development of Partial Discharging Simulation Test Equipment

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Kai, Xue; Genghua, Liu; Yan, Jia; Ziqi, Chai; Jian, Lu

2017-12-01

In the case of partial discharge training for recruits who lack of on-site work experience, the risk of physical shock and damage of the test equipment may be due to the limited skill level and improper operation by new recruits. Partial discharge simulation tester is the use of simulation technology to achieve partial discharge test process simulation, relatively true reproduction of the local discharge process and results, so that the operator in the classroom will be able to get familiar with and understand the use of the test process and equipment.The teacher sets up the instrument to display different partial discharge waveforms so that the trainees can analyze the test results of different partial discharge types.

Suppression of vegetation in LANDSAT ETM+ remote sensing images

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Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

2010-05-01

value and scaling all pixels at each vegetation index level by an amount that shifts the curve to the target digital number (DN). The main drawback of their algorithm is severe distortions of the DN values of non-vegetated areas, a suggested solution is masking outliers such as cloud, water, etc. We therefore extend this algorithm by masking non-vegetated areas. Our algorithm comprises the following three steps: (1) masking of barren or sparsely vegetated areas using a threshold based on a vegetation index that is calculated after atmosphere correction (dark pixel correction and ACTOR were compared) in order to conserve their original spectral information through the subsequent processing; (2) applying Crippen and Blom's forced invariance algorithm to suppress the spectral response of vegetation only in vegetated areas; and (3) combining the processed vegetated areas with the masked barren or sparsely vegetated areas followed by histogram equalization to eliminate the differences in color-scales between these two types of areas, and enhance the integrated image. The output images of both study areas showed significant improvement over the original images in terms of suppression of vegetation reflectance and enhancement of the underlying geological information. The processed images show clear banding, probably associated with lithological variations in the underlying rock formations. The colors of non-vegetated pixels are distorted in the unmasked results but in the same location the pixels in the masked results show regions of higher contrast. We conclude that the algorithm offers an effective way to enhance geological information in LANDSAT TM/ETM+ images of terrains with significant vegetation cover. It is also suitable to other multispectral satellite data have bands in similar wavelength regions. In addition, an application of this method to hyperspectral data may be possible as long as it can provide the vegetation band ratios.

Determination of turbidity patterns in Lake Chicot from LANDSAT MSS imagery

Science.gov (United States)

Lecroy, S. R.

1982-01-01

A historical analysis of all the applicable LANDSAT imagery was conducted on the turbidity patterns of Lake Chicot, located in the southeastern corner of Arkansas. By examining the seasonal and regional turbidity patterns, a record of sediment dynamics and possible disposition can be obtained. Sketches were generated from the suitable imagery, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. Additionally, the upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data

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Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.

2013-12-01

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified

Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China

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XIAO, Xiangming; DONG, Jinwei; QIN, Yuanwei; WANG, Zongming

2016-01-01

Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a fine resolution at the regional scale using multi-temporal Landsat imagery. Sixteen Landsat images from 2010–2012 were used to generate the 30 m paddy rice map in the Sanjiang Plain, northeast China—one of the major paddy rice cultivation regions in China. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI), were used to identify rice fields during the flooding/transplanting and ripening phases. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively. The Landsat-based paddy rice map was an improvement over the paddy rice layer on the National Land Cover Dataset, which was generated through visual interpretation and digitalization on the fine-resolution images. The agricultural census data substantially underreported paddy rice area, raising serious concern about its use for studies on food security. PMID:27695637

LEAST SQUARE APPROACH FOR ESTIMATING OF LAND SURFACE TEMPERATURE FROM LANDSAT-8 SATELLITE DATA USING RADIATIVE TRANSFER EQUATION

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Y. Jouybari-Moghaddam

2017-09-01

Full Text Available Land Surface Temperature (LST is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE. However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11 and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation

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Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

2017-09-01

Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

Incorporating Spatio-temporal Phenological Variation in Detecting Exotic Saltcedar Using Landsat Time Series

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Diao, C.; Wang, L.

2017-12-01

The invasion of exotic species compromises ecosystem functions and causes substantial economic losses at the global scale. Over the past century, non-native saltcedar has expanded into most riparian zones in southwestern United States and posed significant threats to the native biotic communities. Repeated monitoring of saltcedar distribution is essential for conservation agencies to locate highly susceptible areas and develop corresponding control strategies. Throughout the phenological cycle, the leaf senescence stage has been found to be the most crucial in spectrally detecting saltcedar. However, due to climate variability and anthropogenic forcing, the timing of saltcedar leaf senescence may vary over space and time. This spatial and inter-annual variation need to be accommodated to pinpoint the appropriate remotely sensed imagery for saltcedar mapping. The objective of this study was to develop a Landsat-based Multiyear Spectral Angle Clustering (MSAC) model to monitor the inter-annual leaf senescence of exotic saltcedar. At the Landsat scale, the time series analysis of vegetation phenology is usually limited by the temporal resolution of images. The MSAC model can overcome this limit and take advantage of the Landsat images from multiple years to compensate the lack of images in a single year. Results indicated the MSAC model provided a Landsat-based solution to capture the inter-annual leaf senescence of saltcedar. Compared to traditional NDVI-based phenological approaches, the proposed model achieved a more accurate classification results of saltcedar across years. The MSAC model provides unique opportunities to guide the selection of appropriate remotely sensed image for repetitive saltcedar mapping.

Geological analysis of parts of the southern Arabian Shield based on Landsat imagery

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Qari, Mohammed Yousef Hedaytullah T.

This thesis examines the capability and applicability of Landsat multispectral remote sensing data for geological analysis in the arid southern Arabian Shield, which is the eastern segment of the Nubian-Arabian Shield surrounding the Red Sea. The major lithologies in the study area are Proterozoic metavolcanics, metasediments, gneisses and granites. Three test-sites within the study area, located within two tectonic assemblages, the Asir Terrane and the Nabitah Mobile Belt, were selected for detailed comparison of remote sensing methods and ground geological studies. Selected digital image processing techniques were applied to full-resolution Landsat TM imagery and the results are interpreted and discussed. Methods included: image contrast improvement, edge enhancement for detecting lineaments and spectral enhancement for geological mapping. The last method was based on two principles, statistical analysis of the data and the use of arithmetical operators. New and detailed lithological and structural maps were constructed and compared with previous maps of these sites. Examples of geological relations identified using TM imagery include: recognition and mapping of migmatites for the first time in the Arabian Shield; location of the contact between the Asir Terrane and the Nabitah Mobile Belt; and mapping of lithologies, some of which were not identified on previous geological maps. These and other geological features were confirmed by field checking. Methods of lineament enhancement implemented in this study revealed structural lineaments, mostly mapped for the first time, which can be related to regional tectonics. Structural analysis showed that the southern Arabian Shield has been affected by at least three successive phases of deformation. The third phase is the most dominant and widespread. A crustal evolutionary model in the vicinity of the study area is presented showing four stages, these are: arc stage, accretion stage, collision stage and post

Demonstration and validation of automated agricultural field extraction from multi-temporal Landsat data for the majority of United States harvested cropland

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Yan, L.; Roy, D. P.

2014-12-01

The spatial distribution of agricultural fields is a fundamental description of rural landscapes and the location and extent of fields is important to establish the area of land utilized for agricultural yield prediction, resource allocation, and for economic planning, and may be indicative of the degree of agricultural capital investment, mechanization, and labor intensity. To date, field objects have not been extracted from satellite data over large areas because of computational constraints, the complexity of the extraction task, and because consistently processed appropriate resolution data have not been available or affordable. A recently published automated methodology to extract agricultural crop fields from weekly 30 m Web Enabled Landsat data (WELD) time series was refined and applied to 14 states that cover 70% of harvested U.S. cropland (USDA 2012 Census). The methodology was applied to 2010 combined weekly Landsat 5 and 7 WELD data. The field extraction and quantitative validation results are presented for the following 14 states: Iowa, North Dakota, Illinois, Kansas, Minnesota, Nebraska, Texas, South Dakota, Missouri, Indiana, Ohio, Wisconsin, Oklahoma and Michigan (sorted by area of harvested cropland). These states include the top 11 U.S states by harvested cropland area. Implications and recommendations for systematic application to global coverage Landsat data are discussed.

Modeling treatment of ischemic heart disease with partially observable Markov decision processes.

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Hauskrecht, M; Fraser, H

1998-01-01

Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead they are very often dependent and interleaved over time, mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of Partially observable Markov decision processes (POMDPs) developed and used in operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In the paper, we show how the POMDP framework could be used to model and solve the problem of the management of patients with ischemic heart disease, and point out modeling advantages of the framework over standard decision formalisms.

Planning treatment of ischemic heart disease with partially observable Markov decision processes.

Science.gov (United States)

Hauskrecht, M; Fraser, H

2000-03-01

Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead, they are very often dependent and interleaved over time. This is mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of partially observable Markov decision processes (POMDPs) developed and used in the operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In this paper, we show how the POMDP framework can be used to model and solve the problem of the management of patients with ischemic heart disease (IHD), and demonstrate the modeling advantages of the framework over standard decision formalisms.

Landsat Evapotranspiration for Historical Field-scale Water Use (1984-2015) in the Upper Rio Grande River Basin

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Senay, G. B.; Schauer, M.; Singh, R. K.; Friedrichs, M.

2017-12-01

Field-scale water use maps derived from evapotranspiration (ET) can characterize water use patterns and the impacts of water management decisions. This project generated historical (1984-2015) Landsat-based ET maps for the entire Upper Rio Grande basin which makes this one of the largest regions in the United States with remotely sensed historical ET at Landsat resolution. More than 10,000 Landsat images spanning 32 years were processed using the Operational Simplified Surface Energy Balance (SSEBop) model which integrates weather data and remotely sensed images to estimate monthly and annual ET. Time-series analysis focused on three water-intensive study areas within the basin: the San Luis Valley in Colorado, irrigated fields along the Rio Grande River near Albuquerque, NM, and irrigated fields near Las Cruces, NM. Preliminary analysis suggests land use changes result in declining water use in irrigated areas of the basin which corresponds with increases in land surface temperatures. Time-series analysis of water use patterns at multiple temporal and spatial scales demonstrates the impact of water management decisions on the availability of water in the basin. Comparisons with cropland data from the USDA (NASS CDL) demonstrate how water use for particular crop types changes over time in response to land use changes and shifts in water management. This study illustrates a useful application of "Big Data" earth observation science for quantifying impacts of climate and land use changes on water availability within the United States as well as applications in planning water resource allocation, managing water rights, and sustaining agricultural production in the Upper Rio Grande basin.

Green leaf phenology at Landsat resolution: scaling from the plot to satellite

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Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

2005-12-01

Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

Increased hydrazine during partial nitritation process in upflow air-lift reactor fed with supernatant of anaerobic digester effluent

Energy Technology Data Exchange (ETDEWEB)

Choi, Jeongdong [University of Alberta, Alberta (Canada); Jung, Sokhee [Samsung SDS, Seoul (Korea, Republic of); Ahn, Young-Ho [Yeungnam University, Gyungsan (Korea, Republic of)

2013-06-15

The optimal balance of ammonium and nitrite is essential for successful operation of the subsequent anammox process. We conducted a partial nitritation experiment using an upflow air-lift reactor to provide operational parameters for achieving the optimal ratio of ammonium to nitrite, by feeding supernatant of anaerobic digester effluent, high-nitrogen containing rejection water. Semi-continuous operation results show that HRT should be set between 15 and 17 hours to achieve the optimum ration of 1.3 of NO{sub 2}-N/NH{sub 4}-N. In the UAR, nitritation was the dominant reaction due to high concentration of ammonia and low biodegradable organics. The influent contained low concentrations of hydroxylamine and hydrazine. However, hydrazine increased during partial nitritation by ⁓60-130% although there was no potential anammox activity in the reactor. The partial nitritation process successfully provided the ratio of nitrogen species for the anammox reaction, and relived the nitrite restraint on the anammox activity by increasing hydrazine concentration.

Ocean Color Measurements from Landsat-8 OLI using SeaDAS

Science.gov (United States)

Franz, Bryan Alden; Bailey, Sean W.; Kuring, Norman; Werdell, P. Jeremy

2014-01-01

The Operational Land Imager (OLI) is a multi-spectral radiometer hosted on the recently launched Landsat-8 satellite. OLI includes a suite of relatively narrow spectral bands at 30-meter spatial resolution in the visible to shortwave infrared that make it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in SeaDAS, which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of satellite-based multi-spectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote-sensing reflectance (Rrs; sr exp 1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents such as the concentration of the phytoplankton pigment chlorophyll a.

Partial oxidation process for producing a stream of hot purified gas

Science.gov (United States)

Leininger, T.F.; Robin, A.M.; Wolfenbarger, J.K.; Suggitt, R.M.

1995-03-28

A partial oxidation process is described for the production of a stream of hot clean gas substantially free from particulate matter, ammonia, alkali metal compounds, halides and sulfur-containing gas for use as synthesis gas, reducing gas, or fuel gas. A hydrocarbonaceous fuel comprising a solid carbonaceous fuel with or without liquid hydrocarbonaceous fuel or gaseous hydrocarbon fuel, wherein said hydrocarbonaceous fuel contains halides, alkali metal compounds, sulfur, nitrogen and inorganic ash containing components, is reacted in a gasifier by partial oxidation to produce a hot raw gas stream comprising H{sub 2}, CO, CO{sub 2}, H{sub 2}O, CH{sub 4}, NH{sub 3}, HCl, HF, H{sub 2}S, COS, N{sub 2}, Ar, particulate matter, vapor phase alkali metal compounds, and molten slag. The hot raw gas stream from the gasifier is split into two streams which are separately deslagged, cleaned and recombined. Ammonia in the gas mixture is catalytically disproportionated into N{sub 2} and H{sub 2}. The ammonia-free gas stream is then cooled and halides in the gas stream are reacted with a supplementary alkali metal compound to remove HCl and HF. Alkali metal halides, vaporized alkali metal compounds and residual fine particulate matter are removed from the gas stream by further cooling and filtering. The sulfur-containing gases in the process gas stream are then reacted at high temperature with a regenerable sulfur-reactive mixed metal oxide sulfur sorbent material to produce a sulfided sorbent material which is then separated from the hot clean purified gas stream having a temperature of at least 1000 F. 1 figure.

Processing Sentinel-2 data with ATCOR

Science.gov (United States)

Pflug, Bringfried; Makarau, Aliaksei; Richter, Rudolf

2016-04-01

Atmospheric correction of satellite images is necessary for many applications of remote sensing. Among them are applications for agriculture, forestry, land cover and land cover change, urban mapping, emergency and inland water. ATCOR is a widely used atmospheric correction tool which can process data of many optical satellite sensors, for instance Landsat, Sentinel-2, SPOT and RapidEye. ATCOR includes a terrain and adjacency correction of satellite images and several special algorithms like haze detection, haze correction, cirrus correction, de-shadowing and empirical methods for BRDF correction. The atmospheric correction tool ATCOR starts with an estimation of the vertical column Aerosol Optical Thickness (AOT550) at 550 nm. The mean uncertainty of the ATCOR-AOT550-estimation was estimated using Landsat and RapidEye data by direct comparison with sunphotometer data as a reference. For Landsat and RapidEye the uncertainty is ΔAOT550nm ≈ 0.03±0.02 for cloudless conditions with a cloud+haze fraction below 1%. Inclusion of cloudy and hazy satellite images into the analysis results in mean ΔAOT550nm ≈ 0.04±0.03 for both RapidEye and Landsat imagery. About 1/3 of the samples perform with the AOT uncertainty better than 0.02 and about 2/3 perform with AOT uncertainty better than 0.05. An accuracy of the retrieved surface reflectance of ±2% (for reflectance reflectance units (for reflectance > 40%) can be achieved for flat terrain, and avoiding the specular and backscattering regions. ATCOR also supports the processing of Sentinel-2 data. First results of processing S2 data and a comparison with AERONET AOT values will be presented.

AUTOMATIC PADDY RICE MAPPING INTERFACE USING ARCENGINE AND LANDSAT8 IMAGERY (CASE STUDY IN NORTH PART OF IRAN

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Sh. Bahramvash Shams

2014-10-01

Full Text Available Recognition of paddy rice boundaries is an essential step for many agricultural processes such as yield estimation, cadastre and water management. In this study, an automatic rice paddy mapping is proposed. The algorithm is based on two temporal images: an initial period of flooding and after harvesting. The proposed method has several steps include: finding flooded pixels and masking unwanted pixels which contain water bodies, clouds, forests, and swamps. In order to achieve final paddy map, indexes such as Normalized Difference Vegetation Index (NDVI and Land Surface Water Index (LSWI are used. Validation is performed by rice paddy boundaries, which were drawn by an expert operator in Google maps. Due to this appraisal good agreement (close to 90% is reached. The algorithm is applied to Gilan province located in the north part of Iran using Landsat 8 date 2013. Automatic Interface is designed based on proposed algorithm using Arc Engine and visual studio. In the Interface, inputs are Landsat bands of two time periods including: red (0.66 μm, blue (0.48 μm, NIR (0.87 μm, and SWIR (2.20 μm, which should be defined by user. The whole process will run automatically and the final result will provide paddy map of desire year.

Combined Use of Landsat-8 and Sentinel-2 Data for Agricultural Monitoring

Science.gov (United States)

Skakun, S.; Roger, J. C.; Vermote, E.; Franch, B.; Becker-Reshef, I.; Justice, C. O.; Masek, J. G.

2017-12-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). Here, we explore the combined use of Landsat-8 and Sentinel-2 data for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2 data improves both winter crop mapping and winter wheat yield assessment.

A New Automatic Method of Urban Areas Mapping in East Asia from LANDSAT Data

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XU, R.; Jia, G.

2012-12-01

Cities, as places where human activities are concentrated, account for a small percent of global land cover but are frequently cited as the chief causes of, and solutions to, climate, biogeochemistry, and hydrology processes at local, regional, and global scales. Accompanying with uncontrolled economic growth, urban sprawl has been attributed to the accelerating integration of East Asia into the world economy and involved dramatic changes in its urban form and land use. To understand the impact of urban extent on biogeophysical processes, reliable mapping of built-up areas is particularly essential in eastern cities as a result of their characteristics of smaller patches, more fragile, and a lower fraction of the urban landscape which does not have natural than in the West. Segmentation of urban land from other land-cover types using remote sensing imagery can be done by standard classification processes as well as a logic rule calculation based on spectral indices and their derivations. Efforts to establish such a logic rule with no threshold for automatically mapping are highly worthwhile. Existing automatic methods are reviewed, and then a proposed approach is introduced including the calculation of the new index and the improved logic rule. Following this, existing automatic methods as well as the proposed approach are compared in a common context. Afterwards, the proposed approach is tested separately in cities of large, medium, and small scale in East Asia selected from different LANDSAT images. The results are promising as the approach can efficiently segment urban areas, even in the presence of more complex eastern cities. Key words: Urban extraction; Automatic Method; Logic Rule; LANDSAT images; East AisaThe Proposed Approach of Extraction of Urban Built-up Areas in Guangzhou, China

Computer mapping of turbidity and circulation patterns in Saginaw Bay, Michigan from LANDSAT data

Science.gov (United States)

Rogers, R. H. (Principal Investigator); Reed, L. E.; Smith, V. E.

1975-01-01

The author has identified the following significant results. LANDSAT was used as a basis for producing geometrically-corrected, color-coded imagery of turbidity and circulation patterns in Saginaw Bay, Michigan (Lake Huron). This imagery shows nine discrete categories of turbidity, as indicated by nine Secchi depths between 0.3 and 3.3 meters. The categorized imagery provided an economical basis for extrapolating water quality parameters from point samples to unsample areas. LANDSAT furnished a synoptic view of water mass boundaries that no amount of ground sampling or monitoring could provide.

Analysis of the Pyroclastic Flow Deposits of Mount Sinabung and Merapi Using Landsat Imagery and the Artificial Neural Networks Approach

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Prima Riza Kadavi

2017-09-01

Full Text Available Volcanic eruptions cause pyroclastic flows, which can destroy plantations and settlements. We used image data from Landsat 7 Bands 7, 4 and 2 and Landsat 8 Bands 7, 5 and 3 to observe and analyze the distribution of pyroclastic flow deposits for two volcanos, Mount Sinabung and Merapi, over a period of 10 years (2001–2017. The satellite data are used in conjunction with an artificial neural network method to produce maps of pyroclastic precipitation for Landsat 7 and 8, then we calculated the pyroclastic precipitation area using an artificial neural network method after dividing the images into four classes based on color. Red, green, blue and yellow were used to indicate pyroclastic deposits, vegetation and forest, water and cloud, and farmland, respectively. The area affected by a volcanic eruption was deduced from the neural network processing, including calculating the area of pyroclastic deposits. The main differences between the pyroclastic flow deposits of Mount Sinabung and Mount Merapi are: the sediment deposits of the pyroclastic flows of Mount Sinabung tend to widen, whereas those of Merapi elongated; the direction of pyroclastic flow differed; and the area affected by an eruption was greater for Mount Merapi than Mount Sinabung because the VEI (Volcanic Explosivity Index during the last 10 years of Mount Merapi was larger than Mount Sinabung.

