Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

NASA Technical Reports Server (NTRS)

Mcelroy, James L. (Editor); Mcneal, Robert J. (Editor)

1991-01-01

The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

Remote Sensing based modelling of Annual Surface Mass Balances of Chhota Shigiri Glacier, Western Himalayas, India

NASA Astrophysics Data System (ADS)

Chandrasekharan, Anita; Ramsankaran, Raaj

2017-04-01

The current study aims at modelling glacier mass balances over Chhota Shigiri glacier (32.28o N; 77.58° E) in Himachal Pradesh, India using the Equilibrium Line Altitude (ELA) gradient approach proposed by Rabatel et al. (2005). The model requires yearly ELA, average mass balance and mass balance gradient to estimate annual mass balance of a glacier which can be obtained either through field measurements or remote sensing observations. However, in view of the general scenario of lack of field data for Himalayan glaciers, in this study the model has been applied only using the inputs derived through multi-temporal satellite remote sensing observations thus eliminating the need for any field measurements. Preliminary analysis show that the obtained results are comparable with the observed field mass balance. The results also demonstrate that this approach with remote sensing inputs has potential to be used for glacier mass balance estimations provided good quality multi-temporal remote sensing dataset are available.

Remote sensing and the Mississippi high accuracy reference network

NASA Technical Reports Server (NTRS)

Mick, Mark; Alexander, Timothy M.; Woolley, Stan

1994-01-01

Since 1986, NASA's Commercial Remote Sensing Program (CRSP) at Stennis Space Center has supported commercial remote sensing partnerships with industry. CRSP's mission is to maximize U.S. market exploitation of remote sensing and related space-based technologies and to develop advanced technical solutions for spatial information requirements. Observation, geolocation, and communications technologies are converging and their integration is critical to realize the economic potential for spatial informational needs. Global positioning system (GPS) technology enables a virtual revolution in geopositionally accurate remote sensing of the earth. A majority of states are creating GPS-based reference networks, or high accuracy reference networks (HARN). A HARN can be defined for a variety of local applications and tied to aerial or satellite observations to provide an important contribution to geographic information systems (GIS). This paper details CRSP's experience in the design and implementation of a HARN in Mississippi and the design and support of future applications of integrated earth observations, geolocation, and communications technology.

Development of sea ice monitoring with aerial remote sensing technology

NASA Astrophysics Data System (ADS)

Jiang, Xuhui; Han, Lei; Dong, Liang; Cui, Lulu; Bie, Jun; Fan, Xuewei

2014-11-01

In the north China Sea district, sea ice disaster is very serious every winter, which brings a lot of adverse effects to shipping transportation, offshore oil exploitation, and coastal engineering. In recent years, along with the changing of global climate, the sea ice situation becomes too critical. The monitoring of sea ice is playing a very important role in keeping human life and properties in safety, and undertaking of marine scientific research. The methods to monitor sea ice mainly include: first, shore observation; second, icebreaker monitoring; third, satellite remote sensing; and then aerial remote sensing monitoring. The marine station staffs use relevant equipments to monitor the sea ice in the shore observation. The icebreaker monitoring means: the workers complete the test of the properties of sea ice, such as density, salinity and mechanical properties. MODIS data and NOAA data are processed to get sea ice charts in the satellite remote sensing means. Besides, artificial visual monitoring method and some airborne remote sensors are adopted in the aerial remote sensing to monitor sea ice. Aerial remote sensing is an important means in sea ice monitoring because of its strong maneuverability, wide watching scale, and high resolution. In this paper, several methods in the sea ice monitoring using aerial remote sensing technology are discussed.

Predicting and Mitigating Outbreaks of Vector-Borne Disease Utilizing Satellite Remote Sensing Technology and Models

NASA Technical Reports Server (NTRS)

Estes, Sue; Haynes, John; Kiang, Richard; Brown, Molly; Reisen, William

2008-01-01

Satellite earth observations present a unique vantage point of the earth's environment from space which offers a wealth of health applications for the imaginative investigator. The session will present research results of the remote sensing environmental observations of earth and health applications. This session will an overview of many of the NASA public health applications using Remote Sensing Data and will also discuss opportunities to become a research collaborator with NASA.

An Update of NASA Public Health Applications Projects using Remote Sensing Data

NASA Technical Reports Server (NTRS)

Estes, Sue M.; Haynes, J. A.

2009-01-01

Satellite earth observations present a unique vantage point of the earth s environment from space which offers a wealth of health applications for the imaginative investigator. The session will present research results of the remote sensing environmental observations of earth and health applications. This session will an overview of many of the NASA public health applications using Remote Sensing Data and will also discuss opportunities to become a research collaborator with NASA.

China national space remote sensing infrastructure and its application

NASA Astrophysics Data System (ADS)

Li, Ming

2016-07-01

Space Infrastructure is a space system that provides communication, navigation and remote sensing service for broad users. China National Space Remote Sensing Infrastructure includes remote sensing satellites, ground system and related systems. According to the principle of multiple-function on one satellite, multiple satellites in one constellation and collaboration between constellations, series of land observation, ocean observation and atmosphere observation satellites have been suggested to have high, middle and low resolution and fly on different orbits and with different means of payloads to achieve a high ability for global synthetically observation. With such an infrastructure, we can carry out the research on climate change, geophysics global surveying and mapping, water resources management, safety and emergency management, and so on. I This paper gives a detailed introduction about the planning of this infrastructure and its application in different area, especially the international cooperation potential in the so called One Belt and One Road space information corridor.

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

Treesearch

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

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...

Feasibility study ASCS remote sensing/compliance determination system

NASA Technical Reports Server (NTRS)

Duggan, I. E.; Minter, T. C., Jr.; Moore, B. H.; Nosworthy, C. T.

1973-01-01

A short-term technical study was performed by the MSC Earth Observations Division to determine the feasibility of the proposed Agricultural Stabilization and Conservation Service Automatic Remote Sensing/Compliance Determination System. For the study, the term automatic was interpreted as applying to an automated remote-sensing system that includes data acquisition, processing, and management.

The application analysis of the multi-angle polarization technique for ocean color remote sensing

NASA Astrophysics Data System (ADS)

Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Keli

2017-02-01

The multi-angle polarization technique, which uses the intensity of polarized radiation as the observed quantity, is a new remote sensing means for earth observation. With this method, not only can the multi-angle light intensity data be provided, but also the multi-angle information of polarized radiation can be obtained. So, the technique may solve the problems, those could not be solved with the traditional remote sensing methods. Nowadays, the multi-angle polarization technique has become one of the hot topics in the field of the international quantitative research on remote sensing. In this paper, we firstly introduce the principles of the multi-angle polarization technique, then the situations of basic research and engineering applications are particularly summarized and analysed in 1) the peeled-off method of sun glitter based on polarization, 2) the ocean color remote sensing based on polarization, 3) oil spill detection using polarization technique, 4) the ocean aerosol monitoring based on polarization. Finally, based on the previous work, we briefly present the problems and prospects of the multi-angle polarization technique used in China's ocean color remote sensing.

A review of the remote sensing of lower tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles: REMOTE SENSING OF THERMODYNAMIC PROFILES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wulfmeyer, Volker; Hardesty, R. Michael; Turner, David D.

A review of remote sensing technology for lower tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer—usually characterized by an inversion—and the lowermore » troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global navigation satellite system, as well as water vapor and temperature Raman lidar and water vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.« less

[A review on polarization information in the remote sensing detection].

PubMed

Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

2010-04-01

Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

NASA Astrophysics Data System (ADS)

Dong, Chunyu

2018-06-01

Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

NASA Technical Reports Server (NTRS)

Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

2010-01-01

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

Remote sensor response study in the regime of the microwave radiation-induced magnetoresistance oscillations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ye, Tianyu; Mani, R. G.; Wegscheider, W.

2013-11-04

A concurrent remote sensing and magneto-transport study of the microwave excited two dimensional electron system (2DES) at liquid helium temperatures has been carried out using a carbon detector to remotely sense the microwave activity of the 2D electron system in the GaAs/AlGaAs heterostructure during conventional magneto-transport measurements. Various correlations are observed and reported between the oscillatory magnetotransport and the remotely sensed reflection. In addition, the oscillatory remotely sensed signal is shown to exhibit a power law type variation in its amplitude, similar to the radiation-induced magnetoresistance oscillations.

A new multi-angle remote sensing framework for scaling vegetation properties from tower-based spectro-radiometers to next generation "CubeSat"-satellites.

NASA Astrophysics Data System (ADS)

Hilker, T.; Hall, F. G.; Dyrud, L. P.; Slagowski, S.

2014-12-01

Frequent earth observations are essential for assessing the risks involved with global climate change, its feedbacks on carbon, energy and water cycling and consequences for live on earth. Often, satellite-remote sensing is the only practical way to provide such observations at comprehensive spatial scales, but relationships between land surface parameters and remotely sensed observations are mostly empirical and cannot easily be scaled across larger areas or over longer time intervals. For instance, optically based methods frequently depend on extraneous effects that are unrelated to the surface property of interest, including the sun-server geometry or background reflectance. As an alternative to traditional, mono-angle techniques, multi-angle remote sensing can help overcome some of these limitations by allowing vegetation properties to be derived from comprehensive reflectance models that describe changes in surface parameters based on physical principles and radiative transfer theory. Recent results have shown in theoretical and experimental research that multi-angle techniques can be used to infer and scale the photosynthetic rate of vegetation, its biochemical and structural composition robustly from remote sensing. Multi-angle remote sensing could therefore revolutionize estimates of the terrestrial carbon uptake as scaling of primary productivity may provide a quantum leap in understanding the spatial and temporal complexity of terrestrial earth science. Here, we introduce a framework of next generation tower-based instruments to a novel and unique constellation of nano-satellites (Figure 1) that will allow us to systematically scale vegetation parameters from stand to global levels. We provide technical insights, scientific rationale and present results. We conclude that future earth observation from multi-angle satellite constellations, supported by tower based remote sensing will open new opportunities for earth system science and earth system modeling.

Earth observations from space: Outlook for the geological sciences

NASA Technical Reports Server (NTRS)

Short, N. M.; Lowman, P. D., Jr.

1973-01-01

Remote sensing from space platforms is discussed as another tool available to geologists. The results of Nimbus observations, the ERTS program, and Skylab EREP are reviewed, and a multidisciplinary approach is recommended for meeting the challenges of remote sensing.

Observations of the global structure of the stratosphere and mesosphere with sounding rockets and with remote sensing techniques from satellites

NASA Technical Reports Server (NTRS)

Heath, D. F.; Hilsenrath, E.; Krueger, A. J.; Nordberg, W.; Prabhakara, C.; Theon, J. S.

1972-01-01

Brief descriptions are given of the techniques involved in determining the global structure of the mesosphere and stratosphere based on sounding rocket observations and satellite remotely sensed measurements.

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

Satellite Remote Sensing of Aerosol Forcing

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Kaufman, Yoram; Ramaprasad, Jaya; Procopio, Aline; Levin, Zev

1999-01-01

Aerosol and cloud impacts on the earth's climate become a recent hot topic in climate studies. Having near future earth observing satellites, EOS-AM1 (Earth Observing System-AM1), ENVISAT (Environmental Satellites) and ADEOS-2 (Advanced Earth Observation Satellite-2), it will be a good timing to discuss how to obtain and use the microphysical parameters of aerosols and clouds for studying their climate impacts. Center for Climate System Research (CCSR) of the University of Tokyo invites you to 'Symposium on synergy between satellite-remote sensing and climate modeling in aerosol and cloud issues.' Here, we like to discuss the current and future issues in the remote sensing of aerosol and cloud microphysical parameters and their climate modeling studies. This workshop is also one of workshop series on aerosol remote sensing held in 1996, Washington D. C., and Meribel, France in 1999. It should be reminded that NASDA/ADEOS-1 & -2 (National Space Development Agency of Japan/Advanced Earth Observation Satellite-1 & -2) Workshop will be held in the following week (Dec. 6-10, 1999), so that this opportunity will be a perfect period for you to attend two meetings for satellite remote sensing in Japan. A weekend in Kyoto, the old capital of Japan, will add a nice memory to your visiting Japan. *Issues in the symposium: 1) most recent topics in aerosol and cloud remot sensing, and 2) utility of satellite products on climate modeling of cloud-aerosol effects.

Polarization Remote Sensing Physical Mechanism, Key Methods and Application

NASA Astrophysics Data System (ADS)

Yang, B.; Wu, T.; Chen, W.; Li, Y.; Knjazihhin, J.; Asundi, A.; Yan, L.

2017-09-01

China's long-term planning major projects "high-resolution earth observation system" has been invested nearly 100 billion and the satellites will reach 100 to 2020. As to 2/3 of China's area covered by mountains it has a higher demand for remote sensing. In addition to light intensity, frequency, phase, polarization is also the main physical characteristics of remote sensing electromagnetic waves. Polarization is an important component of the reflected information from the surface and the atmospheric information, and the polarization effect of the ground object reflection is the basis of the observation of polarization remote sensing. Therefore, the effect of eliminating the polarization effect is very important for remote sensing applications. The main innovations of this paper is as follows: (1) Remote sensing observation method. It is theoretically deduced and verified that the polarization can weaken the light in the strong light region, and then provide the polarization effective information. In turn, the polarization in the low light region can strengthen the weak light, the same can be obtained polarization effective information. (2) Polarization effect of vegetation. By analyzing the structure characteristics of vegetation, polarization information is obtained, then the vegetation structure information directly affects the absorption of biochemical components of leaves. (3) Atmospheric polarization neutral point observation method. It is proved to be effective to achieve the ground-gas separation, which can achieve the effect of eliminating the atmospheric polarization effect and enhancing the polarization effect of the object.

Remote Sensing Information Sciences Research Group, Santa Barbara Information Sciences Research Group, year 3

NASA Technical Reports Server (NTRS)

Estes, J. E.; Smith, T.; Star, J. L.

1986-01-01

Research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. The focus is on remote sensing and application for the Earth Observing System (Eos) and Space Station, including associated polar and co-orbiting platforms. The remote sensing research activities are being expanded, integrated, and extended into the areas of global science, georeferenced information systems, machine assissted information extraction from image data, and artificial intelligence. The accomplishments in these areas are examined.

Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment

USDA-ARS?s Scientific Manuscript database

We develop a robust understanding of the effects of assimilating remote sensing observations of leaf area index and soil moisture (in the top 5 cm) on DSSAT-CSM CropSim-Ceres wheat yield estimates. Synthetic observing system simulation experiments compare the abilities of the Ensemble Kalman Filter...

Commercial potential of remote sensing data from the Earth observing system

NASA Technical Reports Server (NTRS)

Merry, Carolyn J.; Tomlin, Sandra M.

1992-01-01

The purpose was to assess the market potential of remote sensing value-added products from the Earth Observing System (EOS) platform. Sensors on the EOS platform were evaluated to determine which qualities and capabilities could be useful to the commercial user. The approach was to investigate past and future satellite data distribution programs. A questionnaire was developed for use in a telephone survey. Based on the results of the survey of companies that add value to remotely sensed data, conversations with the principal investigators in charge of each EOS sensor, a study of past commercial satellite data ventures, and reading from the commercial remote sensing industry literature, three recommendations were developed: develop a strategic plan for commercialization of EOS data, define a procedure for commercial users within the EOS data stream, and develop an Earth Observations Commercial Applications Program-like demonstration program within NASA using EOS simulated data.

Review of Remote Sensing Needs and Applications in Africa

NASA Technical Reports Server (NTRS)

Brown, Molly E.

2007-01-01

Remote sensing data has had an important role in identifying and responding to inter-annual variations in the African environment during the past three decades. As a largely agricultural region with diverse but generally limited government capacity to acquire and distribute ground observations of rainfall, temperature and other parameters, remote sensing is sometimes the only reliable measure of crop growing conditions in Africa. Thus, developing and maintaining the technical and scientific capacity to analyze and utilize satellite remote sensing data in Africa is critical to augmenting the continent's local weather/climate observation networks as well as its agricultural and natural resource development and management. The report Review of Remote Sensing Needs and Applications in Africa' has as its central goal to recommend to the US Agency for International Development an appropriate approach to support sustainable remote sensing applications at African regional remote sensing centers. The report focuses on "RS applications" to refer to the acquisition, maintenance and archiving, dissemination, distribution, analysis, and interpretation of remote sensing data, as well as the integration of interpreted data with other spatial data products. The report focuses on three primary remote sensing centers: (1) The AGRHYMET Regional Center in Niamey, Niger, created in 1974, is a specialized institute of the Permanent Interstate Committee for Drought Control in the Sahel (CILSS), with particular specialization in science and techniques applied to agricultural development, rural development, and natural resource management. (2) The Regional Centre for Maiming of Resources for Development (RCMRD) in Nairobi, Kenya, established in 1975 under the auspices of the United Nations Economic Commission for Africa and the Organization of African Unity (now the African Union), is an intergovernmental organization, with 15 member states from eastern and southern Africa. (3) The Regional Remote Sensing Unit (RRSU) in Gaborone, Botswana, began work in June 1988 and operates under the Agriculture Information Management System (AIMS), as part of the Food, Agriculture and Natural Resources (FANR) Directorate, based at the Southern Africa Development Community (SADC) Secretariat.

The Earth Resources Observation Systems data center's training technical assistance, and applications research activities

USGS Publications Warehouse

Sturdevant, J.A.

1981-01-01

The Earth Resources Observation Systems (EROS) Data Center (EDO, administered by the U.S. Geological Survey, U.S. Department of the Interior, provides remotely sensed data to the user community and offers a variety of professional services to further the understanding and use of remote sensing technology. EDC reproduces and sells photographic and electronic copies of satellite images of areas throughout the world. Other products include aerial photographs collected by 16 organizations, including the U.S. Geological Survey and the National Aeronautics and Space Administration. Primary users of the remotely sensed data are Federal, State, and municipal government agencies, universities, foreign nations, and private industries. The professional services available at EDC are primarily directed at integrating satellite and aircraft remote sensing technology into the programs of the Department of the Interior and its cooperators. This is accomplished through formal training workshops, user assistance, cooperative demonstration projects, and access to equipment and capabilities in an advanced data analysis laboratory. In addition, other Federal agencies, State and local governments, universities, and the general public can get assistance from the EDC Staff. Since 1973, EDC has contributed to the accelerating growth in development and operational use of remotely sensed data for land resource problems through its role as educator and by conducting basic and applied remote sensing applications research. As remote sensing technology continues to evolve, EDC will continue to respond to the increasing demand for timely information on remote sensing applications. Questions most often asked about EDC's research and training programs include: Who may attend an EDC remote sensing training course? Specifically, what is taught? Who may cooperate with EDC on remote sensing projects? Are interpretation services provided on a service basis? This report attempts to define the goals and objectives of and policies on the following EDC services: Training Program.User Assistance.Data Analysis Laboratory.Cooperative Demonstration Projects.Research Projects.

Imputing forest structure attributes from stand inventory and remotely sensed data in western Oregon, USA

Treesearch

Andrew T. Hudak; A. Tod Haren; Nicholas L. Crookston; Robert J. Liebermann; Janet L. Ohmann

2014-01-01

Imputation is commonly used to assign reference stand observations to target stands based on covariate relationships to remotely sensed data to assign inventory attributes across the entire landscape. However, most remotely sensed data are collected at higher resolution than the stand inventory data often used by operational foresters. Our primary goal was to compare...

Post-classification approaches to estimating change in forest area using remotely sense auxiliary data.

Treesearch

Ronald E. McRoberts

2014-01-01

Multiple remote sensing-based approaches to estimating gross afforestation, gross deforestation, and net deforestation are possible. However, many of these approaches have severe data requirements in the form of long time series of remotely sensed data and/or large numbers of observations of land cover change to train classifiers and assess the accuracy of...

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

Polarimetric Remote Sensing of Atmospheric Particulate Pollutants

NASA Astrophysics Data System (ADS)

Li, Z.; Zhang, Y.; Hong, J.

2018-04-01

Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF), whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

Remote sensing and human health: new sensors and new opportunities.

PubMed

Beck, L R; Lobitz, B M; Wood, B L

2000-01-01

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Système Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Remote sensing and human health: new sensors and new opportunities

NASA Technical Reports Server (NTRS)

Beck, L. R.; Lobitz, B. M.; Wood, B. L.

2000-01-01

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Systeme Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Empirical validation and proof of added value of MUSICA's tropospheric δD remote sensing products

NASA Astrophysics Data System (ADS)

Schneider, M.; González, Y.; Dyroff, C.; Christner, E.; Wiegele, A.; Barthlott, S.; García, O. E.; Sepúlveda, E.; Hase, F.; Andrey, J.; Blumenstock, T.; Guirado, C.; Ramos, R.; Rodríguez, S.

2015-01-01

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isotopologue remote sensing and in situ observations. This paper presents a first empirical validation of MUSICA's H2O and δD remote sensing products, generated from ground-based FTIR (Fourier transform infrared), spectrometer and space-based IASI (infrared atmospheric sounding interferometer) observation. The study is made in the area of the Canary Islands in the subtropical northern Atlantic. As reference we use well calibrated in situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues, and the scatter with respect to the in situ references suggests a δD random uncertainty for the FTIR product of much better than 45‰ in the lower troposphere and of about 15‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15‰. In both remote sensing data sets we find a positive δD bias of 30-70‰. Complementing H2O observations with δD data allows moisture transport studies that are not possible with H2O observations alone. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data. We document that the δD-H2O curves obtained from the different in situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.

Coastal High-resolution Observations and Remote Sensing of Ecosystems (C-HORSE)

NASA Technical Reports Server (NTRS)

Guild, Liane

2016-01-01

Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.

PREFACE: 35th International Symposium on Remote Sensing of Environment (ISRSE35)

NASA Astrophysics Data System (ADS)

2014-03-01

35th International Symposium on Remote Sensing of Environment (ISRSE35) 22-26 April, 2013, Beijing, China The 35th International Symposium on Remote Sensing of Environment (ISRSE35) was successfully convened in Beijing, China, from April 22nd to 26th, 2013. This was the first event in the ISRSE series being held in China. The symposium was hosted by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, and co-organized by the International Center for Remote Sensing of Environment (ICRSE), the International Society for Photogrammetry and Remote Sensing (ISPRS), the Group on Earth Observations (GEO), the International Society for Digital Earth (ISDE) and the Chinese Academy of Sciences (CAS). The theme of the symposium was ''Earth Observation and Global Environmental Change''. Back in 1962, the first ISRSE was convened at the University of Michigan, USA. Over the past 50 years, Earth observation has advanced significantly, and remote sensing has become a mature technology for observing the Earth and monitoring global environmental change. At present, remote sensing has already entered an era of integrated, coordinated and sustainable global Earth observation and rapid development of spatial information services. It is very exciting to see that remote sensing technologies have become indispensable tools in numerous fields of Earth systems science, and are playing more and more important roles in areas such as land resources surveying and mapping, crop and forest monitoring, mineral exploration, urban development, ocean and coastlines resources surveillance, and in the monitoring and assessment of floods, droughts, forest fires, landslides and earthquakes. Thus, remote sensing has made great contributions to the socio-economic development of the world and it is anticipated that it will provide more powerful support in advancing the fields of Earth systems science and global change research. The 35th ISRSE was a platform for scientists and young scholars to exchange their research results from the cutting-edge frontiers of spatial information sciences, to review the history of remote sensing development and to consider the prospects for the future development of geospatial information. Therefore, this symposium was dedicated to marking the 50th anniversary of remote sensing especially focused on earth observation and global environmental change. The 35th ISRSE attracted over a thousand scientists and researchers from 56 countries and regions. The Technical Program Committee selected 346 oral presentations and 376 poster presentations, out of 1249 submitted abstracts. In order that the papers from this symposium could be published on a well-recognized platform, the organizers decided to produce refereed papers in IOP EES and invited all presenters to contribute to these proceedings. Each submitted paper was refereed by two anonymous reviewers, following the guidelines of the IOP's Peer Review Policy. The final collection of 279 papers covers a broad range of topics under 14 headings, which not only reflects the diversity of the presentations prompted by the current research hotspots related to remote sensing of the environment, but also witnesses to the increasingly mature development of the discipline. We would like to take this opportunity of the publication of the ISRSE35 Proceedings to express our gratitude to all the participants, especially those who contributed with presentations and manuscripts, for making ISRSE35 such a successful conference. Our thanks also go to our colleagues for their support and encouragement, particularly to the reviewers who worked very hard in reviewing the papers and provided thoughtful comments on the manuscripts. Finally, we sincerely hope that 35th ISRSE will prove to be a significant step forward in Earth observation technologies as applied to addressing the persistent challenges related to global sustainable development. Thank you for your interest and please enjoy the Proceedings. Editor-in-Chief: GUO Huadong Executive Editors: WANG Changlin, JING Linhai, WANG Lizhe, and CHEN Fang Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences The organizing structure of the 35th International Symposium on Remote Sensing of Environment can be found in the PDF.

Remote Sensing of Drought: Progress and Opportunities for Improving Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Huning, L. S.; Love, C. A.; Farahmand, A.

2017-12-01

This presentation surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. Satellite observations that are not currently used for operational drought monitoring, such as near-surface air relative humidity and water vapor, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. This presentation describes how different satellite observations can be combined for overall drought development and impact assessment. Finally, we provide an overview of the research gaps and challenges that are facing us ahead in the remote sensing of drought.

Earth Observations from the International Space Station: Benefits for Humanity

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2015-01-01

The International Space Station (ISS) is a unique terrestrial remote sensing platform for observation of the Earth's land surface, oceans, and atmosphere. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted active and passive remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous, sun-synchronous sensor systems in higher altitude polar orbits. Beginning in May 2012, NASA ISS sensor systems have been available to respond to requests for data through the International Charter, Space and Major Disasters, also known as the "International Disaster Charter" or IDC. Data from digital handheld cameras, multispectral, and hyperspectral imaging systems has been acquired in response to IDC activations and delivered to requesting agencies through the United States Geological Survey. The characteristics of the ISS for Earth observation will be presented, including past, current, and planned NASA, International Partner, and commercial remote sensing systems. The role and capabilities of the ISS for humanitarian benefit, specifically collection of remotely sensed disaster response data, will be discussed.

Up Close from Afar: Using Remote Sensing To Teach the American Landscape. Pathways in Geography Series, Title No. 8.

ERIC Educational Resources Information Center

Baumann, Paul R., Ed.

This teaching guide offers educators glimpses into the value of remote sensing, the process of observing and analyzing the earth from a distance. Remote sensing provides information in forms to see spatial patterns over large areas in a more realistic way than thematic maps and allows a macro-scale look at global problems. The six instructional…

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Exploring Remote Rensing Through The Use Of Readily-Available Classroom Technologies

NASA Astrophysics Data System (ADS)

Rogers, M. A.

2013-12-01

Frontier geoscience research using remotely-sensed satellite observation routinely requires sophisticated and novel remote sensing techniques to succeed. Describing these techniques in an educational format presents significant challenges to the science educator, especially with regards to the professional development setting where a small, but competent audience has limited instructor contact time to develop the necessary understanding. In this presentation, we describe the use of simple and cheaply available technologies, including ultrasonic transducers, FLIR detectors, and even simple web cameras to provide a tangible analogue to sophisticated remote sensing platforms. We also describe methods of curriculum development that leverages the use of these simple devices to teach the fundamentals of remote sensing, resulting in a deeper and more intuitive understanding of the techniques used in modern remote sensing research. Sample workshop itineraries using these techniques are provided as well.