Interpretasi Vulkanostratigrafi Daerah Mamuju Berdasarkan Analisis Citra Landsat-8

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Frederikus Dian Indrastomo

2015-11-01

Full Text Available Mamuju and its surrounding area are constructed mainly by volcanic rocks. Volcanoclastic sedimentary rocks and limestones are laid above the volcanic rocks. Volcanic activities create some unique morphologies such as craters, lava domes, and pyroclastic flow paths as their volcanic products. These products are identified from their circular features characters on Landsat-8 imagery. After geometric and atmospheric corrections had been done, a visual interpretation on Landsat-8 imagery was conducted to identify structure, geomorphology, and geological condition of the area. Regional geological structures show trend to southeast – northwest direction which is affects the formation of Adang volcano. Geomorphology of the area are classified into 16 geomorphology units based on their genetic aspects, i.e Sumare fault block ridge, Mamuju cuesta ridge, Adang eruption crater, Labuhan Ranau eruption crater, Sumare eruption crater, Ampalas volcanic cone, Adang lava dome, Labuhan Ranau intrusion hill, Adang pyroclastic flow ridge, Sumare pyroclastic flow ridge, Adang volcanic remnant hills, Malunda volcanic remnant hills, Talaya volcanic remnant hills, Tapalang karst hills, Mamuju alluvium plains, and Karampuang reef terrace plains. Based on the Landsat-8 imagery interpretation result and field confirmation, the geology of Mamuju area is divided into volcanic rocks and sedimentary rocks. There are two groups of volcanic rocks; Talaya complex and Mamuju complex. The Talaya complex consists of Mambi, Malunda, and Kalukku volcanic rocks with andesitic composition, while Mamuju complex consist of Botteng, Ahu, Tapalang, Adang, Ampalas, Sumare, danLabuhanRanau volcanic rocks with andesite to leucitic basalt composition. The volcanostratigraphy of Mamuju area was constructed based on its structure, geomorphology and lithology distribution analysis. Volcanostratigraphy of Mamuju area is classified into Khuluk Talaya and Khuluk Mamuju. The Khuluk Talaya consists

Spatiotemporal Variation in Mangrove Chlorophyll Concentration Using Landsat 8

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Julio Pastor-Guzman

2015-11-01

Full Text Available There is a need to develop indicators of mangrove condition using remotely sensed data. However, remote estimation of leaf and canopy biochemical properties and vegetation condition remains challenging. In this paper, we (i tested the performance of selected hyperspectral and broad band indices to predict chlorophyll concentration (CC on mangrove leaves and (ii showed the potential of Landsat 8 for estimation of mangrove CC at the landscape level. Relative leaf CC and leaf spectral response were measured at 12 Elementary Sampling Units (ESU distributed along the northwest coast of the Yucatan Peninsula, Mexico. Linear regression models and coefficients of determination were computed to measure the association between CC and spectral response. At leaf level, the narrow band indices with the largest correlation with CC were Vogelmann indices and the MTCI (R2 > 0.5. Indices with spectral bands around the red edge (705–753 nm were more sensitive to mangrove leaf CC. At the ESU level Landsat 8 NDVI green, which uses the green band in its formulation explained most of the variation in CC (R2 > 0.8. Accuracy assessment between estimated CC and observed CC using the leave-one-out cross-validation (LOOCV method yielded a root mean squared error (RMSE = 15 mg·cm−2, and R2 = 0.703. CC maps showing the spatiotemporal variation of CC at landscape scale were created using the linear model. Our results indicate that Landsat 8 NDVI green can be employed to estimate CC in large mangrove areas where ground networks cannot be applied, and mapping techniques based on satellite data, are necessary. Furthermore, using upcoming technologies that will include two bands around the red edge such as Sentinel 2 will improve mangrove monitoring at higher spatial and temporal resolutions.

Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

Science.gov (United States)

Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

2014-12-01

Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active

Estimation of Airborne Lidar-Derived Tropical Forest Canopy Height Using Landsat Time Series in Cambodia

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Tetsuji Ota

2014-11-01

Full Text Available In this study, we test and demonstrate the utility of disturbance and recovery information derived from annual Landsat time series to predict current forest vertical structure (as compared to the more common approaches, that consider a sample of airborne Lidar and single-date Landsat derived variables. Mean Canopy Height (MCH was estimated separately using single date, time series, and the combination of single date and time series variables in multiple regression and random forest (RF models. The combination of single date and time series variables, which integrate disturbance history over the entire time series, overall provided better MCH prediction than using either of the two sets of variables separately. In general, the RF models resulted in improved performance in all estimates over those using multiple regression. The lowest validation error was obtained using Landsat time series variables in a RF model (R2 = 0.75 and RMSE = 2.81 m. Combining single date and time series data was more effective when the RF model was used (opposed to multiple regression. The RMSE for RF mean canopy height prediction was reduced by 13.5% when combining the two sets of variables as compared to the 3.6% RMSE decline presented by multiple regression. This study demonstrates the value of airborne Lidar and long term Landsat observations to generate estimates of forest canopy height using the random forest algorithm.

Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

Science.gov (United States)

Oreopoulos, Lazaros; Wilson, Michael J.; Varnai, Tamas

2010-01-01

This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand

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Uday Pimple

2017-02-01

Full Text Available The accurate mapping and monitoring of forests is essential for the sustainable management of forest ecosystems. Advancements in the Landsat satellite series have been very useful for various forest mapping applications. However, the topographic shadows of irregular mountains are major obstacles to accurate forest classification. In this paper, we test five topographic correction methods: improved cosine correction, Minnaert, C-correction, Statistical Empirical Correction (SEC and Variable Empirical Coefficient Algorithm (VECA, with multisource digital elevation models (DEM to reduce the topographic relief effect in mountainous terrain produced by the Landsat Thematic Mapper (TM-5 and Operational Land Imager (OLI-8 sensors. The effectiveness of the topographic correction methods are assessed by visual interpretation and the reduction in standard deviation (SD, by means of the coefficient of variation (CV. Results show that the SEC performs best with the Shuttle Radar Topographic Mission (SRTM 30 m × 30 m DEM. The random forest (RF classifier is used for forest classification, and the overall accuracy of forest classification is evaluated to compare the performances of the topographic corrections. Our results show that the C-correction, SEC and VECA corrected imagery were able to improve the forest classification accuracy of Landsat TM-5 from 78.41% to 81.50%, 82.38%, and 81.50%, respectively, and OLI-8 from 81.06% to 81.50%, 82.38%, and 81.94%, respectively. The highest accuracy of forest type classification is obtained with the newly available high-resolution SRTM DEM and SEC method.

Global 30m 2000-2014 Surface Water Dynamics Map Derived from All Landsat 5, 7, and 8

Science.gov (United States)

Hudson, A.; Hansen, M.

2015-12-01

Water is critical for human life, agriculture, and ecosystems. A better understanding of where it is and how it is changing will enable better management of this valuable resource and guide protection of sensitive ecological areas. Global water maps have typically been representations of surface water at one given time. However, there is both seasonal and interannual variability: rivers meander, lakes disappear, floods arise. To address this ephemeral nature of water, in this study University of Maryland has developed a method that analyzes every Landsat 5, 7, and 8 scene from 1999-2015 to produce global seasonal maps (Winter, Spring, Summer, Fall) of surface water dynamics from 2000-2014. Each Landsat scene is automatically classified into land, water, cloud, haze, shadow, and snow via a decision tree algorithm. The land and water observations are aggregated per pixel into percent occurrence of water in a 3 year moving window for each meteorological season. These annual water percentages form a curve for each season that is discretized into a continuous 3 band RGB map. Frequency of water observation and type of surface water change (loss, gain, peak, or dip) is clearly seen through brightness and hue respectively. Additional data layers include: the year the change began, peak year, minimum year, and the year the change process ended. Currently these maps have been created for 18 1°x1° test tiles scattered around the world, and a portion of the September-November map over Bangladesh is shown below. The entire Landsat archive from 1999-2015 will be processed through a partnership with Google Earth Engine to complete the global product in the coming months. In areas where there is sufficient satellite data density (e.g. the United States), this project could be expanded to 1984-2015. This study provides both scientific researchers and the public an understandable, temporally rich, and globally consistent map showing surface water changes over time.

Application of Landsat Thematic Mapper data for coastal thermal plume analysis at Diablo Canyon

Science.gov (United States)

Gibbons, D. E.; Wukelic, G. E.; Leighton, J. P.; Doyle, M. J.

1989-01-01

The possibility of using Landsat Thematic Mapper (TM) thermal data to derive absolute temperature distributions in coastal waters that receive cooling effluent from a power plant is demonstrated. Landsat TM band 6 (thermal) data acquired on June 18, 1986, for the Diablo Canyon power plant in California were compared to ground truth temperatures measured at the same time. Higher-resolution band 5 (reflectance) data were used to locate power plant discharge and intake positions and identify locations of thermal pixels containing only water, no land. Local radiosonde measurements, used in LOWTRAN 6 adjustments for atmospheric effects, produced corrected ocean surface radiances that, when converted to temperatures, gave values within approximately 0.6 C of ground truth. A contour plot was produced that compared power plant plume temperatures with those of the ocean and coastal environment. It is concluded that Landsat can provide good estimates of absolute temperatures of the coastal power plant thermal plume. Moreover, quantitative information on ambient ocean surface temperature conditions (e.g., upwelling) may enhance interpretation of numerical model prediction.

TEMPERATURA DE SUPERFÍCIE CELSIUS DO SENSOR TIRS/LANDSAT-8: METODOLOGIA E APLICAÇÕES

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André Luiz Nascentes Coelho

2013-11-01

Full Text Available Este trabalho tem como objetivo, contribuir na difusão e operacionalização das geotecnologias, apresentando os algoritmos para obtenção de temperatura da superfície horizontal Celsius na faixa infravermelho termal do sensor TIRS/Landsat-8, banda 10. A aplicação das equações proporcionou não só identificar os maiores percentuais de temperatura de superfície, em diferentes escalas espaciais, como também, definir o perfil do campo térmico em distintas texturas. Além disso, foi possível comparar, em imagens, a melhoria da resolução espacial do canal infravermelho termal Landsat-8 em relação ao Landsat-5. Tal metodologia possibilita a aplicação em outros intervalos de datas e locais distintos, contribuindo nas pesquisas e no auxílio detomadas de decisões.

TEMPERATURA DE SUPERFÍCIE CELSIUS DO SENSOR TIRS/LANDSAT-8: METODOLOGIA E APLICAÇÕES

Directory of Open Access Journals (Sweden)

André Luiz Nascentes Coelho

2015-09-01

Full Text Available Este trabalho tem como objetivo, contribuir na difusão e operacionalização das geotecnologias, apresentando os algoritmos para obtenção de temperatura da superfície horizontal Celsius na faixa infravermelho termal do sensor TIRS/Landsat-8, banda 10. A aplicação das equações proporcionou não só identificar os maiores percentuais de temperatura de superfície, em diferentes escalas espaciais, como também, definir o perfil do campo térmico em distintas texturas. Além disso, foi possível comparar, em imagens, a melhoria da resolução espacial do canal infravermelho termal Landsat-8 em relação ao Landsat-5. Tal metodologia possibilita a aplicação em outros intervalos de datas e locais distintos, contribuindo nas pesquisas e no auxílio detomadas de decisões.

BOREAS RSS-15 SIR-C and Landsat TM Biomass and Landcover Maps of the NSA

Science.gov (United States)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Ranson, K. Jon

2000-01-01

As part of BOREAS, the RSS-15 team conducted an investigation using SIR-C, X-SAR, and Landsat TM data for estimating total above-ground dry biomass for the SSA and NSA modeling grids and component biomass for the SSA. Relationships of backscatter to total biomass and total biomass to foliage, branch, and bole biomass were used to estimate biomass density across the landscape. The procedure involved image classification with SAR and Landsat TM data and development of simple mapping techniques using combinations of SAR channels. For the SSA, the SIR-C data used were acquired on 06-Oct-1994, and the Landsat TM data used were acquired on 02-Sep-1995. The maps of the NSA were developed from SIR-C data acquired on 13-Apr-1994. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Seasonally-managed wetland footprint delineation using Landsat ETM+ satellite imagery

Energy Technology Data Exchange (ETDEWEB)

Quinn, Nigel W. T. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Epshtein, Olga [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Arizona State Univ., Tempe, AZ (United States). School of Sustainable Engineering and the Built Environment

2014-01-09

One major challenge in water resource management is the estimation of evapotranspiration losses from seasonally managed wetlands. Quantifying these losses is complicated by the dynamic nature of the wetlands' areal footprint during the periods of flood-up and drawdown. In this paper, we present a data-lean solution to this problem using an example application in the San Joaquin Basin, California. Through analysis of high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) satellite imagery, we develop a metric to better capture the extent of total flooded wetland area. The procedure is validated using year-long, continuously-logged field datasets for two wetlands within the study area. The proposed classification which uses a Landsat ETM + Band 5 (mid-IR wavelength) to Band 2 (visible green wavelength) ratio improves estimates by 30–50% relative to previous wetland delineation studies. Finally, requiring modest ancillary data, the study results provide a practical and efficient option for wetland management in data-sparse regions or un-gauged watersheds.

Landsat 8 Operational Land Imager (OLI)_Thermal Infared Sensor (TIRS) V1

Data.gov (United States)

National Aeronautics and Space Administration — Abstract:The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are instruments onboard the Landsat 8 satellite, which was launched in February of...

Landsat Data Continuity Mission (LDCM) space to ground mission data architecture

Science.gov (United States)

Nelson, Jack L.; Ames, J.A.; Williams, J.; Patschke, R.; Mott, C.; Joseph, J.; Garon, H.; Mah, G.

2012-01-01

The Landsat Data Continuity Mission (LDCM) is a scientific endeavor to extend the longest continuous multi-spectral imaging record of Earth's land surface. The observatory consists of a spacecraft bus integrated with two imaging instruments; the Operational Land Imager (OLI), built by Ball Aerospace & Technologies Corporation in Boulder, Colorado, and the Thermal Infrared Sensor (TIRS), an in-house instrument built at the Goddard Space Flight Center (GSFC). Both instruments are integrated aboard a fine-pointing, fully redundant, spacecraft bus built by Orbital Sciences Corporation, Gilbert, Arizona. The mission is scheduled for launch in January 2013. This paper will describe the innovative end-to-end approach for efficiently managing high volumes of simultaneous realtime and playback of image and ancillary data from the instruments to the reception at the United States Geological Survey's (USGS) Landsat Ground Network (LGN) and International Cooperator (IC) ground stations. The core enabling capability lies within the spacecraft Command and Data Handling (C&DH) system and Radio Frequency (RF) communications system implementation. Each of these systems uniquely contribute to the efficient processing of high speed image data (up to 265Mbps) from each instrument, and provide virtually error free data delivery to the ground. Onboard methods include a combination of lossless data compression, Consultative Committee for Space Data Systems (CCSDS) data formatting, a file-based/managed Solid State Recorder (SSR), and Low Density Parity Check (LDPC) forward error correction. The 440 Mbps wideband X-Band downlink uses Class 1 CCSDS File Delivery Protocol (CFDP), and an earth coverage antenna to deliver an average of 400 scenes per day to a combination of LGN and IC ground stations. This paper will also describe the integrated capabilities and processes at the LGN ground stations for data reception using adaptive filtering, and the mission operations approach fro- the LDCM

Quantifying BRDF Effects in Comparing Landsat-7 and AVIRIS Near-Simultaneous Acquisitions for Studies of High Plains Vegetation Cover

Science.gov (United States)

Goetz, A. F. H.; Heidebrecht, K. B.; Gutmann, E. D.; Warner, A. S.; Johnson, E. L.; Lestak, L. R.

1999-01-01

Approximately 100,000 sq. km of the High Plains of the central United States are covered by sand dunes and sand sheets deposited during the Holocene. Soil-dating evidence shows that there were at least four periods of dune reactivation during major droughts in the last 10,000 years. The dunes in this region are anchored by vegetation. We have undertaken a study of land-use change in the High Plains from 1985 to the present using Landsat 5 TM and Landsat 7 ETM+ images to map variation in vegetation cover during wet and dry years. Mapping vegetation cover of less than 20% is important in modeling potential surface reactivation since at this level the vegetation no longer sufficiently shields sandy surfaces from movement by wind. Landsat TM data have both the spatial resolution and temporal coverage to facilitate vegetation cover analysis for model development and verification. However, there is still the question of how accurate TM data are for the measurement of both growing and senescent vegetation in and and semi-arid regions. AVIRIS provides both high spectral resolution as well as high signal-to-noise ratio and can be used to test the accuracy of Landsat TM and ETM+ data. We have analyzed data from AVIRIS flown nearly concurrently with a Landsat 7 overpass. The comparison between an AVIRIS image swath of 11 km width subtending a 30 deg. angle and the same area covered by a 0.8 deg. angle from Landsat required accounting for the BRDF. A normalization technique using the ratio of the reflectances from registered AVIRIS and Landsat data proved superior to the techniques of column averaging on AVIRIS data alone published previously by Kennedy et al. This technique can be applied to aircraft data covering a wider swath angle than AVIRIS to develop BRDF responses for a wide variety of surfaces more efficiently than from ground measurements.

CO2 separation by calcium looping from full and partial fuel oxidation processes

International Nuclear Information System (INIS)

Sivalingam, Senthoorselvan

2013-01-01

This thesis work deals with the research and development of calcium looping process for CO 2 separation from full and partial fuel oxidation based power generation systems. CO 2 is the main greenhouse gas and undoubtedly a major contributor to the global warming. It is estimated that more than one third of the total anthropogenic CO 2 emissions come from fossil fuel based heat and power generation. Moreover, fossil fuels are unlikely to be phased out rapidly, since developing alternative energy sources not only take time but also require huge investments and infrastructure. An alternative way to reduce emissions in a medium term is to capture the CO 2 from fossil fueled power plants and store it away from the atmosphere. This process system combining a bunch of technologies is called carbon capture and storage (CCS). CO 2 capture is an important and costly part of CCS and an array of technologies is considered for this. Calcium looping (CaL) is one of such and seems to offer effective and efficient CO 2 separation from fuel oxidation processes. CaL process involves separation of CO 2 at high temperatures (600-700 C) by calcium sorbents (CaO). CO 2 reacts with CaO in a carbonation process and produces CaCO 3 . In a subsequent thermal regeneration (>850 C) called calcination, the CO 2 is released from CaCO 3 . By alternating carbonations and calcinations over multiple cycles, CO 2 is separated from a gas stream. Moreover, the CaL is realised in industrial scale with dual fluidised bed reactors for CO 2 capture (the carbonator) and sorbent regeneration (the calciner). As a process in the development, research is still required in many aspects from thermodynamic modeling to experimental studies. Research works have been carried out in process simulations, sorbent reactivity and optimisation studies in a controlled reactor environment and process parametric studies in a semi-pilot scale CaL test facility. ASPEN Plus power plant simulations integrating the CaL based CO 2

Identifying Spatial Units of Human Occupation in the Brazilian Amazon Using Landsat and CBERS Multi-Resolution Imagery

OpenAIRE

Dal’Asta, Ana Paula; Brigatti, Newton; Amaral, Silvana; Escada, Maria Isabel Sobral; Monteiro, Antonio Miguel Vieira

2012-01-01

Every spatial unit of human occupation is part of a network structuring an extensive process of urbanization in the Amazon territory. Multi-resolution remote sensing data were used to identify and map human presence and activities in the Sustainable Forest District of Cuiabá-Santarém highway (BR-163), west of Pará, Brazil. The limits of spatial units of human occupation were mapped based on digital classification of Landsat-TM5 (Thematic Mapper 5) image (30m spatial resolution). High-spatial-...

LANDSAT M. S. S. IMAGE MOSAIC OF TUNISIA.

Science.gov (United States)

Boswell-Thomas, J. C.; ,

1984-01-01

The Landsat mosaic of Tunisia funded by USAID for the Remote Sensing Laboratory, Soils Division, Ministry of Agriculture, Tunisia, was completed by the USGS in September 1983. It is a mixed mosaic associating digital corrections and enhancements to manual mosaicking and corresponding to the Tunisian request for high resolution and the limited available funds. The scenes were processed by the Environmental Research Institute of Michigan, resampling the data geodesically corrected to fit the Universal Transverse Mercator projection using control points from topographic maps at 1:50,000 and 1:100,000 scales available in the U. S. The mosaicking was done in the Eastern Mapping Center under the supervision of the Graphic Arts System Section. The three black and white mosaics were made at the 1:1,000,000 scale and various products generated. They included color film positives at 1:2,000,000 and 1:4,000,000 scales reproducible in the Remote Sensing Laboratory in Tunis and corresponding color prints as well as tricolor prints at various scales from 1:500,000 to 1:2,000,000.

Gap-Filling of Landsat 7 Imagery Using the Direct Sampling Method

KAUST Repository

Yin, Gaohong; Mariethoz, Gregoire; McCabe, Matthew

2016-01-01

The failure of the Scan Line Corrector (SLC) on Landsat 7 imposed systematic data gaps on retrieved imagery and removed the capacity to provide spatially continuous fields. While a number of methods have been developed to fill these gaps, most

Mapping disturbance dynamics in wet sclerophyll forests using time series Landsat

NARCIS (Netherlands)

Haywood, A.; Verbesselt, J.; Baker, P.J.

2016-01-01

In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat

Post Landsat-D advanced concept evaluation /PLACE/

Science.gov (United States)

Alexander, L. D.; Alvarado, U. R.; Flatow, F. S.

1979-01-01

The aim of the Post Landsat-D Advanced Concept Evaluation (PLACE) program was to identify the key technology requirements of earth resources satellite systems for the 1985-2000 period. The program involved four efforts: (1) examination of future needs in the earth resources area, (2) creation of a space systems technology model capable of satisfying these needs, (3) identification of key technology requirements posed by this model, and (4) development of a methodology (PRISM) to assist in the priority structuring of the resulting technologies.

Near Real-Time Browsable Landsat-8 Imagery

OpenAIRE

Cheng-Chien Liu; Ryosuke Nakamura; Ming-Hsun Ko; Tomoya Matsuo; Soushi Kato; Hsiao-Yuan Yin; Chung-Shiou Huang

2017-01-01

The successful launch and operation of Landsat-8 extends the remarkable 40-year acquisition of space-based land remote-sensing data. To respond quickly to emergency needs, real-time data are directly downlinked to 17 ground stations across the world on a routine basis. With a size of approximately 1 Gb per scene, however, the standard level-1 product provided by these stations is not able to serve the general public. Users would like to browse the most up-to-date and historical images of thei...

Regional estimates of reef carbonate dynamics and productivity Using Landsat 7 ETM+, and potential impacts from ocean acidification

Science.gov (United States)

Moses, C.S.; Andrefouet, S.; Kranenburg, C.; Muller-Karger, F. E.

2009-01-01

Using imagery at 30 m spatial resolution from the most recent Landsat satellite, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), we scale up reef metabolic productivity and calcification from local habitat-scale (10 -1 to 100 km2) measurements to regional scales (103 to 104 km2). Distribution and spatial extent of the North Florida Reef Tract (NFRT) habitats come from supervised classification of the Landsat imagery within independent Landsat-derived Millennium Coral Reef Map geomorphologic classes. This system minimizes the depth range and variability of benthic habitat characteristics found in the area of supervised classification and limits misclassification. Classification of Landsat imagery into 5 biotopes (sand, dense live cover, sparse live cover, seagrass, and sparse seagrass) by geomorphologic class is >73% accurate at regional scales. Based on recently published habitat-scale in situ metabolic measurements, gross production (P = 3.01 ?? 109 kg C yr -1), excess production (E = -5.70 ?? 108 kg C yr -1), and calcification (G = -1.68 ?? 106 kg CaCO 3 yr-1) are estimated over 2711 km2 of the NFRT. Simple models suggest sensitivity of these values to ocean acidification, which will increase local dissolution of carbonate sediments. Similar approaches could be applied over large areas with poorly constrained bathymetry or water column properties and minimal metabolic sampling. This tool has potential applications for modeling and monitoring large-scale environmental impacts on reef productivity, such as the influence of ocean acidification on coral reef environments. ?? Inter-Research 2009.

Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a

Directory of Open Access Journals (Sweden)

Jordan Snyder

2017-06-01

Full Text Available Remote sensing data is useful for selection of aquaculture sites because it can provide water-quality products mapped over large regions at low cost to users. However, the spatial resolution of most ocean color satellites is too coarse to provide usable data within many estuaries. The Landsat 8 satellite, launched February 11, 2013, has both the spatial resolution and the necessary signal to noise ratio to provide temperature, as well as ocean color derived products along complex coastlines. The state of Maine (USA has an abundance of estuarine indentations (~3,500 miles of tidal shoreline within 220 miles of coast, and an expanding aquaculture industry, which makes it a prime case-study for using Landsat 8 data to provide products suitable for aquaculture site selection. We collected the Landsat 8 scenes over coastal Maine, flagged clouds, atmospherically corrected the top-of-the-atmosphere radiances, and derived time varying fields (repeat time of Landsat 8 is 16 days of temperature (100 m resolution, turbidity (30 m resolution, and chlorophyll a (30 m resolution. We validated the remote-sensing-based products at several in situ locations along the Maine coast where monitoring buoys and programs are in place. Initial analysis of the validated fields revealed promising new areas for oyster aquaculture. The approach used is applicable to other coastal regions and the data collected to date show potential for other applications in marine coastal environments, including water quality monitoring and ecosystem management.

Mapping Canopy Height and Growing Stock Volume Using Airborne Lidar, ALOS PALSAR and Landsat ETM+

Directory of Open Access Journals (Sweden)

Wayne Walker

2012-10-01

Full Text Available We have investigated for forest plantations in Chile the stand-level retrieval of canopy height (CH and growing stock volume (GSV using Airborne Laser Scanner (ALS, ALOS PALSAR and Landsat. In a two-stage up-scaling approach, ensemble regression tree models (randomForest were used to relate a suite of ALS canopy structure indices to stand-level in situ measurements of CH and GSV for 319 stands. The retrieval of CH and GSV with ALS yielded high accuracies with R2s of 0.93 and 0.81, respectively. A second set of randomForest models was developed using multi-temporal ALOS PALSAR intensities and repeat-pass coherences in two polarizations as well as Landsat data as predictor and stand-level ALS based estimates of CH and GSV as response variables. At three test sites, the retrieval of CH and GSV with PALSAR/Landsat reached promising accuracies with R2s in the range of 0.7 to 0.85. We show that the combined use of multi-temporal PALSAR intensity, coherence and Landsat yields higher retrieval accuracies than the retrieval with any of the datasets alone. Potential limitations for the large-area application of the fusion approach included (1 the low sensitivity of ALS first/last return data to forest horizontal structure, affecting the retrieval of GSV in less managed types of forest, and (2 the dense ALS sampling required to achieve high retrieval accuracies at larger scale.

Use of GLOBE Observations to Derive a Landsat 8 Split Window Algorithm for Urban Heat Island

Science.gov (United States)

Fagerstrom, L.; Czajkowski, K. P.

2017-12-01

Surface temperature has been studied to investigate the warming of urban climates, also known as urban heat islands, which can impact urban planning, public health, pollution levels, and energy consumption. However, the full potential of remotely sensed images is limited when analyzing land surface temperature due to the daunting task of correcting for atmospheric effects. Landsat 8 has two thermal infrared sensors. With two bands in the infrared region, a split window algorithm (SWA), can be applied to correct for atmospheric effects. This project used in situ surface temperature measurements from NASA's ground observation program, the Global Learning and Observations to Benefit the Environment (GLOBE), to derive the correcting coefficients for use in the SWA. The GLOBE database provided land surface temperature data that coincided with Landsat 8 overpasses. The land surface temperature derived from Landsat 8 SWA can be used to analyze for urban heat island effect.

Partial Nitrification and Denitrifying Phosphorus Removal in a Pilot-Scale ABR/MBR Combined Process.

Science.gov (United States)

Wu, Peng; Xu, Lezhong; Wang, Jianfang; Huang, Zhenxing; Zhang, Jiachao; Shen, Yaoliang

2015-11-01

A pilot-scale combined process consisting of an anaerobic baffled reactor (ABR) and an aerobic membrane bioreactor (MBR) for the purpose of achieving easy management, low energy demands, and high efficiencies on nutrient removal from municipal wastewater was investigated. The process operated at room temperature with hydraulic retention time (HRT) of 7.5 h, recycle ratio 1 of 200%, recycle ratio 2 of 100%, and dissolved oxygen (DO) of 1 mg/L and achieved good effluent quality with chemical oxygen demand (COD) of 25 mg/L, NH4 (+)-N of 4 mg/L, total nitrogen (TN) of 11 mg/L, and total phosphorus (TP) of 0.7 mg/L. The MBR achieved partial nitrification, and NO2 (-)-N has been accumulated (4 mg/L). Efficient short-cut denitrification was occurred in the ABR with a TN removal efficiency of 51%, while the role of denitrification and phosphorus removal removed partial TN (14%). Furthermore, nitrogen was further removed (11%) by simultaneous nitrification and denitrification in the MBR. In addition, phosphorus accumulating organisms in the MBR sufficiently uptake phosphorus; thus, effluent TP further reduced with a TP removal efficiency of 84%. Analysis of fluorescence in situ hybridization (FISH) showed that ammonia oxidizing bacteria (AOB) and phosphorus accumulating organisms (PAOs) were enriched in the process. In addition, the accumulation of NO2 (-)-N was contributed to the inhibition on the activities of the NOB rather than its elimination.

Influence of Oxygen Partial Pressure during Processing on the Thermoelectric Properties of Aerosol-Deposited CuFeO₂.

Science.gov (United States)

Stöcker, Thomas; Exner, Jörg; Schubert, Michael; Streibl, Maximilian; Moos, Ralf

2016-03-24

In the field of thermoelectric energy conversion, oxide materials show promising potential due to their good stability in oxidizing environments. Hence, the influence of oxygen partial pressure during synthesis on the thermoelectric properties of Cu-Delafossites at high temperatures was investigated in this study. For these purposes, CuFeO₂ powders were synthetized using a conventional mixed-oxide technique. X-ray diffraction (XRD) studies were conducted to determine the crystal structures of the delafossites associated with the oxygen content during the synthesis. Out of these powders, films with a thickness of about 25 µm were prepared by the relatively new aerosol-deposition (AD) coating technique. It is based on a room temperature impact consolidation process (RTIC) to deposit dense solid films of ceramic materials on various substrates without using a high-temperature step during the coating process. On these dense CuFeO₂ films deposited on alumina substrates with electrode structures, the Seebeck coefficient and the electrical conductivity were measured as a function of temperature and oxygen partial pressure. We compared the thermoelectric properties of both standard processed and aerosol deposited CuFeO₂ up to 900 °C and investigated the influence of oxygen partial pressure on the electrical conductivity, on the Seebeck coefficient and on the high temperature stability of CuFeO₂. These studies may not only help to improve the thermoelectric material in the high-temperature case, but may also serve as an initial basis to establish a defect chemical model.

Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

Science.gov (United States)

Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

2010-01-01

Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

THE AVAILABILITY VERSUS THE USE OF PARTIAL INFORMATION - MULTIPLE LEVELS OF SELECTIVE PROCESSING BETWEEN PERCEPTION AND ACTION

NARCIS (Netherlands)

SMID, HGOM; MULDER, G

Temporal overlap of cognitive processes occurs when partial information about a stimulus activates associated responses before the stimulus has been fully identified. Recent evidence obtained with psychophysiological measures suggests that such overlap sometimes does, and sometimes does not occur.

Regional Geological Mapping in the Graham Land of Antarctic Peninsula Using LANDSAT-8 Remote Sensing Data

Science.gov (United States)

Pour, A. B.; Hashim, M.; Park, Y.

2017-10-01

Geological investigations in Antarctica confront many difficulties due to its remoteness and extreme environmental conditions. In this study, the applications of Landsat-8 data were investigated to extract geological information for lithological and alteration mineral mapping in poorly exposed lithologies in inaccessible domains such in Antarctica. The north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. Continuum Removal (CR) spectral mapping tool and Independent Components Analysis (ICA) were applied to Landsat-8 spectral bands to map poorly exposed lithologies at regional scale. Pixels composed of distinctive absorption features of alteration mineral assemblages associated with poorly exposed lithological units were detected by applying CR mapping tool to VNIR and SWIR bands of Landsat-8.Pixels related to Si-O bond emission minima features were identified using CR mapping tool to TIR bands in poorly mapped andunmapped zones in north-eastern Graham Land at regional scale. Anomaly pixels in the ICA image maps related to spectral featuresof Al-O-H, Fe, Mg-O-H and CO3 groups and well-constrained lithological attributions from felsic to mafic rocks were detectedusing VNIR, SWIR and TIR datasets of Landsat-8. The approach used in this study performed very well for lithological andalteration mineral mapping with little available geological data or without prior information of the study region.

Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

Science.gov (United States)

Hilbert, Kent; Pagnutti, Mary; Ryan, Robert; Zanoni, Vicki

2002-01-01

This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

Landsat analysis of the Yangjiatan tungsten district, Hunan Province, People's Republic of China

Science.gov (United States)

Carter, W.D.; Kiilsgaard, T.H.

1983-01-01

The Yangjiatan tungsten district at latitude 27??28??? N. and longitude 111??54???E. is located about 140 km southwest of the city of Changsha and 35 km northeast of the town of Shaoyang, southeast Hunan Province, People's Republic of China. The deposits, consisting largely of scheelite in veins (Wang, 1975), are contained in highly folded and faulted sedimentary rocks of Paleozoic, Mesozoic, and Cenozoic age intruded by granitic plutons that are circular in plan view. The major faults and folds trend in a northeasterly direction; whereas, the plutons are clustered in a more easterly trending band across the Landsat image. Landsat image E-2338-02202, acquired December 26, 1975, is number 470 in the "Landsat Image Atlas of the People's Republic of China" printed by the Publishing House of Geology in 1979. A computer-compatible tape of the image was analyzed and used as a demonstration project under a United Nations technical assistance program. Supervised classification of soils, rocks, and vegetation; band ratioing to detect limonite alteration; and edge enhancement were all conducted to demonstrate the flexibility and capability of interactive computer systems. Field evaluation of the results of this work will be conducted by colleagues of the Remote Sensing Center for Geology, Ministry of Geology, in China. ?? 1983.

Glacial lake monitoring in the Karakoram Range using historical Landsat Thematic Mapper archive (1982 - 2014)

Science.gov (United States)

Chan, J. Y. H.; Kelly, R. E. J.; Evans, S. G.

2014-12-01

Glacierized regions are one of the most dynamic land surface environments on the planet (Evans and Delaney, In Press). They are susceptible to various types of natural hazards such as landslides, glacier avalanches, and glacial lake outburst floods (GLOF). GLOF events are increasingly common and present catastrophic flood hazards, the causes of which are sensitive to climate change in complex high mountain topography (IPCC, 2013). Inundation and debris flows from GLOF events have repeatedly caused significant infrastructure damages and loss of human lives in the high mountain regions of the world (Huggel et al, 2002). The research is designed to develop methods for the consistent detection of glacier lakes formation during the Landsat Thematic Mapper (TM) era (1982 - present), to quantify the frequency of glacier lake development and estimate lake volume using Landsat imagery and digital elevation model (DEM) data. Landsat TM scenes are used to identify glacier lakes in the Shimshal and Shaksgam valley, particularly the development of Lake Virjeab in year 2000 and Kyagar Lake in 1998. A simple thresholding technique using Landsat TM infrared bands, along with object-based segmentation approaches are used to isolate lake extent. Lake volume is extracted by intersecting the lake extent with the DEM surface. Based on previous studies and DEM characterization in the region, Shuttle Radar Topography Mission (SRTM) DEM is preferred over Advanced Spaceborne Thermal Emission and Reflection (ASTER) GDEM due to higher accuracy. Calculated errors in SRTM height estimates are 5.81 m compared with 8.34 m for ASTER. SRTM data are preferred because the DEM measurements were made over short duration making the DEM internally consistent. Lake volume derived from the Landsat TM imagery and DEM are incorporated into a simple GLOF model identified by Clague and Matthews (1973) to estimate the potential peak discharge (Qmax) of a GLOF event. We compare the simple Qmax estimates with

Preparing Landsat Image Time Series (LITS for Monitoring Changes in Vegetation Phenology in Queensland, Australia

Directory of Open Access Journals (Sweden)

Santosh Bhandari

2012-06-01

Full Text Available Time series of images are required to extract and separate information on vegetation change due to phenological cycles, inter-annual climatic variability, and long-term trends. While images from the Landsat Thematic Mapper (TM sensor have the spatial and spectral characteristics suited for mapping a range of vegetation structural and compositional properties, its 16-day revisit period combined with cloud cover problems and seasonally limited latitudinal range, limit the availability of images at intervals and durations suitable for time series analysis of vegetation in many parts of the world. Landsat Image Time Series (LITS is defined here as a sequence of Landsat TM images with observations from every 16 days for a five-year period, commencing on July 2003, for a Eucalyptus woodland area in Queensland, Australia. Synthetic Landsat TM images were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM algorithm for all dates when images were either unavailable or too cloudy. This was done using cloud-free scenes and a MODIS Nadir BRDF Adjusted Reflectance (NBAR product. The ability of the LITS to measure attributes of vegetation phenology was examined by: (1 assessing the accuracy of predicted image-derived Foliage Projective Cover (FPC estimates using ground-measured values; and (2 comparing the LITS-generated normalized difference vegetation index (NDVI and MODIS NDVI (MOD13Q1 time series. The predicted image-derived FPC products (value ranges from 0 to 100% had an RMSE of 5.6. Comparison between vegetation phenology parameters estimated from LITS-generated NDVI and MODIS NDVI showed no significant difference in trend and less than 16 days (equal to the composite period of the MODIS data used difference in key seasonal parameters, including start and end of season in most of the cases. In comparison to similar published work, this paper tested the STARFM algorithm in a new (broadleaf forest environment and also

United States forest disturbance trends observed with landsat time series

Science.gov (United States)

Jeffrey G. Masek; Samuel N. Goward; Robert E. Kennedy; Warren B. Cohen; Gretchen G. Moisen; Karen Schleweiss; Chengquan. Huang

2013-01-01

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US 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...

An algorithm to retrieve Land Surface Temperature using Landsat-8 ...

African Journals Online (AJOL)

Ayodeji Ogunode;Mulemwa Akombelwa

The results show temperature variation over a long period of time can be ... Remote sensing of LST using infrared radiation gives the average surface temperature of the scene ... advantage over previous Landsat series. ..... Li, F., Jackson, T. J., Kustas, W. P., Schmugge, T. J., French, A. N., Cosh, M. H. & Bindlish, R. 2004.

Exploring the return-to-work process for workers partially returned to work and partially on long-term sick leave due to common mental disorders : a qualitative study

NARCIS (Netherlands)

Noordik, Erik; Nieuwenhuijsen, Karen; Varekamp, Inge; van der Klink, Jac J.; van Dijk, Frank J.

2011-01-01

Purpose. We conducted a qualitative study into the return-to-work process of workers partially on sick leave due to common mental disorders. Our objectives were to describe the barriers to a full return to work, solutions, communicating to the working environment and the aim of a full return to

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

Science.gov (United States)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

The Potential of Using Landsat 7 Data for the Classification of Sea Ice Surface Conditions During Summer

Science.gov (United States)

Markus, Thorsten; Cavalieri, Donald J.; Ivanoff, Alvaro; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

During spring and summer, the Surface of the Arctic sea ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt pond diameters generally do not exceed a couple of meters, the spatial resolutions of sensors like AVHRR and MODIS are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the pan-chromatic band). The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and meltponded areas, have different signatures in the individual Landsat bands. Consistent with in-situ albedo measurements, melt ponds show up as blueish whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable the distinction of melt ponds. The melt pond fraction for the scene studied in this paper was 37%.

Research and development of LANDSAT-based crop inventory techniques

Science.gov (United States)

Horvath, R.; Cicone, R. C.; Malila, W. A. (Principal Investigator)

1982-01-01

A wide spectrum of technology pertaining to the inventory of crops using LANDSAT without in situ training data is addressed. Methods considered include Bayesian based through-the-season methods, estimation technology based on analytical profile fitting methods, and expert-based computer aided methods. Although the research was conducted using U.S. data, the adaptation of the technology to the Southern Hemisphere, especially Argentina was considered.

Pipeline transportation of emerging partially upgraded bitumen

International Nuclear Information System (INIS)

Luhning, R.W.; Anand, A.; Blackmore, T.; Lawson, D.S.

2002-01-01

The recoverable reserves of Canada's vast oil deposits is estimated to be 335 billion barrels (bbl), most of which are in the Alberta oil sands. Canada was the largest import supplier of crude oil to the United States in 2001, followed by Saudi Arabia. By 2011, the production of oil sands is expected to increase to 50 per cent of Canada's oil, and conventional oil production will decline as more production will be provided by synthetic light oil and bitumen. This paper lists the announced oil sands projects. If all are to proceed, production would reach 3,445,000 bbl per day by 2011. The three main challenges regarding the transportation and marketing of this new production were described. The first is to expand the physical capacity of existing pipelines. The second is the supply of low viscosity diluent (such as natural gas condensate or synthetic diluent) to reduce the viscosity and density of the bitumen as it passes through the pipelines. The current pipeline specifications and procedures to transport partially upgraded products are presented. The final challenge is the projected refinery market constraint to process the bitumen and synthetic light oil into consumer fuel products. These challenges can be addressed by modifying refineries and increasing Canadian access in Petroleum Administration Defense District (PADD) II and IV. The technology for partial upgrading of bitumen to produce pipeline specification oil, reduce diluent requirements and add sales value, is currently under development. The number of existing refineries to potentially accept partially upgraded product is listed. The partially upgraded bitumen will be in demand for additional upgrading to end user products, and new opportunities will be presented as additional pipeline capacity is made available to transport crude to U.S. markets and overseas. The paper describes the following emerging partial upgrading methods: the OrCrude upgrading process, rapid thermal processing, CPJ process for

Exploring the return-to-work process for workers partially returned to work and partially on long-term sick leave due to common mental disorders: a qualitative study

NARCIS (Netherlands)

Noordik, Erik; Nieuwenhuijsen, Karen; Varekamp, Inge; van der Klink, Jac J.; Van Dijk, Frank J.