Predicting Near-Term Water Quality from Satellite Observations of Watershed Conditions

NASA Astrophysics Data System (ADS)

Weiss, W. J.; Wang, L.; Hoffman, K.; West, D.; Mehta, A. V.; Lee, C.

2017-12-01

Despite the strong influence of watershed conditions on source water quality, most water utilities and water resource agencies do not currently have the capability to monitor watershed sources of contamination with great temporal or spatial detail. Typically, knowledge of source water quality is limited to periodic grab sampling; automated monitoring of a limited number of parameters at a few select locations; and/or monitoring relevant constituents at a treatment plant intake. While important, such observations are not sufficient to inform proactive watershed or source water management at a monthly or seasonal scale. Satellite remote sensing data on the other hand can provide a snapshot of an entire watershed at regular, sub-monthly intervals, helping analysts characterize watershed conditions and identify trends that could signal changes in source water quality. Accordingly, the authors are investigating correlations between satellite remote sensing observations of watersheds and source water quality, at a variety of spatial and temporal scales and lags. While correlations between remote sensing observations and direct in situ measurements of water quality have been well described in the literature, there are few studies that link remote sensing observations across a watershed with near-term predictions of water quality. In this presentation, the authors will describe results of statistical analyses and discuss how these results are being used to inform development of a desktop decision support tool to support predictive application of remote sensing data. Predictor variables under evaluation include parameters that describe vegetative conditions; parameters that describe climate/weather conditions; and non-remote sensing, in situ measurements. Water quality parameters under investigation include nitrogen, phosphorus, organic carbon, chlorophyll-a, and turbidity.

The NASA CYGNSS mission: a pathfinder for GNSS scatterometry remote sensing applications

NASA Astrophysics Data System (ADS)

Rose, Randy; Gleason, Scott; Ruf, Chris

2014-10-01

Global Navigation Satellite System (GNSS) based scatterometry offers breakthrough opportunities for wave, wind, ice, and soil moisture remote sensing. Recent developments in electronics and nano-satellite technologies combined with modeling techniques developed over the past 20 years are enabling a new class of remote sensing capabilities that present more cost effective solutions to existing problems while opening new applications of Earth remote sensing. Key information about the ocean and global climate is hidden from existing space borne observatories because of the frequency band in which they operate. Using GNSS-based bi-static scatterometry performed by a constellation of microsatellites offers remote sensing of ocean wave, wind, and ice data with unprecedented temporal resolution and spatial coverage across the full dynamic range of ocean wind speeds in all precipitating conditions. The NASA Cyclone Global Navigation Satellite System (CYGNSS) is a space borne mission being developed to study tropical cyclone inner core processes. CYGNSS consists of 8 GPS bi-static radar receivers to be deployed on separate micro-satellites in October 2016. CYGNSS will provide data to address what are thought to be the principle deficiencies with current tropical cyclone intensity forecasts: inadequate observations and modeling of the inner core. The inadequacy in observations results from two causes: 1) Much of the inner core ocean surface is obscured from conventional remote sensing instruments by intense precipitation in the eye wall and inner rain bands. 2) The rapidly evolving (genesis and intensification) stages of the tropical cyclone life cycle are poorly sampled in time by conventional polar-orbiting, wide-swath surface wind imagers. It is anticipated that numerous additional Earth science applications can also benefit from the cost effective high spatial and temporal sampling capabilities of GNSS remote sensing. These applications include monitoring of rough and dangerous sea states, global observations of sea ice cover and extent, meso-scale ocean circulation studies, and near surface soil moisture observations. This presentation provides a primer for GNSS based scatterometry, an overview of NASA's CYGNSS mission and its expected performance, as well as a summary of possible other GNSS based remote sensing applications.

A review of the remote sensing of lower-tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles

DOE PAGES

Wulfmeyer, Volker; Hardesty, Mike; Turner, David D.; ...

2015-07-08

A review of remote sensing technology for lower-tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land-surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer – usually characterized by an inversion – andmore » the lower troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global positioning system as well as water-vapor and temperature Raman lidar and water-vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.« less

A review of the remote sensing of lower-tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wulfmeyer, Volker; Hardesty, Mike; Turner, David D.

A review of remote sensing technology for lower-tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land-surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer – usually characterized by an inversion – andmore » the lower troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global positioning system as well as water-vapor and temperature Raman lidar and water-vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.« less

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

A star-pointing UV-visible spectrometer for remote-sensing of the stratosphere

NASA Technical Reports Server (NTRS)

Roscoe, Howard K.; Freshwater, Ray A.; Jones, Rod L.; Fish, Debbie J.; Harries, John E.; Wolfenden, Roger; Stone, Phillip

1994-01-01

We have constructed a novel instrument for ground-based remote sensing, by mounting a UV-visible spectrometer on a telescope and observing the absorption by atmospheric constituents of light from stars. Potentially, the instrument can observe stratospheric O3, NO3, NO2, and OClO.

Remote sensing of multimodal transportation systems.

DOT National Transportation Integrated Search

2016-09-01

Hyperspectral remote sensing is an emerging field with many potential applications in the observation, management, and maintenance of the global transportation infrastructure. This report describes the development of an affordable framework to captur...

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Oneill, P. E.

1986-01-01

Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.

Naval EarthMap Observer (NEMO) Hyperspectral Remote Sensing Program

DTIC Science & Technology

2000-10-01

The NEMO hyperspectral remote sensing program will provide unclassified, space-based hyperspectral passive imagery at moderate resolution that offers substantial potential for direct use by Naval forces and the Civil Sector.

A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective

NASA Astrophysics Data System (ADS)

Shafique, Muhammad; van der Meijde, Mark; Khan, M. Asif

2016-03-01

The 8th October 2005 Kashmir earthquake, in northern Pakistan has triggered thousands of landslides, which was the second major factor in the destruction of the build-up environment, after earthquake-induced ground shaking. Subsequent to the earthquake, several researchers from home and abroad applied a variety of remote sensing techniques, supported with field observations, to develop inventories of the earthquake-triggered landslides, analyzed their spatial distribution and subsequently developed landslide-susceptibility maps. Earthquake causative fault rupture, geology, anthropogenic activities and remote sensing derived topographic attributes were observed to have major influence on the spatial distribution of landslides. These were subsequently used to develop a landslide susceptibility map, thereby demarcating the areas prone to landsliding. Temporal studies monitoring the earthquake-induced landslides shows that the earthquake-induced landslides are stabilized, contrary to earlier belief, directly after the earthquake. The biggest landslide induced dam, as a result of the massive Hattian Bala landslide, is still posing a threat to the surrounding communities. It is observed that remote sensing data is effectively and efficiently used to assess the landslides triggered by the Kashmir earthquake, however, there is still a need of more research to understand the mechanism of intensity and distribution of landslides; and their continuous monitoring using remote sensing data at a regional scale. This paper, provides an overview of remote sensing and GIS applications, for the Kashmir-earthquake triggered landslides, derived outputs and discusses the lessons learnt, advantages, limitations and recommendations for future research.

Remote Sensing Information Sciences Research Group, year four

NASA Technical Reports Server (NTRS)

Estes, John E.; Smith, Terence; Star, Jeffrey L.

1987-01-01

The needs of the remote sensing research and application community which will be served by the Earth Observing System (EOS) and space station, including associated polar and co-orbiting platforms are examined. Research conducted was used to extend and expand existing remote sensing research activities in the areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence, and vegetation analysis and modeling. Projects are discussed in detail.

Active and Passive Remote Sensing of Ice

DTIC Science & Technology

1991-11-15

To demonstrate the use of polarimetry in passive remote sensing of azimuthally asymmetric features on a terrain surface, an experiment was designed...azimuthal asymmetry on the remotely sensed soil surface. It is also observed from the experiment that the brightness temperatures for all three Stokes...significant implication of this experiment is that the surface asymmetry can be detected with a measurement of U at a single azimuthal angle. -8

The EROS Data Center

USGS Publications Warehouse

,

1977-01-01

The Earth Resources Observation Systems (EROS) Program of the U.S. Department of the Interior, administered by the Geological Survey, was established in 1966 to apply remote-sensing techniques to the inventory, monitoring, and management of natural resources. To meet its primary objective, the EROS Program includes research and training in the interpretation and application of remotely sensed data and provides remotely sensed data at nominal cost to scientists, resource planners, managers, and the public.

The EROS Data Center

USGS Publications Warehouse

,

1981-01-01

The Earth Resources Observation Systems (EROS) Program of the U.S. Department of the Interior, administered by the Geological Survey, was established in 1966 to apply remote-sensing techniques to the inventory, monitoring, and management of natural resources. To meet its primary objective, the EROS Program includes research and training in the interpretation and application of remotely sensed data and provides remotely sensed data at nominal cost to scientists, resource planners, managers, and the public.

The International Space Station: A Unique Platform For Terrestrial Remote Sensing

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Evans, Cynthia A.

2012-01-01

The International Space Station (ISS) became operational in November of 2000, and until recently remote sensing activities and operations have focused on handheld astronaut photography of the Earth. This effort builds from earlier NASA and Russian space programs (e.g. Evans et al. 2000; Glazovskiy and Dessinov 2000). To date, astronauts have taken more than 600,000 images of the Earth s land surface, oceans, and atmospheric phenomena from orbit using film and digital cameras as part two payloads: NASA s Crew Earth Observations experiment (http://eol.jsc.nasa.gov/) and Russia s Uragan experiment (Stefanov et al. 2012). Many of these images have unique attributes - varying look angles, ground resolutions, and illumination - that are not available from other remote sensing platforms. Despite this large volume of imagery and clear capability for Earth remote sensing, the ISS historically has not been perceived as an Earth observations platform by many remote sensing scientists. With the recent installation of new facilities and sophisticated sensor systems, and additional systems manifested and in development, that perception is changing to take advantage of the unique capabilities and viewing opportunities offered by the ISS.

Tracking diurnal changes of photosynthesis and evapotranspiration using fluorescence, gas exchange and hyperspectral remote sensing measurements

NASA Astrophysics Data System (ADS)

Wang, S.; Zhang, L.; Guanter, L.; Huang, C.

2017-12-01

Photosynthesis and evapotranspiration (ET) are the two most important activities of vegetation and make a great contribution to carbon, water and energy exchanges. Remote sensing provides opportunities for monitoring these processes across time and space. This study focuses on tracking diurnal changes of photosynthesis and evapotranspiration over soybean using multiple measurement techniques. Diurnal changes of both remote sensing-based indicators, including active and passive chlorophyll fluorescence and biophysical-related parameters, including photosynthesis rate (photo) and leaf stomatal conductance (cond), were observed. Results showed that both leaf-level steady-state fluorescence (Fs) and canopy-level solar-induced chlorophyll fluorescence were linearly correlated to photosynthetically active radiation (PAR) during the daytime. A double-peak diurnal change curve was observed for leaf-level photo and cond but not for Fs or SIF. Photo and cond showed a strong nonlinear (second-order) correlation, indicating that photosynthesis, which might be remotely sensed by SIF, has the opportunity to track short-term changes of ET. Results presented in this report will be helpful for better understanding the relationship between remote-sensing-based indices and vegetation's biophysical processes.

Needs Assessment for the Use of NASA Remote Sensing Data in the Development and Implementation of Estuarine and Coastal Water Quality Standards

NASA Technical Reports Server (NTRS)

Spiering, Bruce; Underwood, Lauren; Ellis, Chris; Lehrter, John; Hagy, Jim; Schaeffer, Blake

2010-01-01

The goals of the project are to provide information from satellite remote sensing to support numeric nutrient criteria development and to determine data processing methods and data quality requirements to support nutrient criteria development and implementation. The approach is to identify water quality indicators that are used by decision makers to assess water quality and that are related to optical properties of the water; to develop remotely sensed data products based on algorithms relating remote sensing imagery to field-based observations of indicator values; to develop methods to assess estuarine water quality, including trends, spatial and temporal variability, and seasonality; and to develop tools to assist in the development and implementation of estuarine and coastal nutrient criteria. Additional slides present process, criteria development, typical data sources and analyses for criteria process, the power of remote sensing data for the process, examples from Pensacola Bay, spatial and temporal variability, pixel matchups, remote sensing validation, remote sensing in coastal waters, requirements for remotely sensed data products, and needs assessment. An additional presentation examines group engagement and information collection. Topics include needs assessment purpose and objectives, understanding water quality decision making, determining information requirements, and next steps.

A new simple concept for ocean colour remote sensing using parallel polarisation radiance

PubMed Central

He, Xianqiang; Pan, Delu; Bai, Yan; Wang, Difeng; Hao, Zengzhou

2014-01-01

Ocean colour remote sensing has supported research on subjects ranging from marine ecosystems to climate change for almost 35 years. However, as the framework for ocean colour remote sensing is based on the radiation intensity at the top-of-atmosphere (TOA), the polarisation of the radiation, which contains additional information on atmospheric and water optical properties, has largely been neglected. In this study, we propose a new simple concept to ocean colour remote sensing that uses parallel polarisation radiance (PPR) instead of the traditional radiation intensity. We use vector radiative transfer simulation and polarimetric satellite sensing data to demonstrate that using PPR has two significant advantages in that it effectively diminishes the sun glint contamination and enhances the ocean colour signal at the TOA. This concept may open new doors for ocean colour remote sensing. We suggest that the next generation of ocean colour sensors should measure PPR to enhance observational capability. PMID:24434904

Urban Methane Point Sources Detected by Tiered System of Remote-sensing Observations

NASA Image and Video Library

2015-07-10

This image captured by a prototype NASA satellite instrument at NASA California Laboratory for Atmospheric Remote Sensing CLARS shows a persistent methane hotspot central red area over Los Angeles basin.

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Quantitative comparison of airborne remote-sensed and in situ Rhodamine WT dye and temperature during RIVET & IB09

NASA Astrophysics Data System (ADS)

Lenain, L.; Clark, D. B.; Guza, R. T.; Hally-Rosendahl, K.; Statom, N.; Feddersen, F.

2012-12-01

The transport and evolution of temperature, sediment, chlorophyll, fluorescent dye, and other tracers is of significant oceanographic interest, particularly in complex coastal environments such as the nearshore, river mouths, and tidal inlets. Remote sensing improves spatial coverage over in situ observations, and ground truthing remote sensed observations is critical for its use. Here, we present remotely sensed observations of Rhodamine WT dye and Sea Surface Temperature (SST) using the SIO Modular Aerial Sensing System (MASS) and compare them with in situ observations from the IB09 (0-300 m seaward of the surfzone, Imperial Beach, CA, October 2009) and RIVET (New River Inlet, NC, May 2012) field experiments. Dye concentrations are estimated from a unique multispectral camera system that measures the emission and absorption wavelengths of Rhodamine WT dye. During RIVET, dye is also characterized using a pushbroom hyperspectral imaging system (SPECIM AISAEagle VNIR 400-990 nm) while SST is estimated using a long-wave infrared camera (FLIR SC6000HS) coupled with an infrared pyrometer (Heitronics KT19.85II). Repeated flight passes over the dye plume were conducted approximately every 5 min for up to 4.5 hr in duration with a swath width ranging from 400 to 2000 m (altitude dependent), and provided a unique spatio-temporal depiction of the plume. A dye proxy is developed using the measured radiance at the emission and absorption wavelengths of the Rhodamine WT dye. During IB09 and RIVET, in situ dye and temperature were measured with two GPS-tracked jet skis, a small boat, and moored observations. The in situ observations are compared with the remotely sensed data in these two complex coastal environments. Funding was provided by the Office of Naval Research.

Quantitative evaluation of water quality in the coastal zone by remote sensing

NASA Technical Reports Server (NTRS)

James, W. P.

1971-01-01

Remote sensing as a tool in a waste management program is discussed. By monitoring both the pollution sources and the environmental quality, the interaction between the components of the exturaine system was observed. The need for in situ sampling is reduced with the development of improved calibrated, multichannel sensors. Remote sensing is used for: (1) pollution source determination, (2) mapping the influence zone of the waste source on water quality parameters, and (3) estimating the magnitude of the water quality parameters. Diffusion coefficients and circulation patterns can also be determined by remote sensing, along with subtle changes in vegetative patterns and density.

Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Limaye, Ashutosh; Manu, Andrew; Archer, Frank

2005-01-01

We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.

Apollo 16 landing site: Summary of earth based remote sensing data, part W

NASA Technical Reports Server (NTRS)

Zisk, S. H.; Masursky, H.; Milton, D. J.; Schaber, G. G.; Shorthill, R. W.; Thompson, T. W.

1972-01-01

Infrared and radar studies of the Apollo 16 landing site are summarized. Correlations and comparisons between earth based remote sensing data, IR observations, and other data are discussed in detail. Remote sensing studies were devoted to solving two problems: (1) determining the physical difference between Cayley and Descartes geologic units near the landing site; and (2) determining the nature of the bright unit of Descartes mountain material.

Remote sensing of atmosphere and oceans; Proceedings of Symposium 1 and of the Topical Meeting of the 27th COSPAR Plenary Meeting, Espoo, Finland, July 18-29, 1988

NASA Technical Reports Server (NTRS)

Raschke, E. (Editor); Ghazi, A. (Editor); Gower, J. F. R. (Editor); Mccormick, P. (Editor); Gruber, A. (Editor); Hasler, A. F. (Editor)

1989-01-01

Papers are presented on the contribution of space remote sensing observations to the World Climate Research Program and the Global Change Program, covering topics such as space observations for global environmental monitoring, experiments related to land surface fluxes, studies of atmospheric composition, structure, motions, and precipitation, and remote sensing for oceanography, observational studies of the atmosphere, clouds, and the earth radiation budget. Also, papers are given on results from space observations for meteorology, oceanography, and mesoscale atmospheric and ocean processes. The topics include vertical atmospheric soundings, surface water temperature determination, sea level variability, data on the prehurricane atmosphere, linear and circular mesoscale convective systems, Karman vortex clouds, and temporal patterns of phytoplankton abundance.

Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images.

PubMed

Doi, Ryoichi

2012-09-01

Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2 greater than 0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique's general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6-11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies' spectral profiles. Future aspects of this technique are discussed herein.

Remote Sensing of Precipitation from Space

NASA Technical Reports Server (NTRS)

Stocker, Erich Franz

2010-01-01

This slide presentation reviews the use of remote sensing of precipitation from satellite observations. The purpose of the presentation is to introduce the three prime instrument types for measuring precipitation from space, give an overview of the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) mission, provides examples of how measurements from space can be used, and provides simple, high level scenarios for how remote sensed precipitation data can be used by planners and managers.

Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Rosen, Paul A.

2012-01-01

This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

PubMed

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

Remote sensing new model for monitoring the east Asian migratory locust infections based on its breeding circle

NASA Astrophysics Data System (ADS)

Han, Xiuzhen; Ma, Jianwen; Bao, Yuhai

2006-12-01

Currently the function of operational locust monitor system mainly focused on after-hazards monitoring and assessment, and to found the way effectively to perform early warning and prediction has more practical meaning. Through 2001, 2002 two years continuously field sample and statistics for locusts eggs hatching, nymph growth, adults 3 phases observation, sample statistics and calculation, spectral measurements as well as synchronically remote sensing data processing we raise the view point of Remote Sensing three stage monitor the locust hazards. Based on the point of view we designed remote sensing monitor in three stages: (1) during the egg hitching phase remote sensing can retrieve parameters of land surface temperature (LST) and soil moisture; (2) during nymph growth phase locust increases appetite greatly and remote sensing can calculate vegetation index, leaf area index, vegetation cover and analysis changes; (3) during adult phase the locust move and assembly towards ponds and water ditches as well as less than 75% vegetation cover areas and remote sensing combination with field data can monitor and predicts potential areas for adult locusts to assembly. In this way the priority of remote sensing technology is elaborated effectively and it also provides technique support for the locust monitor system. The idea and techniques used in the study can also be used as reference for other plant diseases and insect pests.

NASA Remote Sensing Research as Applied to Archaeology

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Thomas, Michael R.

2002-01-01

The use of remotely sensed images is not new to archaeology. Ever since balloons and airplanes first flew cameras over archaeological sites, researchers have taken advantage of the elevated observation platforms to understand sites better. When viewed from above, crop marks, soil anomalies and buried features revealed new information that was not readily visible from ground level. Since 1974 and initially under the leadership of Dr. Tom Sever, NASA's Stennis Space Center, located on the Mississippi Gulf Coast, pioneered and expanded the application of remote sensing to archaeological topics, including cultural resource management. Building on remote sensing activities initiated by the National Park Service, archaeologists increasingly used this technology to study the past in greater depth. By the early 1980s, there were sufficient accomplishments in the application of remote sensing to anthropology and archaeology that a chapter on the subject was included in fundamental remote sensing references. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, or nearing deployment, offer significantly finer spatial and spectral resolutions than were previously available. Paired with new techniques of image analysis, this technology may make the direct detection of archaeological sites a realistic goal.

Adding Remote Sensing Data Products to the Nutrient Management Decision Support Toolbox

NASA Technical Reports Server (NTRS)

Lehrter, John; Schaeffer, Blake; Hagy, Jim; Spiering, Bruce; Blonski, Slawek; Underwood, Lauren; Ellis, Chris

2011-01-01

Some of the primary issues that manifest from nutrient enrichment and eutrophication (Figure 1) may be observed from satellites. For example, remotely sensed estimates of chlorophyll a (chla), total suspended solids (TSS), and light attenuation (Kd) or water clarity, which are often associated with elevated nutrient inputs, are data products collected daily and globally for coastal systems from satellites such as NASA s MODIS (Figure 2). The objective of this project is to inform water quality decision making activities using remotely sensed water quality data. In particular, we seek to inform the development of numeric nutrient criteria. In this poster we demonstrate an approach for developing nutrient criteria based on remotely sensed chla.

Development of multi-mission satellite data systems at the German Remote Sensing Data Centre

NASA Astrophysics Data System (ADS)

Lotz-Iwen, H. J.; Markwitz, W.; Schreier, G.

1998-11-01

This paper focuses on conceptual aspects of the access to multi-mission remote sensing data by online catalogue and information systems. The system ISIS of the German Remote Sensing Data Centre is described as an example of a user interface to earth observation data. ISIS has been designed to support international scientific research as well as operational applications by offering online access to the database via public networks. It provides catalogue retrieval, visualisation and transfer of image data, and is integrated in international activities dedicated to catalogue and archive interoperability. Finally, an outlook is given on international projects dealing with access to remote sensing data in distributed archives.

Remote sensing of Essential Biodiversity Variables: new measurements linking ecosystem structure, function and composition

NASA Astrophysics Data System (ADS)

Schimel, D.; Pavlick, R.; Stavros, E. N.; Townsend, P. A.; Ustin, S.; Thompson, D. R.

2017-12-01

Remote sensing can inform a wide variety of essential biodiversity variables, including measurements that define primary productivity, forest structure, biome distribution, plant communities, land use-land cover change and climate drivers of change. Emerging remote sensing technologies can add significantly to remote sensing of EBVs, providing new, large scale insights on plant and habitat diversity itself, as well as causes and consequences of biodiversity change. All current biodiversity assessments identify major data gaps, with insufficient coverage in critical regions, limited observations to monitor change over time, with very limited revisit of sample locations, as well as taxon-specific biased biases. Remote sensing cannot fill many of the gaps in global biodiversity observations, but spectroscopic measurements in terrestrial and marine environments can aid in assessing plant/phytoplankton functional diversity and efficiently reveal patterns in space, as well as changes over time, and, by making use of chlorophyll fluorescence, reveal associated patterns in photosynthesis. LIDAR and RADAR measurements quantify ecosystem structure, and can precisely define changes due to growth, disturbance and land use. Current satellite-based EBVs have taken advantage of the extraordinary time series from LANDSAT and MODIS, but new measurements more directly reveal ecosystem structure, function and composition. We will present results from pre-space airborne studies showing the synergistic ability of a suite of new remote observation techniques to quantify biodiversity and ecosystem function and show how it changes during major disturbance events.

Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

NASA Astrophysics Data System (ADS)

Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

2015-05-01

Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

Estimating dissolved organic carbon concentration in turbid coastal waters using optical remote sensing observations

NASA Astrophysics Data System (ADS)

Cherukuru, Nagur; Ford, Phillip W.; Matear, Richard J.; Oubelkheir, Kadija; Clementson, Lesley A.; Suber, Ken; Steven, Andrew D. L.

2016-10-01

Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20-520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.

Remote sensing of plant functional types.

PubMed

Ustin, Susan L; Gamon, John A

2010-06-01

Conceptually, plant functional types represent a classification scheme between species and broad vegetation types. Historically, these were based on physiological, structural and/or phenological properties, whereas recently, they have reflected plant responses to resources or environmental conditions. Often, an underlying assumption, based on an economic analogy, is that the functional role of vegetation can be identified by linked sets of morphological and physiological traits constrained by resources, based on the hypothesis of functional convergence. Using these concepts, ecologists have defined a variety of functional traits that are often context dependent, and the diversity of proposed traits demonstrates the lack of agreement on universal categories. Historically, remotely sensed data have been interpreted in ways that parallel these observations, often focused on the categorization of vegetation into discrete types, often dependent on the sampling scale. At the same time, current thinking in both ecology and remote sensing has moved towards viewing vegetation as a continuum rather than as discrete classes. The capabilities of new remote sensing instruments have led us to propose a new concept of optically distinguishable functional types ('optical types') as a unique way to address the scale dependence of this problem. This would ensure more direct relationships between ecological information and remote sensing observations.

A revised surface resistance parameterisation for estimating latent heat flux from remotely sensed data

NASA Astrophysics Data System (ADS)

Song, Yi; Wang, Jiemin; Yang, Kun; Ma, Mingguo; Li, Xin; Zhang, Zhihui; Wang, Xufeng

2012-07-01

Estimating evapotranspiration (ET) is required for many environmental studies. Remote sensing provides the ability to spatially map latent heat flux. Many studies have developed approaches to derive spatially distributed surface energy fluxes from various satellite sensors with the help of field observations. In this study, remote-sensing-based λE mapping was conducted using a Landsat Thematic Mapper (TM) image and an Enhanced Thematic Mapper Plus (ETM+) image. The remotely sensed data and field observations employed in this study were obtained from Watershed Allied Telemetry Experimental Research (WATER). A biophysics-based surface resistance model was revised to account for water stress and temperature constraints. The precision of the results was validated using 'ground truth' data obtained by eddy covariance (EC) system. Scale effects play an important role, especially for parameter optimisation and validation of the latent heat flux (λE). After considering the footprint of EC, the λE derived from the remote sensing data was comparable to the EC measured value during the satellite's passage. The results showed that the revised surface resistance parameterisation scheme was useful for estimating the latent heat flux over cropland in arid regions.

The International Geoscience and Remote Sensing Symposium (IGARSS) 84. Remote Sensing: from Research Towards Operational Use, Volume 2

NASA Technical Reports Server (NTRS)

Guyenne, T. D. (Editor); Hunt, James J. (Editor)

1984-01-01

Synthetic aperature radar; systems components; data collection; data evaluation; optical sensor data; air pollution; water pollution; land and sea observation; active sensors (ir and w); and ers-1 are discussed.