2011-01-01

We conducted a qualitative study into the return-to-work process of workers partially on sick leave due to common mental disorders. Our objectives were to describe the barriers to a full return to work, solutions, communicating to the working environment and the aim of a full return to work, all as

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

Science.gov (United States)

Robert E. Kennedy; Zhiqiang Yang; Warren B. Cohen

2010-01-01

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks (LTS). The method brings together two themes in time-series analysis of LTS: capture of short-duration events and smoothing of long-term trends. Our strategy is...

Spreading paths in partially observed social networks

Science.gov (United States)

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Spreading paths in partially observed social networks.

Science.gov (United States)

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Assessing error sources for Landsat time series analysis for tropical test sites in Viet Nam and Ethiopia

Science.gov (United States)

Schultz, Michael; Verbesselt, Jan; Herold, Martin; Avitabile, Valerio

2013-10-01

Researchers who use remotely sensed data can spend half of their total effort analysing prior data. If this data preprocessing does not match the application, this time spent on data analysis can increase considerably and can lead to inaccuracies. Despite the existence of a number of methods for pre-processing Landsat time series, each method has shortcomings, particularly for mapping forest changes under varying illumination, data availability and atmospheric conditions. Based on the requirements of mapping forest changes as defined by the United Nations (UN) Reducing Emissions from Forest Degradation and Deforestation (REDD) program, the accurate reporting of the spatio-temporal properties of these changes is necessary. We compared the impact of three fundamentally different radiometric preprocessing techniques Moderate Resolution Atmospheric TRANsmission (MODTRAN), Second Simulation of a Satellite Signal in the Solar Spectrum (6S) and simple Dark Object Subtraction (DOS) on mapping forest changes using Landsat time series data. A modification of Breaks For Additive Season and Trend (BFAST) monitor was used to jointly map the spatial and temporal agreement of forest changes at test sites in Ethiopia and Viet Nam. The suitability of the pre-processing methods for the occurring forest change drivers was assessed using recently captured Ground Truth and high resolution data (1000 points). A method for creating robust generic forest maps used for the sampling design is presented. An assessment of error sources has been performed identifying haze as a major source for time series analysis commission error.

LBA-ECO CD-34 Landsat Fractional Land Cover Analysis, Manaus, Brazil: 2004-2005

Data.gov (United States)

National Aeronautics and Space Administration — This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October...

Using the Landsat data archive to assess long-term regional forest dynamics assessment in Eastern Europe, 1985-2012

Science.gov (United States)

Turubanova, S.; Potapov, P.; Krylov, A.; Tyukavina, A.; McCarty, J. L.; Radeloff, V. C.; Hansen, M. C.

2015-04-01

Dramatic political and economic changes in Eastern European countries following the dissolution of the "Eastern Bloc" and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national

Automated Method for Monitoring Water Quality Using Landsat Imagery

Directory of Open Access Journals (Sweden)

D. Clay Barrett

2016-06-01

Full Text Available Regular monitoring of water quality is increasingly necessary to keep pace with rapid environmental change and protect human health and well-being. Remote sensing has been suggested as a potential solution for monitoring certain water quality parameters without the need for in situ sampling, but universal methods and tools are lacking. While many studies have developed predictive relationships between remotely sensed surface reflectance and water parameters, these relationships are often unique to a particular geographic region and have little applicability in other areas. In order to remotely monitor water quality, these relationships must be developed on a region by region basis. This paper presents an automated method for processing remotely sensed images from Landsat Thematic Mapper (TM and Enhanced Thematic Mapper Plus (ETM+ and extracting corrected reflectance measurements around known sample locations to allow rapid development of predictive water quality relationships to improve remote monitoring. Using open Python scripting, this study (1 provides an openly accessible and simple method for processing publicly available remote sensing data; and (2 allows determination of relationships between sampled water quality parameters and reflectance values to ultimately allow predictive monitoring. The method is demonstrated through a case study of the Ozark/Ouchita-Appalachian ecoregion in eastern Oklahoma using data collected for the Beneficial Use Monitoring Program (BUMP.

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images.

Science.gov (United States)

Bustamante, Javier; Pacios, Fernando; Díaz-Delgado, Ricardo; Aragonés, David

2009-05-01

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630-690 nm), band 5 (1550-1750 nm) and the ratio between bands 1 (450-520 nm) and 4 (760-900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520-600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

Science.gov (United States)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Bora Bora, Tahaa, and Raiatea, French Polynesia, Landsat and SIR-C Images Compared to SRTM Shaded

Science.gov (United States)

2005-01-01

actually measure topographic height. They therefore have not fully characterized the three-dimensional shape of landforms. The shape and height of Earth's landforms affects nearly every natural process and human activity that occurs at Earth's surface, including vegetative growth, water supply, transportation, and radio communication. Thus, the new information provided by SRTM is highly valuable in understanding and interacting with our environment. The Landsat image is an enhanced display of natural visible color (Landsat bands 1,2,3 in blue, green, red). As is evident from the cloud shadows, the morning sun shines from the northeast (upper right). The SIR-C image displays the L-band radar data (23.5 centimeter wavelength, vertical transmit and receive) in red, C-band radar data (5.8 centimeter wavelength, vertical transmit and receive) in green, and a difference of the two (L minus C) in blue. Cosmetic color adjustments were used to enhance the green and blue display of land and water. The 'side-looking' transmitted radar illumination was from the northeast as the Space Shuttle Endeavour passed from northwest to southeast on a descending orbit. Two visualization methods were combined to produce the SRTM image: color coding of topographic height plus shading of the topographic model. Color coding is directly related to topographic height, with green at the lower elevations, rising through yellow and tan, to white at the highest elevations. Shading was derived by computing topographic slope in the northeast-southwest direction, so that northeast slopes appear bright and southwest slopes appear dark, generally consistent with the Landsat and SIR-C illumination directions. Elevation data used in this image were acquired by the Shuttle Radar Topography Mission aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space

Comparison of LANDSAT-2 and field spectrometer reflectance signatures of south Texas rangeland plant communities

Science.gov (United States)

Richardson, A. J.; Escobar, D. E.; Gausman, H. W.; Everitt, J. H. (Principal Investigator)

1982-01-01

The accuracy was assessed for an atmospheric correction method that depends on clear water bodies to infer solar and atmospheric parameters for radiative transfer equations by measuring the reflectance signature of four prominent south Texas rangeland plants with the LANDSAT satellite multispectral scanner (MSS) and a ground based spectroradiometer. The rangeland plant reflectances produced by the two sensors were correlated with no significant deviation of the slope from unity or of the intercept from zero. These results indicated that the atmospheric correction produced LANDSAT MSS estimates of rangeland plant reflectances that are as accurate as the ground based spectroradiometer.

Mission to planet earth: A call to repeal the Landsat Act

International Nuclear Information System (INIS)

Gabrynowicz, J.I.; Wood, C.A.

1991-01-01

Mission to Planet Earth (MPE) is being planned to provide scientists with data and information about global climate change so that policymakers can make informed decisions in directing the nation's response to the change. A crucial component of MPE is the Landsat system and the continuous, multidecade database it has produced. Yet because of an ill-conceived and poorly-executed commercialization policy, MPE researchers are being deprived of these vital national assets, profoundly hampering their ability to carry out the work of MPE. Effects of the US commercialization policy have reached abroad. The French, Japanese, and Canadians, following the US lead, have also commercialized their existing and future land remote sensing systems - further inhibiting the free flow of data among these complementary systems and preventing a truly international, scientific effort in MPE. Meeting the challenges of global climate change requires reconsidering the proper role of the Landsat system and identifying appropriate and inappropriate commercial remote sensing activities

LBA-ECO LC-24 Landsat ETM+ Forest Cover Classification, Uruara, Para, Brazil: 1999

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This...

Monitoring of suspended sediment variation using Landsat and MODIS in the Saemangeum coastal area of Korea.

Science.gov (United States)

Min, Jee-Eun; Ryu, Joo-Hyung; Lee, Seok; Son, Seunghyun

2012-02-01

Suspended sediment concentration (SS) is an important indicator of marine environmental changes due to natural causes such as tides, tidal currents, and river discharges, as well as human activities such as construction in coastal regions. In the Saemangeum area on the west coast of Korea, construction of a huge tidal dyke for land reclamation has strongly influenced the coastal environment. This study used remotely sensed data to analyze the SS changes in coastal waters caused by the dyke construction. Landsat and MODIS satellite images were used for the spatial analysis of finer patterns and for the detailed temporal analysis, respectively. Forty Landsat scenes and 105 monthly composite MODIS images observed during 1985-2010 were employed, and four field campaigns (from 2005 to 2006) were performed to verify the image-derived SS. The results of the satellite data analyses showed that the seawater was clear before the dyke construction, with SS values lower than 20 g/m(3). These values increased continuously as the dyke construction progressed. The maximum SS values appeared just before completion of the fourth dyke. Values decreased to below 5 g/m(3) after dyke construction. These changes indicated tidal current modification. Some eddies and plumes were observed in the images generated from Landsat data. Landsat and MODIS can reveal that coastal water turbidity was greatly reduced after completion of the construction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive

Science.gov (United States)

Huntington, Justin; McGwire, Kenneth C.; Morton, Charles; Snyder, Keirith A.; Peterson, Sarah; Erickson, Tyler; Niswonger, Richard G.; Carroll, Rosemary W.H.; Smith, Guy; Allen, Richard

2016-01-01

Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors of the Landsat TM, ETM +, and OLI lineage for assessing GDEs in a variety of land and water management contexts. Changes in vegetation vigor based on climate, groundwater availability, and land management in arid landscapes are detectable with Landsat. However, the effective quantification of these ecosystem changes can be undermined if changes in spectral bandwidths between different Landsat sensors introduce biases in derived vegetation indices, and if climate, and land and water management histories are not well understood. The objective of this work is to 1) use the Landsat 8 under-fly dataset to quantify differences in spectral reflectance and NDVI between Landsat 7 ETM + and Landsat 8 OLI for a range of vegetation communities in arid and semiarid regions of the southwestern United States, and 2) demonstrate the value of 30-year historical vegetation index and climate datasets for assessing GDEs. Specific study areas were chosen to represent a range of GDEs and environmental conditions important for three scenarios: baseline monitoring of vegetation and climate, riparian restoration, and groundwater level changes. Google's Earth Engine cloud computing and environmental monitoring platform is used to rapidly access and analyze the Landsat archive

LBA-ECO LC-24 Landsat ETM+ Forest Cover Classification, Uruara, Para, Brazil: 1999

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This image may...

Proposal for a remote sensing trophic state index based upon Thematic Mapper/Landsat images

Directory of Open Access Journals (Sweden)

Evlyn Márcia Leão de Moraes Novo

2013-12-01

Full Text Available This work proposes a trophic state index based on the remote sensing retrieval of chlorophyll-α concentration. For that, in situ Bidirectional Reflectance Factor (BRF data acquired in the Ibitinga reservoir were resampled to match Landsat/TM spectral simulated bands (TM_sim bands and used to run linear correlation with concurrent measurements of chlorophyll-α concentration. Monte Carlo simulation was then applied to select the most suitable model relating chlorophyll-α concentration and simulated TM/Landsat reflectance. TM4_sim/TM3_sim ratio provided the best model with a R2 value of 0.78. The model was then inverted to create a look-up-table (LUT relating TM4_sim/TM3_sim ratio intervals to chlorophyll-α concentration trophic state classes covering the entire range measured in the reservoir. Atmospheric corrected Landsat TM images converted to surface reflectance were then used to generate a TM4/TM3 ratio image. The ratio image frequency distribution encompassed the range of TM4_sim/TM3_sim ratio indicating agreement between in situ and satellite data and supporting the use of satellite data to map chlorophyll- concentration trophic state distribution in the reservoir. Based on that, the LUT was applied to a Landsat/TM ratio image to map the spatial distribution of chlorophyll- trophic state classes in Ibitinga reservoir. Despite the stochastic selection of TM4_sim/TM3_sim ratio as the best input variable for modeling the chlorophyll-α concentration, it has a physical basis: high concentration of phytoplankton increases the reflectance in the near-infrared (TM4 and decreases the reflectance in the red (TM3. The band ratio, therefore, enhances the relationship between chlorophyll- concentration and remotely sensed reflectance.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

Science.gov (United States)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

Two techniques for mapping and area estimation of small grains in California using Landsat digital data

Science.gov (United States)

Sheffner, E. J.; Hlavka, C. A.; Bauer, E. M.

1984-01-01

Two techniques have been developed for the mapping and area estimation of small grains in California from Landsat digital data. The two techniques are Band Ratio Thresholding, a semi-automated version of a manual procedure, and LCLS, a layered classification technique which can be fully automated and is based on established clustering and classification technology. Preliminary evaluation results indicate that the two techniques have potential for providing map products which can be incorporated into existing inventory procedures and automated alternatives to traditional inventory techniques and those which currently employ Landsat imagery.

Long-term dynamic and pseudo-state modeling of complete partial nitrification process at high nitrogen loading rates in a sequential batch reactor (SBR).

Science.gov (United States)

Soliman, Moomen; Eldyasti, Ahmed

2017-06-01

Recently, partial nitrification has been adopted widely either for the nitrite shunt process or intermediate nitrite generation step for the Anammox process. However, partial nitrification has been hindered by the complexity of maintaining stable nitrite accumulation at high nitrogen loading rates (NLR) which affect the feasibility of the process for high nitrogen content wastewater. Thus, the operational data of a lab scale SBR performing complete partial nitrification as a first step of nitrite shunt process at NLRs of 0.3-1.2kg/(m 3 d) have been used to calibrate and validate a process model developed using BioWin® in order to describe the long-term dynamic behavior of the SBR. Moreover, an identifiability analysis step has been introduced to the calibration protocol to eliminate the needs of the respirometric analysis for SBR models. The calibrated model was able to predict accurately the daily effluent ammonia, nitrate, nitrite, alkalinity concentrations and pH during all different operational conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discrimination of uranium alteration zones in selected areas by use of LANDSAT MSS imagery. Final report

International Nuclear Information System (INIS)

Kober, C.L.; Procter-Gregg, H.D.

1977-02-01

The surface alteration halos of fifty known uranium occurrences in the Western United States have been analyzed to determine spectral signatures in imagery acquired by the LANDSAT Multi-Spectral Scanner. The deposits included veins and metasediments in the northeast of Washington, batholitic districts in the northwest of Idaho, veins and intrusives in a portion of the Colorado Front Range and sedimentary deposits on the Colorado Plateau. Image analysis employed an analog hybrid video processing system composed of a light table, vidicon camera, image analyzer and color output monitor. A complete description of the theory and methodology is provided in the report

Landsat 9 OLI 2 focal plane subsystem: design, performance, and status

Science.gov (United States)

Malone, Kevin J.; Schrein, Ronald J.; Bradley, M. Scott; Irwin, Ronda; Berdanier, Barry; Donley, Eric

2017-09-01

The Landsat 9 mission will continue the legacy of Earth remote sensing that started in 1972. The Operational Land Imager 2 (OLI 2) is one of two instruments on the Landsat 9 satellite. The OLI 2 instrument is essentially a copy of the OLI instrument flying on Landsat 8. A key element of the OLI 2 instrument is the focal plane subsystem, or FPS, which consists of the focal plane array (FPA), the focal plane electronics (FPE) box, and low-thermal conductivity cables. This paper presents design details of the OLI 2 FPS. The FPA contains 14 critically-aligned focal plane modules (FPM). Each module contains 6 visible/near-IR (VNIR) detector arrays and three short-wave infrared (SWIR) arrays. A complex multi-spectral optical filter is contained in each module. Redundant pixels for each array provide exceptional operability. Spare detector modules from OLI were recharacterized after six years of storage. Radiometric test results are presented and compared with data recorded in 2010. Thermal, optical, mechanical and structural features of the FPA will be described. Special attention is paid to the thermal design of the FPA since thermal stability is crucial to ensuring low-noise and low-drift operation of the detectors which operate at -63°C. The OLI 2 FPE provides power, timing, and control to the focal plane modules. It also digitizes the video data and formats it for the solid-state recorder. Design improvements to the FPA-FPE cables will be discussed and characterization data will be presented. The paper will conclude with the status of the flight hardware assembly and testing.

Regional analysis of tertiary volcanic Calderas (western U.S.) using Landsat Thematic Mapper imagery

Science.gov (United States)

Spatz, David M.; Taranik, James V.

1989-01-01

The Landsat Thematic Mapper (TM) imagery of the Basin and Range province of southern Nevada was analyzed to identify and map volcanic rock assemblages at three Tertiary calderas. It was found that the longer-wavelength visible and the NIR TM Bands 3, 5, and 7 provide more effective lithologic discrimination than the shorter-wavelength bands, due partly to deeper penetration of the longer-wavelength bands, resulting in more lithologically driven radiances. Shorter-wavelength TM Bands 1 and 2 are affected more by surficial weathering products including desert varnish which may or may not provide an indirect link to lithologic identity. Guidelines for lithologic analysis of volcanic terrains using Landsat TM imagery are outlined.

An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface Reflectance and MODIS BRDF

Science.gov (United States)

Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.

2011-01-01

We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.

Development of computer software to analyze entire LANDSAT scenes and to summarize classification results of variable-size polygons

Science.gov (United States)

Turner, B. J. (Principal Investigator); Baumer, G. M.; Myers, W. L.; Sykes, S. G.

1981-01-01

The Forest Pest Management Division (FPMD) of the Pennsylvania Bureau of Forestry has the responsibility for conducting annual surveys of the State's forest lands to accurately detect, map, and appraise forest insect infestations. A standardized, timely, and cost-effective method of accurately surveying forests and their condition should enhance the probability of suppressing infestations. The repetitive and synoptic coverage provided by LANDSAT (formerly ERTS) makes such satellite-derived data potentially attractive as a survey medium for monitoring forest insect damage over large areas. Forest Pest Management Division personnel have expressed keen interest in LANDSAT data and have informally cooperated with NASA/Goddard Space Flight Center (GSFC) since 1976 in the development of techniques to facilitate their use. The results of this work indicate that it may be feasible to use LANDSAT digital data to conduct annual surveys of insect defoliation of hardwood forests.

An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

Directory of Open Access Journals (Sweden)

Fei Wang

2015-04-01

variation of the extremely hot weather, a frequently-occurring phenomenon of an abnormal heat flux process in summer along the Yangtze River Basin, had been thoroughly analyzed. This successful application suggested that the IMW algorithm presented in the study could be used as an efficient method for LST retrieval from the Landsat 8 TIRS Band 10 data.

The Use of Landsat and Aerial Photography for the Assessment of ...

African Journals Online (AJOL)

Coastal erosion is a worldwide hazard, the consequences of which can only be mitigated via thorough and efficient monitoring of erosion. This study aimed to employ remote sensing techniques on aerial photographs and Landsat TM/ETM+ imagery for the detection and monitoring of coastal erosion in False Bay, South ...

Characterization of tropospheric desert aerosols at solar wavelengths by multispectral radiometry from landsat

International Nuclear Information System (INIS)

Otterman, J.; Fraser, R.S.; Bahethi, O.P.

1982-01-01

Characteristics of tropospheric desert aerosols are derived by comparing nadir spectral reflectivities computed from the radiative transfer models with reflectivities measured from Landsat. Over the ocean, reflectivites are compared, but over land the comparison is carried out by determining the ratios of the nadir reflectivity of the surface-atmpsphere system over heavy aerosol concentration to the reflectivity of the underlying surface. This remote sensing technique is found to be a sensitive approach for measuring n 2 , the imaginary part of the refractive index. The desert aerosols under study, in the Iran and Pakistan area, are essentially pure scatterers, inasmuch as an n 2 value of 0.001 +- 0.001 was determined for each of the four Landsat spectral bands, that is, for a spectral interval from 0.5 to 1.1 μm

A forest map of Southern Africa with the aid of LANDSAT imagery

CSIR Research Space (South Africa)

Van der Zel, DW

1988-01-01

Full Text Available Even after 300 years of indigenous forest protection as well as 100 years of plantation forestry, no forestry map of South Africa was available. The development and availability of LANDSAT images in the early 1970s opened possibility to use...

PROCAMS - A second generation multispectral-multitemporal data processing system for agricultural mensuration

Science.gov (United States)

Erickson, J. D.; Nalepka, R. F.

1976-01-01

PROCAMS (Prototype Classification and Mensuration System) has been designed for the classification and mensuration of agricultural crops (specifically small grains including wheat, rye, oats, and barley) through the use of data provided by Landsat. The system includes signature extension as a major feature and incorporates multitemporal as well as early season unitemporal approaches for using multiple training sites. Also addressed are partial cloud cover and cloud shadows, bad data points and lines, as well as changing sun angle and atmospheric state variations.

LANDSAT-4 MSS and Thematic Mapper data quality and information content analysis

Science.gov (United States)

Anuta, P.; Bartolucci, L.; Dean, E.; Lozano, F.; Malaret, E.; Mcgillem, C. D.; Valdes, J.; Valenzuela, C.

1984-01-01

LANDSAT-4 thematic mapper (TM) and multispectral scanner (MSS) data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and supervised classifiers on test data. A detailed spectral class analysis (multispectral classification) was carried out to compare the information content of the MSS and TM for a large number of scene classes. A temperature-mapping experiment was carried out for a cooling pond to test the quality of thermal-band calibration. Overall TM data quality is very good. The MSS data are noisier than previous LANDSAT results.

Improving automated disturbance maps using snow-covered landsat time series stacks

Science.gov (United States)

Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

2012-01-01

Snow-covered winter Landsat time series stacks are used to develop a nonforest mask to enhance automated disturbance maps produced by the Vegetation Change Tracker (VCT). This method exploits the enhanced spectral separability between forested and nonforested areas that occurs with sufficient snow cover. This method resulted in significant improvements in Vegetation...

Performance of the METRIC model in estimating evapotranspiration fluxes over an irrigated field in Saudi Arabia using Landsat-8 images

Science.gov (United States)

Madugundu, Rangaswamy; Al-Gaadi, Khalid A.; Tola, ElKamil; Hassaballa, Abdalhaleem A.; Patil, Virupakshagouda C.

2017-12-01

Accurate estimation of evapotranspiration (ET) is essential for hydrological modeling and efficient crop water management in hyper-arid climates. In this study, we applied the METRIC algorithm on Landsat-8 images, acquired from June to October 2013, for the mapping of ET of a 50 ha center-pivot irrigated alfalfa field in the eastern region of Saudi Arabia. The METRIC-estimated energy balance components and ET were evaluated against the data provided by an eddy covariance (EC) flux tower installed in the field. Results indicated that the METRIC algorithm provided accurate ET estimates over the study area, with RMSE values of 0.13 and 4.15 mm d-1. The METRIC algorithm was observed to perform better in full canopy conditions compared to partial canopy conditions. On average, the METRIC algorithm overestimated the hourly ET by 6.6 % in comparison to the EC measurements; however, the daily ET was underestimated by 4.2 %.

Study of the Nevada Test Site using Landsat satellite imagery

International Nuclear Information System (INIS)

Zimmerman, P.D.

1993-07-01

In the period covered by the purchase order CSIS has obtained one Landsat image and determined that two images previously supplied to the principal investigator under a subcontract with George Washington University were inherently defective. We have negotiated with EOSAT over the reprocessing of those scenes and anticipate final delivery within the next few weeks. A critical early purchase during the subcontract period was of an EXABYTE tape drive, Adaptec SCSI interface, and the appropriate software with which to read Landsat images at CSIS. This gives us the capability of reading and manipulating imagery in house without reliance on outside services which have not proven satisfactory. In addition to obtaining imagery for the study, we have also performed considerable analytic work on the newly and previously purchased images. A technique developed under an earlier subcontract for identifying underground nuclear tests at Pahute Mesa has been significantly refined, and similar techniques were applied to the summit of Rainier Mesa and to the Yucca Flats area. An entirely new technique for enhancing the spectral signatures of different regions of NTS was recently developed, and appears to have great promise of success

Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia

Science.gov (United States)

González-Márquez, Luis Carlos; Torres-Bejarano, Franklin M.; Torregroza-Espinosa, Ana Carolina; Hansen-Rodríguez, Ivette Renée; Rodríguez-Gallegos, Hugo B.

2018-03-01

The aim of this study was to evaluate the viability of using Landsat 8 spectral images to estimate water quality parameters and depth in El Guájaro Reservoir. On February and March 2015, two samplings were carried out in the reservoir, coinciding with the Landsat 8 images. Turbidity, dissolved oxygen, electrical conductivity, pH and depth were evaluated. Through multiple regression analysis between measured water quality parameters and the reflectance of the pixels corresponding to the sampling stations, statistical models with determination coefficients between 0.6249 and 0.9300 were generated. Results indicate that from a small number of measured parameters we can generate reliable models to estimate the spatial variation of turbidity, dissolved oxygen, pH and depth, as well the temporal variation of electrical conductivity, so models generated from Landsat 8 can be used as a tool to facilitate the environmental, economic and social management of the reservoir.

Analyzing Landsat time-series data across adjacent path/rows and across multiple cycles of FIA: Lessons learned in southern Missouri

Science.gov (United States)

Mark Nelson; Sean Healey; W. Keith Moser; Mark Hansen; Warren Cohen; Mark Hatfield; Nancy Thomas; Jeff Masek

2009-01-01

The North American Forest Dynamics (NAFD) Program is assessing disturbance and regrowth in the forests of the continent. These forest dynamics are interpreted from per-pixel estimates of forest biomass, which are produced for a time series of Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced TM Plus images. Image data are combined with sample plot data from the...

Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images

Science.gov (United States)

Vieira, D.; Teodoro, A.; Gomes, A.

2016-10-01

Land Surface Temperature (LST) is an important parameter related to land surface processes that changes continuously through time. Assessing its dynamics during a volcanic eruption has both environmental and socio-economical interest. Lava flows and other volcanic materials produced and deposited throughout an eruption transform the landscape, contributing to its heterogeneity and altering LST measurements. This paper aims to assess variations of satellite-derived LST and to detect patterns during the latest Fogo Island (Cape Verde) eruption, extending from November 2014 through February 2015. LST data was obtained through four processed Landsat 8 images, focused on the caldera where Pico do Fogo volcano sits. QGIS' plugin Semi-Automatic Classification was used in order to apply atmospheric corrections and radiometric calibrations. The algorithm used to retrieve LST values is a single-channel method, in which emissivity values are known. The absence of in situ measurements is compensated by the use of MODIS sensor-derived LST data, used to compare with Landsat retrieved measurements. LST data analysis shows as expected that the highest LST values are located inside the caldera. High temperature values were also founded on the south-facing flank of the caldera. Although spatial patterns observed on the retrieved data remained roughly the same during the time period considered, temperature values changed throughout the area and over time, as it was also expected. LST values followed the eruption dynamic experiencing a growth followed by a decline. Moreover, it seems possible to recognize areas affected by lava flows of previous eruptions, due to well-defined LST spatial patterns.

Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

Directory of Open Access Journals (Sweden)

Offer Rozenstein

2014-03-01

Full Text Available Land surface temperature (LST is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS. This paper presents an adjustment of the split window algorithm (SWA for TIRS that uses atmospheric transmittance and land surface emissivity (LSE as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.

Arctic Sea Ice Structure and Texture over Four Decades Using Landsat Archive Data

Science.gov (United States)

Doulgeris, A. P.; Scambos, T.; Tiampo, K. F.

2017-12-01

Arctic sea ice cover is a sensitive indicator of Arctic climate change, and has shown dramatic changes in recent decades, having thinned by 70% ( 3.5 m to 1.2 m between 1980 and 2015). Age distribution of the ice has changed in a similar fashion, with over 90% of the ice older than 5 winters now lost relative to 1985. To date, most of the data have been based on the continuous passive microwave record that began in 1978, which has 25 km grid resolution, or on SAR imagery with somewhat less frequent, less continuous observations. Landsat image data exist for the Arctic sea ice region north of Alaska and the MacKenzie River Delta area in Canada, the Canadian Archipelago, and Baffin Bay, extending back over 40 years. Resolution of the earliest Landsat MSS data is 56-70 m per pixel, and after 1984 many additional images at 30 m resolution are available. This 40+ year time period is used to investigate long-term changes in sea ice properties, such as comparing image-based snapshots with the trend in seasonal extents today, as well as more novel properties like sea ice roughness, lead structure and texture. The proposed study will initially investigate Landsat image analysis techniques to extract quantitative measures of ice roughness, lead fraction and perhaps morphological measures like lead linearity (which potentially indicate strength and compression history within the ice), and to explore these measures over the 40+ year time frame.

Influence of the oxygen partial pressure on the phase evolution during Bi-2212 wire melt processing

CERN Document Server

Scheuerlein, C.; Rikel, M.O.; Kadar, J.; Doerrer, C.; Di Michiel, M.; Ballarino, A.; Bottura, L.; Jiang, J.; Kametani, F.; Hellstrom, E.E.; Larbalestier, D.C.

2016-01-01

We have studied the influence of the oxygen partial pressure pO2 up to 5.5 bar on the phase changes that occur during melt processing of a state-of-the-art Bi-2212 multifilamentary wire. Phase changes have been monitored in situ by high energy synchrotron X-ray diffraction (XRD). We found that the stability of Bi-2212 phase is reduced with increasing pO2. For pO2>1 bar a significant amount of Bi-2212 phase decomposes upon heating in the range 400 to 650 °C. The extent of decomposition strongly increases with increasing pO2, and at pO2=5.5 bar Bi-2212 decomposes completely in the solid state. Textured Bi-2212 can be formed during solidification when pO2 is reduced to 0.45 bar when the precursor is molten. Since the formation of current limiting second phases is very sensitive to pO2 when it exceeds 1 bar, we recommend to reduce the oxygen partial pressure below the commonly used pO2=1 bar, in order to increase the pO2 margins and to make the overpressure process more robust.

LANDSAT TM and SAR - ERS1 data for analysis of Vrancea seismic region

International Nuclear Information System (INIS)

Zoran, M.

2002-01-01

This paper is aimed to present the results of the application of LANDSAT TM and SAR- ERS1 satellite data for Vrancea seismic area investigation, in order to emphasize geomorphological features as well as to identify faulting zones responsible of seismic events generation. Remote sensing analysis and field studies of active faults can provide a geologic history that overcomes many of the shortcomings of instrumental and historic records. Vrancea - Focsani is structurally and seismically complex area, bounded by latitudes 45.6 angle N and 46.0 angle N and longitudes 26.5 angle E and 27.5 angle E. The Peceneaga -Camena Fault, a deep crustal fracture with dextral slip, is considered to be North-Eastern boundary of the Moesian Platform. The Eastern unit of the Moesian Sub-Plate is characterized by a series of principal faults with a North-Western orientation and by a secondary system of faults orientated NE-SW. NW trending crustal fractures are also evidenced East of the Peceneaga-Camena Fault, within our test area. A SAR- ERS1 image and a multispectral Landsat TM data set were used and processed with EASI/PACE image processing software package as well as with developed algorithms. In order to a better management all the information available on the study area, data acquired have been integrated in a unique database. This information consists of thematic maps from cartography, land use map from classification of remotely sensed data. This study revealed that satellite data used are excellent for recognizing the continuity and regional relationships of faults. Linear features in TM images appear shorter and denser distributed, whereas ERS1 images are dominated by the principal structures. In certain cases they complete the lineaments and lineament patterns derived from TM data. Higher spatial resolution satellite data and SAR interferometric data are needed for mapping of these features. Remote sensing techniques provide a means for locating, identifying and mapping

Land use change detection with LANDSAT-2 data for monitoring and predicting regional water quality degradation. [Arkansas

Science.gov (United States)

Macdonald, H.; Steele, K. (Principal Investigator); Waite, W.; Rice, R.; Shinn, M.; Dillard, T.; Petersen, C.

1977-01-01

The author has identified the following significant results. Comparison between LANDSAT 1 and 2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing LANDSAT change detection analyses.

Comparison of satellite imagery from LISS-III/Resourcesat-1 and TM/Landsat 5 to estimate stand-level timber volume

Directory of Open Access Journals (Sweden)

Elias Fernando Berra

2017-01-01

Full Text Available After Landsat 5 activities were discontinued, sensors on board ResourceSat-1 satellite have been pointed as an option for Landsat series. The aim of this study is to estimate timber volume from a slash pine (Pinus elliottii Engelm. stand using images from both LISS-III/ResourceSat-1 and TM/Landsat 5 sensors, cross comparing their performances. Reflectance values from the four spectral bands considered equivalent for both sensors were compared regarding sensitivity to changes in timber volume. Trends were similar, with direct relationship in the near-infrared bands and inverse relationships in the visible and mid-infrared bands. Significant differences were only found in the equivalent band of green. Multiple linear regressions were used to select spectral bands that would better explain variations in timber volume. The best fit equations for each sensor were inverted to generate maps of timber volume, estimates which were compared at pixel and stand level. None of the scales showed significant differences between estimates generated from the two sensors. We concluded that LISS-III and TM have generally very similar performance for monitoring timber volume, and LISS-III could therefore be potentially used as a complement or substitute to Landsat series.

Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor

Science.gov (United States)

Chander, G.; Meyer, D.J.; Helder, D.L.

2004-01-01

As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.

a Preliminary Investigation on Comparison and Transformation of SENTINEL-2 MSI and Landsat 8 Oli

Science.gov (United States)

Chen, F.; Lou, S.; Fan, Q.; Li, J.; Wang, C.; Claverie, M.

2018-05-01

A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2-3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance) of the corresponding channels between two sensors. Spectral response function (SRF) is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less) in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI) and Landsat 8 Operational Land Imager (OLI). Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (model is not ensured when the target belongs to another spectra collection. If an improper transformation model is selected, the between-sensor discrepancy will even largely increase. In conclusion, improvement in between-sensor consistency is possibly a challenge, through linear transformation based on model(s) generated from other spectra collections.

Budapest, Hungary, Perspective View, SRTM Elevation Model with Landsat Overlay

Science.gov (United States)

2004-01-01

After draining the northern flank of the Alps Mountains in Germany and Austria, the Danube River flows east as it enters this west-looking scene (upper right) and forms the border between Slovakia and Hungary. The river then leaves the border as it enters Hungary and transects the Transdanubian Mountains, which trend southwest to northeast. Upon exiting the mountains, the river turns southward, flowing past Budapest (purplish blue area) and along the western margin of the Great Hungarian Plain.South and west of the Danube, the Transdanubian Mountains have at most only about 400 meters (about 1300 feet) of relief but they exhibit varied landforms, which include volcanic, tectonic, fluvial (river), and eolian (wind) features. A thick deposit of loess (dust deposits likely blown from ancient glacial outwash) covers much of this area, and winds from the northwest, funneled between the Alps and the Carpathian Mountains, are apparently responsible for a radial pattern of erosional streaks across the entire region.This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 3-times vertical exaggeration to enhance topographic expression. The false colors of the scene result from displaying Landsat bands 1, 4, and 7 in blue, green, and red, respectively. Band 1 is visible blue light, but bands 4 and 7 are reflected infrared light. This band combination maximizes color contrasts between the major land cover types, namely vegetation (green), bare ground (red), and water (blue). Shading of the elevation model was used to further highlight the topographic features.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space

CO{sub 2} separation by calcium looping from full and partial fuel oxidation processes

Energy Technology Data Exchange (ETDEWEB)

Sivalingam, Senthoorselvan

2013-06-05

This thesis work deals with the research and development of calcium looping process for CO{sub 2} separation from full and partial fuel oxidation based power generation systems. CO{sub 2} is the main greenhouse gas and undoubtedly a major contributor to the global warming. It is estimated that more than one third of the total anthropogenic CO{sub 2} emissions come from fossil fuel based heat and power generation. Moreover, fossil fuels are unlikely to be phased out rapidly, since developing alternative energy sources not only take time but also require huge investments and infrastructure. An alternative way to reduce emissions in a medium term is to capture the CO{sub 2} from fossil fueled power plants and store it away from the atmosphere. This process system combining a bunch of technologies is called carbon capture and storage (CCS). CO{sub 2} capture is an important and costly part of CCS and an array of technologies is considered for this. Calcium looping (CaL) is one of such and seems to offer effective and efficient CO{sub 2} separation from fuel oxidation processes. CaL process involves separation of CO{sub 2} at high temperatures (600-700 C) by calcium sorbents (CaO). CO{sub 2} reacts with CaO in a carbonation process and produces CaCO{sub 3}. In a subsequent thermal regeneration (>850 C) called calcination, the CO{sub 2} is released from CaCO{sub 3}. By alternating carbonations and calcinations over multiple cycles, CO{sub 2} is separated from a gas stream. Moreover, the CaL is realised in industrial scale with dual fluidised bed reactors for CO{sub 2} capture (the carbonator) and sorbent regeneration (the calciner). As a process in the development, research is still required in many aspects from thermodynamic modeling to experimental studies. Research works have been carried out in process simulations, sorbent reactivity and optimisation studies in a controlled reactor environment and process parametric studies in a semi-pilot scale CaL test facility

Modeling of multi-strata forest fire severity using Landsat TM data

Science.gov (United States)

Q. Meng; R.K. Meentemeyer

2011-01-01

Most of fire severity studies use field measures of composite burn index (CBI) to represent forest fire severity and fit the relationships between CBI and Landsat imagery derived differenced normalized burn ratio (dNBR) to predict and map fire severity at unsampled locations. However, less attention has been paid on the multi-strata forest fire severity, which...

Assessment of coastal wetland resources of central west coast, India, using LANDSAT data

Digital Repository Service at National Institute of Oceanography (India)

Jagtap, T.G.; Naik, S.; Nagle, V.L.

The part of central west coast (Maharashtra and Goa) of India has been classified and quantified for coastal wetlands using LANDSAT data of 1985-86. The classification accuracy of the maps and area estimates achieved was 84% at 90% confidence level...

Detecting of forest afforestation and deforestation in Hainan Jianfengling Forest Park (China) using yearly Landsat time-series images

Science.gov (United States)

Jiao, Quanjun; Zhang, Xiao; Sun, Qi

2018-03-01

The availability of dense time series of Landsat images pro-vides a great chance to reconstruct forest disturbance and change history with high temporal resolution, medium spatial resolution and long period. This proposal aims to apply forest change detection method in Hainan Jianfengling Forest Park using yearly Landsat time-series images. A simple detection method from the dense time series Landsat NDVI images will be used to reconstruct forest change history (afforestation and deforestation). The mapping result showed a large decrease occurred in the extent of closed forest from 1980s to 1990s. From the beginning of the 21st century, we found an increase in forest areas with the implementation of forestry measures such as the prohibition of cutting and sealing in our study area. Our findings provide an effective approach for quickly detecting forest changes in tropical original forest, especially for afforestation and deforestation, and a comprehensive analysis tool for forest resource protection.

A regional land use survey based on remote sensing and other data: A report on a LANDSAT and computer mapping project, volume 2

Science.gov (United States)

Nez, G. (Principal Investigator); Mutter, D.

1977-01-01

The author has identified the following significant results. The project mapped land use/cover classifications from LANDSAT computer compatible tape data and combined those results with other multisource data via computer mapping/compositing techniques to analyze various land use planning/natural resource management problems. Data were analyzed on 1:24,000 scale maps at 1.1 acre resolution. LANDSAT analysis software and linkages with other computer mapping software were developed. Significant results were also achieved in training, communication, and identification of needs for developing the LANDSAT/computer mapping technologies into operational tools for use by decision makers.

Analysis of partially pulsating fatigue process on carbon steel with microstructural observation

International Nuclear Information System (INIS)

Shimano, Hiroyuki; Faiz, M. Khairi; Hara, Asato; Yoshizumi, Kyoko; Yoshida, Makoto; Horibe, Susumu

2016-01-01

Pulsating low-cycle fatigue processes, up to the present, have been divided into three states: the transient state, steady state, and accelerating state of ratcheting. In our previous work, we suggested that fatigue behavior of pulsating fatigue process should be classified into five stages in which the plastic strain amplitude and the ratcheting strain rate are plotted on the X and Y axis, respectively. In this study, at the condition of R=−0.3 (partially pulsating fatigue), the change in the plastic strain amplitude and ratcheting strain rate for each cycle to failure was examined on AISI 1025 carbon steel. The dislocation substructure was examined using transmission electron microscopy (TEM) for each stage, except for stage I. It was also demonstrated that the fatigue process can be divided into five stages: stage I corresponds to the un-pinning of dislocations from the Cottrell atmosphere and propagation of the Luders band. Stage II corresponds to the restriction of dislocation movement by dislocation tangles. Stage III corresponds to the formation of dislocation cells. Stage IV corresponds to the promotion of the to-and-fro (back-and-forth) motion of dislocations by a re-arrangement of the dislocations in the cells. Stage V corresponds to the release of dislocation movement by the collapse of dislocation cells.