Sea State and Boundary Layer Physics of the Emerging Arctic Ocean

DTIC Science & Technology

2013-09-01

meteorological stations; weather observations; upper-air (rawinsondes, balloons and tethered kit); turbulent fluxes; radiation; surface temperature...remote sensing, in-field remote sensing will be employed, using small unmanned aerial vehicles (UAV), balloons , and manned aircraft (funded by other

Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

DTIC Science & Technology

2002-09-30

integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to develop hyperspectral remote sensing techniques in optically complex nearshore coastal waters.

Earth Remote Sensing for Weather Forecasting and Disaster Applications

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Bell, Jordan; Case, Jonathan; Cole, Tony; Elmer, Nicholas; McGrath, Kevin; Schultz, Lori; Zavodsky, Brad

2016-01-01

NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.

Ionospheric Profiles from Ultraviolet Remote Sensing

DTIC Science & Technology

1998-01-01

remote sensing of the ionosphere from orbiting space platforms. Remote sensing of the nighttime ionosphere is a relatively straightforward process due to the absence of the complications brought about by daytime solar radiation. Further, during the nighttime hours, the O(+)-H(+) transition level in both the mid- and low-latitude ionospheres lies around 750 km, which is within the range of accuracy of the path matrix inversion. The intensity of the O(+)-e(-) recombination radiation as observed from orbiting space platforms can now be used to

Accessing, Utilizing and Visualizing NASA Remote Sensing Data for Malaria Modeling and Surveillance

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Adimi, Farida; Kempler, Steven

2007-01-01

This poster presentation reviews the use of NASA remote sensing data that can be used to extract environmental information for modeling malaria transmission. The authors discuss the remote sensing data from Landsat, Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing One (EO-1), Advanced Land Imager (ALI) and Seasonal to Interannual Earth Science Information Partner (SIESIP) dataset.

Aircraft remote sensing of soil moisture and hydrologic parameters, Taylor Creek, Florida, and Little River, Georgia, 1979 data report

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Schmugge, T. J.; Allen, L. H., Jr.; Oneill, P.; Slack, R.; Wang, J.; Engman, E. T.

1981-01-01

Experiments were conducted to evaluate aircraft remote sensing techniques for hydrology in a wide range of physiographic and climatic regions using several sensor platforms. The data were collected in late 1978 and during 1979 in two humid areas--Taylor Creek, Fla., and Little River, Ga. Soil moisture measurements and climatic observations are presented as well as the remote sensing data collected using thermal infrared, passive microwave, and active microwave systems.

Validation of Ocean Color Remote Sensing Reflectance Using Autonomous Floats

NASA Technical Reports Server (NTRS)

Gerbi, Gregory P.; Boss, Emanuel; Werdell, P. Jeremy; Proctor, Christopher W.; Haentjens, Nils; Lewis, Marlon R.; Brown, Keith; Sorrentino, Diego; Zaneveld, J. Ronald V.; Barnard, Andrew H.;

A three stage sampling model for remote sensing applications

NASA Technical Reports Server (NTRS)

Eisgruber, L. M.

1972-01-01

A conceptual model and an empirical application of the relationship between the manner of selecting observations and its effect on the precision of estimates from remote sensing are reported. This three stage sampling scheme considers flightlines, segments within flightlines, and units within these segments. The error of estimate is dependent on the number of observations in each of the stages.

Teaching global and local environmental change through Remote Sensing

NASA Astrophysics Data System (ADS)

Mauri, Emanuela Paola; Rossi, Giovanni

2013-04-01

Human beings perceive the world primarily through their sense of sight. This can explain why the use of images is so important and common in educational materials, in particular for scientific subjects. The development of modern technologies for visualizing the scientific features of the Earth has provided new opportunities for communicating the increasing complexity of science both to the public and in school education. In particular, the use of Earth observation satellites for civil purposes, which started in the 70s, has opened new perspectives in the study of natural phenomena and human impact on the environment; this is particularly relevant for those processes developing on a long term period and on a global scale. Instruments for Remote Sensing increase the power of human sight, giving access to additional information about the physical world, which the human eye could not otherwise perceive. The possibility to observe from a remote perspective significant processes like climate change, ozone depletion, desertification, urban development, makes it possible for observers to better appreciate and experience the complexity of environment. Remote Sensing reveals the impact of human activities on ecosystems: this allows students to understand important concepts like global and local change in much more depth. This poster describes the role and effectiveness of Remote Sensing imagery in scientific education, and its importance towards a better global environmental awareness.

The micron- to kilometer-scale Moon: linking samples to orbital observations, Apollo to LRO

NASA Astrophysics Data System (ADS)

Crites, S.; Lucey, P. G.; Taylor, J.; Martel, L.; Sun, L.; Honniball, C.; Lemelin, M.

2017-12-01

The Apollo missions have shaped the field of lunar science and our understanding of the Moon, from global-scale revelations like the magma ocean hypothesis, to providing ground truth for compositional remote sensing and absolute ages to anchor cratering chronologies. While lunar meteorite samples can provide a global- to regional-level view of the Moon, samples returned from known locations are needed to directly link orbital-scale observations with laboratory measurements-a link that can be brought to full fruition with today's extremely high spatial resolution observations from Lunar Reconnaissance Orbiter and other recent missions. Korotev et al. (2005) described a scenario of the Moon without Apollo to speculate about our understanding of the Moon if our data were confined to lunar meteorites and remote sensing. I will review some of the major points discussed by Korotev et al. (2005), and focus on some of the ways in which spectroscopic remote sensing in particular has benefited from the Apollo samples. For example, could the causes and effects of lunar-style space weathering have been unraveled without the Apollo samples? What would be the limitations on remote sensing compositional measurements that rely on Apollo samples for calibration and validation? And what new opportunities to bring together orbital and sample analyses now exist, in light of today's high spatial and spectral resolution remote sensing datasets?

Spatial and temporal remote sensing data fusion for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

The suite of available remote sensing instruments varies widely in terms of sensor characteristics, spatial resolution and acquisition frequency. For example, the Moderate-resolution Imaging Spectroradiometer (MODIS) provides daily global observations at 250m to 1km spatial resolution. While imagery...

Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa.

PubMed

Ardö, Jonas

2015-12-01

Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types. Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship. Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Developing the remote sensing-based water environmental model for monitoring alpine river water environment over Plateau cold zone

NASA Astrophysics Data System (ADS)

You, Y.; Wang, S.; Yang, Q.; Shen, M.; Chen, G.

2017-12-01

Alpine river water environment on the Plateau (such as Tibetan Plateau, China) is a key indicator for water security and environmental security in China. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. In this study some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a), water turbidity (WT) or water clarity (SD), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC)) over the china's southwest highland rivers, such as the Brahmaputra. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based on various types of satellite data, at first we developed the techniques of multi-sensor data correction, atmospheric correction. Second, we also built the inversion spectral database derived from long-term remote sensing data and field sampling data. Then we have studied and developed a high-precision inversion model over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration. Third, take the middle reaches of the Brahmaputra river as the study area, we validated the key water environmental parameters and further improved the inversion model. The results indicate that our proposed water environment inversion model can be a good inversion for alpine water environmental parameters, and can improve the monitoring and warning ability for the alpine river water environment in the future.

Empirical validation and proof of added value of MUSICA's tropospheric δD remote sensing products

NASA Astrophysics Data System (ADS)

Schneider, M.; González, Y.; Dyroff, C.; Christner, E.; Wiegele, A.; Barthlott, S.; García, O. E.; Sepúlveda, E.; Hase, F.; Andrey, J.; Blumenstock, T.; Guirado, C.; Ramos, R.; Rodríguez, S.

2014-07-01

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isototopologue remote sensing and in-situ observations. This paper presents a first empirical validation of MUSICA's H2O and δD remote sensing products (generated from ground-based FTIR, Fourier Transform InfraRed, spectrometer and space-based IASI, Infrared Atmospheric Sounding Interferometer, observation). As reference we use well calibrated in-situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues and the scatter with respect to the in-situ references suggests a δD random uncertainty for the FTIR product of much better than 45‰ in the lower troposphere and of about 15‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15‰. In addition, we find indications for a positive δD bias in the remote sensing products. The δD data are scientifically interesting only if they add information to the H2O observations. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data by comparing δD-vs.-H2O curves. First, we show that the added value of δD as seen in the Picarro data is similarly seen in FTIR data measured in coincidence. Second, we document that the δD-vs.-H2O curves obtained from the different in-situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

NASA Astrophysics Data System (ADS)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

Remote Sensing Via Satellite: The Canadian Experience

ERIC Educational Resources Information Center

Classen, Hans George

1974-01-01

Describes the joint effort of Canada and NASA in monitoring the Canadian environment using remote-sensing techniques. The project involves the Earth Resources Technology Satellite and has been used to observe seasonal changes, extent of snow cover, crop growth, sea ice, and land use patterns. (GS)

The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales.

PubMed

Strong, James Asa; Elliott, Michael

2017-03-15

The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process. Copyright © 2017 Elsevier Ltd. All rights reserved.

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

1998-01-01

Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.

Thirty years of use and improvement of remote sensing, applied to epidemiology: from early promises to lasting frustration.

PubMed

Herbreteau, Vincent; Salem, Gérard; Souris, Marc; Hugot, Jean-Pierre; Gonzalez, Jean-Paul

2007-06-01

Remote sensing, referring to the remote study of objects, was originally developed for Earth observation, through the use of sensors on board planes or satellites. Improvements in the use and accessibility of multi-temporal satellite-derived environmental data have, for 30 years, contributed to a growing use in epidemiology. Despite the potential of remote-sensed images and processing techniques for a better knowledge of disease dynamics, an exhaustive analysis of the bibliography shows a generalized use of pre-processed spatial data and low-cost images, resulting in a limited adaptability when addressing biological questions.

The Integration of Remote-Sensing Detection Techniques into the Operational Decision-Making of Marine Oil Spills

NASA Astrophysics Data System (ADS)

Garron, J.; Trainor, S.

2017-12-01

Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill responses. Using automated synthetic aperture radar analyses of oil spills in a common operational picture as a scientific case study, this presentation is a demonstration of how landscape-level scientific data can be integrated into Arctic planning and operational decision-making.

Commercial Earth Observation

NASA Technical Reports Server (NTRS)

1995-01-01

Through the Earth Observation Commercial Applications Program (EOCAP) at Stennis Space Center, Applied Analysis, Inc. developed a new tool for analyzing remotely sensed data. The Applied Analysis Spectral Analytical Process (AASAP) detects or classifies objects smaller than a pixel and removes the background. This significantly enhances the discrimination among surface features in imagery. ERDAS, Inc. offers the system as a modular addition to its ERDAS IMAGINE software package for remote sensing applications. EOCAP is a government/industry cooperative program designed to encourage commercial applications of remote sensing. Projects can run three years or more and funding is shared by NASA and the private sector participant. Through the Earth Observation Commercial Applications Program (EOCAP), Ocean and Coastal Environmental Sensing (OCENS) developed SeaStation for marine users. SeaStation is a low-cost, portable, shipboard satellite groundstation integrated with vessel catch and product monitoring software. Linked to the Global Positioning System, SeaStation provides real time relationships between vessel position and data such as sea surface temperature, weather conditions and ice edge location. This allows the user to increase fishing productivity and improve vessel safety. EOCAP is a government/industry cooperative program designed to encourage commercial applications of remote sensing. Projects can run three years or more and funding is shared by NASA and the private sector participant.

Essential Biodiversity Variables: A framework for communication between the biodiversity community and space agencies

NASA Astrophysics Data System (ADS)

Leidner, A. K.; Skidmore, A. K.; Turner, W. W.; Geller, G. N.

2017-12-01

The biodiversity community is working towards developing a consensus on a set of Essential Biodiversity Variables (EBVs) that can be used to measure and monitor biodiversity change over time. These EBVs will inform research, modeling, policy, and assessment efforts. The synoptic coverage provided by satellite data make remote sensing a particularly important observation tool to inform many EBVs. Biodiversity is a relatively new subject matter for space agencies, and thus the definition, description, and requirements of EBVs with a significant remote sensing component can foster ways for the biodiversity community to clearly and concisely communicate observational needs to space agencies and the Committee on Earth Observing Satellites (CEOS, the international coordinating body for civilian space agencies). Here, we present an overview of EBVs with a particular emphasis on those for which remote sensing will play a significant role and also report on the results of recent workshops to prioritize and refine EBVs. Our goal is to provide a framework for the biodiversity community to coalesce around a set of observational needs to convey to space agencies. Compared to many physical science disciplines, the biodiversity community represents a wide range of sub-disciplines and organizations (academia, non-governmental organizations, research institutes, national and local natural resource management agencies, etc.), which creates additional challenges when communicating needs to space agencies unfamiliar with the topic. EBVs thus offer a communication pathway that could increase awareness within space agencies of the uses of remote sensing for biodiversity research and applications, which in turn could foster greater use of remote sensing in the broader biodiversity community.

Remote Sensing Information Sciences Research Group: Santa Barbara Information Sciences Research Group, year 4

NASA Technical Reports Server (NTRS)

Estes, John E.; Smith, Terence; Star, Jeffrey L.

1987-01-01

Information Sciences Research Group (ISRG) research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. Particular focus in on the needs of the remote sensing research and application science community which will be served by the Earth Observing System (EOS) and Space Station, including associated polar and co-orbiting platforms. The areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence and both natural and cultural vegetation analysis and modeling research will be expanded.

Studies related to ocean dynamics. Task 3.2: Aircraft Field Test Program to investigate the ability of remote sensing methods to measure current/wind-wave interactions

NASA Technical Reports Server (NTRS)

Huang, N. E.; Flood, W. A.; Brown, G. S.

1975-01-01

The feasibility of remote sensing of current flows in the ocean and the remote sensing of ocean currents by backscattering cross section techniques was studied. It was established that for capillary waves, small scale currents could be accurately measured through observation of wave kinematics. Drastic modifications of waves by changing currents were noted. The development of new methods for the measurement of capillary waves are discussed. Improvement methods to resolve data processing problems are suggested.

Simulating optoelectronic systems for remote sensing with SENSOR

NASA Astrophysics Data System (ADS)

Boerner, Anko

2003-04-01

The consistent end-to-end simulation of airborne and spaceborne remote sensing systems is an important task and sometimes the only way for the adaptation and optimization of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software ENvironment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. It allows the simulation of a wide range of optoelectronic systems for remote sensing. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. Part three consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimization requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and examples of its use are given. The verification of SENSOR is demonstrated.

Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook.

PubMed

Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Raso, Giovanna; Utzinger, Jürg

2015-03-17

Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions. We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised. We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from. Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.

Remote Sensing of Terrestrial Snow and Ice for Global Change Studies

NASA Technical Reports Server (NTRS)

Kelly, Richard; Hall, Dorothy K.

2007-01-01

Snow and ice play a significant role in the Earth's water cycle and are sensitive and informative indicators climate change. Significant changes in terrestrial snow and ice water storage are forecast, and while evidence of large-scale changes is emerging, in situ measurements alone are insufficient to help us understand and explain these changes. Imaging remote sensing systems are capable of successfully observing snow and ice in the cryosphere. This chapter examines how those remote sensing sensors, that now have more than 35 years of observation records, are capable of providing information about snow cover, snow water equivalent, snow melt, ice sheet temperature and ice sheet albedo. While significant progress has been made, especially in the last five years, a better understanding is required of the records of satellite observations of these cryospheric variables.

Satellite Remote Sensing: Aerosol Measurements

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

An investigation of satellite sounding products for the remote sensing of the surface energy balance and soil moisture

NASA Technical Reports Server (NTRS)

Diak, George R.

1989-01-01

Improved techniques for the remote sensing of the land surface energy balance (SEB) and soil moisture would greatly improve prediction of climate and weather as well as be of benefit to agriculture, hydrology and many associated fields. Most of the satellite remote sensing methods which were researched to date rely upon satellite-measured infrared surface temperatures or their time changes as a remote sensing signal. Optimistically, only four or five levels of information (wet to dry) in surface heating/evaporation are discernable by surface temperature methods and a good understanding of atmospheric conditions is necessary to bring them to this accuracy level. Skin temperature methods were researched as well as begun work on several new methods for the remote sensing of the SEB, some elements of which are applicable to current and retrospective data sources and some which will rely on instrumentation from the Earth Observing System (EOS) program in the 1990s.

Toward Linking Aboveground Vegetation Properties and Soil Microbial Communities Using Remote Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Yuki; Gilbert, Jack A.; Larsen, Peter E.

2014-04-01

Despite their vital role in terrestrial ecosystem function, the distributions and dynamics of soil microbial communities (SMCs) are poorly understood. Vegetation and soil properties are the primary factors that influence SMCs. This paper discusses the potential effectiveness of remote sensing science and technologies for mapping SMC biogeography by characterizing surface biophysical properties (e.g., plant traits and community composition) strongly correlated with SMCs. Using remotely sensed biophysical properties to predict SMC distributions is extremely challenging because of the intricate interactions between biotic and abiotic factors and between above- and belowground ecosystems. However, the integration of biophysical and soil remote sensing withmore » geospatial information about the e nvironment holds great promise for mapping SMC biogeography. Additional research needs invol ve microbial taxonomic definition, soil environmental complexity, and scaling strategies. The collaborative effort of experts from diverse disciplines is essential to linking terrestrial surface biosphere observations with subsurface microbial community distributions using remote sensing.« less

Toward Linking Aboveground Vegetation Properties and Soil Microbial Communities Using Remote Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Yuki; Gilbert, Jack A.; Larsen, Peter E.

2014-04-01

Despite their vital role in terrestrial ecosystem function, the distributions and dynamics of soil microbial communities (SMCs) are poorly understood. Vegetation and soil properties are the primary factors that influence SMCs. This paper discusses the potential effectiveness of remote sensing science and technologies for mapping SMC biogeography by characterizing surface biophysical properties (e.g., plant traits and community composition) strongly correlated with SMCs. Using remotely sensed biophysical properties to predict SMC distributions is extremely challenging because of the intricate interactions between biotic and abiotic factors and between above- and below-ground ecosystems. However, the integration of biophysical and soil remote sensing withmore » geospatial information about the environment holds great promise for mapping SMC biogeography. Additional research needs involve microbial taxonomic definition, soil environmental complexity, and scaling strategies. The collaborative effort of experts from diverse disciplines is essential to linking terrestrial surface biosphere observations with subsurface microbial community distributions using remote sensing.« less

Surveillance of Arthropod Vector-Borne Infectious Diseases Using Remote Sensing Techniques: A Review

PubMed Central

Kalluri, Satya; Gilruth, Peter; Rogers, David; Szczur, Martha

2007-01-01

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed. PMID:17967056

Validation plays the role of a "bridge" in connecting remote sensing research and applications

NASA Astrophysics Data System (ADS)

Wang, Zhiqiang; Deng, Ying; Fan, Yida

2018-07-01

Remote sensing products contribute to improving earth observations over space and time. Uncertainties exist in products of different levels; thus, validation of these products before and during their applications is critical. This study discusses the meaning of validation in depth and proposes a new definition of reliability for use with such products. In this context, validation should include three aspects: a description of the relevant uncertainties, quantitative measurement results and a qualitative judgment that considers the needs of users. A literature overview is then presented evidencing improvements in the concepts associated with validation. It shows that the root mean squared error (RMSE) is widely used to express accuracy; increasing numbers of remote sensing products have been validated; research institutes contribute most validation efforts; and sufficient validation studies encourage the application of remote sensing products. Validation plays a connecting role in the distribution and application of remote sensing products. Validation connects simple remote sensing subjects with other disciplines, and it connects primary research with practical applications. Based on the above findings, it is suggested that validation efforts that include wider cooperation among research institutes and full consideration of the needs of users should be promoted.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR data

NASA Astrophysics Data System (ADS)

Wiegele, A.; Schneider, M.; Hase, F.; Barthlott, S.; García, O. E.; Sepúlveda, E.; González, Y.; Blumenstock, T.; Raffalski, U.; Gisi, M.; Kohlhepp, R.

2014-04-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in-situ datasets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing dataset is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, mid-latitudes, and arctic) and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier-Transform InfraRed) remote sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study is both, a theoretical and an empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR data

NASA Astrophysics Data System (ADS)

Wiegele, A.; Schneider, M.; Hase, F.; Barthlott, S.; García, O. E.; Sepúlveda, E.; González, Y.; Blumenstock, T.; Raffalski, U.; Gisi, M.; Kohlhepp, R.

2014-08-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in situ data sets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing data set is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, midlatitudes, and Arctic), and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote-sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform InfraRed) remote-sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study presents theoretical and empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

Observations in the solar spectrum interest for remote sensing purposes

NASA Technical Reports Server (NTRS)

Herman, M.; Vanderbilt, V.

1994-01-01

The polarization of the sunlight scattered by atmospheric aerosols or cloud droplets and reflected from ground surfaces or plant canopies may convey much information when used for remote sensing purposes. The typical polarization features of aerosols, cloud droplets, and plant canopies, as observed by ground based and airborne sensors, are investigated, looking especially for those invariant properties amenable to description by simple models when possible. The question of polarization measurements from space is addressed. The interest of such measurements for remote sensing purposes is investigated, and their feasibility is tested by using results obtained during field campaigns of the airborne POLDER instrument, a radiometer designed to measure the directionality and polarization of the sunlight scattered by the ground atmosphere system.

Remote sensing terminology: past experience and recent needs

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana

2013-10-01

Terminology is a key issue for a better understanding among people using various languages. Terminology accuracy is essential during all phases of international cooperation. It is crucial to keep up with the latest quantitative and qualitative developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have wide and ever extending applications in various domains of human activity. The importance of the correct use of remote sensing terms refers not only to people working in this field but also to experts in many disciplines who handle remote sensing data and information products. The paper is devoted to terminology issues that refer to all aspects of remote sensing research and application areas. The attention is drawn on the recent needs and peculiarities of compiling specialized dictionaries in the subject area of remote sensing. Details are presented about the work in progress on the preparation of an English-Bulgarian dictionary of remote sensing terms focusing on Earth observations and geoinformation science. Our belief is that the elaboration of bilingual and multilingual dictionaries and glossaries in this spreading, most technically advanced and promising field of human expertise is of great practical importance. Any interest in cooperation and initiating of suchlike collaborative multilingual projects is welcome and highly appreciated.

Introduction to the Special Session on Thermal Remote Sensing Data for Earth Science Research: The Critical Need for Continued Data Collection and Development of Future Thermal Satellite Sensors

NASA Technical Reports Server (NTRS)

Quattrochi, Dale a.; Luvall, Jeffrey C.; Anderson, Martha; Hook, Simon

2006-01-01

There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse iairesolutions.

The role of remote sensing observations and models in hydrology: The science of evapotranspiration

USGS Publications Warehouse

Nagler, Pamela

2011-01-01

ensuing years. These advances can be attributed largely to three convergent themes: 1) technical innovation; 2) synergy between disciplines; and 3) expressed need. The papers in this special issue address all of these three themes on remote sensing methods for ET estimation.

Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet, understanding of the relationship between GPP and remote sensing observations and how it changes as a function of factors such as scale, biophysical constraint, and vegetation ...

Applications of satellite remote sensing to forested ecosystems

Treesearch

Louis R. Iverson; Robin Lambert Graham; Elizabeth A. Cook; Elizabeth A. Cook

1989-01-01

Since the launch of the first civilian earth-observing satellite in 1972, satellite remote sensing has provided increasingly sophisticated information on the structure and function of forested ecosystems. Forest classification and mapping, common uses of satellite data, have improved over the years as a result of more discriminating sensors, better classification...

Topographic Signatures in Aquarius Radiometer/Scatterometer Response: Initial Results

NASA Technical Reports Server (NTRS)

Utku, C.; LeVine, D. M.

2012-01-01

The effect of topography on remote sensing at L-band is examined using the co-located Aquarius radiometer and scatterometer observations over land. A correlation with slope standard deviation is demonstrated for both the radiometer and scatterometer at topographic scales. Although the goal of Aquarius is remote sensing of sea surface salinity, the radiometer and scatterometer are on continuously and collect data for remote sensing research over land. Research is reported here using the data over land to determine if topography could have impact on the passive remote sensing at L-band. In this study, we report observations from two study regions: North Africa between 15 deg and 30 deg Northern latitudes and Australia less the Tasmania Island. Common to these two regions are the semi-arid climate and low population density; both favorable conditions to isolate the effect of topography from other sources of scatter and emission such as vegetation and urban areas. Over these study regions, topographic scale slopes within each Aquarius pixel are computed and their standard deviations are compared with Aquarius scatterometer and radiometer observations over a 36 day period between days 275 and 311 of 2011.

A feasibility study of using remotely sensed data for water resource models

NASA Technical Reports Server (NTRS)

Ruff, J. F.

1973-01-01

Remotely sensed data were collected to demonstrate the feasibility of applying the results to water resource problems. Photographs of the Wolf Creek watershed in southwestern Colorado were collected over a one year period. Cloud top temperatures were measured using a radiometer. Thermal imagery of the Wolf Creek Pass area was obtained during one pre-dawn flight. Remote sensing studies of water resource problems for user agencies were also conducted. The results indicated that: (1) remote sensing techniques could be used to assist in the solution of water resource problems; (2) photogrammetric determination of snow depths is feasible; (3) changes in turbidity or suspended material concentration can be observed; and (4) surface turbulence can be related to bed scour; and (5) thermal effluents into rivers can be monitored.

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

NASA Astrophysics Data System (ADS)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Wageningen UR Unmanned Aerial Remote Sensing Facility - Overview of activities

NASA Astrophysics Data System (ADS)

Bartholomeus, Harm; Keesstra, Saskia; Kooistra, Lammert; Suomalainen, Juha; Mucher, Sander; Kramer, Henk; Franke, Jappe

2016-04-01

To support environmental management there is an increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems. In 2012, different groups within Wageningen University and Research Centre have established an Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold: a) To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments; b) To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community; and c) To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment. The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics (EI) of Alterra. The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angles for characterization of BRDF and flexibility in use of camera's and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested. In the last years we developed and implemented different camera systems (e.g. a hyperspectral pushbroom system, and multispectral frame cameras) which we operated in projects all around the world, while new camera systems are being planned such as LiDAR and a full frame hyperspectral camera. In the presentation we will give an overview of our activities, ranging from erosion studies, decision support for precision agriculture, determining leaf biochemistry and canopy structure in tropical forests to the mapping of coastal zones.

FOREWORD: Satellite Remote Sensing Beyond 2015

NASA Technical Reports Server (NTRS)

Tucker, Compton J.