Analysis of partially pulsating fatigue process on carbon steel with microstructural observation

Energy Technology Data Exchange (ETDEWEB)

Shimano, Hiroyuki, E-mail: tales-of-destiny@akane.waseda.jp [Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, 3-4-1 Shinjyuku-ku Okubo, Tokyo 169-8555 (Japan); Faiz, M. Khairi; Hara, Asato; Yoshizumi, Kyoko [Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, 3-4-1 Shinjyuku-ku Okubo, Tokyo 169-8555 (Japan); Yoshida, Makoto [Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, 3-4-1 Shinjyuku-ku Okubo, Tokyo 169-8555 (Japan); Kagami Memorial Research Institute for Materials Science and Technology, Waseda University, 2-8-26, Nishi-Waseda, Shinjyuku-ku, Tokyo 169-0051 (Japan); Horibe, Susumu [Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, 3-4-1 Shinjyuku-ku Okubo, Tokyo 169-8555 (Japan)

2016-01-10

Pulsating low-cycle fatigue processes, up to the present, have been divided into three states: the transient state, steady state, and accelerating state of ratcheting. In our previous work, we suggested that fatigue behavior of pulsating fatigue process should be classified into five stages in which the plastic strain amplitude and the ratcheting strain rate are plotted on the X and Y axis, respectively. In this study, at the condition of R=−0.3 (partially pulsating fatigue), the change in the plastic strain amplitude and ratcheting strain rate for each cycle to failure was examined on AISI 1025 carbon steel. The dislocation substructure was examined using transmission electron microscopy (TEM) for each stage, except for stage I. It was also demonstrated that the fatigue process can be divided into five stages: stage I corresponds to the un-pinning of dislocations from the Cottrell atmosphere and propagation of the Luders band. Stage II corresponds to the restriction of dislocation movement by dislocation tangles. Stage III corresponds to the formation of dislocation cells. Stage IV corresponds to the promotion of the to-and-fro (back-and-forth) motion of dislocations by a re-arrangement of the dislocations in the cells. Stage V corresponds to the release of dislocation movement by the collapse of dislocation cells.

Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager

Directory of Open Access Journals (Sweden)

Shannon L. Savage

2018-03-01

Full Text Available There is a pressing need to map changes in forest structure from the earliest time period possible given forest management policies and accelerated disturbances from climate change. The availability of Landsat data from over four decades helps researchers study an ecologically meaningful length of time. Forest structure is most often mapped utilizing lidar data, however these data are prohibitively expensive and cover a narrow temporal window relative to the Landsat archive. Here we describe a technique to use the entire length of the Landsat archive from Multispectral Scanner to Operational Land Imager (M2O to produce three novel outcomes: (1 we used the M2O dataset and standard change vector analysis methods to classify annual forest structure in northwestern Montana from 1972 to 2015, (2 we improved the accuracy of each yearly forest structure classification by applying temporal continuity rules to the whole time series, with final accuracies ranging from 97% to 68% respectively for two and six-category classifications, and (3 we demonstrated the importance of pre-1984 Landsat data for long-term change studies. As the Landsat program continues to acquire Earth imagery into the foreseeable future, time series analyses that aid in classifying forest structure accurately will be key to the success of any land management changes in the future.

Global Water Surface Dynamics: Toward a Near Real Time Monitoring Using Landsat and Sentinel Data

Science.gov (United States)

Pekel, J. F.; Belward, A.; Gorelick, N.

2017-12-01

Global surface water dynamics and its long-term changes have been documented at 30m spatial resolution using the entire multi-temporal orthorectified Landsat 5, 7 and 8 archive for the years 1984 to 2015. This validated dataset recorded the months and years when water was present, where occurrence changed and what form changes took (in terms of seasonality), documents inter-annual variability, and multi-annual trends. This information is freely available from the global surface water explorer https://global-surface-water.appspot.com. Here we extend this work (doi:10.1038/nature20584 ) by combining post 2015 Landsat 7 and 8 data with imagery from the Copernicus program's Sentinel 2a and b satellites. Using these data in combination improves the spatial resolution (from 30m to a nominal 10m) and temporal resolution (from 8 days to 4 days revisit time at the equator). The improved geographic and temporal completeness of the combined Landsat / Sentinel dataset also offers new opportunities for the identification and characterization of seasonally occurring waterbodies. These improvements are also being examined in the light of reporting progress against Agenda 2030's Sustainable Development Goal 6, especially the indicator used to measure 'change in the extent of water-related ecosystems over time'.

Partially ordered models

NARCIS (Netherlands)

Fernandez, R.; Deveaux, V.

2010-01-01

We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).

Analysis of land cover/use changes using Landsat 5 TM data and indices.

Science.gov (United States)

Ettehadi Osgouei, Paria; Kaya, Sinasi

2017-04-01

Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.

Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors

Science.gov (United States)

Chander, Gyanesh; Markham, Brian L.; Helder, Dennis L.

2009-01-01

This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of- Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.

Automated Sargassum Detection for Landsat Imagery

Science.gov (United States)

McCarthy, S.; Gallegos, S. C.; Armstrong, D.

2016-02-01

We implemented a system to automatically detect Sargassum, a floating seaweed, in 30-meter LANDSAT-8 Operational Land Imager (OLI) imagery. Our algorithm for Sargassum detection is an extended form of Hu's approach to derive a floating algae index (FAI) [1]. Hu's algorithm was developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data, but we extended it for use with the OLI bands centered at 655, 865, and 1609 nm, which are comparable to the MODIS bands located at 645, 859, and 1640 nm. We also developed a high resolution true color product to mask cloud pixels in the OLI scene by applying a threshold to top of the atmosphere (TOA) radiances in the red (655 nm), green (561 nm), and blue (443 nm) wavelengths, as well as a method for removing false positive identifications of Sargassum in the imagery. Hu's algorithm derives a FAI for each Sargassum identified pixel. Our algorithm is currently set to only flag the presence of Sargassum in an OLI pixel by classifying any pixel with a FAI > 0.0 as Sargassum. Additionally, our system geo-locates the flagged Sargassum pixels identified in the OLI imagery into the U.S. Navy Global HYCOM model grid. One element of the model grid covers an area 0.125 degrees of latitude by 0.125 degrees of longitude. To resolve the differences in spatial coverage between Landsat and HYCOM, a scheme was developed to calculate the percentage of pixels flagged within the grid element and if above a threshold, it will be flagged as Sargassum. This work is a part of a larger system, sponsored by NASA/Applied Science and Technology Project at J.C. Stennis Space Center, to forecast when and where Sargassum will land on shore. The focus area of this work is currently the Texas coast. Plans call for extending our efforts into the Caribbean. References: [1] Hu, Chuanmin. A novel ocean color index to detect floating algae in the global oceans. Remote Sensing of Environment 113 (2009) 2118-2129.

Utilizing LANDSAT imagery to monitor land-use change - A case study in Ohio

Science.gov (United States)

Gordon, S. I.

1980-01-01

A study, performed in Ohio, of the nature and extent of interpretation errors in the application of Landsat imagery to land-use planning and modeling is reported. Potential errors associated with the misalignment of pixels after geometric correction and with misclassification of land cover or land use due to spectral similarities were identified on interpreted computer-compatible tapes of a portion of Franklin County for two adjacent days of 1975 and one day of 1973, and the extents of these errors were quantified by comparison with a ground-checked set of aerial-photograph interpretations. The open-space and agricultural categories are found to be the most consistently classified, while the more urban areas were classified correctly only from about 43 to 8% of the time. It is thus recommended that the direct application of Landsat data to land-use planning must await improvements in classification techniques and accuracy.

Regional scale net radiation estimation by means of Landsat and TERRA/AQUA imagery and GIS modeling

Science.gov (United States)

Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.

2009-04-01

Net radiation (Rn) is one of the most important variables for the estimation of surface energy budget and is used for various applications including agricultural meteorology, climate monitoring and weather prediction. Moreover, net radiation is an essential input variable for potential as well as actual evapotranspiration modeling. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute net radiation at regional scales in a feasible way. In this study we present a regional scale estimation of the daily Rn on clear days, (Catalonia, NE of the Iberian Peninsula), using a set of 22 Landsat images (17 Landsat-5 TM and 5 Landsat-7 ETM+) and 171 TERRA/AQUA images MODIS from 2000 to 2007 period. TERRA/AQUA MODIS images have been downloaded by means of the EOS Gateway. We have selected three different types of products which contain the remote sensing data we have used to model daily Rn: daily LST product, daily calibrated reflectances product and daily atmospheric water vapour product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital Elevation Model, obtaining an RMS less than 30 m. Radiometric correction of Landsat non-thermal bands has been done following the methodology proposed by Pons and Solé (1994), which allows to reduce the number of undesired artifacts that are due to the effects of the atmosphere or to the differential illumination which is, in turn, due to the time of the day, the location in the Earth and the relief (zones being more illuminated than others, shadows, etc). Atmospheric correction of Landsat thermal band has been carried out by means of a single-channel algorithm improvement developed by Cristóbal et al. (2009) and the land surface emissivity computed by means of the methodology proposed by Sobrino and Raissouni (2000). Rn has been estimated through the

Application of EREP, LANDSAT, and aircraft image data to environmental problems related to coal mining

Science.gov (United States)

Amato, R. V.; Russell, O. R.; Martin, K. R.; Wier, C. E.

1975-01-01

Remote sensing techniques were used to study coal mining sites within the Eastern Interior Coal Basin (Indiana, Illinois, and western Kentucky), the Appalachian Coal Basin (Ohio, West Virginia, and Pennsylvania) and the anthracite coal basins of northeastern Pennsylvania. Remote sensor data evaluated during these studies were acquired by LANDSAT, Skylab and both high and low altitude aircraft. Airborne sensors included multispectral scanners, multiband cameras and standard mapping cameras loaded with panchromatic, color and color infrared films. The research conducted in these areas is a useful prerequisite to the development of an operational monitoring system that can be peridically employed to supply state and federal regulatory agencies with supportive data. Further research, however, must be undertaken to systematically examine those mining processes and features that can be monitored cost effectively using remote sensors and for determining what combination of sensors and ground sampling processes provide the optimum combination for an operational system.

FEASIBILITY STUDY OF LANDSAT-8 IMAGERY FOR RETRIEVING SEA SURFACE TEMPERATURE (CASE STUDY PERSIAN GULF

Directory of Open Access Journals (Sweden)

F. Bayat

2016-06-01

Full Text Available Sea surface temperature (SST is one of the critical parameters in marine meteorology and oceanography. The SST datasets are incorporated as conditions for ocean and atmosphere models. The SST needs to be investigated for various scientific phenomenon such as salinity, potential fishing zone, sea level rise, upwelling, eddies, cyclone predictions. On the other hands, high spatial resolution SST maps can illustrate eddies and sea surface currents. Also, near real time producing of SST map is suitable for weather forecasting and fishery applications. Therefore satellite remote sensing with wide coverage of data acquisition capability can use as real time tools for producing SST dataset. Satellite sensor such as AVHRR, MODIS and SeaWIFS are capable of extracting brightness values at different thermal spectral bands. These brightness temperatures are the sole input for the SST retrieval algorithms. Recently, Landsat-8 successfully launched and accessible with two instruments on-board: (1 the Operational Land Imager (OLI with nine spectral bands in the visual, near infrared, and the shortwave infrared spectral regions; and (2 the Thermal Infrared Sensor (TIRS with two spectral bands in the long wavelength infrared. The two TIRS bands were selected to enable the atmospheric correction of the thermal data using a split window algorithm (SWA. The TIRS instrument is one of the major payloads aboard this satellite which can observe the sea surface by using the split-window thermal infrared channels (CH10: 10.6 μm to 11.2 μm; CH11: 11.5 μm to 12.5 μm at a resolution of 30 m. The TIRS sensors have three main advantages comparing with other previous sensors. First, the TIRS has two thermal bands in the atmospheric window that provide a new SST retrieval opportunity using the widely used split-window (SW algorithm rather than the single channel method. Second, the spectral filters of TIRS two bands present narrower bandwidth than that of the thermal band

Results of agriclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

International Nuclear Information System (INIS)

Choudhury, A.M.

1990-08-01

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. (author). 3 refs

ADI splitting schemes for a fourth-order nonlinear partial differential equation from image processing

KAUST Repository

Calatroni, Luca

2013-08-01

We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H -1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation.

ADI splitting schemes for a fourth-order nonlinear partial differential equation from image processing

KAUST Repository

Calatroni, Luca; Dü ring, Bertram; Schö nlieb, Carola-Bibiane

2013-01-01

We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H -1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation.

Uma biblioteca de pontos de controle para imagens MSS Landsat

OpenAIRE

Fernando Augusto Mitsuo Ii

1985-01-01

O objetivo deste trabalho e desenvolver um sistema para criacao, manutencao e gerenciamento de uma biblioteca de pontos de controle para imagens MSS Landsat. Um ponto de controle e uma caracteristica fisicamente detectavel numa cena, cuja localizacao geodesica e precisamente conhecida. O uso destes pontos e de fundamental importancia num sistema de correcao geometrica de imagens de satelite. A biblioteca permitira que pontos de controle pertencentes a uma dada cena sejam recuperados de uma ma...

MAPPING DISTURBANCE DYNAMICS IN WET SCLEROPHYLL FORESTS USING TIME SERIES LANDSAT

Directory of Open Access Journals (Sweden)

A. Haywood

2016-06-01

. This study demonstrates the potential of landsat time series mapping for fire and timber harvesting disturbances at the agent level and highlights the need for distinguishing between agents to fully capture their impacts on ecosystem processes.

Integrating Landsat Data and High-Resolution Imagery for Applied Conservation Assessment of Forest Cover in Latin American Heterogenous Landscapes

Science.gov (United States)

Thomas, N.; Rueda, X.; Lambin, E.; Mendenhall, C. D.

2012-12-01

Large intact forested regions of the world are known to be critical to maintaining Earth's climate, ecosystem health, and human livelihoods. Remote sensing has been successfully implemented as a tool to monitor forest cover and landscape dynamics over broad regions. Much of this work has been done using coarse resolution sensors such as AVHRR and MODIS in combination with moderate resolution sensors, particularly Landsat. Finer scale analysis of heterogeneous and fragmented landscapes is commonly performed with medium resolution data and has had varying success depending on many factors including the level of fragmentation, variability of land cover types, patch size, and image availability. Fine scale tree cover in mixed agricultural areas can have a major impact on biodiversity and ecosystem sustainability but may often be inadequately captured with the global to regional (coarse resolution and moderate resolution) satellite sensors and processing techniques widely used to detect land use and land cover changes. This study investigates whether advanced remote sensing methods are able to assess and monitor percent tree canopy cover in spatially complex human-dominated agricultural landscapes that prove challenging for traditional mapping techniques. Our study areas are in high altitude, mixed agricultural coffee-growing regions in Costa Rica and the Colombian Andes. We applied Random Forests regression tree analysis to Landsat data along with additional spectral, environmental, and spatial variables to predict percent tree canopy cover at 30m resolution. Image object-based texture, shape, and neighborhood metrics were generated at the Landsat scale using eCognition and included in the variable suite. Training and validation data was generated using high resolution imagery from digital aerial photography at 1m to 2.5 m resolution. Our results are promising with Pearson's correlation coefficients between observed and predicted percent tree canopy cover of .86 (Costa

Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree.

Science.gov (United States)

Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang

2016-07-12

Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation

Directory of Open Access Journals (Sweden)

Flavia Di Palma

2016-07-01

Full Text Available The negative impacts of land take on natural components and economic resources affect planning choices and territorial policies. The importance of land take monitoring, in Italy, has been only recently considered, but despite this awareness, in the great part of the country, effective monitoring and containment measures have not been started, yet. This research proposes a methodology to map and monitor land use changes. To this end, a time series from 1985–2010, based on the multi-temporal Landsat data Thematic Mapper (TM, has been analyzed in the Vulture Alto-Bradano area, a mountain zone of the Basilicata region (Southern Italy. Results confirm a double potentiality of using these data: on the one hand, the use of multi-temporal Landsat data allows going very back in time, producing accurate datasets that provide a phenomenon trend over time; on the other hand, these data can be considered a first experience of open data in the field of spatial information. The proposed methodology provides agencies, local authorities and practitioners with a valuable tool to implement monitoring actions. This represents the first step to pursue territorial governance methods based on sustainability, limiting the land take.

Assessing the effectiveness of Landsat 8 chlorophyll a retrieval algorithms for regional freshwater monitoring.

Science.gov (United States)

Boucher, Jonah; Weathers, Kathleen C; Norouzi, Hamid; Steele, Bethel

2018-06-01

Predicting algal blooms has become a priority for scientists, municipalities, businesses, and citizens. Remote sensing offers solutions to the spatial and temporal challenges facing existing lake research and monitoring programs that rely primarily on high-investment, in situ measurements. Techniques to remotely measure chlorophyll a (chl a) as a proxy for algal biomass have been limited to specific large water bodies in particular seasons and narrow chl a ranges. Thus, a first step toward prediction of algal blooms is generating regionally robust algorithms using in situ and remote sensing data. This study explores the relationship between in-lake measured chl a data from Maine and New Hampshire, USA lakes and remotely sensed chl a retrieval algorithm outputs. Landsat 8 images were obtained and then processed after required atmospheric and radiometric corrections. Six previously developed algorithms were tested on a regional scale on 11 scenes from 2013 to 2015 covering 192 lakes. The best performing algorithm across data from both states had a 0.16 correlation coefficient (R 2 ) and P ≤ 0.05 when Landsat 8 images within 5 d, and improved to R 2 of 0.25 when data from Maine only were used. The strength of the correlation varied with the specificity of the time window in relation to the in-situ sampling date, explaining up to 27% of the variation in the data across several scenes. Two previously published algorithms using Landsat 8's Bands 1-4 were best correlated with chl a, and for particular late-summer scenes, they accounted for up to 69% of the variation in in-situ measurements. A sensitivity analysis revealed that a longer time difference between in situ measurements and the satellite image increased uncertainty in the models, and an effect of the time of year on several indices was demonstrated. A regional model based on the best performing remote sensing algorithm was developed and was validated using independent in situ measurements and satellite

A procedure for merging land cover/use data from Landsat, aerial photography, and map sources - Compatibility, accuracy and cost

Science.gov (United States)

Enslin, W. R.; Tilmann, S. E.; Hill-Rowley, R.; Rogers, R. H.

1977-01-01

A method is developed to merge land cover/use data from Landsat, aerial photography and map sources into a grid-based geographic information system. The method basically involves computer-assisted categorization of Landsat data to provide certain user-specified land cover categories; manual interpretation of aerial photography to identify other selected land cover/use categories that cannot be obtained from Landsat data; identification of special features from aerial photography or map sources; merging of the interpreted data from all the sources into a computer compatible file under a standardized coding structure; and the production of land cover/use maps, thematic maps, and tabular data. The specific tasks accomplished in producing the merged land cover/use data file and subsequent output products are identified and discussed. It is shown that effective implementation of the merging method is critically dependent on selecting the 'best' data source for each user-specified category in terms of accuracy and time/cost tradeoffs.

Volcano stratigraphy interpretation of Mamuju area based on Landsat-8 imagery analysis

International Nuclear Information System (INIS)

Frederikus Dian Indrastomo; I Gde Sukadana; Dhatu Kamajati; Asep Saepuloh; Agus Handoyo Harsolumakso

2015-01-01

Mamuju and its surrounding area are constructed mainly by volcanic rocks. Volcanoclastic sedimentary rocks and limestones are laid above the volcanic rocks. Volcanic activities create some unique morphologies such as craters, lava domes, and pyroclastic flow paths as their volcanic products. These products are identified from their circular features characters on Landsat-8 imagery. Geometric and atmospheric corrections had been done, a visual interpretation on Landsat-8 imagery was conducted to identify structure, geomorphology, and geological condition of the area. Regional geological structures show trend to southeast – northwest direction which is affects the formation of Adang volcano. Geomorphology of the area are classified into 16 geomorphology units based on their genetic aspects, i.e Sumare fault block ridge, Mamuju cuesta ridge, Adang eruption crater, Labuhan Ranau eruption crater, Sumare eruption crater, Ampalas volcanic cone, Adang lava dome, Labuhan Ranau intrusion hill, Adang pyroclastic flow ridge, Sumare pyroclastic flow ridge, Adang volcanic remnant hills, Malunda volcanic remnant hills, Talaya volcanic remnant hills, Tapalang karst hills, Mamuju alluvium plains, and Karampuang reef terrace plains. Based on the Landsat-8 imagery interpretation result and field confirmation, the geology of Mamuju area is divided into volcanic rocks and sedimentary rocks. There are two groups of volcanic rocks; Talaya complex and Mamuju complex. The Talaya complex consists of Mambi, Malunda, and Kalukku volcanic rocks with andesitic composition, while Mamuju complex consist of Botteng, Ahu, Tapalang, Adang, Ampalas, Sumare, and Labuhan Ranau volcanic rocks with andesite to leucitic basalt composition. The volcano stratigraphy of Mamuju area was constructed based on its structure, geomorphology and lithology distribution analysis. Volcano stratigraphy of Mamuju area is classified into Khuluk Talaya and Khuluk Mamuju. The Khuluk Talaya consists of Gumuk Mambi, Gumuk

Geothermal Anomaly Mapping Using Landsat ETM+ Data in Ilan Plain, Northeastern Taiwan

Science.gov (United States)

Chan, Hai-Po; Chang, Chung-Pai; Dao, Phuong D.