2017-01-01

Satellite remote sensing has progressed tremendously since the first Landsat was launched on June 23, 1972. Since the 1970s, satellite remote sensing and associated airborne and in situ measurements have resulted in vital and indispensable observations for understanding our planet through time. These observations have also led to dramatic improvements in numerical simulation models of the coupled atmosphere-land-ocean systems at increasing accuracies and predictive capability. The same observations document the Earth's climate and are driving the consensus that Homo sapiens is changing our climate through greenhouse gas emissions. These accomplishments are the combined work of many scientists from many countries and a dedicated cadre of engineers who build the instruments and satellites that collect Earth observation data from satellites, all working toward the goal of improving our understanding of the Earth. This edition of the Remote Sensing Handbook (Vol. I, II, and III) is a compendium of information for many research areas of our Planet that have contributed to our substantial progress since the 1970s. Remote sensing community is now using multiple sources of satellite and in situ data to advance our studies, what ever they might be. In the following paragraphs, I will illustrate how valuable and pivotal role satellite remote sensing has played in climate system study over last five decades, The Chapters in the Remote Sensing Handbook (Vol. I, II, and III) provides many other specific studies on land, water, and other applications using EO data of last five decades, The Landsat system of Earth-observing satellites has led the way in pioneering sustained observations of our planet. From 1972 to the present, at least one and sometimes two Landsat satellites have been in operation. Starting with the launch of the first NOAA-NASA Polar Orbiting Environmental Satellites NOAA-6 in 1978, improved imaging of land, clouds, and oceans and atmospheric soundings of temperature were accomplished. The NOAA system of polar-orbiting meteorological satellites has continued uninterrupted since that time, providing vital observations for numerical weather prediction. These same satellites are also responsible for the remarkable records of sea surface temperature and land vegetation index from the Advanced Very High Resolution Radiometers (AVHRR) that now span more than 33 years, although no one anticipated these valuable climate records from this instrument before the launch of NOAA-7 in 1981. The success of data from the AVHRR led to the design of the MODIS instruments on NASA's Earth Observing System of satellite platforms that improved substantially upon the AVHRR. The first of the EOS platforms, Terra, was launched in 2000 and the second of these platforms, Aqua, was launched in 2002.

A remote sensing applications update: Results of interviews with Earth Observations Commercialization Program (EOCAP) participants

NASA Technical Reports Server (NTRS)

Mcvey, Sally

1991-01-01

Earth remote sensing is a uniquely valuable tool for large-scale resource management, a task whose importance will likely increase world-wide through the foreseeable future. NASA research and engineering have virtually created the existing U.S. system, and will continue to push the frontiers, primarily through Earth Observing System (EOS) instruments, research, and data and information systems. It is the researchers' view that the near-term health of remote sensing applications also deserves attention; it seems important not to abandon the system or its clients. The researchers suggest that, like its Landsat predecessor, a successful Earth Observing System program is likely to reinforce pressure to 'manage' natural resources, and consequently, to create more pressure for Earth Observations Commercialization (EOCAP) type applications. The current applications programs, though small, are valuable because of their technical and commercial results, and also because they support a community whose contributions will increase along with our ability to observe the Earth from space.

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Remote Sensing Terminology in a Global and Knowledge-Based World

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana

The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy, GIS, etc. Our belief is that the elaboration of bilingual and multilingual dictionaries and glossaries in this spreading, most technically advanced and promising field of human expertise is of great practical importance. The work on an English-Bulgarian Dictionary of Remote Sensing Terms is described including considerations on its scope, structure, information content, sellection of terms, and etc. The vision builds upon previous national and international experience and makes use of ongoing activities on the subject. Any interest in cooperation and initiating suchlike collaborative projects is welcome and highly appreciated.

Investigation on sense of control parameters for joystick interface in remote operated container crane application

NASA Astrophysics Data System (ADS)

Abdullah, U. N. N.; Handroos, H.

2017-09-01

Introduction: This paper presents the study of sense of control parameters to improve the lack of direct motion feeling through remote operated container crane station (ROCCS) joystick interface. The investigations of the parameters in this study are important to develop the engineering parameters related to the sense of control goal in the next design process. Methodology: Structured interviews and observations were conducted to obtain the user experience data from thirteen remote container crane operators from two international terminals. Then, interview analysis, task analysis, activity analysis and time line analysis were conducted to compare and contrast the results from interviews and observations. Results: Four experience parameters were identified to support the sense of control goal in the later design improvement of the ROCC joystick interface. The significance of difficulties to control, unsynchronized movements, facilitate in control and decision making in unexpected situation as parameters to the sense of control goal were validated by' feedbacks from operators as well as analysis. Contribution: This study provides feedback directly from end users towards developing a sustainable control interface for ROCCS in specific and remote operated off-road vehicles in general.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

Data Integration Framework Data Management Plan Remote Sensing Dataset

DTIC Science & Technology

2016-07-01

performed by the Coastal Observations and Analysis Branch (CEERD-HFA) of the Flood and Storm Protection Division (CEERD-HF), U.S. Army Engineer Research... Protection Division, Coastal Observations and Analysis Branch CESAM U.S. Army Corps of Engineers, Mobile District CESAM-OP-J U.S. Army Corps of Engineers...ER D C/ CH L SR -1 6- 2 Coastal Ocean Data Systems Program Data Integration Framework Data Management Plan Remote Sensing Dataset Co

Dimension Reduction of Hyperspectral Data on Beowulf Clusters

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek

2000-01-01

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operation. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold a great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, which is used widely in remote sensing, is the Principal Components Analysis (PCA). In light of the growing number of spectral channels of modern instruments, the paper reports on the development of a parallel PCA and its implementation on two Beowulf cluster configurations, on with fast Ethernet switch and the other is with a Myrinet interconnection.

Other remote sensing systems: Retrospect and outlook

NASA Technical Reports Server (NTRS)

1982-01-01

The history of remote sensing is reviewed and the scope and versatility of the several remote sensing systems already in orbit are discussed, especially those with sensors operating in other EM spectral modes. The multisensor approach is examined by interrelating LANDSAT observations with data from other satellite systems. The basic principles and practices underlying the use of thermal infrared and radar sensors are explored and the types of observations and interpretations emanating from the Nimbus, Heat Capacity Mapping Mission, and SEASAT programs are examined. Approved or proposed Earth resources oriented missions for the 1980's previewed include LANDSAT D, Stereosat, Gravsat, the French satellite SPOT-1, and multimission modular spacecraft launched from space shuttle. The pushbroom imager, the linear array pushbroom radiometer, the multispectral linear array, and the operational LANDSAT observing system, to be designed the LANDSAT-E series are also envisioned for this decade.

Propagation Limitations in Remote Sensing.

DTIC Science & Technology

Contents: Multi-sensors and systems in remote sensing ; Radar sensing systems over land; Remote sensing techniques in oceanography; Influence of...propagation media and background; Infrared techniques in remote sensing ; Photography in remote sensing ; Analytical studies in remote sensing .

High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

Treesearch

Jonathan P. Dandois; Erle C. Ellis

2013-01-01

High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing...

High resolution remote sensing missions of a tethered satellite

NASA Technical Reports Server (NTRS)

Vetrella, S.; Moccia, A.

1986-01-01

The application of the Tethered Satellite (TS) as an operational remote sensing platform is studied. It represents a new platform capable of covering the altitudes between airplanes and free flying satellites, offering an adequate lifetime, high geometric and radiometric resolution and improved cartographic accuracy. Two operational remote sensing missions are proposed: one using two linear array systems for along track stereoscopic observation and one using a synthetic aperture radar combined with an interferometric technique. These missions are able to improve significantly the accuracy of future real time cartographic systems from space, also allowing, in the case of active microwave systems, the Earth's observation both in adverse weather and at any time, day or night. Furthermore, a simulation program is described in which, in order to examine carefully the potentiality of the TS as a new remote sensing platform, the orbital and attitude dynamics description of the TSS is integrated with the sensor viewing geometry, the Earth's ellipsoid, the atmospheric effects, the Sun illumination and the digital elevation model. A preliminary experiment has been proposed which consist of a metric camera to be deployed downwards during the second Shuttle demonstration flight.

Advances in U.S. Land Imaging Capabilities

NASA Astrophysics Data System (ADS)

Stryker, T. S.

2017-12-01

Advancements in Earth observations, cloud computing, and data science are improving everyday life. Information from land-imaging satellites, such as the U.S. Landsat system, helps us to better understand the changing landscapes where we live, work, and play. This understanding builds capacity for improved decision-making about our lands, waters, and resources, driving economic growth, protecting lives and property, and safeguarding the environment. The USGS is fostering the use of land remote sensing technology to meet local, national, and global challenges. A key dimension to meeting these challenges is the full, free, and open provision of land remote sensing observations for both public and private sector applications. To achieve maximum impact, these data must also be easily discoverable, accessible, and usable. The presenter will describe the USGS Land Remote Sensing Program's current capabilities and future plans to collect and deliver land remote sensing information for societal benefit. He will discuss these capabilities in the context of national plans and policies, domestic partnerships, and international collaboration. The presenter will conclude with examples of how Landsat data is being used on a daily basis to improve lives and livelihoods.

Aerial Vehicle Surveys of other Planetary Atmospheres and Surfaces: Imaging, Remote-sensing, and Autonomy Technology Requirements

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Gregory; Ippolito, Corey; Alena, Rick

2005-01-01

The objective of this paper is to review the anticipated imaging and remote-sensing technology requirements for aerial vehicle survey missions to other planetary bodies in our Solar system that can support in-atmosphere flight. In the not too distant future such planetary aerial vehicle (a.k.a. aerial explorers) exploration missions will become feasible. Imaging and remote-sensing observations will be a key objective for these missions. Accordingly, it is imperative that optimal solutions in terms of imaging acquisition and real-time autonomous analysis of image data sets be developed for such vehicles.

The Federal Oil Spill Team for Emergency Response Remote Sensing (FOSTERRS)

NASA Astrophysics Data System (ADS)

Stough, T.; Jones, C. E.; Leifer, I.; Lindsay, F. E.; Murray, J. J.; Ramirez, E. M.; Salemi, A.; Streett, D.

2014-12-01

Oil spills can cause enormous ecological and economic devastation, necessitating application of the best science and technology available, for which remote sensing plays a critical role in detection and monitoring of oil spills. The FOSTERRS interagency working group seeks to ensure that during an oil spill, remote sensing assets (satellite/aircraft) and analysis techniques are quickly, effectively and seamlessly available to oil spills responders. FOSTERRS enables cooperation between agencies with core environmental remote sensing assets and capabilities and academic and industry experts to act as an oil spill remote sensing information clearinghouse. The US government and its collaborators have a broad variety of aircraft and satellite sensors, imagery interrogation techniques and other technology that can provide indispensable remote sensing information to agencies, emergency responders and the public during an oil spill. Specifically, FOSTERRS will work to ensure that (1) suitable aircraft and satellite imagery and radar observations are quickly made available in a manner that can be integrated into oil spill detection and mitigation efforts, (2) existing imagery interrogation techniques are in the hands of those who will provide the 24 x 7 operational support and (3) efforts are made to develop new technology where the existing techniques do not provide oil spills responders with important information they need. The FOSTERRS mission goal places it in an ideal place for identification of critical technological needs, and identifying bottlenecks in technology acceptance. The core FOSTERRS team incorporates representation for operations and science for agencies with relevant instrumental and platform assets (NASA, NOAA, USGS, NRL). FOSTERRS membership will open to a wide range of end-user agencies and planned observer status from industry and academic experts, and eventually international partners. Through these collaborations, FOSTERRS facilitates interagency and cooperation and communication to the larger end-user community on remote sensing and its best use.

Development of a Cost-Effective Airborne Remote Sensing System for Coastal Monitoring

PubMed Central

Kim, Duk-jin; Jung, Jungkyo; Kang, Ki-mook; Kim, Seung Hee; Xu, Zhen; Hensley, Scott; Swan, Aaron; Duersch, Michael

2015-01-01

Coastal lands and nearshore marine areas are productive and rapidly changing places. However, these areas face many environmental challenges related to climate change and human-induced impacts. Space-borne remote sensing systems may be restricted in monitoring these areas because of their spatial and temporal resolutions. In situ measurements are also constrained from accessing the area and obtaining wide-coverage data. In these respects, airborne remote sensing sensors could be the most appropriate tools for monitoring these coastal areas. In this study, a cost-effective airborne remote sensing system with synthetic aperture radar and thermal infrared sensors was implemented to survey coastal areas. Calibration techniques and geophysical model algorithms were developed for the airborne system to observe the topography of intertidal flats, coastal sea surface current, sea surface temperature, and submarine groundwater discharge. PMID:26437413

Development of a Cost-Effective Airborne Remote Sensing System for Coastal Monitoring.

PubMed

Kim, Duk-jin; Jung, Jungkyo; Kang, Ki-mook; Kim, Seung Hee; Xu, Zhen; Hensley, Scott; Swan, Aaron; Duersch, Michael

2015-09-30

Coastal lands and nearshore marine areas are productive and rapidly changing places. However, these areas face many environmental challenges related to climate change and human-induced impacts. Space-borne remote sensing systems may be restricted in monitoring these areas because of their spatial and temporal resolutions. In situ measurements are also constrained from accessing the area and obtaining wide-coverage data. In these respects, airborne remote sensing sensors could be the most appropriate tools for monitoring these coastal areas. In this study, a cost-effective airborne remote sensing system with synthetic aperture radar and thermal infrared sensors was implemented to survey coastal areas. Calibration techniques and geophysical model algorithms were developed for the airborne system to observe the topography of intertidal flats, coastal sea surface current, sea surface temperature, and submarine groundwater discharge.

The Citizens and Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote Sensing Data with Local Environmental Awareness

NASA Technical Reports Server (NTRS)

Acker, James; Riebeek, Holli; Ledley, Tamara Shapiro; Herring, David; Lloyd, Steven

2008-01-01

"Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on environmental issues.

Analysis and modeling of atmospheric turbulence on the high-resolution space optical systems

NASA Astrophysics Data System (ADS)

Lili, Jiang; Chen, Xiaomei; Ni, Guoqiang

2016-09-01

Modeling and simulation of optical remote sensing system plays an unslightable role in remote sensing mission predictions, imaging system design, image quality assessment. It has already become a hot research topic at home and abroad. Atmospheric turbulence influence on optical systems is attached more and more importance to as technologies of remote sensing are developed. In order to study the influence of atmospheric turbulence on earth observation system, the atmospheric structure parameter was calculated by using the weak atmospheric turbulence model; and the relationship of the atmospheric coherence length and high resolution remote sensing optical system was established; then the influence of atmospheric turbulence on the coefficient r0h of optical remote sensing system of ground resolution was derived; finally different orbit height of high resolution optical system imaging quality affected by atmospheric turbulence was analyzed. Results show that the influence of atmospheric turbulence on the high resolution remote sensing optical system, the resolution of which has reached sub meter level meter or even the 0.5m, 0.35m and even 0.15m ultra in recent years, image quality will be quite serious. In the above situation, the influence of the atmospheric turbulence must be corrected. Simulation algorithms of PSF are presented based on the above results. Experiment and analytical results are posted.

Combining optical remote sensing, agricultural statistics and field observations for culture recognition over a peri-urban region

NASA Astrophysics Data System (ADS)

Delbart, Nicolas; Emmanuelle, Vaudour; Fabienne, Maignan; Catherine, Ottlé; Jean-Marc, Gilliot

2017-04-01

This study explores the potential of multi-temporal optical remote sensing, with high revisit frequency, to derive missing information on agricultural calendar and crop types over the agricultural lands in the Versailles plain in the western Paris suburbs. This study comes besides past and ongoing studies on the use of radar and high spatial resolution optical remote sensing to monitor agricultural practices in this study area (e.g. Vaudour et al. 2014). Agricultural statistics, such as the Land Parcel Identification System (LPIS) for France, permit to know the nature of annual crops for each digitized declared field of this land parcel registry. However, within each declared field several cropped plots and a diversity of practices may exist, being marked by agricultural rotations which vary both spatially and temporally within it and differ from one year to the other. Even though the new LPIS to be released in 2016 is expected to describe individual plots within declared fields, its attributes may not enable to discriminate between winter and spring crops. Here we evaluate the potential of high observation frequency remote sensing to differentiate seasonal crops based essentially on the seasonality of the spectral properties. In particular, we use the Landsat data to spatially disaggregate the LPIS statistical data, on the basis of the analysis of the remote sensing spectral seasonality measured on a number of selected ground-observed fields. This work is carried out in the framework of the CNES TOSCA-PLEIADES-CO of the French Space Agency.

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

DOE PAGES

Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly; ...

2017-01-07

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less

A Prototype Hydrologic Observatory for the Neuse River Basin Using Remote Sensing Data as a Part of the CUAHSI-HIS Effort

NASA Astrophysics Data System (ADS)

Kanwar, R.; Narayan, U.; Lakshmi, V.

2005-12-01

Remote sensing has the potential to immensely advance the science and application of hydrology as it provides multi-scale and multi-temporal measurements of several hydrologic parameters. There is a wide variety of remote sensing data sources available to a hydrologist with a myriad of data formats, access techniques, data quality issues and temporal and spatial extents. It is very important to make data availability and its usage as convenient as possible for potential users. The CUAHSI Hydrologic Information System (HIS) initiative addresses this issue of better data access and management for hydrologists with a focus on in-situ data, that is point measurements of water and energy fluxes which make up the 'more conventional' sources of hydrologic data. This paper explores various sources of remotely sensed hydrologic data available, their data formats and volumes, current modes of data acquisition by end users, metadata associated with data itself, and requirements from potential data models that would allow a seamless integration of remotely sensed hydrologic observations into the Hydrologic Information System. Further, a prototype hydrologic observatory (HO) for the Neuse River Basin is developed using surface temperature, vegetation indices and soil moisture estimates available from remote sensing. The prototype (HO) uses the CUAHSI digital library system (DLS) on the back (server) end. On the front (client) end, a rich visual environment has been developed in order to provide better decision making tools in order to make an optimal choice in the selection of remote sensing data for a particular application. An easy point and click interface to the remote sensing data is also implemented for common users who are just interested in location based query of hydrologic variable values.

Satellite Remote Sensing of Harmful Algal Blooms (HABs) and a Potential Synthesized Framework

PubMed Central

Shen, Li; Xu, Huiping; Guo, Xulin

2012-01-01

Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. PMID:22969372

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

PubMed Central

Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

2016-01-01

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment. PMID:27922592

Transitioning Earth Remote Sensing Data to Benefit Society: A Paradigm for a Center of Excellence

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Bjorgo, Einar; Burn, Anthony

2015-01-01

Over the past decade there has been a substantial increase in the number of Earth remote sensing satellites launched for research and operational usage and numerous others planned by the international community. These satellites have been used to varying degrees by their supporting agencies for weather and environmental monitoring, climate studies, disaster monitoring and response, and other humanitarian activities. While there are success stories on useful applications of remote sensing data, the broader use of these satellite assets by other organizations and entities has been limited for a number of reasons including lack of data services, data dissemination issues, and a general failure to engage the broader end user community with useful data access and knowledge of how to use the data and products. This paper describes some of these current limitations on the broader use of Earth remote sensing data by the international community and describes the concept of a general "Center of Excellence" to facilitate the development, transition, and utilization of these Earth remote sensing observations by the broader international community.

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

NASA Astrophysics Data System (ADS)

Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

2016-12-01

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification.

PubMed

Bradbury, Kyle; Saboo, Raghav; L Johnson, Timothy; Malof, Jordan M; Devarajan, Arjun; Zhang, Wuming; M Collins, Leslie; G Newell, Richard

2016-12-06

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

[An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

PubMed

Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

2009-10-01

Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

Earth view: A business guide to orbital remote sensing

NASA Technical Reports Server (NTRS)

Bishop, Peter C.

1990-01-01

The following subject areas are covered: Earth view - a guide to orbital remote sensing; current orbital remote sensing systems (LANDSAT, SPOT image, MOS-1, Soviet remote sensing systems); remote sensing satellite; and remote sensing organizations.

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

NASA Technical Reports Server (NTRS)

Brown, Molly Elizabeth; Brickley, Elizabeth B

2012-01-01

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Remotely-sensed and in-situ observations of Greenland firn aquifers

NASA Astrophysics Data System (ADS)

Forster, R. R.; Miège, C.; Koenig, L.; Solomon, D. K.; Schmerr, N. C.; Miller, O. L.; Ligtenberg, S.; Montgomery, L. N.; Brucker, L.; Miller, J.; Legchenko, A.

2017-12-01

In 2011, prior to seasonal melt, our research team drilled into an unknown firn aquifer system in Southeast Greenland. Since 2013, we have conducted four field seasons, complemented with modeling and remote sensing to gain knowledge regarding firn aquifers and surrounding snow/firn/ice. We aim to provide a more complete picture of the system including formation conditions, controlling mechanisms, spatial and temporal changes, and connections with the larger ice sheet hydrologic system. This work summarizes remote sensing data since 1993 showing the spatial and temporal evolution of the aquifer extent. To complement the remote sensing and better characterize the firn aquifer in the field, we use a combination of three different geophysics methods. Ground penetrating radar provides us knowledge of the water table elevation and its variations, magnetic-resonance soundings give us the water volume held in the aquifer and the active seismic data allow us to locate the bottom of the aquifer. In addition, firn/ice-core stratigraphy suggests that the timing and evolution of the aquifer bottom is controlled by thermodynamics. Our compilation of remote sensing measurements point to a dynamic and expanding aquifer system. We found that firn aquifers have existed at least since 1993 (dataset start) in the high melt and high accumulation region of the South Eastern Greenland ice sheet. Firn aquifers are now growing toward the interior related to the warming air temperatures in the Arctic and more intense melt during summers. These remotely sensed observations and in-situ measurements are required to validate improved ice sheet mass balance models that incorporate firn aquifers. They are also needed to further investigate the potential of firn aquifer discharge to the glacier bed via crevasse hydrofracturing influencing ice dynamics.

New Earth Observation Capabilities For The Commercial Sector

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2017-01-01

Earth observation data collected from orbital remote sensing systems are becoming increasingly critical to the short- and long-term operations of many commercial industries including agriculture, energy exploration, environmental management, transportation, and urban planning and operations. In this panel, I will present an overview of current and planned NASA remote sensing systems for Earth observation with relevance to commercial and industrial applications. Special emphasis will be given to the International Space Station (ISS) as a platform for both commercial technology demonstration/development and operational data collection through the ISS National Laboratory.

Near-surface remote sensing of spatial and temporal variation in canopy phenology

Treesearch

Andrew D. Richardson; Bobby H. Braswell; David Y. Hollinger; Julian P. Jenkins; Scott V. Ollinger

2009-01-01

There is a need to document how plant phenology is responding to global change factors, particularly warming trends. "Near-surface" remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and...

Technology study of quantum remote sensing imaging

NASA Astrophysics Data System (ADS)

Bi, Siwen; Lin, Xuling; Yang, Song; Wu, Zhiqiang

2016-02-01

According to remote sensing science and technology development and application requirements, quantum remote sensing is proposed. First on the background of quantum remote sensing, quantum remote sensing theory, information mechanism, imaging experiments and prototype principle prototype research situation, related research at home and abroad are briefly introduced. Then we expounds compress operator of the quantum remote sensing radiation field and the basic principles of single-mode compression operator, quantum quantum light field of remote sensing image compression experiment preparation and optical imaging, the quantum remote sensing imaging principle prototype, Quantum remote sensing spaceborne active imaging technology is brought forward, mainly including quantum remote sensing spaceborne active imaging system composition and working principle, preparation and injection compression light active imaging device and quantum noise amplification device. Finally, the summary of quantum remote sensing research in the past 15 years work and future development are introduced.

Satellite imaging coral reef resilience at regional scale. A case-study from Saudi Arabia.

PubMed

Rowlands, Gwilym; Purkis, Sam; Riegl, Bernhard; Metsamaa, Liisa; Bruckner, Andrew; Renaud, Philip

2012-06-01

We propose a framework for spatially estimating a proxy for coral reef resilience using remote sensing. Data spanning large areas of coral reef habitat were obtained using the commercial QuickBird satellite, and freely available imagery (NASA, Google Earth). Principles of coral reef ecology, field observation, and remote observations, were combined to devise mapped indices. These capture important and accessible components of coral reef resilience. Indices are divided between factors known to stress corals, and factors incorporating properties of the reef landscape that resist stress or promote coral growth. The first-basis for a remote sensed resilience index (RSRI), an estimate of expected reef resilience, is proposed. Developed for the Red Sea, the framework of our analysis is flexible and with minimal adaptation, could be extended to other reef regions. We aim to stimulate discussion as to use of remote sensing to do more than simply deliver habitat maps of coral reefs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Quantification of Glacier Depletion in the Central Tibetan Plateau by Using Integrated Satellite Remote Sensing and Gravimetry

NASA Astrophysics Data System (ADS)

Tseng, K.-H.; Liu, K. T.; Shum, C. K.; Jia, Y.; Shang, K.; Dai, C.

2016-06-01

Glaciers over the Tibetan Plateau have experienced accelerated depletion in the last few decades due primarily to the global warming. The freshwater drained into brackish lakes is also observed by optical remote sensing and altimetry satellites. However, the actual water storage change is difficult to be quantified since the altimetry or remote sensing only provide data in limited dimensions. The altimetry data give an elevation change of surface while the remote sensing images provide an extent variation in horizontal plane. Hence a data set used to describe the volume change is needed to measure the exact mass transition in a time span. In this study, we utilize GRACE gravimetry mission to quantify the total column mass change in the central Tibetan Plateau, especially focused on the lakes near Tanggula Mountains. By removing these factors, the freshwater storage change of glacier system at study area can be potentially isolated.

Autonomous Exploration for Gathering Increased Science

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin J.; Castano, Rebecca; Estlin, Tara A.; Gaines, Daniel M.; Anderson, Robert C.; Thompson, David R.; DeGranville, Charles K.; Chien, Steve A.; Tang, Benyang; Burl, Michael C.;

Possibility of Cloudless Optical Remote Sensing Images Acquisition Study by Using Meteorological Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, T.; Lei, B.; Hu, Y.; Liu, K.; Gan, Y.

2018-04-01

Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.

When Models and Observations Collide: Journeying towards an Integrated Snow Depth Product

NASA Astrophysics Data System (ADS)

Webster, M.; Petty, A.; Boisvert, L.; Markus, T.; Kurtz, N. T.; Kwok, R.; Perovich, D. K.

2017-12-01

Knowledge of snow depth is essential for assessing changes in sea ice mass balance due to snow's insulating and reflective properties. In remote sensing applications, the accuracy of sea ice thickness retrievals from altimetry crucially depends on snow depth. Despite the need for snow depth data, we currently lack continuous observations that capture the basin-scale snow depth distribution and its seasonal evolution. Recent in situ and remote sensing observations are sparse in space and time, and contain uncertainties, caveats, and/or biases that often require careful interpretation. Likewise, using model output for remote sensing applications is limited due to uncertainties in atmospheric forcing and different treatments of snow processes. Here, we summarize our efforts in bringing observational and model data together to develop an approach for an integrated snow depth product. We start with a snow budget model and incrementally incorporate snow processes to determine the effects on snow depth and to assess model sensitivity. We discuss lessons learned in model-observation integration and ideas for potential improvements to the treatment of snow in models.

Irrigated lands: Monitoring by remote sensing

NASA Technical Reports Server (NTRS)

Epiphanio, J. C. N.; Vitorelli, I.

1983-01-01

The use of remote sensing for irrigated areas, especially in the region of Guaira, Brazil (state of Sao Paulo), is examined. Major principles of utilizing LANDSAT data for the detection and mapping of irrigated lands are discussed. In addition, initial results obtained by computer processing of digital data, use of MSS (Multispectral Scanner System)/LANDSAT products, and the availability of new remote sensing products are highlighted. Future activities include the launching of the TM (Thematic Mapper)/LANDSAT 4 with 30 meters of resolution and SPOT (Systeme Probatorie d'Observation de la Terre) with 10 to 20 meters of resolution, to be operational in 1984 and 1986 respectively.

New Observational Technologies Scientific and Societal Impacts

NASA Astrophysics Data System (ADS)

Fabry, F.; Zawadzki, I.

INTRODUCTION REMOTE SENSING OF THE ATMOSPHERE REMOTE SENSORS AND THEIR SCIENTIFIC IMPACTS Air Temperature and Moisture Clouds and Precipitation Wind Others Related Scientific Considerations SOCIETAL IMPACTS CONCLUSIONS REFERENCES

Using NASA Remote Sensing Data to Reduce Uncertainty of Land-use Transitions in Global Carbon-Climate Models

NASA Astrophysics Data System (ADS)

Chini, L. P.; Hurtt, G. C.; Frolking, S. E.; Sahajpal, R.; Potapov, P.; Hansen, M.; Fisk, J.

2016-12-01

For the 5th IPCC Assessment almost all Earth System Models (ESMs) incorporated new gridded products of land-use and land-use change that were harmonized to ensure a continuous transition from historical to future data in a consistent format for all models. However, these Land-Use Harmonization (LUH) data products are estimates, constrained with data where available, and with modeling assumptions, and the remaining challenge is to quantify, and reduce, the uncertainty in these products. At the same time, satellite remote sensing of the terrestrial biosphere has also evolved. Global-scale land cover extent and change monitoring is now possible given systematically acquired earth observation data sets, advanced characterization algorithms and data intensive computing capabilities. Here we consider: how can satellite remote sensing products be used to generate (and reduce uncertainty in) new gridded maps of land-use transitions for use in coupled carbon-climate simulations? As part of the international effort to develop the next generation of land-use datasets (LUH2), new NASA remote-sensing-based maps of global forest extent and change (Hansen et al. 2013) were used as both an added constraint and diagnostic in the LUH process. Harmonizing this remote sensing data with the LUH data was a major computational challenge involving 143 billion 30m Landsat pixels, and the simulation of over 20 billion LUH unknowns. Our approach involved first harmonizing the definitions of forest loss between the observed and simulated data for the years 2000-2012. Next, new spatial patterns of historical wood harvest were calculated to match the observed forest loss transitions while simultaneously meeting all other constraints of the model, and ensuring consistency throughout the historical time-period. After reconciling definitions and developing new wood harvest patterns the LUH2 global forest loss for the period 2000-2012 was reduced from over 8.3 million km2 to 1.78 million km2 (compared with the remote-sensing-based forest loss of 2.03 million km2). Next steps are to evaluate the ability of these land-use transitions to improve the representation of land-use-related climate forcings in ESM experiments, and to then build upon the LUH framework to incorporate additional remote-sensing data constraints.

Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

2014-05-01

Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety of land cover types. Remote sensing data from the Tropical Rainfall Measuring Mission satellite (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sensors were obtained for the period from 2000 to 2012, and observation data from 99 weather stations, 441 streamflow gauges, as well as the gridded observation data from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE) were obtained for validation. The objective blends of multiple indicators helped better assessment of various types of drought, and can be useful for drought early warning system. Since the improved SDCI is based on remotely sensed data, it can be easily applied to regions with limited or no observation data for drought assessment and monitoring.

International Conference on Remote Sensing Applications for Archaeological Research and World Heritage Conservation

NASA Technical Reports Server (NTRS)

2002-01-01

Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes. Archaeology through Space: Experience in Indian Subcontinent. The creation of a GIS Archaeological Site Location Catalogue in Yucatan: A Tool to preserve its Cultural Heritage. Mapping the Ancient Anasazi Roads of Southeast Utah. Remote Sensing and GIS Technology for Identification of Conservation and Heritage sites in Urban Planning. Mapping Angkor: For a new appraisal of the Angkor region. Angkor and radar imaging: seeing a vast pre-industrial low-density, dispersed urban complex. Technical and methodological aspects of archaeological CRM integrating high resolution satellite imagery. The contribution of satellite imagery to archaeological survey: an example from western Syria. The use of satellite images, digital elevation models and ground truth for the monitoring of land degradation in the "Cinque Terre" National park. Remote Sensing and GIS Applications for Protection and Conservation of World Heritage Site on the coast - Case Study of Tamil Nadu Coast, India. Multispectral high resolution satellite imagery in combination with "traditional" remote sensing and ground survey methods to the study of archaeological landscapes. The case study of Tuscany. Use of Remotely-Sensed Imagery in Cultural Landscape. Characterisation at Fort Hood, Texas. Heritage Learning and Data Collection: Biodiversity & Heritage Conservation through Collaborative Monitoring & Research. A collaborative project by UNESCO's WHC (World Heritage Center) & The GLOBE Program (Global Learning and Observations to Benefit the Environment). Practical Remote Sensing Activities in an Interdisciplinary Master-Level Space Course.

Airborne Remote Observations of L-Band Radio Frequency Interference and Implications for Satellite Missions

NASA Technical Reports Server (NTRS)

Laymon, Charles; Srinivasan, Karthik; Limaye, Ashutosh

2011-01-01

Passive remote sensing of the Earth s surface and atmosphere from space has significant importance in operational and research environmental studies, in particular for the scientific understanding, monitoring and prediction of climate change and its impacts. Passive remote sensing requires the measurement of naturally occurring radiations, usually of very low power levels, which contain essential information on the physical process under investigation. As such, these sensed radio frequency bands are a unique natural resource enabling space borne passive sensing of the atmosphere and the Earth s surface that deserves adequate allocation to the Earth Exploration Satellite Service and absolute protection from interference. Unfortunately, radio frequency interference (RFI) is an increasing problem for Earth remote sensing, particularly for passive observations of natural emissions. Because these natural signals tend to be very weak, even low levels of interference received by a passive sensor may degrade the fidelity of scientific data. The characteristics of RFI (low-level interference and radar-pulse noise) are not well known because there has been no systematic surveillance, spectrum inventory or mapping of RFI. While conducting a flight experiment over central Tennessee in May 2010, RFI, a concern for any instrument operating in the passive L band frequency, was observed across 16 subbands between 1402-1427 MHz. Such a survey provides rare characterization data from which to further develop mitigation technologies as well as to identify bandwidths to avoid in future sensor formulation.

A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

NASA Astrophysics Data System (ADS)

Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

2011-12-01

The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

FLUXNET to MODIS: Connecting the dots to capture heterogenious biosphere metabolism

NASA Astrophysics Data System (ADS)

Woods, K. D.; Schwalm, C.; Huntzinger, D. N.; Massey, R.; Poulter, B.; Kolb, T.

2015-12-01

Eddy co-variance flux towers provide our most widely distributed network of direct observations for land-atmosphere carbon exchange. Carbon flux sensitivity analysis is a method that uses in situ networks to understand how ecosystems respond to changes in climatic variables. Flux towers concurrently observe key ecosystem metabolic processes (e..g. gross primary productivity) and micrometeorological variation, but only over small footprints. Remotely sensed vegetation indices from MODIS offer continuous observations of the vegetated land surface, but are less direct, as they are based on light use efficiency algorithms, and not on the ground observations. The marriage of these two data products offers an opportunity to validate remotely sensed indices with in situ observations and translate information derived from tower sites to globally gridded products. Here we provide correlations between Enhanced Vegetation Index (EVI), Leaf Area Index (LAI) and MODIS gross primary production with FLUXNET derived estimates of gross primary production, respiration and net ecosystem exchange. We demonstrate remotely sensed vegetation products which have been transformed to gridded estimates of terrestrial biosphere metabolism on a regional-to-global scale. We demonstrate anomalies in gross primary production, respiration, and net ecosystem exchange as predicted by both MODIS-carbon flux sensitivities and meteorological driver-carbon flux sensitivities. We apply these sensitivities to recent extreme climatic events and demonstrate both our ability to capture changes in biosphere metabolism, and differences in the calculation of carbon flux anomalies based on method. The quantification of co-variation in these two methods of observation is important as it informs both how remotely sensed vegetation indices are correlated with on the ground tower observations, and with what certainty we can expand these observations and relationships.

Ground-based remote sensing of volcanic CO2 and correlated SO2, HF, HCl, and BrO, in safe-distance from the crater

NASA Astrophysics Data System (ADS)

Butz, Andre; Solvejg Dinger, Anna; Bobrowski, Nicole; Kostinek, Julian; Fieber, Lukas; Fischerkeller, Constanze; Giuffrida, Giovanni Bruno; Hase, Frank; Klappenbach, Friedrich; Kuhn, Jonas; Lübcke, Peter; Tirpitz, Lukas; Tu, Qiansi

2017-04-01

Remote sensing of CO2 enhancements in volcanic plumes can be a tool to estimate volcanic CO2 emissions and thereby, to gain insight into the geological carbon cycle and into volcano interior processes. However, remote sensing of the volcanic CO2 is challenged by the large atmospheric background concentrations masking the minute volcanic signal. Here, we report on a demonstrator study conducted in September 2015 at Mt. Etna on Sicily, where we deployed an EM27/SUN Fourier Transform Spectrometer together with a UV spectrometer on a mobile remote sensing platform. The spectrometers were operated in direct-sun viewing geometry collecting cross-sectional scans of solar absorption spectra through the volcanic plume by operating the platform in stop-and-go patterns in 5 to 10 kilometers distance from the crater region. We successfully detected correlated intra-plume enhancements of CO2 and volcanic SO2, HF, HCl, and BrO. The path-integrated volcanic CO2 enhancements amounted to about 0.5 ppm (on top of the ˜400 ppm background). Key to successful detection of volcanic CO2 was A) the simultaneous observation of the O2 total column which allowed for correcting changes in the CO2 column caused by changes in observer altitude and B) the simultaneous measurement of volcanic species co-emitted with CO2 which allowed for discriminating intra-plume and extra-plume observations. The latter were used for subtracting the atmospheric CO2 background. The field study suggests that our remote sensing observatory is a candidate technique for volcano monitoring in safe distance from the crater region.

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

NASA Astrophysics Data System (ADS)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

Modeling, simulation, and analysis of optical remote sensing systems

NASA Technical Reports Server (NTRS)

Kerekes, John Paul; Landgrebe, David A.

1989-01-01

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

[Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

PubMed

Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

2018-02-01

Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

Sensing our Environment: Remote sensing in a physics classroom

NASA Astrophysics Data System (ADS)

Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit

2017-04-01

Remote sensing is defined as data acquisition of an object, deprived physical contact. Fundamentally, most remote sensing applications are referred to as the use of satellite- or aircraft-based sensor technologies to detect and classify objects mainly on Earth or other planets. In the last years there have been efforts to bring the important subject of remote sensing into schools, however, most of these attempts focused on geography disciplines - restricting to the applications of remote sensing and to a less extent the technique itself and the physics behind it. Optical remote sensing is based on physical principles and technical devices, which are very meaningful from a theoretical point of view as well as for "hands-on" teaching. Some main subjects are radiation, atom and molecular physics, spectroscopy, as well as optics and the semiconductor technology used in modern digital cameras. Thus two objectives were outlined for this project: 1) to investigate the possibilities of using remote sensing techniques in physics teaching, and 2) to identify its impact on pupil's interest in the field of natural sciences. This joint project of the DLR_School_Lab, Oberpfaffenhofen of the German Aerospace Center (DLR) and the Earth and Planetary Image Facility (EPIF) at BGU, was conducted in 2016. Thirty teenagers (ages 16-18) participated in the project and were exposed to the cutting edge methods of earth observation. The pupils on both sides participated in the project voluntarily, knowing that at least some of the project's work had to be done in their leisure time. The pupil's project started with a day at EPIF and DLR respectively, where the project task was explained to the participants and an introduction to remote sensing of vegetation was given. This was realized in lectures and in experimental workshops. During the following two months both groups took several measurements with modern optical remote sensing systems in their home region with a special focus on flora. The teams then processed their data and presented it to their foreign partners for evaluation in a video conference call. Alongside exciting insights about their respective environments and living conditions, the young scientists had daily access to live satellite sensors and remote sensing through the DLR_School_Lab in Germany and the Earth and Planetary Image Facility in Israel. This paper provides an overview regarding the project, the techniques used and the evaluation results following a pre-past-questionnaire design, and above all demonstrates the use of remote sensing as an application for physics teaching in a significant learning environment.

Flood warnings, flood disaster assessments, and flood hazard reduction: the roles of orbital remote sensing

NASA Technical Reports Server (NTRS)

Brakenridge, G. R.; Anderson, E.; Nghiem, S. V.; Caquard, S.; Shabaneh, T. B.

2003-01-01

Orbital remote sensing of the Earth is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction.

Dynamic stratification of the landscape of Mexico: analysis of vegetation patterns observed with multitemporal remotely sensed images

Treesearch

Franz Mora; Louis R. Iverson; Louis R. Iverson

1997-01-01

Rapid deforestation in Mexico, when coupled with poor access to current and consistent ecological information across the country underscores the need for an ecological classification system that can be readily updated as new data become available. In this study, regional vegetation resources in Mexico were evaluated using remotely sensed information. Multitemporal...

Moderate resolution remote sensing alternatives: a review of Landsat-like sensors and their applications

Treesearch

Scott L. Powell; Dirk Pflugmacher; Alan A. Kirschbaum; Yunsuk Kim; Warren B. Cohen

2007-01-01

Earth observation with Landsat and other moderate resolution sensors is a vital component of a wide variety of applications across disciplines. Despite the widespread success of the Landsat program, recent problems with Landsat 5 and Landsat 7 create uncertainty about the future of moderate resolution remote sensing. Several other Landsat-like sensors have demonstrated...

Informing a hydrological model of the Ogooué with multi-mission remote sensing data

NASA Astrophysics Data System (ADS)

Kittel, Cecile; Bauer-Gottwein, Peter; Nielsen, Karina; Tøttrup, Christian

2017-04-01

Knowledge on hydrological regimes of river basins is crucial for water management. However, data requirements often limit the applicability of hydrological models in basins with scarce in-situ data. Remote sensing provides a unique possibility to acquire information on hydrological variables in these basins. This study explores how multi-mission remote sensing data can inform a hydrological model. The Ogooué basin in Gabon is used as study area. No previous modelling efforts have been conducted for the basin and only historical flow and precipitation observations are available. Publicly available remote sensing observations are used to parametrize, force, calibrate and validate a hydrological model of the Ogooué. The modelling framework used in the study, is a lumped conceptual rainfall-runoff model based on the Budyko framework coupled to a Muskingum routing scheme. Precipitation is a crucial driver of the land-surface water balance, therefore two satellite-based rainfall estimates, Tropical Rainfall Measuring Mission (TRMM) product 3B42 version 7 and Famine Early Warning System - Rainfall Estimate (FEWS-RFE), are compared. The comparison shows good seasonal and spatial agreement between the products; however, TRMM consistently predicts significantly more precipitation: 1726 mm on average per year against 1556 mm for FEWS-RFE. Best modeling results are obtained with the TRMM precipitation forcing. Model calibration combines historical in-situ flow observations and GRACE total water storage observations using the Jet Propulsion Laboratory (JPL) mascon solution in a multi-objective approach. The two models are calibrated using flow duration curves and climatology benchmarks to overcome the lack of simultaneity between simulated and observed discharge. The objectives are aggregated into a global objective function, and the models are calibrated using the Shuffled Complex Evolution Algorithm. Water height observations from drifting orbit altimetry missions are extracted along the river line, using a detailed water mask based on Sentinel-1 SAR imagery. 1399 single CryoSat-2 altimetry observations and 48 ICESat observations are acquired. Additionally, water heights have been measured by the repeat-orbit satellite missions Envisat and Jason-2 at 12 virtual stations along the river. The four missions show generally good agreement in terms of mean annual water height amplitudes. The altimetry observations are used to validate the hydrological model of the Ogooué River. By combining hydrological modelling and remote sensing, new information on an otherwise unstudied basin is obtained. The study shows the potential of using remote sensing observations to parameterize, force, calibrate and validate models of poorly gauged river basins. Specifically, the study shows how Sentinel-1 SAR imagery supports the extraction of satellite altimetry data over rivers. The model can be used to assess climate change scenarios, evaluate hydraulic infrastructure development projects and predict the impact of irrigation diversions.

ASTER VNIR 15 years growth to the standard imaging radiometer in remote sensing

NASA Astrophysics Data System (ADS)

Hiramatsu, Masaru; Inada, Hitomi; Kikuchi, Masakuni; Sakuma, Fumihiro

2015-10-01

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Visible and Near Infrared Radiometer (VNIR) is the remote sensing equipment which has 3 spectral bands and one along-track stereoscopic band radiometer. ASTER VNIR's planned long life design (more than 5 years) is successfully achieved. ASTER VNIR has been imaging the World-wide Earth surface multiband images and the Global Digital Elevation Model (GDEM). VNIR data create detailed world-wide maps and change-detection of the earth surface as utilization transitions and topographical changes. ASTER VNIR's geometric resolution is 15 meters; it is the highest spatial resolution instrument on NASA's Terra spacecraft. Then, ASTER VNIR was planned for the geometrical basis map makers in Terra instruments. After 15-years VNIR growth to the standard map-maker for space remote-sensing. This paper presents VNIR's feature items during 15-year operation as change-detection images , DEM and calibration result. VNIR observed the World-wide Earth images for biological, climatological, geological, and hydrological study, those successful work shows a way on space remote sensing instruments. Still more, VNIR 15 years observation data trend and onboard calibration trend data show several guide or support to follow-on instruments.

Airborne Particles: What We Have Learned About Their Role in Climate from Remote Sensing, and Prospects for Future Advances

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Desert dust, wildfire smoke, volcanic ash, biogenic and urban pollution particles, all affect the regional-scale climate of Earth in places and at times; some have global-scale impacts on the column radiation balance, cloud properties, atmospheric stability structure, and circulation patterns. Remote sensing has played a central role in identifying the sources and transports of airborne particles, mapping their three-dimensional distribution and variability, quantifying their amount, and constraining aerosol air mass type. The measurements obtained from remote sensing have strengths and limitations, and their value for characterizing Earths environment is enhanced immensely when they are combined with direct, in situ observations, and used to constrain aerosol transport and climate models. A similar approach has been taken to study the role particles play in determining the climate of Mars, though based on far fewer observations. This presentation will focus what we have learned from remote sensing about the impacts aerosol have on Earths climate; a few points about how aerosols affect the climate of Mars will also be introduced, in the context of how we might assess aerosol-climate impacts more generally on other worlds.

An Examination of Intertidal Temperatures Through Remotely Sensed Satellite Observations

NASA Astrophysics Data System (ADS)

Lakshmi, V.

2010-12-01

MODIS Aqua and Terra satellites produce both land surface temperatures and sea surface temperatures using calibrated algorithms. In this study, the land surface temperatures were retrieved during clear-sky (non-cloudy) conditions at a 1 km2 resolution (overpass time at 10:30 am) whereas the sea surface temperatures are also retrieved during clear-sky conditions at approximately 4 km resolution (overpass time at 1:30 pm). The purpose of this research was to examine remotely sensed sea surface (SST), intertidal (IST), and land surface temperatures (LST), in conjunction with observed in situ mussel body temperatures, as well as associated weather and tidal data. In Strawberry Hill, Oregon, it was determined that intertidal surface temperatures are similar to but distinctly different from land surface temperatures although influenced by sea surface temperatures. The air temperature and differential heating throughout the day, as well as location in relation to the shore, can greatly influence the remotely sensed surface temperatures. Therefore, remotely sensed satellite data is a very useful tool in examining intertidal temperatures for regional climatic changes over long time periods and may eventually help researchers forecast expected climate changes and help determine associated biological implications.

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

NASA Technical Reports Server (NTRS)

Ransom, K. J.; Sun, G.; Kharuk, V. I.; Howl, J.

2011-01-01

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

The AmericaView Project - Putting the Earth into Your Hands

USGS Publications Warehouse

,

2005-01-01

The U.S. Geological Survey (USGS) is a leader in collecting, archiving, and distributing geospatial data and information about the Earth. Providing quick, reliable access to remotely sensed images and geospatial data is the driving principle behind the AmericaView Project. A national not-for-profit organization, AmericaView, Inc. was established and is supported by the USGS to coordinate the activities of a national network of university-led consortia with the primary objective of the advancement of the science of remote sensing. Individual consortia members include academic institutions, as well as state, local, and tribal government agencies. AmericaView's focus is to expand the understanding and use of remote sensing through education and outreach efforts and to provide affordable, integrated remote sensing information access and delivery to the American public. USGS's Landsat and NASA's Earth Observing System (EOS) satellite data are downlinked from satellites or transferred from other facilities to the USGS Center for Earth Resources Observation and Science (EROS) ground receiving station in Sioux Falls, South Dakota. The data can then be transferred over high-speed networks to consortium members, where it is archived and made available for public use.

Applications of Remote Sensing to Emergency Management.

DTIC Science & Technology

1980-02-15

Contents: Foundations of Remote Sensing : Data Acquisition and Interpretation; Availability of Remote Sensing Technology for Disaster Response...Imaging Systems, Current and Near Future Satellite and Aircraft Remote Sensing Systems; Utilization of Remote Sensing in Disaster Response: Categories of...Disasters, Phases of Monitoring Activities; Recommendations for Utilization of Remote Sensing Technology in Disaster Response; Selected Reading List.

Intelligent Systems: Terrestrial Observation and Prediction Using Remote Sensing Data

NASA Technical Reports Server (NTRS)

Coughlan, Joseph C.

2005-01-01

NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.

On the sensitivity of numerical weather prediction to remotely sensed marine surface wind data - A simulation study

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.; Halem, M.; Halberstam, I.

1981-01-01

The reported investigation has the objective to assess the potential impact on numerical weather prediction (NWP) of remotely sensed surface wind data. Other investigations conducted with similar objectives have not been satisfactory in connection with a use of procedures providing an unrealistic distribution of initial errors. In the current study, care has been taken to duplicate the actual distribution of information in the conventional observing system, thus shifting the emphasis from accuracy of the data to the data coverage. It is pointed out that this is an important consideration in assessing satellite observing systems since experience with sounder data has shown that improvements in forecasts due to satellite-derived information is due less to a general error reduction than to the ability to fill data-sparse regions. The reported study concentrates on the evaluation of the observing system simulation experimental design and on the assessment of the potential of remotely sensed marine surface wind data.

Watermarking techniques for electronic delivery of remote sensing images

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Magli, Enrico; Olmo, Gabriella

2002-09-01

Earth observation missions have recently attracted a growing interest, mainly due to the large number of possible applications capable of exploiting remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products. Such a need is a very crucial one, because the Internet and other public/private networks have become preferred means of data exchange. A critical issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: assessment of the requirements imposed by remote sensing applications on watermark-based copyright protection, and modification of two well-established digital watermarking techniques to meet such constraints. More specifically, the concept of near-lossless watermarking is introduced and two possible algorithms matching such a requirement are presented. Experimental results are shown to measure the impact of watermark introduction on a typical remote sensing application, i.e., unsupervised image classification.

An Open Source Software and Web-GIS Based Platform for Airborne SAR Remote Sensing Data Management, Distribution and Sharing

NASA Astrophysics Data System (ADS)

Changyong, Dou; Huadong, Guo; Chunming, Han; Ming, Liu

2014-03-01

With more and more Earth observation data available to the community, how to manage and sharing these valuable remote sensing datasets is becoming an urgent issue to be solved. The web based Geographical Information Systems (GIS) technology provides a convenient way for the users in different locations to share and make use of the same dataset. In order to efficiently use the airborne Synthetic Aperture Radar (SAR) remote sensing data acquired in the Airborne Remote Sensing Center of the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), a Web-GIS based platform for airborne SAR data management, distribution and sharing was designed and developed. The major features of the system include map based navigation search interface, full resolution imagery shown overlaid the map, and all the software adopted in the platform are Open Source Software (OSS). The functions of the platform include browsing the imagery on the map navigation based interface, ordering and downloading data online, image dataset and user management, etc. At present, the system is under testing in RADI and will come to regular operation soon.

Simulating Local and Intercontinental Pollutant Effects of Biomass Burning: Integration of Several Remotely Sensed Datasets

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Vastano, John A.; Guild, Liane; Hlavka, Christine; Brass, James A.; Russell, Philip B. (Technical Monitor)

1994-01-01

Burning to clear land for crops and to destroy pests is an integral and largely unavoidable part of tropical agriculture. It is easy to note but difficult to quantify using remote sensing. This report describes our efforts to integrate remotely sensed data into our computer model of tropical chemical trace-gas emissions, weather, and reaction chemistry (using the MM5 mesoscale model and our own Global-Regional Atmospheric Chemistry Simulator). The effects of burning over the continents of Africa and South America have been noticed in observations from several satellites. Smoke plumes hundreds of kilometers long may be seen individually, or may merge into a large smoke pall over thousands of kilometers of these continents. These features are related to intense pollution in the much more confined regions with heavy burning. These emissions also translocate nitrogen thousands of kilometers in the tropical ecosystems, with large fixed-nitrogen losses balanced partially by locally intense fertilization downwind, where nitric acid is rained out. At a much larger scale, various satellite measurements have indicated the escape of carbon monoxide and ozone into large filaments which extend across the Tropical and Southern Atlantic Ocean. Our work relates the source emissions, estimated in part from remote sensing, in part from conventional surface reports, to the concentrations of these gases over these intercontinental regions. We will mention work in progress to use meteorological satellite data (AVHRR, GOES, and Meteosat) to estimate the surface temperature and extent and height of clouds, and explain why these uses are so important in our computer simulations of global biogeochemistry. We will compare our simulations and interpretation of remote observations to the international cooperation involving Brazil, South Africa, and the USA in the TRACE-A (Transport and Atmospheric Chemistry near the Equator - Atlantic) and SAFARI (Southern Africa Fire Atmosphere Research Initiative) and remote-sensing /aircraft/ecosystem observational campaigns.

Accomplishments of the MUSICA project to provide accurate, long-term, global and high-resolution observations of tropospheric {H2O,δD} pairs - a review

NASA Astrophysics Data System (ADS)

Schneider, Matthias; Wiegele, Andreas; Barthlott, Sabine; González, Yenny; Christner, Emanuel; Dyroff, Christoph; García, Omaira E.; Hase, Frank; Blumenstock, Thomas; Sepúlveda, Eliezer; Mengistu Tsidu, Gizaw; Takele Kenea, Samuel; Rodríguez, Sergio; Andrey, Javier

2016-07-01

In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

NASA Remote Sensing Observations for Water Resource and Infrastructure Management

NASA Astrophysics Data System (ADS)

Granger, S. L.; Armstrong, L.; Farr, T.; Geller, G.; Heath, E.; Hyon, J.; Lavoie, S.; McDonald, K.; Realmuto, V.; Stough, T.; Szana, K.