2018-01-01

Geothermal energy is an increasingly important component of green energy in the globe. A prerequisite for geothermal energy development is to acquire the local and regional geothermal prospects. Existing geophysical methods of estimating the geothermal potential are usually limited to the scope of prospecting because of the operation cost and site reachability in the field. Thus, explorations in a large-scale area such as the surface temperature and the thermal anomaly primarily rely on satellite thermal infrared imagery. This study aims to apply and integrate thermal infrared (TIR) remote sensing technology with existing geophysical methods for the geothermal exploration in Taiwan. Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) imagery is used to retrieve the land surface temperature (LST) in Ilan plain. Accuracy assessment of satellite-derived LST is conducted by comparing with the air temperature data from 11 permanent meteorological stations. The correlation coefficient of linear regression between air temperature and LST retrieval is 0.76. The MODIS LST product is used for the cross validation of Landsat derived LSTs. Furthermore, Landsat ETM+ multi-temporal brightness temperature imagery for the verification of the LST anomaly results were performed. LST Results indicate that thermal anomaly areas appear correlating with the development of faulted structure. Selected geothermal anomaly areas are validated in detail by field investigation of hot springs and geothermal drillings. It implies that occurrences of hot springs and geothermal drillings are in good spatial agreement with anomaly areas. In addition, the significant low-resistivity zones observed in the resistivity sections are echoed with the LST profiles when compared with in the Chingshui geothermal field. Despite limited to detecting the surficial and the shallow buried geothermal resources, this work suggests that TIR remote sensing is a valuable tool by providing an effective way of mapping

Comparison of MODIS and Landsat TM5 images for mapping tempo-spatial dynamics of Secchi disk depths in Poyang Lake national nature reserve, China

NARCIS (Netherlands)

Wu, G.; Leeuw, de J.; Skidmore, A.K.; Prins, H.H.T.; Liu, Y.

2008-01-01

Landsat has successfully been applied to map Secchi disk depth of inland water bodies. Operational use for monitoring a dynamic variable like Secchi disk depth is however limited by the 16-day overpass cycle of the Landsat system and cloud cover. Low spatial resolution Moderate Resolution Imaging

Local search for optimal global map generation using mid-decadal landsat images

Science.gov (United States)

Khatib, L.; Gasch, J.; Morris, Robert; Covington, S.

2007-01-01

NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

Science.gov (United States)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California

Science.gov (United States)

Soulard, Christopher E.; Albano, Christine M.; Villarreal, Miguel; Walker, Jessica

2016-01-01

To assess how montane meadow vegetation recovered after a wildfire that occurred in Yosemite National Park, CA in 1996, Google Earth Engine image processing was applied to leverage the entire Landsat Thematic Mapper archive from 1985 to 2012. Vegetation greenness (normalized difference vegetation index [NDVI]) was summarized every 16 days across the 28-year Landsat time series for 26 meadows. Disturbance event detection was hindered by the subtle influence of low-severity fire on meadow vegetation. A hard break (August 1996) was identified corresponding to the Ackerson Fire, and monthly composites were used to compare NDVI values and NDVI trends within burned and unburned meadows before, immediately after, and continuously for more than a decade following the fire date. Results indicate that NDVI values were significantly lower at 95% confidence level for burned meadows following the fire date, yet not significantly lower at 95% confidence level in the unburned meadows. Burned meadows continued to exhibit lower monthly NDVI in the dormant season through 2012. Over the entire monitoring period, the negative-trending, dormant season NDVI slopes in the burned meadows were also significantly lower than unburned meadows at 90% confidence level. Lower than average NDVI values and slopes in the dormant season compared to unburned meadows, coupled with photographic evidence, strongly suggest that evergreen vegetation was removed from the periphery of some meadows after the fire. These analyses provide insight into how satellite imagery can be used to monitor low-severity fire effects on meadow vegetation.

Use of Landsat data in soil and agricultural land use studies

Science.gov (United States)

Westin, F. C.; Brandner, T. M.

1980-01-01

This paper describes how the synoptic, multispectral, and temporal characteristics of Landsat can be used to locate Soil Association boundaries. Then, using these techniques we describe how a low intensity soil survey was conducted and how some interpretive maps were developed from this. Finally, we describe how soil suitability and land use interpretations were made to aid in defining Agrophysical units used in crop inventories.

Partial purification and biochemical characterization of acid ...

African Journals Online (AJOL)

Mung bean (Vigna radiata) is one of the important crops of the North Eastern Region of India. In the present study, acid phosphatase enzyme was isolated and partially purified from germinated local mung bean seeds. The sequential partial purification process was performed using ammonium sulphate precipitation method.

Landsat 5 TM images and DEM in lithologic mapping of Payen Volcanic Field (Mendoza Province, Argentina)

International Nuclear Information System (INIS)

Fornaciai, A.; Bisson, M.; Mazzarini, F.; Del Carlo, P.; Pasquare, G.

2009-01-01

Satellite image such as Landsat 5 TM scene provides excellent representation of Earth and synoptic view of large geographic areas in different band combination. Landsat TM images allow automatic and semi-automatic classification of land cover, nevertheless the software frequently may some difficulties in distinguishing between similar radiometric surfaces. In this case, the use of Digital Elevation Model (DEM) can be an important tool to identify different surface covers. In this study, several False Color Composite (FCC) of Landsat 5 TM Image, DEM and the respective draped image of them, were used to delineate lithological boundaries and tectonic features of regional significance of the Paven Volcanic Field (PVF). PFV is a Quaternary fissural structure belonging to the black-arc extensional areas of the Andes in the Mendoza Province (Argentina) characterized by many composite basaltic lava flow fields. The necessity to identify different lava flows with the same composition, and then with same spectral features, allows to highlight the improvement of synergic use of TM images and shaded DEM in the visual interpretation. Information obtained from Satellite data and DEM have been compared with previous geological maps and transferred into a topographical base map. Based on these data a new lithological map at 1:100.000 scale has been presented [it

Using space-time features to improve detection of forest disturbances from Landsat time series

NARCIS (Netherlands)

Hamunyela, E.; Reiche, J.; Verbesselt, J.; Herold, M.

2017-01-01

Current research on forest change monitoring using medium spatial resolution Landsat satellite data aims for accurate and timely detection of forest disturbances. However, producing forest disturbance maps that have both high spatial and temporal accuracy is still challenging because of the

Change detection of bare areas in the Xolobeni region, South Africa using Landsat NDVI

CSIR Research Space (South Africa)

Singh, RG

2015-06-01

Full Text Available to provide some information on the inter-relationship between vegetated classes and bare areas. Normalised Difference Vegetation Index (NDVI) data derived from multi-temporal Landsat 5 imagery has formed the baseline information for this study. A density...

Browning of the landscape of interior Alaska based on 1986-2009 Landsat sensor NDVI

Science.gov (United States)

Rebecca A. Baird; David Verbyla; Teresa N. Hollingsworth

2012-01-01

We used a time series of 1986-2009 Landsat sensor data to compute the Normalized Difference Vegetation Index (NDVI) for 30 m pixels within the Bonanza Creek Experimental Forest of interior Alaska. Based on simple linear regression, we found significant (p

ShapeSelectForest: a new r package for modeling landsat time series

Science.gov (United States)

Mary Meyer; Xiyue Liao; Gretchen Moisen; Elizabeth Freeman

2015-01-01

We present a new R package called ShapeSelectForest recently posted to the Comprehensive R Archival Network. The package was developed to fit nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral...

LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes:...

LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest,...

Geomorphic domains and linear features on Landsat images, Circle Quadrangle, Alaska

Science.gov (United States)

Simpson, S.L.

1984-01-01

A remote sensing study using Landsat images was undertaken as part of the Alaska Mineral Resource Assessment Program (AMRAP). Geomorphic domains A and B, identified on enhanced Landsat images, divide Circle quadrangle south of Tintina fault zone into two regional areas having major differences in surface characteristics. Domain A is a roughly rectangular, northeast-trending area of relatively low relief and simple, widely spaced drainages, except where igneous rocks are exposed. In contrast, domain B, which bounds two sides of domain A, is more intricately dissected showing abrupt changes in slope and relatively high relief. The northwestern part of geomorphic domain A includes a previously mapped tectonostratigraphic terrane. The southeastern boundary of domain A occurs entirely within the adjoining tectonostratigraphic terrane. The sharp geomorphic contrast along the southeastern boundary of domain A and the existence of known faults along this boundary suggest that the southeastern part of domain A may be a subdivision of the adjoining terrane. Detailed field studies would be necessary to determine the characteristics of the subdivision. Domain B appears to be divisible into large areas of different geomorphic terrains by east-northeast-trending curvilinear lines drawn on Landsat images. Segments of two of these lines correlate with parts of boundaries of mapped tectonostratigraphic terranes. On Landsat images prominent north-trending lineaments together with the curvilinear lines form a large-scale regional pattern that is transected by mapped north-northeast-trending high-angle faults. The lineaments indicate possible lithlogic variations and/or structural boundaries. A statistical strike-frequency analysis of the linear features data for Circle quadrangle shows that northeast-trending linear features predominate throughout, and that most northwest-trending linear features are found south of Tintina fault zone. A major trend interval of N.64-72E. in the linear

Use of ERS-2 Sar and Landsat TM Images for Geological Mapping and Mineral Exploration Of Sol Hamid Area, South Eastern Desert, Egypt

International Nuclear Information System (INIS)

Ramadan, T.M.

2003-01-01

Sol hamid area is chiefy occupied by neo proterozoic rocks, partly covered by miocene sediments and recent sand sheets and dunes. The neo proterozoic rocks include ophiolitic ultramafic to mafic rocks, meta volcano-sedimentary rocks, meta volcanics, gabbros-diorite rocks, granodiorites, biotite granites and alkali granites. Magnesite, chromite, iron ores, manganese and barite ore deposits are hosted in different at the study area. ERS-2 SAR data enabled to obtain an image that reveals some buried fluvial features beneath the surface cover of desert sand. These features are not observable in Landsat TM image of similar resolution. In this work, Principal Component Analysis (PCA) technique was used for merging ERS-2 SAR and Landsat TM images to make use of the potential of data fusion technique of image processing in the interpretation of geological features. This procedure has resulted in enhancing subsurface structure such as faults that control distribution of several deposits in the study area. This study represents an example to demonstrate the utility of merging various remote sensing data for exploring mineral deposits in arid region

SEDIMENT ANALYSIS NETWORK FOR DECISION SUPPORT (SANDS) LANDSAT GEOLOGICAL SURVEY OF AL (GSA) ANALYSIS V1

Data.gov (United States)

National Aeronautics and Space Administration — The Sediment Analysis Network for Decision Support (SANDS) Landsat Geological Survey of AL (GSA) Analysis dataset analyzed changes in the coastal shoreline and...

Partial dynamical systems, fell bundles and applications

CERN Document Server

Exel, Ruy

2017-01-01

Partial dynamical systems, originally developed as a tool to study algebras of operators in Hilbert spaces, has recently become an important branch of algebra. Its most powerful results allow for understanding structural properties of algebras, both in the purely algebraic and in the C*-contexts, in terms of the dynamical properties of certain systems which are often hiding behind algebraic structures. The first indication that the study of an algebra using partial dynamical systems may be helpful is the presence of a grading. While the usual theory of graded algebras often requires gradings to be saturated, the theory of partial dynamical systems is especially well suited to treat nonsaturated graded algebras which are in fact the source of the notion of "partiality". One of the main results of the book states that every graded algebra satisfying suitable conditions may be reconstructed from a partial dynamical system via a process called the partial crossed product. Running in parallel with partial dynamica...

Computer implemented land cover classification using LANDSAT MSS digital data: A cooperative research project between the National Park Service and NASA. 3: Vegetation and other land cover analysis of Shenandoah National Park

Science.gov (United States)

Cibula, W. G.

1981-01-01

Four LANDSAT frames, each corresponding to one of the four seasons were spectrally classified and processed using NASA-developed computer programs. One data set was selected or two or more data sets were marged to improve surface cover classifications. Selected areas representing each spectral class were chosen and transferred to USGS 1:62,500 topographic maps for field use. Ground truth data were gathered to verify the accuracy of the classifications. Acreages were computed for each of the land cover types. The application of elevational data to seasonal LANDSAT frames resulted in the separation of high elevation meadows (both with and without recently emergent perennial vegetation) as well as areas in oak forests which have an evergreen understory as opposed to other areas which do not.

Revealing livestock effects on bunchgrass vegetation with Landsat ETM+ data across a grazing season

Science.gov (United States)

Jansen, Vincent S.

Remote sensing provides monitoring solutions for more informed grazing management. To investigate the ability to detect the effects of cattle grazing on bunchgrass vegetation with Landsat Enhanced Thematic Mapper Plus (ETM+) data, we conducted a study on the Zumwalt Prairie in northeastern Oregon across a gradient of grazing intensities. Biophysical vegetation data was collected on vertical structure, biomass, and cover at three different time periods during the grazing season: June, August, and October 2012. To relate these measures to the remotely sensed Landsat ETM+ data, Pearson's correlations and multiple regression models were computed. Using the best models, predicted vegetation metrics were then mapped across the study area. Results indicated that models using common vegetation indices had the ability to discern different levels of grazing across the study area. Results can be distributed to land managers to help guide grassland conservation by improving monitoring of bunchgrass vegetation for sustainable livestock management.

LANDSAT remote sensing: observations of an Appalachian mountaintop surface coal mining and reclamation operation

International Nuclear Information System (INIS)

1979-10-01

The potential benefits of using LANDSAT remote sensing data by state agencies as an aide in monitoring surface coal mining operations are reviewed. A mountaintop surface mine in eastern Kentucky was surveyed over a 5 year period using satellite multispectral scanner data that were classified by computer analyses. The analyses were guided by aerial photography and by ground surveys of the surface mines procured in 1976. The application of the LANDSAT data indicates that: (1) computer classification of the various landcover categories provides information for monitoring the progress of surface mining and reclamation operations, (2) successive yearly changes in barren and revegetated areas can be qualitatively assessed for surface mines of 100 acres or more of disrupted area, (3) barren areas consisting of limestone and shale mixtures may be recognized, and revegetated areas in various stages of growth may be identified against the hilly forest background

An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

Science.gov (United States)

Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

2015-12-01

Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

Partial Orders and Fully Abstract Models for Concurrency

DEFF Research Database (Denmark)

Engberg, Uffe Henrik

1990-01-01

In this thesis sets of labelled partial orders are employed as fundamental mathematical entities for modelling nondeterministic and concurrent processes thereby obtaining so-called noninterleaving semantics. Based on different closures of sets of labelled partial orders, simple algebraic language...

Regional and landscape-scale variability of Landsat-observed vegetation dynamics in northwest Siberian tundra

International Nuclear Information System (INIS)

Frost, Gerald V; Epstein, Howard E; Walker, Donald A

2014-01-01

Widespread increases in Arctic tundra productivity have been documented for decades using coarse-scale satellite observations, but finer-scale observations indicate that changes have been very uneven, with a high degree of landscape- and regional-scale heterogeneity. Here we analyze time-series of the Normalized Difference Vegetation Index (NDVI) observed by Landsat (1984–2012), to assess landscape- and regional-scale variability of tundra vegetation dynamics in the northwest Siberian Low Arctic, a little-studied region with varied soils, landscape histories, and permafrost attributes. We also estimate spatio-temporal rates of land-cover change associated with expansion of tall alder (Alnus) shrublands, by integrating Landsat time-series with very-high-resolution imagery dating to the mid-1960s. We compiled Landsat time-series for eleven widely-distributed landscapes, and performed linear regression of NDVI values on a per-pixel basis. We found positive net NDVI trends (‘greening’) in nine of eleven landscapes. Net greening occurred in alder shrublands in all landscapes, and strong greening tended to correspond to shrublands that developed since the 1960s. Much of the spatial variability of greening within landscapes was linked to landscape physiography and permafrost attributes, while between-landscape variability largely corresponded to differences in surficial geology. We conclude that continued increases in tundra productivity in the region are likely in upland tundra landscapes with fine-textured, cryoturbated soils; these areas currently tend to support discontinuous vegetation cover, but are highly susceptible to rapid increases in vegetation cover, as well as land-cover changes associated with the development of tall shrublands. (paper)

Frontal Underactivation During Working Memory Processing in Adults With Acute Partial Sleep Deprivation: A Near-Infrared Spectroscopy Study

Directory of Open Access Journals (Sweden)

Michael K. Yeung

2018-05-01

Full Text Available Individuals with partial sleep deprivation may have working memory (WM impairment, but the underlying neural mechanism of this phenomenon is relatively unknown. The present study examined neural processing during WM performance in individuals with and without partial sleep deprivation using near-infrared spectroscopy (NIRS. Forty college students (10 males were equally split into Sufficient Sleep (SS and Insufficient Sleep (IS groups based on self-reports of previous night's sleep duration. Participants in the SS group obtained the recommended amounts of sleep according to various sleep organizations (i.e., >7.0 h, whereas those in the IS group obtained amounts of sleep no greater than the lower limit of the recommendation (i.e., ≤7.0 h. All participants underwent an n-back paradigm with a WM load (i.e., 3-back and a control condition (i.e., 0-back while their prefrontal hemodynamics were recorded by NIRS. The IS and SS groups performed the tasks comparably well. However, unlike the SS group, which exhibited bilateral frontal activation indicated by increased oxyhemoglobin concentration and decreased deoxyhemoglobin concentration during WM processing (i.e., 3-back > 0-back, the IS group did not exhibit such activation. In addition, levels of WM-related frontal activation, especially those on the left side, correlated with sleep duration the night before, even when habitual sleep duration was controlled for. The findings suggest the presence of frontal lobe dysfunction in the absence of evident WM difficulties in individuals with acute partial sleep deprivation. They also highlight the importance of a good night's sleep to brain health.

How to test for partially predictable chaos.

Science.gov (United States)

Wernecke, Hendrik; Sándor, Bulcsú; Gros, Claudius

2017-04-24

For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation can split into an initial exponential decrease and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. Both processes can be either of the same or of very different time scales. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall extent of the attractor) for exceedingly long times and remain partially predictable. Standard tests for chaos widely use inter-orbital correlations as an indicator. However, testing partially predictable chaos yields mostly ambiguous results, as this type of chaos is characterized by attractors of fractally broadened braids. For a resolution we introduce a novel 0-1 indicator for chaos based on the cross-distance scaling of pairs of initially close trajectories. This test robustly discriminates chaos, including partially predictable chaos, from laminar flow. Additionally using the finite time cross-correlation of pairs of initially close trajectories, we are able to identify laminar flow as well as strong and partially predictable chaos in a 0-1 manner solely from the properties of pairs of trajectories.

LANDSAT/MMS propulsion module design. Tas4.4: Concept design

Science.gov (United States)

Mansfield, J. M.; Etheridge, F. G.; Indrikis, J.

1976-01-01

Evaluations are presented of alternative LANDSAT follow-on launch configurations to derive the propulsion requirements for the multimission modular spacecraft (MMS). Two basic types were analyzed including use of conventional launch vehicles and shuttle supported missions. It was concluded that two sizes of modular hydrazine propulsion modules would provide the most cost-effective combination for future missions of this spacecraft. Conceptual designs of the selected propulsion modules were performed to the depth permitting determination of mass properties and estimated costs.

Estimation of watershed-level distributed forest structure metrics relevant to hydrologic modeling using LiDAR and Landsat

Science.gov (United States)

Varhola, Andrés; Coops, Nicholas C.

2013-04-01

SummaryA detailed characterization of vegetation structure is fundamental for physically-based hydrologic models to simulate various processes that determine rates of snow accumulation and ablation, evapotranspiration and water dynamics. However, major efforts focused on developing complex equations to describe hydrologic processes as a function of vegetation structure at the plot level have not been accompanied by corresponding attempts to adequately extrapolate these metrics over the wider landscape in order to parameterize fully-distributed models. Recent advances in remote sensing technologies offer alternatives to overcome these difficulties and therefore improve our capacity to monitor vegetation and hydrologic processes extensively. Airborne Laser Scanning (ALS) stands out as the most promising tool to provide detailed, 3-dimensional representations of vegetation from which a wide array of structural metrics can be estimated. On the other hand, moderate scale optical remote sensing imagery such as Landsat Thematic Mapper (TM) offers the capacity to extrapolate these metrics across the landscape by virtue of its spatial and temporal resolutions. Here we correlate ALS-derived forest cover (FC), tree height (H), leaf area index (LAI) and sky view-factor (SVF) - the four main structural parameters used by hydrologic models - with a suite of spectral indices obtained from six spectral bands of a Landsat 5 TM image. Despite numerous sources of variation that affect the relationships between 2-dimensional spectral indices and three-dimensional structural metrics, models to predict FC, H, LAI and SVF with reasonable accuracy were developed. The extrapolation of these variables across a watershed in British Columbia severely affected by insect disturbance resulted in highly-detailed 30 m spatial resolution maps and frequency distributions consistent with the natural variation ranges of each metric - a major improvement compared to traditional approaches that use

Combining Estimation of Green Vegetation Fraction in an Arid Region from Landsat 7 ETM+ Data

Directory of Open Access Journals (Sweden)

Kun Jia

2017-11-01

Full Text Available Fractional vegetation cover (FVC, or green vegetation fraction, is an important parameter for characterizing conditions of the land surface vegetation, and also a key variable of models for simulating cycles of water, carbon and energy on the land surface. There are several types of FVC estimation models using remote sensing data, and evaluating their performance over a specific region is of great significance. Therefore, this study firstly evaluated three types of FVC estimation models using Landsat 7 ETM+ data in an agriculture region of Heihe River Basin, China, and then proposed a combination strategy from different individual models to improve the FVC estimation accuracy, which employed the multiple linear regression (MLR and Bayesian model average (BMA methods. The validation results indicated that the spectral mixture analysis model with three endmembers (SMA3 achieved the best FVC estimation accuracy (determination coefficient (R2 = 0.902, root mean square error (RMSE = 0.076 among the seven individual models using Landsat 7 ETM+ data. In addition, the MLR and BMA combination methods could both improve FVC estimation accuracy (R2 = 0.913, RMSE = 0.063 and R2 = 0.904, RMSE = 0.069 for MLR and BMA, respectively. Therefore, it could be concluded that both MLR and BMA combination methods integrating FVC estimates from different models using Landsat 7 ETM+ data could effectively weaken the estimation errors of individual models and improve the final FVC estimation accuracy.