2008-12-01

Decision support tools employed by water resource and infrastructure managers often utilize data products obtained from local sources or national/regional databases of historic surveys and observations. Incorporation of data from these sources can be laborious and time consuming as new products must be identified, cleaned and archived for each new study site. Adding remote sensing observations to the list of sources holds promise for a timely, consistent, global product to aid decision support at regional and global scales by providing global observations of geophysical parameters including soil moisture, precipitation, atmospheric temperature, derived evapotranspiration, and snow extent needed for hydrologic models and decision support tools. However, issues such as spatial and temporal resolution arise when attempting to integrate remote sensing observations into existing decision support tools. We are working to overcome these and other challenges through partnerships with water resource managers, tool developers and other stakeholders. We are developing a new data processing framework, enabled by a core GIS server, to seamlessly pull together observations from disparate sources for synthesis into information products and visualizations useful to the water resources community. A case study approach is being taken to develop the system by working closely with water infrastructure and resource managers to integrate remote observations into infrastructure, hydrologic and water resource decision tools. We present the results of a case study utilizing observations from the PALS aircraft instrument as a proxy for NASA's upcoming Soil Moisture Active Passive (SMAP) mission and an existing commercial decision support tool.

Remote sensing of the boundary layer over the oceans. [by IRIS measurements

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Dalu, G.; Nath, N. R.; Lo, R.

1978-01-01

The paper explores the possibility of remotely sensing the boundary layer structure over the oceans by means of the Nimbus 4 IR Interferometric Spectrometer (IRIS) measurements in the water vapor bands. It is found from theoretical considerations that the moderately strong spectral lines in the 9-micron water vapor window region contain useful information about the lowest layers in the atmosphere. The difference between the observed line strength and the theoretically predicted line strength provides information about the departure in the atmospheric temperature and water vapor profiles from standard conditions. The observations of METEOR oceanographic expedition over the North and South Atlantic, and the Indian Ocean expedition make it possible to model the inversion conditions. It is concluded that significant characteristics of the temperature and water vapor profiles in the boundary layer of the atmosphere can be remotely sensed using the water vapor spectral measurements over the oceans.

The Earth Observation Technology Cluster

NASA Astrophysics Data System (ADS)

Aplin, P.; Boyd, D. S.; Danson, F. M.; Donoghue, D. N. M.; Ferrier, G.; Galiatsatos, N.; Marsh, A.; Pope, A.; Ramirez, F. A.; Tate, N. J.

2012-07-01

The Earth Observation Technology Cluster is a knowledge exchange initiative, promoting development, understanding and communication about innovative technology used in remote sensing of the terrestrial or land surface. This initiative provides an opportunity for presentation of novel developments from, and cross-fertilisation of ideas between, the many and diverse members of the terrestrial remote sensing community. The Earth Observation Technology Cluster involves a range of knowledge exchange activities, including organisation of technical events, delivery of educational materials, publication of scientific findings and development of a coherent terrestrial EO community. The initiative as a whole covers the full range of remote sensing operation, from new platform and sensor development, through image retrieval and analysis, to data applications and environmental modelling. However, certain topical and strategic themes have been selected for detailed investigation: (1) Unpiloted Aerial Vehicles, (2) Terrestrial Laser Scanning, (3) Field-Based Fourier Transform Infra-Red Spectroscopy, (4) Hypertemporal Image Analysis, and (5) Circumpolar and Cryospheric Application. This paper presents general activities and achievements of the Earth Observation Technology Cluster, and reviews state-of-the-art developments in the five specific thematic areas.

REMOTE SENSING TECHNOLOGIES APPLICATIONS RESEARCH

EPA Science Inventory

Remote sensing technologies applications research supports the ORD Landscape Sciences Program (LSP) in two separate areas: operational remote sensing, and remote sensing research and development. Operational remote sensing is provided to the LSP through the use of current and t...

High Performance Parallel Architectures

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek; Kaewpijit, Sinthop

1998-01-01

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operational. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, aimed at concentrating the vital information and discarding redundant data. One such transformation, which is widely used in remote sensing, is the Principal Components Analysis (PCA). This report summarizes our progress on the development of a parallel PCA and its implementation on two Beowulf cluster configuration; one with fast Ethernet switch and the other with a Myrinet interconnection. Details of the implementation and performance results, for typical sets of multispectral and hyperspectral NASA remote sensing data, are presented and analyzed based on the algorithm requirements and the underlying machine configuration. It will be shown that the PCA application is quite challenging and hard to scale on Ethernet-based clusters. However, the measurements also show that a high- performance interconnection network, such as Myrinet, better matches the high communication demand of PCA and can lead to a more efficient PCA execution.

A Citizen Science Campaign to Validate Snow Remote-Sensing Products

NASA Astrophysics Data System (ADS)

Wikstrom Jones, K.; Wolken, G. J.; Arendt, A. A.; Hill, D. F.; Crumley, R. L.; Setiawan, L.; Markle, B.

2017-12-01

The ability to quantify seasonal water retention and storage in mountain snow packs has implications for an array of important topics, including ecosystem function, water resources, hazard mitigation, validation of remote sensing products, climate modeling, and the economy. Runoff simulation models, which typically rely on gridded climate data and snow remote sensing products, would be greatly improved if uncertainties in estimates of snow depth distribution in high-elevation complex terrain could be reduced. This requires an increase in the spatial and temporal coverage of observational snow data in high-elevation data-poor regions. To this end, we launched Community Snow Observations (CSO). Participating citizen scientists use Mountain Hub, a multi-platform mobile and web-based crowdsourcing application that allows users to record, submit, and instantly share geo-located snow depth, snow water equivalence (SWE) measurements, measurement location photos, and snow grain information with project scientists and other citizen scientists. The snow observations are used to validate remote sensing products and modeled snow depth distribution. The project's prototype phase focused on Thompson Pass in south-central Alaska, an important infrastructure corridor that includes avalanche terrain and the Lowe River drainage and is essential to the City of Valdez and the fisheries of Prince William Sound. This year's efforts included website development, expansion of the Mountain Hub tool, and recruitment of citizen scientists through a combination of social media outreach, community presentations, and targeted recruitment of local avalanche professionals. We also conducted two intensive field data collection campaigns that coincided with an aerial photogrammetric survey. With more than 400 snow depth observations, we have generated a new snow remote-sensing product that better matches actual SWE quantities for Thompson Pass. In the next phase of the citizen science portion of this project we will focus on expanding our group of participants to a larger geographic area in Alaska, further develop our partnership with Mountain Hub, and build relationships in new communities as we conduct a photogrammetric survey in a different region next year.

Remote sensing strategies for global resource exploration and environmental management

NASA Astrophysics Data System (ADS)

Henderson, Frederick B.

Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources. If, however, satellite producing countries follow the Russian and Indian lead and restrict civil satellite data as tools of their national security and economic policies, remote sensing technology may become internationally competitive in space, redundant, prohibitively expensive, and generally unavailable to the world community.

Multi- and hyperspectral geologic remote sensing: A review

NASA Astrophysics Data System (ADS)

van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie

2012-02-01

Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region allowed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc.). The step toward quantitative and validated (subpixel) surface mineralogic mapping was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectra and to unravel mixed pixel spectra to pure endmember spectra to derive subpixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) data continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly workflows should be multidisciplinary and remote sensing data should be integrated with field observations and subsurface geophysical data to monitor and understand geologic processes.

National Satellite Land Remote Sensing Data Archive

USGS Publications Warehouse

Faundeen, John L.; Longhenry, Ryan

2018-06-13

The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.

Space-Based Remote Sensing of the Earth: A Report to the Congress

NASA Technical Reports Server (NTRS)

1987-01-01

The commercialization of the LANDSAT Satellites, remote sensing research and development as applied to the Earth and its atmosphere as studied by NASA and NOAA is presented. Major gaps in the knowledge of the Earth and its atmosphere are identified and a series of space based measurement objectives are derived. The near-term space observations programs of the United States and other countries are detailed. The start is presented of the planning process to develop an integrated national program for research and development in Earth remote sensing for the remainder of this century and the many existing and proposed satellite and sensor systems that the program may include are described.

The CORSAGE Programme: Continuous Orbital Remote Sensing of Archipelagic Geochemical Effects

NASA Technical Reports Server (NTRS)

Acker, J. G.; Brown, C. W.; Hine, A. C.

1997-01-01

Current and pending oceanographic remote sensing technology allows the conceptualization of a programme designed to investigate ocean island interactions that could induce short-term nearshore fluxes of particulate organic carbon and biogenic calcium carbonate from pelagic island archipelagoes. These events will influence the geochemistry of adjacent waters, particularly the marine carbon system. Justification and design are provided for a study that would combine oceanographic satellite remote sensing (visible and infrared radiometry, altimetry and scatterometry) with shore-based facilities. A programme incorporating the methodology outlined here would seek to identify the mechanisms that cause such events, assess their geochemical significance, and provide both analytical and predictive capabilities for observations on greater temporal and spatial scales.

Remote sensing of selective logging in Amazonia Assessing limitations based on detailed field observations, Landsat ETM+, and textural analysis.

Treesearch

Gregory P. Asner; Michael Keller; Rodrigo Pereira; Johan C. Zweede

2002-01-01

We combined a detailed field study of forest canopy damage with calibrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) reflectance data and texture analysis to assess the sensitivity of basic broadband optical remote sensing to selective logging in Amazonia. Our field study encompassed measurements of ground damage and canopy gap fractions along a chronosequence of...

ISS Has an Attitude! Determining ISS Attitude at the ISS Window Observational Research Facility (WORF) Using Landmarks

NASA Technical Reports Server (NTRS)

Runco, Susan K.; Pickard,Henry; Kowtha, Vijayanand; Jackson, Dan

2011-01-01

Universities and secondary schools can help solve a real issue for remote sensing from the ISS WORF through hands-on engineering and activities. Remote sensing technology is providing scientists with higher resolution, higher sensitivity sensors. Where is it pointing? - To take full advantage of these improved sensors, space platforms must provide commensurate improvements in attitude determination

Comparing near-earth and satellite remote sensing based phenophase estimates: an analysis using multiple webcams and MODIS (Invited)

NASA Astrophysics Data System (ADS)

Hufkens, K.; Richardson, A. D.; Migliavacca, M.; Frolking, S. E.; Braswell, B. H.; Milliman, T.; Friedl, M. A.

2010-12-01

In recent years several studies have used digital cameras and webcams to monitor green leaf phenology. Such "near-surface" remote sensing has been shown to be a cost effective means of accurately capturing phenology. Specifically, it allows for accurate tracking of intra- and inter-annual phenological dynamics at high temporal frequency and over broad spatial scales compared to visual observations or tower-based fAPAR and broadband NDVI measurements. Near surface remote sensing measurements therefore show promise for bridging the gap between traditional in-situ measurements of phenology and satellite remote sensing data. For this work, we examined the relationship between phenophase estimates derived from satellite remote sensing (MODIS) and near-earth remote sensing derived from webcams for a select set of sites with high-quality webcam data. A logistic model was used to characterize phenophases for both the webcam and MODIS data. We documented model fit accuracy, phenophase estimates, and model biases for both data sources. Our results show that different vegetation indices (VI's) derived from MODIS produce significantly different phenophase estimates compared to corresponding estimates derived from webcam data. Different VI's showed markedly different radiometric properties, and as a result, influenced phenophase estimates. The study shows that phenophase estimates are not only highly dependent on the algorithm used but also depend on the VI used by the phenology retrieval algorithm. These results highlight the need for a better understanding of how near-earth and satellite remote data relate to eco-physiological and canopy changes during different parts of the growing season.

Multi-scale assimilation of remotely sensed snow observations for hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, K.; Lettenmaier, D.

2008-12-01

Data assimilation provides a framework for optimally merging model predictions and remote sensing observations of snow properties (snow cover extent, water equivalent, grain size, melt state), ideally overcoming limitations of both. A synthetic twin experiment is used to evaluate a data assimilation system that would ingest remotely sensed observations from passive microwave and visible wavelength sensors (brightness temperature and snow cover extent derived products, respectively) with the objective of estimating snow water equivalent. Two data assimilation techniques are used, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter (EnMKF). One of the challenges inherent in such a data assimilation system is the discrepancy in spatial scales between the different types of snow-related observations. The EnMKF represents the sample model error covariance with a tree that relates the system state variables at different locations and scales through a set of parent-child relationships. This provides an attractive framework to efficiently assimilate observations at different spatial scales. This study provides a first assessment of the feasibility of a system that would assimilate observations from multiple sensors (MODIS snow cover and AMSR-E brightness temperatures) and at different spatial scales for snow water equivalent estimation. The relative value of the different types of observations is examined. Additionally, the error characteristics of both model and observations are discussed.

Tunnel-Site Selection by Remote Sensing Techniques

DTIC Science & Technology

A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave

Remote Sensing of Aerosol and their Radiative Forcing of Climate

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Remer, Lorraine A.

1999-01-01

Remote sensing of aerosol and aerosol radiative forcing of climate is going through a major transformation. The launch in next few years of new satellites designed specifically for remote sensing of aerosol is expected to further revolutionized aerosol measurements: until five years ago satellites were not designed for remote sensing of aerosol. Aerosol optical thickness was derived as a by product, only over the oceans using one AVHRR channel with errors of approx. 50%. However it already revealed a very important first global picture of the distribution and sources of aerosol. In the last 5 years we saw the introduction of polarization and multi-view observations (POLDER and ATSR) for satellite remote sensing of aerosol over land and ocean. Better products are derived from AVHRR using its two channels. The new TOMS aerosol index shows the location and transport of aerosol over land and ocean. Now we anticipate the launch of EOS-Terra with MODIS, MISR and CERES on board for multi-view, multi-spectral remote sensing of aerosol and its radiative forcing. This will allow application of new techniques, e.g. using a wide spectral range (0.55-2.2 microns) to derive precise optical thickness, particle size and mass loading. Aerosol is transparent in the 2.2 microns channel, therefore this channel can be used to detect surface features that in turn are used to derive the aerosol optical thickness in the visible part of the spectrum. New techniques are developed to derive the aerosol single scattering albedo, a measure of absorption of sunlight, and techniques to derive directly the aerosol forcing at the top of the atmosphere. In the last 5 years a global network of sun/sky radiometers was formed, designed to communicate in real time the spectral optical thickness from 50-80 locations every day, every 15 minutes. The sky angular and spectral information is also measured and used to retrieve the aerosol size distribution, refractive index, single scattering albedo and the spectral flux reaching the surface. Effort to introduce remote sensing from lidars will literally additional dimension to aerosol remote sensing. The vertical dimension is a critical link between the global satellite observations and modeling of aerosol transport. Lidars are also critical to study aerosol impact on cloud microphysics and reflectance. Both lidar ground networks and satellite systems are in development. This new capability is expected to put remote sensing in the forefront of aerosol and climate studies. Together with field experiments, chemical analysis and chemical transport models we anticipate, in the next decade, to be able to resolve some of the outstanding questions regarding the role of aerosol in climate, in atmospheric chemistry and its influence on human health and life on this planet.

System and method for evaluating wind flow fields using remote sensing devices

DOEpatents

Schroeder, John; Hirth, Brian; Guynes, Jerry

2016-12-13

The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

Hyperspectral Remote Sensing of Foliar Nitrogen Content

NASA Technical Reports Server (NTRS)

Knyazikhin, Yuri; Schull, Mitchell A.; Stenberg, Pauline; Moettus, Matti; Rautiainen, Miina; Yang, Yan; Marshak, Alexander; Carmona, Pedro Latorre; Kaufmann, Robert K.; Lewis, Philip;

Remote sensing reflectance simulation of coastal optical complex water in the East China Sea

NASA Astrophysics Data System (ADS)

He, Shuo; Lou, Xiulin; Zhang, Huaguo; Zheng, Gang

2018-02-01

In this work, remote sensing reflectance (Rrs) spectra of the Zhejiang coastal water in the East China Sea (ECS) were simulated by using the Hydrolight software with field data as input parameters. The seawater along the Zhejiang coast is typical Case II water with complex optical properties. A field observation was conducted in the Zhejiang coastal region in late May of 2016, and the concentration of ocean color constituents (pigment, SPM and CDOM), IOPs (absorption and backscattering coefficients) and Rrs were measured at 24 stations of 3 sections covering the turbid to clear inshore coastal waters. Referring to these ocean color field data, an ocean color model suitable for the Zhejiang coastal water was setup and applied in the Hydrolight. A set of 11 remote sensing reflectance spectra above water surface were modeled and calculated. Then, the simulated spectra were compared with the filed measurements. Finally, the spectral shape and characteristics of the remote sensing reflectance spectra were analyzed and discussed.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

PubMed Central

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2018-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

High resolution remote sensing information identification for characterizing uranium mineralization setting in Namibia

NASA Astrophysics Data System (ADS)

Zhang, Jie-Lin; Wang, Jun-hu; Zhou, Mi; Huang, Yan-ju; Xuan, Yan-xiu; Wu, Ding

2011-11-01

The modern Earth Observation System (EOS) technology takes important role in the uranium geological exploration, and high resolution remote sensing as one of key parts of EOS is vital to characterize spectral and spatial information of uranium mineralization factors. Utilizing satellite high spatial resolution and hyperspectral remote sensing data (QuickBird, Radarsat2, ASTER), field spectral measurement (ASD data) and geological survey, this paper established the spectral identification characteristics of uranium mineralization factors including six different types of alaskite, lower and upper marble of Rössing formation, dolerite, alkali metasomatism, hematization and chloritization in the central zone of Damara Orogen, Namibia. Moreover, adopted the texture information identification technology, the geographical distribution zones of ore-controlling faults and boundaries between the different strata were delineated. Based on above approaches, the remote sensing geological anomaly information and image interpretation signs of uranium mineralization factors were extracted, the metallogenic conditions were evaluated, and the prospective areas have been predicted.

Small unmanned aircraft systems for remote sensing and Earth science research

NASA Astrophysics Data System (ADS)

Hugenholtz, Chris H.; Moorman, Brian J.; Riddell, Kevin; Whitehead, Ken

2012-06-01

To understand and predict Earth-surface dynamics, scientists often rely on access to the latest remote sensing data. Over the past several decades, considerable progress has been made in the development of specialized Earth observation sensors for measuring a wide range of processes and features. Comparatively little progress has been made, however, in the development of new platforms upon which these sensors can be deployed. Conventional platforms are still almost exclusively restricted to piloted aircraft and satellites. For many Earth science research questions and applications these platforms do not yet have the resolution or operational flexibility to provide answers affordably. The most effective remote sensing data match the spatiotemporal scale of the process or feature of interest. An emerging technology comprising unmanned aircraft systems (UAS), also known as unmanned aerial vehicles (UAV), is poised to offer a viable alternative to conventional platforms for acquiring high-resolution remote sensing data with increased operational flexibility, lower cost, and greater versatility (Figure 1).

[Contribution of remote sensing to malaria control].

PubMed

Machault, V; Pages, F; Rogier, C

2009-04-01

Despite national and international efforts, malaria remains a major public health problem and the fight to control the disease is confronted by numerous hurdles. Study of space and time dynamics of malaria is necessary as a basis for making appropriate decision and prioritizing intervention including in areas where field data are rare and sanitary information systems are inadequate. Evaluation of malarial risk should also help anticipate the risk of epidemics as a basis for early warning systems. Since 1960-70 civilian satellites launched for earth observation have been providing information for the measuring or evaluating geo-climatic and anthropogenic factors related to malaria transmission and burden. Remotely sensed data gathered for several civilian or military studies have allowed setup of entomological, parasitological, and epidemiological risk models and maps for rural and urban areas. Mapping of human populations at risk has also benefited from remotely sensing. The results of the published studies show that remote sensing is a suitable tool for optimizing planning, efficacy and efficiency of malaria control.

Concept for a hyperspectral remote sensing algorithm for floating marine macro plastics.

PubMed

Goddijn-Murphy, Lonneke; Peters, Steef; van Sebille, Erik; James, Neil A; Gibb, Stuart

2018-01-01

There is growing global concern over the chemical, biological and ecological impact of plastics in the ocean. Remote sensing has the potential to provide long-term, global monitoring but for marine plastics it is still in its early stages. Some progress has been made in hyperspectral remote sensing of marine macroplastics in the visible (VIS) to short wave infrared (SWIR) spectrum. We present a reflectance model of sunlight interacting with a sea surface littered with macro plastics, based on geometrical optics and the spectral signatures of plastic and seawater. This is a first step towards the development of a remote sensing algorithm for marine plastic using light reflectance measurements in air. Our model takes the colour, transparency, reflectivity and shape of plastic litter into account. This concept model can aid the design of laboratory, field and Earth observation measurements in the VIS-SWIR spectrum and explain the results. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards.

PubMed

Wright, Daniel B; Mantilla, Ricardo; Peters-Lidard, Christa D

2017-04-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

NASA Technical Reports Server (NTRS)

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2017-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, Rainy Day can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, Rainy Day can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. Rainy Day can be useful for hazard modeling under nonstationary conditions.

Exploring Models and Data for Remote Sensing Image Caption Generation

NASA Astrophysics Data System (ADS)

Lu, Xiaoqiang; Wang, Binqiang; Zheng, Xiangtao; Li, Xuelong

2018-04-01

Inspired by recent development of artificial satellite, remote sensing images have attracted extensive attention. Recently, noticeable progress has been made in scene classification and target detection.However, it is still not clear how to describe the remote sensing image content with accurate and concise sentences. In this paper, we investigate to describe the remote sensing images with accurate and flexible sentences. First, some annotated instructions are presented to better describe the remote sensing images considering the special characteristics of remote sensing images. Second, in order to exhaustively exploit the contents of remote sensing images, a large-scale aerial image data set is constructed for remote sensing image caption. Finally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption. Extensive experiments on the proposed data set demonstrate that the content of the remote sensing image can be completely described by generating language descriptions. The data set is available at https://github.com/201528014227051/RSICD_optimal

A Design of a Novel Airborne Aerosol Spectrometer for Remote Sensing Validation

NASA Astrophysics Data System (ADS)

Adler, G. A.; Brock, C. A.; Dube, W. P.; Erdesz, F.; Gordon, T.; Law, D. C.; Manfred, K.; Mason, B. J.; McLaughlin, R. J.; Richardson, M.; Wagner, N. L.; Washenfelder, R. A.; Murphy, D. M.

2016-12-01

Aerosols and their effect on the radiative properties of clouds contribute one of the largest sources of uncertainty to the Earth's energy budget. Many current global assessments, of atmospheric aerosol radiative forcing rely heavily on remote sensing observation; therefore, in situ aircraft and ground-based measurements are essential for validation of remote sensing measurements. Cavity ringdown spectrometers (CRD) measure aerosol extinction and are commonly used to validate remote sensing observations. These instruments have been deployed on aircraft based platforms over the years thus providing the opportunity to measure these properties over large areas in various conditions. However, deployment of the CRD on an aircraft platform has drawbacks. Typically, aircraft based CRDs draw sampled aerosol into a cabin based instrument through long lengths of tubing. This limits the ability of the instrument to measure: 1) Course mode aerosols (e.g. dust) 2) Aerosols at high relative humidity (above 90%) Here we describe the design of a novel aircraft based open path CRD. The open path CRD is intended to be mounted external to the cabin and has no sample tubing for aerosol delivery, thus measuring optical properties of all aerosol at the ambient conditions. However, the design of an open path CRD for operation on a wing-mounted aircraft platform has certain design complexities. The instrument's special design features include 2 CRD channels, 2 airfoils around the open Path CRD and a configuration which could be easily aligned and rigid at the same time. This novel implementation of cavity ringdown spectroscopy will provide a better assessment of the accuracy of remote sensing satellite measurements

Research on active imaging information transmission technology of satellite borne quantum remote sensing

NASA Astrophysics Data System (ADS)

Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

Introduction to the physics and techniques of remote sensing

NASA Technical Reports Server (NTRS)

Elachi, Charles

1987-01-01

This book presents a comprehensive overview of the basics behind remote-sensing physics, techniques, and technology. The physics of wave/matter interactions, techniques of remote sensing across the electromagnetic spectrum, and the concepts behind remote sensing techniques now established and future ones under development are discussed. Applications of remote sensing are described for a wide variety of earth and planetary atmosphere and surface sciences. Solid surface sensing across the electromagnetic spectrum, ocean surface sensing, basic principles of atmospheric sensing and radiative transfer, and atmospheric remote sensing in the microwave, millimeter, submillimeter, and infrared regions are examined.

Application of remote sensor data to geologic analysis of the Bonanza test site, Colorado

NASA Technical Reports Server (NTRS)

Lee, K. (Compiler)

1972-01-01

A variety of remote sensor data has aided geologic mapping in central Colorado. This report summarizes the application of sensor data to both regional and local geologic mapping and presents some conclusions on the practical use of remote sensing for solving geologic mapping problems. It is emphasized that this study was not conducted primarily to test or evaluate remote sensing systems or data, but, rather, to apply sensor data as an accessory tool for geologic mapping. The remote sensor data used were acquired by the NASA Earth Observations Aircraft Program. Conclusions reached on the utility of the various sensor data and interpretation techniques for geologic mapping were by-products of attempts to use them.

Active and Passive 3D Vector Radiative Transfer with Preferentially-Aligned Ice Particles

NASA Technical Reports Server (NTRS)

Adams, Ian S.; Munchak, Stephen J.; Pelissier, Craig S.; Kuo, Kwo-Sen; Heymsfield, Gerald M.

2017-01-01

For the purposes of interpreting active (radar) and passive (radiometer) microwave and millimeter wave remote sensing data, we have constructed a consistent radiative transfer modeling framework to simulate the responses for arbitrary sensors with differing sensing geometries and hardware configurations. As part of this work, we have implemented a recent method for calculating the electromagnetic properties of individual ice crystals and snow flakes. These calculations will allow us to exploit polarized remote sensing observations to discriminate different particles types and elucidate dynamics of cloud and precipitating systems.

Theory on data processing and instrumentation. [remote sensing

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1978-01-01

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

Scaling from instantaneous remote-sensing-based latent heat flux to daytime integrated value with the help of SiB2

NASA Astrophysics Data System (ADS)

Song, Yi; Ma, Mingguo; Li, Xin; Wang, Xufeng

2011-11-01

This research dealt with a daytime integration method with the help of Simple Biosphere Model, Version 2 (SiB2). The field observations employed in this study were obtained at the Yingke (YK) oasis super-station, which includes an Automatic Meteorological Station (AMS), an eddy covariance (EC) system and a Soil Moisture and Temperature Measuring System (SMTMS). This station is located in the Heihe River Basin, the second largest inland river basin in China. The remotely sensed data and field observations employed in this study were derived from Watershed Allied Telemetry Experimental Research (WATER). Daily variations of EF in temporal and spatial scale would be detected by using SiB2. An instantaneous midday EF was calculated based on a remote-sensing-based estimation of surface energy budget. The invariance of daytime EF was examined using the instantaneous midday EF calculated from a remote-sensing-based estimation. The integration was carried out using the constant EF method in the intervals with a steady EF. Intervals with an inconsistent EF were picked up and ET in these intervals was integrated separately. The truth validation of land Surface ET at satellite pixel scale was carried out using the measurement of eddy covariance (EC) system.

[Thematic Issue: Remote Sensing.

ERIC Educational Resources Information Center

Howkins, John, Ed.