Fundamental studies on the reaction process of partial hydropyrolysis of coal

Energy Technology Data Exchange (ETDEWEB)

O. Yamada; H. Yasuda; M. Kaiho [National Institute of Advanced Industrial Science and Technology, Ibaraki (Japan). Energy Technology Research Institute

2005-07-01

In order to make up a simulator to support the development of coal partial hydropyrolysis process, material balance of the reaction was investigated precisely. Amount of H{sub 2} evolved by pyrolysis under inert gas atmosphere was found almost equal to that of (CO+2CO{sub 2}), therefore, most of H{sub 2} seemed to be generated through water gas reaction and shift reaction. CH{sub 4} seemed to be stable even at 1073K and 7.1MPa of H{sub 2}, its generation was simply accelerated in proportion to H{sub 2} pressure. Hydrocarbons, other than CH{sub 4}, were fundamentally unstable at 1073K and 0.93 -7.1MPa of H{sub 2}, however the rate of decomposition of them were so slow that amounts of them evolved were apparently proportion to reaction time and H{sub 2} pressure. BTX and naphthalene were increased apparently with H{sub 2} pressure when the reaction time was less than 5s. 4 refs., 20 figs.

Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery

Directory of Open Access Journals (Sweden)

Yuanwei Qin

2016-11-01

Full Text Available Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS PALSAR Fine Beam Dual Polarization (FBD mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA, National Land Cover Database (NLCD, Oklahoma Ecological Systems Map (OKESM and Oklahoma Forest Resource Assessment (OKFRA, the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2, but much larger than those from JAXA (32,403 km2 and NLCD (37,628 km2. We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010 and gain (3630 km2, 9.0% in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be

A cloud shadow detection method combined with cloud height iteration and spectral analysis for Landsat 8 OLI data

Science.gov (United States)

Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying

2018-04-01

Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct

Development of a simultaneous partial nitrification and anaerobic ammonia oxidation process in a single reactor.

Science.gov (United States)

Cho, Sunja; Fujii, Naoki; Lee, Taeho; Okabe, Satoshi

2011-01-01

Up-flow oxygen-controlled biofilm reactors equipped with a non-woven fabric support were used as a single reactor system for autotrophic nitrogen removal based on a combined partial nitrification and anaerobic ammonium oxidation (anammox) reaction. The up-flow biofilm reactors were initiated as either a partial nitrifying reactor or an anammox reactor, respectively, and simultaneous partial nitrification and anammox was established by careful control of the aeration rate. The combined partial nitrification and anammox reaction was successfully developed in both biofilm reactors without additional biomass inoculation. The reactor initiated as the anammox reactor gave a slightly higher and more stable mean nitrogen removal rate of 0.35 (±0.19) kg-N m(-3) d(-1) than the reactor initiated as the partial nitrifying reactor (0.23 (±0.16) kg-N m(-3) d(-1)). FISH analysis revealed that the biofilm in the reactor started as the anammox reactor were composed of anammox bacteria located in inner anoxic layers that were surrounded by surface aerobic AOB layers, whereas AOB and anammox bacteria were mixed without a distinguishable niche in the biofilm in the reactor started as the partial nitrifying reactor. However, it was difficult to efficiently maintain the stable partial nitrification owing to inefficient aeration in the reactor, which is a key to development of the combined partial nitrification and anammox reaction in a single biofilm reactor. Copyright © 2010 Elsevier Ltd. All rights reserved.

Monitoring Forest Dynamics in the Andean Amazon: The Applicability of Breakpoint Detection Methods Using Landsat Time-Series and Genetic Algorithms

Directory of Open Access Journals (Sweden)

Fabián Santos

2017-01-01

Full Text Available The Andean Amazon is an endangered biodiversity hot spot but its forest dynamics are less studied than those of the Amazon lowland and forests from middle or high latitudes. This is because its landscape variability, complex topography and cloudy conditions constitute a challenging environment for any remote-sensing assessment. Breakpoint detection with Landsat time-series data is an established robust approach for monitoring forest dynamics around the globe but has not been properly evaluated for implementation in the Andean Amazon. We analyzed breakpoint detection-generated forest dynamics in order to determine its limitations when applied to three different study areas located along an altitude gradient in the Andean Amazon in Ecuador. Using all available Landsat imagery for the period 1997–2016, we evaluated different pre-processing approaches, noise reduction techniques, and breakpoint detection algorithms. These procedures were integrated into a complex function called the processing chain generator. Calibration was not straightforward since it required us to define values for 24 parameters. To solve this problem, we implemented a novel approach using genetic algorithms. We calibrated the processing chain generator by applying a stratified training sampling and a reference dataset based on high resolution imagery. After the best calibration solution was found and the processing chain generator executed, we assessed accuracy and found that data gaps, inaccurate co-registration, radiometric variability in sensor calibration, unmasked cloud, and shadows can drastically affect the results, compromising the application of breakpoint detection in mountainous areas of the Andean Amazon. Moreover, since breakpoint detection analysis of landscape variability in the Andean Amazon requires a unique calibration of algorithms, the time required to optimize analysis could complicate its proper implementation and undermine its application for large

Land and Land-use Change in the Climate Sensitive High Plains: An Automated Approach with Landsat

Science.gov (United States)

Goetz, Alexander F.; Williams, D. L. (Technical Monitor)

2002-01-01

The High Plains is an economically important and climatologically sensitive region of the United States and Canada. The High Plains contain 100,000 sq km of Holocene sand dunes and sand sheets that are currently stabilized by natural vegetation. Droughts and the larger threat of global warming are climate phenomena that could cause depletion of natural vegetation and make this region susceptible to sand dune reactivation. The original proposal was directed toward the use of Landsat TM data to establish the state and ongoing changes of the surface in the 1.2 million sq. km, semi-arid High Plains region of the central US, A key objective was to develop a model to predict the reactivation of the 100,000 sq. km of Holocene dunes found on the High Plains during an extended drought. At least one Landsat 5 image per year for 1985, 1988 and 1996 was obtained for 32 scenes on the High Plains to coincide with wet and dry years. Additional Landsat 7 data were acquired for 1999 and 2000 primarily for Colorado and Nebraska. As luck would have it, there was no severe drought during the study period 1985-2000. Attention was focused on developing methods for mapping dry vs. green vegetation on sparsely vegetated rangelands in sandy soils, since these were the areas most susceptible to surface reactivation during a drought.

A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+

Science.gov (United States)

Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.

2011-04-01

The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

Crowdfunding Through a Partial Organization Lens

DEFF Research Database (Denmark)

Nielsen, Kristian Roed

2018-01-01

Crowdfunding has become a rapidly growing source of alternative financing for a wide range of products and service ideas. The crowdfunding process itself necessitates the successful interaction between a number of actors including the central organizing platform, a number of content providing...... campaigns, and a large diverse group of funders. By utilizing the literature on complete and partial organizations and rejecting the commonly applied organizational molds to describe the process, this paper proposes that crowdfunding is organized and enabled as a fluid and co-dependent interaction between...... the various actors. The concept of partial organizations and its emphasis on key organizational decisions reveal that crowdfunding may be conceived of as a “co-dependent organization” in which the relationship of the involved actors is so interdependent that the crowdfunding process can neither be maintained...

Analysis of the Relationship between Land Surface Temperature and Wildfire Severity in a Series of Landsat Images

Directory of Open Access Journals (Sweden)

Lidia Vlassova

2014-06-01

Full Text Available The paper assesses spatio-temporal patterns of land surface temperature (LST and fire severity in the Las Hurdes wildfire of Pinus pinaster forest, which occurred in July 2009, in Extremadura (Spain, from a time series of fifteen Landsat 5 TM images corresponding to 27 post-fire months. The differenced Normalized Burn Ratio (dNBR was used to evaluate burn severity. The mono-window algorithm was applied to estimate LST from the Landsat thermal band. The burned zones underwent a significant increase in LST after fire. Statistically significant differences have been detected between the LST within regions of burn severity categories. More substantial changes in LST are observed in zones of greater fire severity, which can be explained by the lower emissivity of combustion products found in the burned area and changes in the energy balance related to vegetation removal. As time progresses over the 27 months after fire, LST differences decrease due to vegetation regeneration. The differences in LST and Normalized Difference Vegetation Index (NDVI values between burn severity categories in each image are highly correlated (r = 0.84. Spatial patterns of severity and post-fire LST obtained from Landsat time series enable an evaluation of the relationship between these variables to predict the natural dynamics of burned areas.

Intrinsic Nonlinearities and Layout Impacts of 100 V Integrated Power MOSFETs in Partial SOI Process

DEFF Research Database (Denmark)

Fan, Lin; Knott, Arnold; Jørgensen, Ivan Harald Holger

Parasitic capacitances of power semiconductors are a part of the key design parameters of state-of-the-art very high frequency (VHF) power supplies. In this poster, four 100 V integrated power MOSFETs with different layout structures are designed, implemented, and analyzed in a 0.18 ȝm partial...... Silicon-on-Insulator (SOI) process with a die area 2.31 mm2.  A small-signal model of power MOSFETs is proposed to systematically analyze the nonlinear parasitic capacitances in different transistor states: off-state, sub-threshold region, and on-state in the linear region. 3D plots are used to summarize...

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Directory of Open Access Journals (Sweden)

Alfonso F. Torres-Rua

2016-04-01

Full Text Available Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and energy balance products derived from satellite (Landsat imagery and weather data as identified in scientific literature. This methodology employs a statistical learning machine called a Relevance Vector Machine (RVM to identify and relate the potential predictors to soil moisture by means of stratified cross-validation and forward variable selection. Surface soil moisture measurements from irrigated agricultural fields in Central Utah in the 2012 irrigation season were used, along with weather data, Landsat vegetation indices, and energy balance products. The methodology, data collection, processing, and estimation accuracy are presented and discussed.

TOTAL WOOD VOLUME ESTIMATION OF EUCALYPTUS SPECIES BY IMAGES OF LANDSAT SATELLITE

Directory of Open Access Journals (Sweden)

Elias Fernando Berra

2012-12-01

Full Text Available http://dx.doi.org/10.5902/198050987566Models relating spectral answers with biophysical parameters aim estimate variables, like wood volume, without the necessity of frequent field measurements. The objective was to develop models to estimate wood volume by Landsat 5 TM images, supported by regional forest inventory data. The image was geo-referenced and converted to spectral reflectance. After, the images-index NDVI (Normalized Difference Vegetation Index and SR (Simple Ratio was generated. The reflectance values of the bands (TM1, TM2, TM3 e TM4 and of the indices (NDVI and SR was related with the wood volume. The biggest correlation with volume was with the NDVI and SR indices. The variables selection was made by Stepwise method, which returned three regression models as significant to explain the variation in volume. Finally, the best fitted model was selected (volume = -830,95 + 46,05 (SR + 107,47 (TM2, which was applied on the Landsat image where the pixels had started to represent the estimated volume in m³/ha on the Eucalyptus sp. production units. This model, significant at 95% confidence level, explains 68% of the wood volume variation.

Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

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Haoming Xia

2017-01-01

Full Text Available Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV and Landsat-8 Operational Land Imager (OLI data. A reference subpixel inundation percentage (SIP map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m. The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU, Artificial neural networks (ANN, and Regression tree (RT. Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R2 = 0.933, RMSE = 8.73% compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems.

An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

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Spruce, Joseph P.; Sader, Steve; Smoot, James

2012-01-01

This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades

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Jones, John W.; Hall, Annette E.; Foster, Ann M.; Smith, Thomas J.

2013-01-01

The ability to document the frequency, extent, and severity of fires in wetlands, as well as the dynamics of post-fire wetland land cover, informs fire and wetland science, resource management, and ecosystem protection. Available information on Everglades burn history has been based on field data collection methods that evolved through time and differ by land management unit. Our objectives were to (1) design and test broadly applicable and repeatable metrics of not only fire scar delineation but also post-fire land cover dynamics through exhaustive use of the Landsat satellite data archives, and then (2) explore how those metrics relate to various hydrologic and anthropogenic factors that may influence post-fire land cover dynamics. Visual interpretation of every Landsat scene collected over the study region during the study time frame produced a new, detailed database of burn scars greater than 1.6 ha in size in the Water Conservation Areas and post-fire land cover dynamics for Everglades National Park fires greater than 1.6 ha in area. Median burn areas were compared across several landscape units of the Greater Everglades and found to differ as a function of administrative unit and fire history. Some burned areas transitioned to open water, exhibiting water depths and dynamics that support transition mechanisms proposed in the literature. Classification tree techniques showed that time to green-up and return to pre-burn character were largely explained by fire management practices and hydrology. Broadly applicable as they use data from the global, nearly 30-year-old Landsat archive, these methods for documenting wetland burn extent and post-fire land cover change enable cost-effective collection of new data on wetland fire ecology and independent assessment of fire management practice effectiveness.

Human-induced geomorphology: Modeling slope failure in Dominical, Costa Rica using Landsat imagery

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Miller, Andrew J.

Unchecked human development has ravaged the region between Dominical and Uvita, Costa Rica. Much of the development transition has been driven by tourism and further foreign direct investment in residential, service and commercial enterprises. The resulting land-use/land-cover change has removed traditional forest cover in exchange for impervious surfaces, physical structures, and bare ground which is no longer mechanically supported by woody vegetation. Combined with a tropical climate, deeply weathered soils and lithography which are prone to erosion, land cover change has led to an increase in slope failure occurrences. Given the remoteness of the Dominical-Uvita region, its rate of growth and the lack of monitoring, new techniques for monitoring land use and slope failure susceptibility are needed. Two new indices are presented here that employ a Digital Elevation Model (DEM) and widely available Landsat imagery to assist in this endeavor. The first index, or Vegetation Influenced Landslide Index (VILI), incorporates slope derived from a DEM and Lu et al.'s (2007) Surface Cover Index to quantify vegetative cover as a means of mechanical stabilization in landslide prone areas. The second index, or Slope Multiplier Index (SMI), uses individual Landsat data bands and basic Landsat band ratios as environmental proxies to replicate soil, vegetative and hydrologic properties. Both models achieve accuracy over 70% and rival results from more complicated published literature. The accuracy of the indices was assessed with the creation of a landslide inventory developed from field observations occurring in December 2007 and November 2008. The creation of these indices represents an efficient and accurate way of determining landslide susceptibility zonation in data poor areas where environmental protection practitioners may be overextended, under-trained or both.

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

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Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

2017-01-01

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

Landsat Thematic Mapper monitoring of turbid inland water quality

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Lathrop, Richard G., Jr.

1992-01-01

This study reports on an investigation of water quality calibration algorithms under turbid inland water conditions using Landsat Thematic Mapper (TM) multispectral digital data. TM data and water quality observations (total suspended solids and Secchi disk depth) were obtained near-simultaneously and related using linear regression techniques. The relationships between reflectance and water quality for Green Bay and Lake Michigan were compared with results for Yellowstone and Jackson Lakes, Wyoming. Results show similarities in the water quality-reflectance relationships, however, the algorithms derived for Green Bay - Lake Michigan cannot be extrapolated to Yellowstone and Jackson Lake conditions.

Improved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF

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Yanli Zhang

2015-05-01

Full Text Available In rugged terrain, the accuracy of surface reflectance estimations is compromised by atmospheric and topographic effects. We propose a new method to simultaneously eliminate atmospheric and terrain effects in Landsat Thematic Mapper (TM images based on a 30 m digital elevation model (DEM and Moderate Resolution Imaging Spectroradiometer (MODIS atmospheric products. Moreover, we define a normalized factor of a Bidirectional Reflectance Distribution Function (BRDF to convert the sloping pixel reflectance into a flat pixel reflectance by using the Ross Thick-Li Sparse BRDF model (Ambrals algorithm and MODIS BRDF/albedo kernel coefficient products. Sole atmospheric correction and topographic normalization were performed for TM images in the upper stream of the Heihe River Basin. The results show that using MODIS atmospheric products can effectively remove atmospheric effects compared with the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH model and the Landsat Climate Data Record (CDR. Moreover, superior topographic effect removal can be achieved by considering the surface BRDF when compared with the surface Lambertian assumption of topographic normalization.

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

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Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide

An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers

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Quattrochi, D. A.

1984-01-01

An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.

A Generic Approach for Inversion of Surface Reflectance over Land: Overview, Application and Validation Using MODIS and LANDSAT8 Data

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Vermote, E.; Roger, J. C.; Justice, C. O.; Franch, B.; Claverie, M.

2016-01-01

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This technique builds on the extensive dataset acquired by the Terra platform by combining MODIS and MISR to derive an explicit and dynamic map of band ratio's between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. We will present the generic approach and the application to MODIS and LANDSAT data and its validation using the AERONET data.

MONITORING MANGROVE AREA IN BENOA BAY USING LANDSAT TM AND ETM + DATA

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Ni Luh Made Ari Sugianthi

2012-11-01

Full Text Available Mangrove ecosystems are crucial for the management of some coastal resources in Indonesia. Thisresearch used Landsat TM 1994, Landsat ETM+ 2002 with the purpose to know mangrove area change foreight years, mangrove density and accuracy of image as source of data to mangrove area in Benoa Bay. Fromimage analysis that using maximum likelihood method, the mangrove is classified into 3 classes i.e.:mangroves with high density, medium density and low density. For the ground check, used single plotmethod by using 6 trees.The extent of mangrove area in Benoa Bay were 447.69 ha in 1994 and 622.08 ha in 2002. Thechange of the extent of mangrove area during 8 years (1994 – 2002 increased by 174.41 ha. The area ofdensities in 1994, high density was 225.15 ha, medium density was 122.48 ha and low density was 130.05ha. In 2002, high density was 262.8 ha, medium density was 265.95 ha, and low density was 133.30 ha.Based on the regression analysis between mangrove density and the value of interpretation, the density ofmangrove in Benoa Bay which the criteria of high density is 364.723 – 466.311 tree/ha, medium density is237.738 - 364.723 tree/ha and low density is 186.944 – 237.738 tree/ha. The determination coefficient (r2was 0.6312. Based on the regression analysis in 2002 used in interpretation of mangrove density in 1994,which the criteria of high density is 357.10 tree/ha –316.47 tree/ha, medium density is 273.29 tree/ha –316.47 tree/ha and low density is 252.98 tree/ha –273.29 tree/ha.The accuracy of the Landsat ETM+ 2002 for mangrove area classification in Benoa Bay was 90%.These values were above the acceptable limit of accuracy stated of 80 %, so that this classification accuracywas acceptable.

A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI

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F. Chen

2018-05-01

Full Text Available A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2–3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance of the corresponding channels between two sensors. Spectral response function (SRF is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI and Landsat 8 Operational Land Imager (OLI. Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (< 5 %, including the Costal Aerosol channel, a NIR (855–875 nm channel, the SWIR channels, and the Cirrus channel. Meanwhile, for channels covering Blue, Green, Red, and NIR (785–900 nm, the between-sensor differences are significantly presented. Compared with the difference in reflectance of each individual channel, the difference in derived spectral index is more

Downscaling of Aircraft, Landsat, and MODIS-bases Land Surface Temperature Images with Support Vector Machines

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High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at s...

On formation of a partially coherent beam in a stable-resonator laser

International Nuclear Information System (INIS)

Suvorov, A A

2010-01-01

A new method involving the expansion of the field coherence function in partially coherent modes - the eigensolutions of the problem for the second-order coherence function in a stable resonator - is proposed for the theoretical description of the process of multimode laser beam formation. The method for solving the problem for arbitrary partially coherent modes is formulated and the expressions for these modes are derived in the general form. The characteristics of the fundamental partially coherent mode, which coincides with the coherence function of a Gaussian partially coherent beam, are analysed in detail. The partially coherent modes are shown to possess two spatial scales - the effective radius and the coherence radius, which makes them a convenient tool for solving the problem of generation of a partially coherent beam. It is found that the unambiguous relation between the characteristics of partially coherent modes and the stable-resonator parameters is achieved by involving into consideration not only the process of the beam formation by the resonator mirrors but also the process of interaction of radiation with the active laser medium. (laser beams and resonators)

Mixed-Poisson Point Process with Partially-Observed Covariates: Ecological Momentary Assessment of Smoking.

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