1978-01-01

Four of the articles in this publication discuss the remote sensing of the Earth and its resources by satellites. Among the topics dealt with are the development and management of remote sensing systems, types of satellites used for remote sensing, the uses of remote sensing, and issues involved in using information obtained through remote…

75 FR 65304 - Advisory Committee on Commercial Remote Sensing (ACCRES); Request for Nominations

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-22

... Commercial Remote Sensing (ACCRES); Request for Nominations AGENCY: National Oceanic and Atmospheric... Commercial Remote Sensing (ACCRES). SUMMARY: The Advisory Committee on Commercial Remote Sensing (ACCRES) was... Atmosphere, on matters relating to the U.S. commercial remote sensing industry and NOAA's activities to carry...

Two Optical Atmospheric Remote Sensing Techniques and AN Associated Analytic Solution to a Class of Integral Equations

NASA Astrophysics Data System (ADS)

Manning, Robert Michael

This work concerns itself with the analysis of two optical remote sensing methods to be used to obtain parameters of the turbulent atmosphere pertinent to stochastic electromagnetic wave propagation studies, and the well -posed solution to a class of integral equations that are central to the development of these remote sensing methods. A remote sensing technique is theoretically developed whereby the temporal frequency spectrum of the scintillations of a stellar source or a point source within the atmosphere, observed through a variable radius aperture, is related to the space-time spectrum of atmospheric scintillation. The key to this spectral remote sensing method is the spatial filtering performed by a finite aperture. The entire method is developed without resorting to a priori information such as results from stochastic wave propagation theory. Once the space-time spectrum of the scintillations is obtained, an application of known results of atmospheric wave propagation theory and simple geometric considerations are shown to yield such important information such as the spectrum of atmospheric turbulence, the cross-wind velocity, and the path profile of the atmospheric refractive index structure parameter. A method is also developed to independently verify the Taylor frozen flow hypothesis. The success of the spectral remote sensing method relies on the solution to a Fredholm integral equation of the first kind. An entire class of such equations, that are peculiar to inverse diffraction problems, is studied and a well-posed solution (in the sense of Hadamard) is obtained and probed. Conditions of applicability are derived and shown not to limit the useful operating range of the spectral remote sensing method. The general integral equation solution obtained is then applied to another remote sensing problem having to do with the characterization of the particle size distribution to atmospheric aerosols and hydrometeors. By measuring the diffraction pattern in the focal plane of a lens created by the passage of a laser beam through a distribution of particles, it is shown that the particle-size distribution of the particles can be obtained. An intermediate result of the analysis also gives the total volume concentration of the particles.

Spatial Statistical Data Fusion (SSDF)

NASA Technical Reports Server (NTRS)

Braverman, Amy J.; Nguyen, Hai M.; Cressie, Noel

2013-01-01

As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is fundamentally different than other approaches to data fusion for remote sensing data because it is inferential rather than merely descriptive. All approaches combine data in a way that minimizes some specified loss function. Most of these are more or less ad hoc criteria based on what looks good to the eye, or some criteria that relate only to the data at hand.

Alaska Testbed for the Fusion of Citizen Science and Remote Sensing of Sea Ice and Snow

NASA Astrophysics Data System (ADS)

Walsh, J. E.; Sparrow, E.; Lee, O. A.; Brook, M.; Brubaker, M.; Casas, J.

2017-12-01

Citizen science, remote sensing and related environmental information sources for the Alaskan Arctic are synthesized with the objectives of (a) placing local observations into a broader geospatial framework and (b) enabling the use of local observations to evaluate sea ice, snow and land surface products obtained from remote sensing. In its initial phase, the project instituted a coordinated set of community-based observations of sea ice and snow in three coastal communities in western and northern Alaska: Nome, Point Hope and Barrow. Satellite maps of sea ice concentration have been consolidated with the in situ reports, leading to a three-part depiction of surface conditions at each site: narrative reports, surface-based photos, and satellite products. The project has developed a prototype visualization package, enabling users to select a location and date for which the three information sources can be viewed. Visual comparisons of the satellite products and the local reports show generally consistent depictions of the sea ice concentrations in the vicinity of the coastlines, although the satellite products are generally biased low, especially in coastal regions where shorefast ice persists after the appearance of open water farther offshore. A preliminary comparison of the local snow reports and the MODIS daily North American snow cover images indicates that areas of snow persisted in the satellite images beyond the date of snow disappearance reported by the observers. The "in-town" location of most of the snow reports is a factor that must be addressed in further reporting and remote sensing comparisons.

Research on optimal path planning algorithm of task-oriented optical remote sensing satellites

NASA Astrophysics Data System (ADS)

Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng

2015-08-01

GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.

a Framework for Capacity Building in Mapping Coastal Resources Using Remote Sensing in the Philippines

NASA Astrophysics Data System (ADS)

Tamondong, A.; Cruz, C.; Ticman, T.; Peralta, R.; Go, G. A.; Vergara, M.; Estabillo, M. S.; Cadalzo, I. E.; Jalbuena, R.; Blanco, A.

2016-06-01

Remote sensing has been an effective technology in mapping natural resources by reducing the costs and field data gathering time and bringing in timely information. With the launch of several earth observation satellites, an increase in the availability of satellite imageries provides an immense selection of data for the users. The Philippines has recently embarked in a program which will enable the gathering of LiDAR data in the whole country. The capacity of the Philippines to take advantage of these advancements and opportunities is lacking. There is a need to transfer the knowledge of remote sensing technology to other institutions to better utilize the available data. Being an archipelagic country with approximately 36,000 kilometers of coastline, and most of its people depending on its coastal resources, remote sensing is an optimal choice in mapping such resources. A project involving fifteen (15) state universities and colleges and higher education institutions all over the country headed by the University of the Philippines Training Center for Applied Geodesy and Photogrammetry and funded by the Department of Science and Technology was formed to carry out the task of capacity building in mapping the country's coastal resources using LiDAR and other remotely sensed datasets. This paper discusses the accomplishments and the future activities of the project.

EROS: A space program for Earth resources

USGS Publications Warehouse

Metz, G.G.; Wiepking, P.J.

1980-01-01

Within the technology of the space age lies a key to increased knowledge about the resources and environment of the Earth. This key is remote sensing detecting the nature of an object without actually touching it. Although the photographic camera is the most familiar remote-sensing device, other instrument systems, such as scanning radiometers and radar, also can produce photographs and images. On the basis of the potential of this technology, and in response to the critical need for greater knowledge of the Earth and its resources, the Department of the Interior established the Earth Resources Observation Systems (EROS) Program to gather and use remotely sensed data collected by satellite and aircraft of natural and manmade features on the Earth's surface.

Research of BRDF effects on remote sensing imagery

NASA Astrophysics Data System (ADS)

Nina, Peng; Kun, Wang; Tao, Li; Yang, Pan

2011-08-01

The gray distribution and contrast of the optical satellite remote sensing imagery in the same kind of ground surface acquired by sensor is quite different, it depends not only on the satellite's observation and the sun incidence orientation but also the structural and optical properties of the surface. Therefore, the objectives of this research are to analyze the different BRDF characters of soil, vegetation, water and urban surface and also their BRDF effects on the quality of satellite image through 6S radiative transfer model. Furthermore, the causation of CCD blooming and spilling by ground reflectance is discussed by using QUICKBIRD image data and the corresponding ground image data. The general conclusion of BRDF effects on remote sensing imagery is proposed.

Literature relevant to remote sensing of water quality

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Marcell, R. F.

1983-01-01

References relevant to remote sensing of water quality were compiled, organized, and cross-referenced. The following general categories were included: (1) optical properties and measurement of water characteristics; (2) interpretation of water characteristics by remote sensing, including color, transparency, suspended or dissolved inorganic matter, biological materials, and temperature; (3) application of remote sensing for water quality monitoring; (4) application of remote sensing according to water body type; and (5) manipulation, processing and interpretation of remote sensing digital water data.

Learning Methods of Remote Sensing In the 2013 Curriculum of Secondary School

NASA Astrophysics Data System (ADS)

Lili Somantri, Nandi

2016-11-01

The new remote sensing material included in the subjects of geography in the curriculum of 1994. For geography teachers generation of 90s and over who in college do not get the material remote sensing, for teaching is a tough matter. Most teachers only give a theoretical matter, and do not carry out practical reasons in the lack of facilities and infrastructure of computer laboratories. Therefore, in this paper studies the importance about the method or manner of teaching remote sensing material in schools. The purpose of this paper is 1) to explain the position of remote sensing material in the study of geography, 2) analyze the Geography Curriculum 2013 Subjects related to remote sensing material, 3) describes a method of teaching remote sensing material in schools. The method used in this paper is a descriptive analytical study supported by the literature. The conclusion of this paper that the position of remote sensing in the study of geography is a method or a way to obtain spatial data earth's surface. In the 2013 curriculum remote sensing material has been applied to the study of land use and transportation. Remote sensing methods of teaching must go through a practicum, which starts from the introduction of the theory of remote sensing, data extraction phase of remote sensing imagery to produce maps, both visually and digitally, field surveys, interpretation of test accuracy, and improved maps.

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

JPRS Report, Science & Technology, China, Remote Sensing Systems, Applications.

DTIC Science & Technology

1991-01-17

Partial Contents: Short Introduction to Nation’s Remote Sensing Units, Domestic Airborne Remote - Sensing System, Applications in Monitoring Natural...Disasters, Applications of Imagery From Experimental Satellites Launched in 1985, 1986, Current Status, Future Prospects for Domestic Remote - Sensing -Satellite...Ground Station, and Radar Remote - Sensing Technology Used to Monitor Yellow River Delta,

Progress in remote sensing (1972-1976)

USGS Publications Warehouse

Fischer, W. A.; Hemphill, W.R.; Kover, Allan

1976-01-01

This report concerns the progress in remote sensing during the period 1972–1976. Remote sensing has been variously defined but is basically the art or science of telling something about an object without touching it. During the past four years, the major research thrusts have been in three areas: (1) computer-assisted enhancement and interpretation systems; (2) earth science applications of Landsat data; (3) and investigations of the usefulness of observations of luminescence, thermal infrared, and microwave energies. Based on the data sales at the EROS Data Center, the largest users of the Landsat data are industrial companies, followed by government agencies (both national and foreign), and academic institutions. Thermal surveys from aircraft have become largely operational, however, significant research is being undertaken in the field of thermal modeling and analysis of high altitude images. Microwave research is increasing rapidly and programs are being developed for satellite observations. Microwave research is concentrating on oil spill detection, soil moisture measurement, and observations of ice distributions. Luminescence investigations offer promise for becoming a quantitative method of assessing vegetation stress and pollutant concentrations.

A telescopic cinema sound camera for observing high altitude aerospace vehicles

NASA Astrophysics Data System (ADS)

Slater, Dan

2014-09-01

Rockets and other high altitude aerospace vehicles produce interesting visual and aural phenomena that can be remotely observed from long distances. This paper describes a compact, passive and covert remote sensing system that can produce high resolution sound movies at >100 km viewing distances. The telescopic high resolution camera is capable of resolving and quantifying space launch vehicle dynamics including plume formation, staging events and payload fairing jettison. Flight vehicles produce sounds and vibrations that modulate the local electromagnetic environment. These audio frequency modulations can be remotely sensed by passive optical and radio wave detectors. Acousto-optic sensing methods were primarily used but an experimental radioacoustic sensor using passive micro-Doppler radar techniques was also tested. The synchronized combination of high resolution flight vehicle imagery with the associated vehicle sounds produces a cinema like experience that that is useful in both an aerospace engineering and a Hollywood film production context. Examples of visual, aural and radar observations of the first SpaceX Falcon 9 v1.1 rocket launch are shown and discussed.

Remote distinction of a noxious weed (musk thistle: Carduus nutans) using airborne hyperspectral imagery and the support vector machine classifier

USDA-ARS?s Scientific Manuscript database

Remote detection of invasive plant species using geospatial imagery may significantly improve monitoring, planning, and management practices by eliminating shortfalls such as observer bias and accessibility involved in ground-based surveys. The use of remote sensing for accurate mapping invasion ex...

Software for a GPS-Reflection Remote-Sensing System

NASA Technical Reports Server (NTRS)

Lowe, Stephen

2003-01-01

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. II - Marine stratocumulus observations

NASA Technical Reports Server (NTRS)

Nakajima, Teruyuki; King, Michael D.; Spinhirne, James D.; Radke, Lawrence F.

1991-01-01

A multispectral scanning radiometer has been used to obtain measurements of the reflection function of marine stratocumulus clouds at 0.75 micron and at 1.65 and 2.16 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE, conducted off the coast of southern California during July 1987. Multispectral images of the reflection function were used to derive the optical thickness and the effective particle radius of stratiform cloud layers on four days. In addition to the radiation measurements, in situ microphysical measurements were obtained from an aircraft. In this paper, the remote sensing results are compared with in situ observations, which show a good spatial correlation for both optical thickness and effective radius. These comparisons further show systematic differences between remote sensing and in situ values, with a tendency for remote sensing to overestimate the effective radius by about 2-3 microns, independent of particle radius. The optical thickness, in contrast, is somewhat overestimated for small optical thicknesses and underestimated for large optical thicknesses. An introduction of enhanced gaseous absorption at a wavelength of 2.16 microns successfully explains some of these observed discrepancies.

Interannual variation of the surface temperature of tropical forests from satellite observations

DOE PAGES

Gao, Huilin; Zhang, Shuai; Fu, Rong; ...

2016-01-01

Land surface temperatures (LSTs) within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS), providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability ofmore » cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Lastly, the differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP) reanalysis data).« less

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modeling

NASA Astrophysics Data System (ADS)

Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

2015-09-01

The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather high temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes, a simple dynamics model of the Asai-Kasahara (AK) type is combined with detailed spectral microphysics (SPECS) forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics, as well as main cloud features, to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity), whereas the ice phase is much more sensitive to the microphysical parameters (ice nucleating particle (INP) number, ice particle shape). The choice of ice particle shape may induce large uncertainties that are on the same order as those for the temperature-dependent INP number distribution.

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modelling

NASA Astrophysics Data System (ADS)

Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

2015-01-01

The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

PubMed

Qiu, Guo Yu; Zhao, Ming

2010-03-01

Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

Remote sensing in biological oceanography

NASA Technical Reports Server (NTRS)

Esaias, W. E.

1981-01-01

The main attribute of remote sensing is seen as its ability to measure distributions over large areas on a synoptic basis and to repeat this coverage at required time periods. The way in which the Coastal Zone Color Scanner, by showing the distribution of chlorophyll a, can locate areas productive in both phytoplankton and fishes is described. Lidar techniques are discussed, and it is pointed out that lidar will increase the depth range for observations.

Remote sensing and geologic studies of the planetary crusts

NASA Technical Reports Server (NTRS)

Hawke, B. R.

1983-01-01

Dark haloed craters and regions of the Moon which were sites of ancient volcanism were remotely sensed as well as KREEP deposits in the Inbrium region. The relationship between geology and geochemistry in the Undarum/Spumans region was also examined. Results are summarized for observations of the Reiner Gamma formation, studies of impact cratering mechanics and processes, spectral variations of asteroidal surfaces, albedo and color variations on Ganymede, and studies of lunar impact structures.

Role of Remotely Sensed Observations and Computational Systems in Support of Decision-Making in Developing and Fragile States

NASA Technical Reports Server (NTRS)

Khan, Maudood; Rickman, Doug; Limaye, Ashutosh; Crosson, Bill; Layman, Charles; Hemmings, Sarah

2010-01-01

The topics covered in this slide presentation are: (1) Post-war growth of U.S scientific enterprise, (2) Success of air quality regulations, (3) Complexity and coupled systems, (4) Advances in remote sensing technology, (5) Development planning in the 21stcentury, (5a) The challenge for policy maker and scientist, (5b) Decision-making science, (5c) Role of public-private partnerships.

Remote monitoring of the Gravelly Run thermal plume at Hopewell and the thermal plume at the Surry Nuclear Power Plant on the James River

NASA Technical Reports Server (NTRS)

Talay, T. A.; Sykes, K. W.; Kuo, C. Y.

1979-01-01

On May 17, 1977, a remote sensing experiment was conducted on the James River, Virginia, whereby thermal spectrometer and near-infrared photography data of thermal discharges at Hopewell and the Surry nuclear power plant were obtained by an aircraft for one tidal cycle. These data were used in subsequent investigations into the near field discharge trajectories. For the Gravelly Run thermal plume at Hopewell, several empirical expressions for the plume centerline were evaluated by comparisons of the computed trajectories and those observed in the remote sensing images.

Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science

NASA Astrophysics Data System (ADS)

Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.

2017-09-01

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

An integrated multiscale river basin observing system in the Heihe River Basin, northwest China

NASA Astrophysics Data System (ADS)

Li, X.; Liu, S.; Xiao, Q.; Ma, M.; Jin, R.; Che, T.

2015-12-01

Using the watershed as the unit to establish an integrated watershed observing system has been an important trend in integrated eco-hydrologic studies in the past ten years. Thus far, a relatively comprehensive watershed observing system has been established in the Heihe River Basin, northwest China. In addition, two comprehensive remote sensing hydrology experiments have been conducted sequentially in the Heihe River Basin, including the Watershed Allied Telemetry Experimental Research (WATER) (2007-2010) and the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) (2012-2015). Among these two experiments, an important result of WATER has been the generation of some multi-scale, high-quality comprehensive datasets, which have greatly supported the development, improvement and validation of a series of ecological, hydrological and quantitative remote-sensing models. The goal of a breakthrough for solving the "data bottleneck" problem has been achieved. HiWATER was initiated in 2012. This project has established a world-class hydrological and meteorological observation network, a flux measurement matrix and an eco-hydrological wireless sensor network. A set of super high-resolution airborne remote-sensing data has also been obtained. In addition, there has been important progress with regard to the scaling research. Furthermore, the automatic acquisition, transmission, quality control and remote control of the observational data has been realized through the use of wireless sensor network technology. The observation and information systems have been highly integrated, which will provide a solid foundation for establishing a research platform that integrates observation, data management, model simulation, scenario analysis and decision-making support to foster 21st-century watershed science in China.

Using Copernicus earth observation services to monitor climate change impacts and adaptations

NASA Astrophysics Data System (ADS)

Becker, Daniel; Zebisch, Marc; Sonnenschein, Ruth; Schönthaler, Konstanze; von Andrian-Werburg, Stefan

2016-04-01

In the last years, earth observation made a big leap towards an operational monitoring of the state of environment. Remote sensing provides for instance information on the dynamics, trends and anomalies of snow and glaciers, vegetation, soil moisture or water temperature. In particular, the European Copernicus initiative offers new opportunities through new satellites with a higher temporal and spatial resolution, operational services for environmental monitoring and an open data access policy. With the Copernicus climate change service and the ESA climate change initiative, specific earth observation programs are in place to address the impacts of climate change. However, such products and services are until now rarely picked up in the field of policy or decision making oriented climate impact or climate risk assessments. In this talk, we will present results of a study, which focus on the question, if and how remote sensing approaches could be integrated into operational monitoring activities of climate impacts and response measures on a national and subnational scale. We assessed all existing and planned Copernicus services regarding their relevance for climate impact monitoring by comparing them against the indication fields from an indicator system for climate impact and response monitoring in Germany, which has lately been developed in the framework of the German national adaptation strategy. For several climate impact or response indicators, an immediate integration of remote sensing data could be identified and been recommended. For these cases, we will show practical examples on the benefit of remote sensing data. For other indication fields, promising approaches were found, which need further development. We argue that remote sensing is a very valuable complement to the existing indicator schemes by contributing with spatial explicit, timely information but not always easy to integrate with classical approaches, which are oriented towards consistent long term monitoring. Furthermore, we provide specific recommendations for the Copernicus services to ensure a consistent climate change monitoring in future and we indicate options and limitations for integrating service products into practical assessment and monitoring activities.

Investigation of Arctic mixed-phase clouds by combining airborne remote sensing and in situ observations during VERDI, RACEPAC and ACLOUD

NASA Astrophysics Data System (ADS)

Ehrlich, André; Bierwirth, Eike; Borrmann, Stephan; Crewell, Susanne; Herber, Andreas; Hoor, Peter; Jourdan, Olivier; Krämer, Martina; Lüpkes, Christof; Mertes, Stephan; Neuber, Roland; Petzold, Andreas; Schnaiter, Martin; Schneider, Johannes; Weigel, Ralf; Weinzierl, Bernadett; Wendisch, Manfred

2016-04-01

To improve our understanding of Arctic mixed-phase clouds a series of airborne research campaigns has been initiated by a collaboration of German research institutes. Clouds in areas dominated by a close sea-ice cover were observed during the research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) and the Radiation-Aerosol-Cloud Experiment in the Arctic Circle (RACEPAC, April/May 2014) which both were based in Inuvik, Canada. The aircraft (Polar 5 & 6, Basler BT-67) operated by the Alfred Wegener Institute for Polar and Marine Research, Germany did cover a wide area above the Canadian Beaufort with in total 149 flight hours (62h during VERDI, 87h during RACEPAC). For May/June 2017 a third campaign ACLOUD (Arctic Clouds - Characterization of Ice, aerosol Particles and Energy fluxes) with base in Svalbard is planned within the Transregional Collaborative Research Centre TR 172 ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3 to investigate Arctic clouds in the transition zone between open ocean and sea ice. The aim of all campaigns is to combine remote sensing and in-situ cloud, aerosol and trace gas measurements to investigate interactions between radiation, cloud and aerosol particles. While during VERDI remote sensing and in-situ measurements were performed by one aircraft subsequently, for RACEPAC and ACLOUD two identical aircraft are coordinated at different altitudes to horizontally collocate both remote sensing and in-situ measurements. The campaign showed that in this way radiative and microphysical processes in the clouds can by studied more reliably and remote sensing methods can be validated efficiently. Here we will illustrate the scientific strategy of the projects including the progress in instrumentation. Differences in the general synoptic and sea ice situation and related changes in cloud properties at the different locations and seasons will be addressed to illustrate the broad spectrum of the observations. Exemplary results will be highlighted.

Remote sensing to detect the movement of wheat curl mites through the spatial spread of virus symptoms, and identification of thrips as predators of wheat curl mites

NASA Astrophysics Data System (ADS)

Stilwell, Abby R.

The wheat curl mite (WCM), Aceria tosichella Keifer, transmits three viruses to winter wheat: wheat streak mosaic virus, High Plains virus, and Triticum mosaic virus. This virus complex causes yellowing of the foliage and stunting of plants. WCMs disperse by wind, and an increased understanding of mite movement and subsequent virus spread is necessary in determining the risk of serious virus infections in winter wheat. These risk parameters will help growers make better decisions regarding WCM management. The objectives of this study were to evaluate the capabilities of remote sensing to identify virus infected plants and to establish the potential of using remote sensing to track virus spread and consequently, mite movement. Although the WCM is small and very hard to track, the viruses it vectors produce symptoms that can be detected with remote sensing. Field plots of simulated volunteer wheat were established between 2006 and 2009, infested with WCMs, and spread mites and virus into adjacent winter wheat. The virus gradients created by WCM movement allowed for the measurement of mite movement potential with both proximal and aerial remote sensing instruments. The ability to detect WCM-vectored viruses with remote sensing was investigated by comparing vegetation indices calculated from proximal remote sensing data to ground truth data obtained in the field. Of the ten vegetation indices tested, the red edge position (REP) index had the best relationship with ground truth data. The spatial spread of virus from WCM source plots was modeled with cokriging. Virus symptoms predicted by cokriging occurred in an oval pattern displaced to the southeast. Data from the spatial spread in small plots of this study were used to estimate the potential sphere of influence for volunteer wheat fields. The impact of thrips on WCM populations was investigated by a series of greenhouse, field, and observational studies. WCM populations in winter wheat increased more slowly when thrips populations were higher, both in the field and in the greenhouse. Two species of thrips, Thrips tabaci Lindeman and Frankliniella occidentalis (Pergande) were observed to feed directly on WCMs. The collective results from this study identify thrips as a regulating factor for WCM populations.

Hyperspectral remote sensing application for monitoring and preservation of plant ecosystems

NASA Astrophysics Data System (ADS)

Krezhova, Dora; Maneva, Svetla; Zdravev, Tomas; Petrov, Nikolay; Stoev, Antoniy

Remote sensing technologies have advanced significantly at last decade and have improved the capability to gather information about Earth’s resources and environment. They have many applications in Earth observation, such as mapping and updating land-use and cover, weather forecasting, biodiversity determination, etc. Hyperspectral remote sensing offers unique opportunities in the environmental monitoring and sustainable use of natural resources. Remote sensing sensors on space-based platforms, aircrafts, or on ground, are capable of providing detailed spectral, spatial and temporal information on terrestrial ecosystems. Ground-based sensors are used to record detailed information about the land surface and to create a data base for better characterizing the objects which are being imaged by the other sensors. In this paper some applications of two hyperspectral remote sensing techniques, leaf reflectance and chlorophyll fluorescence, for monitoring and assessment of the effects of adverse environmental conditions on plant ecosystems are presented. The effect of stress factors such as enhanced UV-radiation, acid rain, salinity, viral infections applied to some young plants (potato, pea, tobacco) and trees (plums, apples, paulownia) as well as of some growth regulators were investigated. Hyperspectral reflectance and fluorescence data were collected by means of a portable fiber-optics spectrometer in the visible and near infrared spectral ranges (450-850 nm and 600-900 nm), respectively. The differences between the reflectance data of healthy (control) and injured (stressed) plants were assessed by means of statistical (Student’s t-criterion), first derivative, and cluster analysis and calculation of some vegetation indices in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (690-720 nm) and near infrared (720-780 nm). Fluorescence spectra were analyzed at five characteristic wavelengths located at the maximums of the emitted radiation and at the forefronts and rear slopes. The strong relationship, which was found between the results from the two remote sensing techniques and some biochemical and serological analyses (stress markers, DAS-ELISA test), indicates the importance of hyperspectral reflectance and fluorescence techniques for conducting, easily and without damage, rapid health condition assessments of vegetation. This study fills in the existed spectral data base and exemplifies the benefits of integrating remote sensing, Earth observation, plant physiology, ecology, and conducting of interdisciplinary investigations of terrestrial ecosystems.

Impact of NO2 horizontal heterogeneity on tropospheric NO2 vertical columns retrieved from satellite, multi-axis differential optical absorption spectroscopy, and in situ measurements

NASA Astrophysics Data System (ADS)

Mendolia, D.; D'Souza, R. J. C.; Evans, G. J.; Brook, J.

2013-01-01

Tropospheric NO2 vertical column densities were retrieved for the first time in Toronto, Canada using three methods of differing spatial scales. Remotely-sensed NO2 vertical column densities, retrieved from multi-axis differential optical absorption spectroscopy and satellite remote sensing, were evaluated by comparison with in situ vertical column densities derived using a pair of chemiluminescence monitors situated 0.01 and 0.5 km above ground level. The chemiluminescence measurements were corrected for the influence of NOz, which reduced the NO2 concentrations at 0.01 and 0.5 km by 8 ± 1% and 12 ± 1%, respectively. The average absolute decrease in the chemiluminescence NO2 measurement as a result of this correction was less than 1 ppb. Good correlation was observed between the remotely sensed and in situ NO2 vertical column densities (Pearson R ranging from 0.68 to 0.79), but the in situ vertical column densities were 27% to 55% greater than the remotely-sensed columns. These results indicate that NO2 horizontal heterogeneity strongly impacted the magnitude of the remotely-sensed columns. The in situ columns reflected an urban environment with major traffic sources, while the remotely-sensed NO2 vertical column densities were representative of the region, which included spatial heterogeneity introduced by residential neighbourhoods and Lake Ontario. Despite the difference in absolute values, the reasonable correlation between the vertical column densities determined by three distinct methods increased confidence in the validity of the values provided by each of the methods.

Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas

NASA Astrophysics Data System (ADS)

Wei, Guifeng; Tang, Danling; Wang, Sufen

Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology.

Remote Sensing Applications to Water Quality Management in Florida

NASA Astrophysics Data System (ADS)

Lehrter, J. C.; Schaeffer, B. A.; Hagy, J.; Spiering, B.; Barnes, B.; Hu, C.; Le, C.; McEachron, L.; Underwood, L. W.; Ellis, C.; Fisher, B.

2013-12-01

Optical datasets from estuarine and coastal systems are increasingly available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data for local and regional coastal water quality management. Our presentation will highlight two recent applications of optical data and remote sensing to water quality decision-making in coastal regions of the state of Florida; (1) informing the development of estuarine and coastal nutrient criteria for the state of Florida and (2) informing the rezoning of the Florida Keys National Marine Sanctuary. These efforts involved building up the underlying science to demonstrate the applicability of satellite data as well as an outreach component to educate decision-makers about the use, utility, and uncertainties of remote sensing data products. Scientific developments included testing existing algorithms and generating new algorithms for water clarity and chlorophylla in case II (CDOM or turbidity dominated) estuarine and coastal waters and demonstrating the accuracy of remote sensing data products in comparison to traditional field based measurements. Including members from decision-making organizations on the research team and interacting with decision-makers early and often in the process were key factors for the success of the outreach efforts and the eventual adoption of satellite data into the data records and analyses used in decision-making. Florida coastal water bodies (black boxes) for which remote sensing imagery were applied to derive numeric nutrient criteria and in situ observations (black dots) used to validate imagery. Florida ocean color applied to development of numeric nutrient criteria

Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2016-12-01

Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

Inroads of remote sensing into hydrologic science during the WRR era

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.; Alsdorf, Doug; Dozier, Jeff; Huffman, George J.; Pan, Ming; Wood, Eric F.

2015-09-01

The first issue of WRR appeared eight years after the launch of Sputnik, but by WRR's 25th anniversary, only seven papers that used remote sensing had appeared. Over the journal's second 25 years, that changed remarkably, and remote sensing is now widely used in hydrology and other geophysical sciences. We attribute this evolution to production of data sets that scientists not well versed in remote sensing can use, and to educational initiatives like NASA's Earth System Science Fellowship program that has supported over a thousand scientists, many in hydrology. We review progress in remote sensing in hydrology from a water balance perspective. We argue that progress is primarily attributable to a creative use of existing and past satellite sensors to estimate such variables as evapotranspiration rates or water storage in lakes and reservoirs and to new and planned missions. Recent transforming technologies include the Gravity Recovery and Climate Experiment (GRACE), the European Soil Moisture and Ocean Salinity (SMOS) and U.S. Soil Moisture Active Passive (SMAP) missions, and the Global Precipitation Measurement (GPM) mission. Future missions include Surface Water and Ocean Topography (SWOT) to measure river discharge and lake, reservoir, and wetland storage. Measurement of some important hydrologic variables remains problematic: retrieval of snow water equivalent (SWE) from space remains elusive especially in mountain areas, even though snow cover extent is well observed, and was the topic of 4 of the first 5 remote sensing papers published in WRR. We argue that this area deserves more strategic thinking from the hydrology community.

Adult mortality in a low-density tree population using high-resolution remote sensing.

PubMed

Kellner, James R; Hubbell, Stephen P

2017-06-01

We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-yr period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage. Using the fraction of 123 individuals from an independent field sample that were detected by satellite data (109 individuals, 88.6%), we estimate that the adult population for this species on BCI was 1,135 individuals. We used a Bayesian state-space model that explicitly accounted for the probability of tree detection and missing observations to compute an annual adult mortality rate of 0.2%·yr -1 (SE = 0.1, 95% CI = 0.06-0.45). An independent estimate of the adult mortality rate from 260 field-checked trees closely matched the landscape-scale estimate (0.33%·yr -1 , SE = 0.16, 95% CI = 0.12-0.74). Our proof-of-concept study shows that one can remotely estimate adult mortality rates for canopy tree species precisely in the presence of variable detection and missing observations. © 2017 by the Ecological Society of America.

Variations in the Characteristics of Craters of the Moon Lava Flows from Vent to Termination: Remotely Sensed Spectra and Field Observations

NASA Astrophysics Data System (ADS)

Hobson, V. R.; Shervais, J. W.

2004-12-01

Developing a method to characterize the physical, chemical and temporal aspects of terrestrial volcanics is a necessary step toward studying volcanics on other planetary bodies. Volcanoes and flows close to populated centers have been studied to varying degree, but remote volcanics remain largely unstudied. Remotely sensed data and derived information can be used to select field sites on Earth and on other planets. Scientists studying volcanics in dangerous areas would benefit from as much advance knowledge of the area as possible before beginning fieldwork. By using satellites and other remote sensing methods, information about the eruptive history can be derived and potentially, the hazard these remote volcanic areas may pose to current and future generations can be estimated. Using Landsat TM, ASTER and other remotely sensed data, the extent and characteristics of lava flows can be examined, but verification and refinement of these methods requires collection of data on the ground. Young lava flows at Craters of the Moon National Park were selected to test methods for remote mapping of recent volcanics. These late Pleistocene to Holocene basalt flows have been mapped to 1:100,000 scale (Kuntz et al, 1988) and have only minor vegetative cover. A range of remotely sensed spectral images were combined to optimize recovery of the mapped flows. Major flow units can be distinguished from each other using unsupervised classification of Landsat TM Bands 1-7, but differentiation of flows within these units presents greater difficulty. Principal component analyses revealed that during the daytime, thermal infrared variations outweigh variations in all other bands. Larger-scale features were observed like edge effects attributable to changes in surface roughness or texture that might occur at flow fronts or at boundaries between flows. Using a digitized version of the geologic map, TM and ASTER data for individual flows were isolated and examined for changes with distance from the source vent or fissure. Several flows were selected for further examination in the field, based on accessibility and scientific interest.

Spatial Inference for Distributed Remote Sensing Data

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Katzfuss, M.; Nguyen, H.

2014-12-01

Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent processes. Geophysical variables such as atmopsheric temperature, cloud properties, humidity, aerosols and carbon dioxide all exhibit spatial patterns, and satellite observations can help us learn about the physical mechanisms driving them. However, remote sensing observations are often noisy and incomplete, so inferring properties of true geophysical fields from them requires some care. These data can also be massive, which is both a blessing and a curse: using more data drives uncertainties down, but also drives costs up, particularly when data are stored on different computers or in different physical locations. In this talk I will discuss a methodology for spatial inference on massive, distributed data sets that does not require moving large volumes of data. The idea is based on a combination of ideas including modeling spatial covariance structures with low-rank covariance matrices, and distributed estimation in sensor or wireless networks.

Assimilation of Passive and Active Microwave Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.

2012-01-01

Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.

Applications of a High-Altitude Powered Platform (HAPP)

NASA Technical Reports Server (NTRS)

Kuhner, M. B.; Earhart, R. W.; Madigan, J. A.; Ruck, G. T.

1977-01-01

A list of potential uses for the (HAPP) and conceptual system designs for a small subset of the most promising applications were investigated. The method was to postulate a scenario for each application specifying a user, a set of system requirements and the most likely competitor among conventional aircraft and satellite systems. As part of the study of remote sensing applications, a parametric cost comparison was done between aircraft and HAPPS. For most remote sensing applications, aircraft can supply the same data as HAPPs at substantially lower cost. The critical parameters in determining the relative costs of the two systems are the sensor field of view and the required frequency of the observations being made. The HAPP is only competitive with an airplane when sensors having a very wide field of view are appropriate and when the phenomenon being observed must be viewed at least once per day. This eliminates the majority of remote sensing applications from any further consideration.

Remote sensing of surface currents with single shipborne high-frequency surface wave radar

NASA Astrophysics Data System (ADS)

Wang, Zhongbao; Xie, Junhao; Ji, Zhenyuan; Quan, Taifan

2016-01-01

High-frequency surface wave radar (HFSWR) is a useful technology for remote sensing of surface currents. It usually requires two (or more) stations spaced apart to create a two-dimensional (2D) current vector field. However, this method can only obtain the measurements within the overlapping coverage, which wastes most of the data from only one radar observation. Furthermore, it increases observation's costs significantly. To reduce the number of required radars and increase the ocean area that can be measured, this paper proposes an economical methodology for remote sensing of the 2D surface current vector field using single shipborne HFSWR. The methodology contains two parts: (1) a real space-time multiple signal classification (MUSIC) based on sparse representation and unitary transformation techniques is developed for measuring the radial currents from the spreading first-order spectra, and (2) the stream function method is introduced to obtain the 2D surface current vector field. Some important conclusions are drawn, and simulations are included to validate the correctness of them.

Historical record of Landsat global coverage

USGS Publications Warehouse

Goward, Samuel; Arvidson, Terry; Williams, Darrel; Faundeen, John; Irons, James; Franks, Shannon

2006-01-01

The long-term, 34+ year record of global Landsat remote sensing data is a critical resource to study the Earth system and human impacts on this system. The National Satellite Land Remote Sensing Data Archive (NSLRSDA) is charged by public law to: “maintain a permanent, comprehensive Government archive of global Landsat and other land remote sensing data for long-term monitoring and study of the changing global environment” (U.S. Congress, 1992). The advisory committee for NSLRSDA requested a detailed analysis of observation coverage within the U.S. Landsat holdings, as well as that acquired and held by International Cooperator (IC) stations. Our analyses, to date, have found gaps of varying magnitude in U.S. holdings of Landsat global coverage data, which appear to reflect technical or administrative variations in mission operations. In many cases it may be possible to partially fill these gaps in U.S. holdings through observations that were acquired and are now being held at International Cooperator stations.

Program on Earth Observation Data Management Systems (EODMS)

NASA Technical Reports Server (NTRS)

Eastwood, L. F., Jr.; Gohagan, J. K.; Hill, C. T.; Morgan, R. P.; Hays, T. R.; Ballard, R. J.; Crnkovick, G. R.; Schaeffer, M. A.

1976-01-01

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.

Integrated solution for the complete remote sensing process - Earth Observation Mission Control Centre (EOMC2)

NASA Astrophysics Data System (ADS)

Czapski, Paweł

2016-07-01

We are going to show the latest achievements of the Remote Sensing Division of the Institute of Aviation in the area of remote sensing, i.e. the project of the integrated solution for the whole remote sensing process ranging from acquiring to providing the end user with required information. Currently, these tasks are partially performed by several centers in Poland, however there is no leader providing an integrated solution. Motivated by this fact, the Earth Observation Mission Control Centre (EOMC2) was established in the Remote Sensing Division of the Institute of Aviation that will provide such a comprehensive approach. Establishing of EOMC2 can be compared with creating Data Center Aerial and Satellite Data Centre (OPOLIS) in the Institute of Geodesy and Cartography in the mid-70s in Poland. OPOLIS was responsible for broadly defined data processing, it was a breakthrough innovation that initiated the use of aerial image analysis in Poland. Operation center is a part of the project that will be created, which in comparison with the competitors will provide better solutions, i.e.: • Centralization of the acquiring, processing, publishing and archiving of data, • Implementing elements of the INSPIRE directive recommendations on spatial data management, • Providing the end-user with information in the near real-time, • Ability of supplying the system with images of various origin (aerial, satellite, e.g. EUMETCast, Sentinel, Landsat) and diversity of telemetry data, data aggregation and using the same algorithms to images obtained from different sources, • System reconfiguration and batch processing of large data sets at any time, • A wide range of potential applications: precision agriculture, environmental protection, crisis management and national security, aerial, small satellite and sounding rocket missions monitoring.

Implications of sampling design and sample size for national carbon accounting systems.

PubMed

Köhl, Michael; Lister, Andrew; Scott, Charles T; Baldauf, Thomas; Plugge, Daniel

2011-11-08

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources. We compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives. Our results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

Modeling Atmospheric CO2 Processes to Constrain the Missing Sink

NASA Technical Reports Server (NTRS)

Kawa, S. R.; Denning, A. S.; Erickson, D. J.; Collatz, J. C.; Pawson, S.

2005-01-01

We report on a NASA supported modeling effort to reduce uncertainty in carbon cycle processes that create the so-called missing sink of atmospheric CO2. Our overall objective is to improve characterization of CO2 source/sink processes globally with improved formulations for atmospheric transport, terrestrial uptake and release, biomass and fossil fuel burning, and observational data analysis. The motivation for this study follows from the perspective that progress in determining CO2 sources and sinks beyond the current state of the art will rely on utilization of more extensive and intensive CO2 and related observations including those from satellite remote sensing. The major components of this effort are: 1) Continued development of the chemistry and transport model using analyzed meteorological fields from the Goddard Global Modeling and Assimilation Office, with comparison to real time data in both forward and inverse modes; 2) An advanced biosphere model, constrained by remote sensing data, coupled to the global transport model to produce distributions of CO2 fluxes and concentrations that are consistent with actual meteorological variability; 3) Improved remote sensing estimates for biomass burning emission fluxes to better characterize interannual variability in the atmospheric CO2 budget and to better constrain the land use change source; 4) Evaluating the impact of temporally resolved fossil fuel emission distributions on atmospheric CO2 gradients and variability. 5) Testing the impact of existing and planned remote sensing data sources (e.g., AIRS, MODIS, OCO) on inference of CO2 sources and sinks, and use the model to help establish measurement requirements for future remote sensing instruments. The results will help to prepare for the use of OCO and other satellite data in a multi-disciplinary carbon data assimilation system for analysis and prediction of carbon cycle changes and carbodclimate interactions.

Improving simulations of snow water equivalent and total water storage changes over the Upper Yangtze River basin using multi-source remote sensing data

NASA Astrophysics Data System (ADS)

Han, P.; Long, D.

2017-12-01

Snow water equivalent (SWE) and total water storage (TWS) changes are important hydrological state variables over cryospheric regions, such as China's Upper Yangtze River (UYR) basin. Accurate simulation of these two state variables plays a critical role in understanding hydrological processes over this region and, in turn, benefits water resource management, hydropower development, and ecological integrity over the lower reaches of the Yangtze River, one of the largest rivers globally. In this study, an improved CREST model coupled with a snow and glacier melting module was used to simulate SWE and TWS changes over the UYR, and to quantify contributions of snow and glacier meltwater to the total runoff. Forcing, calibration, and validation data are mainly from multi-source remote sensing observations, including satellite-based precipitation estimates, passive microwave remote sensing-based SWE, and GRACE-derived TWS changes, along with streamflow measurements at the Zhimenda gauging station. Results show that multi-source remote sensing information can be extremely valuable in model forcing, calibration, and validation over the poorly gauged region. The simulated SWE and TWS changes and the observed counterparts are highly consistent, showing NSE coefficients higher than 0.8. The results also show that the contributions of snow and glacier meltwater to the total runoff are 8% and 6%, respectively, during the period 2003‒2014, which is an important source of runoff. Moreover, from this study, the TWS is found to increase at a rate of 5 mm/a ( 0.72 Gt/a) for the period 2003‒2014. The snow melting module may overestimate SWE for high precipitation events and was improved in this study. Key words: CREST model; Remote Sensing; Melting model; Source Region of the Yangtze River

Applications of Earth Remote Sensing for Identifying Tornado and Severe Weather Damage

NASA Astrophysics Data System (ADS)

Burks, J. E.; Molthan, A.; Schultz, L. A.; McGrath, K.; Bell, J. R.; Cole, T.; Angle, K.

2014-12-01

In 2014, collaborations between the Short-term Prediction Research and Transition (SPoRT) Center at NASA Marshall Space Flight Center, the National Weather Service (NWS), and the USGS led to the incorporation of Earth remote sensing imagery within the NOAA/NWS Damage Assessment Toolkit (DAT). The DAT is a smartphone, tablet, and web-based application that allows NWS meteorologists to acquire, quality control, and manage various storm damage indicators following a severe weather event, such as a tornado, occurrence of widespread damaging winds, or significant hail. Earth remote sensing supports the damage assessment process by providing a broad overview of how various acquired damage indicators relate to scarring visible from space, ranging from high spatial resolution commercial imagery (~1-4m) acquired via USGS and in collaboration with other federal and private sector partners, to moderate resolution imaging from NASA sensors (~15-30m) such as those aboard Landsat 7 and 8 and Terra's ASTER, to lower resolution but routine imaging from NASA's Terra and Aqua MODIS, or the Suomi-NPP VIIRS instrument. In several cases, the acquisition and delivery of imagery in the days after a severe weather event has proven helpful in confirming or in some cases adjusting the preliminary damage track acquired during a ground survey. For example, limited road networks and access to private property may make it difficult to observe the entire length of a tornado track, while satellite imagery can fill in observation gaps to complete a more detailed damage track assessment. This presentation will highlight successful applications of Earth remote sensing for the improvement of damage surveys, discuss remaining challenges, and provide direction on future efforts that will improve the delivery of remote sensing data and use through new automation processes and training opportunities.

Applications of Earth Remote Sensing for Identifying Tornado and Severe Weather Damage

NASA Astrophysics Data System (ADS)

Burks, J. E.; Molthan, A.; Schultz, L. A.; McGrath, K.; Bell, J. R.; Cole, T.; Angle, K.

2015-12-01

In 2014, collaborations between the Short-term Prediction Research and Transition (SPoRT) Center at NASA Marshall Space Flight Center, the National Weather Service (NWS), and the USGS led to the incorporation of Earth remote sensing imagery within the NOAA/NWS Damage Assessment Toolkit (DAT). The DAT is a smartphone, tablet, and web-based application that allows NWS meteorologists to acquire, quality control, and manage various storm damage indicators following a severe weather event, such as a tornado, occurrence of widespread damaging winds, or significant hail. Earth remote sensing supports the damage assessment process by providing a broad overview of how various acquired damage indicators relate to scarring visible from space, ranging from high spatial resolution commercial imagery (~1-4m) acquired via USGS and in collaboration with other federal and private sector partners, to moderate resolution imaging from NASA sensors (~15-30m) such as those aboard Landsat 7 and 8 and Terra's ASTER, to lower resolution but routine imaging from NASA's Terra and Aqua MODIS, or the Suomi-NPP VIIRS instrument. In several cases, the acquisition and delivery of imagery in the days after a severe weather event has proven helpful in confirming or in some cases adjusting the preliminary damage track acquired during a ground survey. For example, limited road networks and access to private property may make it difficult to observe the entire length of a tornado track, while satellite imagery can fill in observation gaps to complete a more detailed damage track assessment. This presentation will highlight successful applications of Earth remote sensing for the improvement of damage surveys, discuss remaining challenges, and provide direction on future efforts that will improve the delivery of remote sensing data and use through new automation processes and training opportunities.

Near-earth orbital guidance and remote sensing

NASA Technical Reports Server (NTRS)

Powers, W. F.

1972-01-01

The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

Operational programs in forest management and priority in the utilization of remote sensing

NASA Technical Reports Server (NTRS)

Douglass, R. W.

1978-01-01

A speech is given on operational remote sensing programs in forest management and the importance of remote sensing in forestry is emphasized. Forest service priorities in using remote sensing are outlined.

Remote sensing, land use, and demography - A look at people through their effects on the land

NASA Technical Reports Server (NTRS)

Paul, C. K.; Landini, A. J.

1976-01-01

Relevant causes of failure by the remote sensing community in the urban scene are analyzed. The reasons for the insignificant role of remote sensing in urban land use data collection are called the law of realism, the incompatibility of remote sensing and urban management system data formats is termed the law of nominal/ordinal systems compatibility, and the land use/population correlation dilemma is referred to as the law of missing persons. The study summarizes the three laws of urban land use information for which violations, avoidance, or ignorance have caused the decline of present remote sensing research. Particular attention is given to the rationale for urban land use information and for remote sensing. It is shown that remote sensing of urban land uses compatible with the three laws can be effectively developed by realizing the 10 percent contribution of remote sensing to urban land use planning data collection.

Thematic Conference on Geologic Remote Sensing, 8th, Denver, CO, Apr. 29-May 2, 1991, Proceedings. Vols. 1 & 2

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings contain papers discussing the state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing, along with the research and development activities aimed at increasing the future capabilities of this technology. The following topics are addressed: spectral geology, U.S. and international hydrocarbon exporation, radar and thermal infrared remote sensing, engineering geology and hydrogeology, mineral exploration, remote sensing for marine and environmental applications, image processing and analysis, geobotanical remote sensing, and data integration and geographic information systems. Particular attention is given to spectral alteration mapping with imaging spectrometers, mapping the coastal plain of the Congo with airborne digital radar, applications of remote sensing techniques to the assessment of dam safety, remote sensing of ferric iron minerals as guides for gold exploration, principal component analysis for alteration mappping, and the application of remote sensing techniques for gold prospecting in the north Fujian province.

Methods of training the graduate level and professional geologist in remote sensing technology

NASA Technical Reports Server (NTRS)

Kolm, K. E.

1981-01-01

Requirements for a basic course in remote sensing to accommodate the needs of the graduate level and professional geologist are described. The course should stress the general topics of basic remote sensing theory, the theory and data types relating to different remote sensing systems, an introduction to the basic concepts of computer image processing and analysis, the characteristics of different data types, the development of methods for geological interpretations, the integration of all scales and data types of remote sensing in a given study, the integration of other data bases (geophysical and geochemical) into a remote sensing study, and geological remote sensing applications. The laboratories should stress hands on experience to reinforce the concepts and procedures presented in the lecture. The geologist should then be encouraged to pursue a second course in computer image processing and analysis of remotely sensed data.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1993-01-01

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

ChinaSpec: a network of SIF observations to bridge flux measurements and remote sensing data

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wang, S.; Liu, L.; Ju, W.; Zhu, X.

2017-12-01

Accurately quantifying atmosphere-biosphere interactions across multiple scale still remains a challenge. Remote sensing, especially satellite data, has been widely used as a solution to resolve the broad scale estimation of carbon flux by upscaling the point measurements of eddy covariance (EC) technique. However, critical gaps remain between the EC observations and coarse satellite data due to the scale mismatch. In this regard, it is necessary to build a network of in situ optical observations to bridge the scale-mismatch between EC measurements and satellite remote sensing data. Internationally, a few networks have already been established (e.g., SpecNet and EuroSpec), but still at its early stage. ChinaSpec is a network of linking in situ spectral measurements, especially sun-induce chlorophyll fluorescence (SIF), with point EC observations for better understanding the interactions of atmosphere-biosphere. One main focus of ChinsSpec is to conduct continuous field SIF measurements at multiple EC sites across the mainland of China. This will help us better understand the mechanics of SIF and photosynthesis, and resolve the missing gaps between recent SIF retrievals from coarse satellite data and EC observations. In this presentation, we introduce the background, current stage, and the development of ChinaSpec network.

Remote sensing by satellite - Technical and operational implications for international cooperation

NASA Technical Reports Server (NTRS)

Doyle, S. E.

1976-01-01

International cooperation in the U.S. Space Program is discussed and related to the NASA program for remote sensing of the earth. Satellite remote sensing techniques are considered along with the selection of the best sensors and wavelength bands. The technology of remote sensing satellites is considered with emphasis on the Landsat system configuration. Future aspects of remote sensing satellites are considered.

eFarm: A Tool for Better Observing Agricultural Land Systems

PubMed Central

Yu, Qiangyi; Shi, Yun; Tang, Huajun; Yang, Peng; Xie, Ankun; Liu, Bin; Wu, Wenbin

2017-01-01

Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable social surveys at a large spatial coverage. In this paper, we introduce a smartphone-based app, called eFarm: a crowdsourcing and human sensing tool to collect the geotagged ALS information at the land parcel level, based on the high resolution remotely-sensed images. We illustrate its main functionalities, including map visualization, data management, and data sensing. Results of the trial test suggest the system works well. We believe the tool is able to acquire the human–land integrated information which is broadly-covered and timely-updated, thus presenting great potential for improving sensing, mapping, and modeling of ALS studies. PMID:28245554

A remote sensing assessment of pest infestation on sorghum

NASA Astrophysics Data System (ADS)

Singh, D.; Sao, R.; Singh, K. P.

The damage caused by the pest to crop is well known. The major aspects of remote sensing are timely estimates of agriculture crop yield, prediction of pest. Therefore, in this paper, an attempt has been made to investigate the utility and potential application of microwave remote sensing for detection of pest infestation within sorghum field. The studies were made on crop sorghum (Meethi Sudan) that is a forage variety and the pest observed was a species of grasshopper. The beds of crop sorghum were specially prepared for pests as well as microwave scattering measurements. In first phase of study, dependence of occurrence of pests on sorghum plant parameters (i.e., crop covered moist soil (SM), plant height (PH), leaf area index (LAI), percentage biomass (BIO), total chlorophyll (TC)) have been observed and analyzed and it was noticed that pests were more dependent on sorghum chlorophyll than other plant parameters, while climatic conditions were taken as constant. An empirical relationship has been developed between occurrence of pests and TC with quite significant values of coefficient of determination ( r2 = 0.82). These crop parameters are easily assessable through microwave remote sensing and therefore they can form the basis for prediction of pest remotely. In the second phase of this study, several observations were carried out for various growth stages of sorghum using scatterometer for both like polarizations (i.e., HH- and VV-) and different incidence angles at X-band (9.5 GHz). Linear regression analysis was carried out to obtain the best suitable incidence angle and polarization to assess the sorghum TC. VV-pol gives better results than HH-pol and incidence angle should be more than 40° for both like polarizations for assessing the sorghum TC at X-band. A negative correlation has been obtained between TC and scattering coefficient with the r2 values (0.69 and 0.75 for HH- and VV-pol, respectively). The TC assessed by the microwave measurements was helpful to estimate the occurrence of pests on sorghum. Based on both phase of study an algorithm is proposed to estimate the number of pest on sorghum by remote sensing method. There is a quite good agreement between observed occurrence of pest and assessed occurrence of pest.

U.S. Geological Survey, remote sensing, and geoscience data: Using standards to serve us all

USGS Publications Warehouse

Benson, Michael G.; Faundeen, John L.

2000-01-01

The U.S. Geological Survey (USGS) advocates the use of standards with geosciences and remotely sensed data and metadata for its own purposes and those of its customers. In activities that range from archiving data to making a product, the incorporation of standards makes these functions repeatable and understandable. More important, when accepted standards are followed, data discovery and sharing can be more efficient and the overall value to society can be expanded. The USGS archives many terabytes of digital geoscience and remotely sensed data. Several million photographs are also available to the research community. To manage these vast holdings and ensure that strict preservation and high usability criteria are observed, the USGS uses standards within the archival, data management, public access and ordering, and data distribution areas. The USGS uses Federal and international standards in performing its role as the U.S. National Satellite Land Remote Sensing Data Archive and in its mission as the long-term archive and production center for aerial photographs and cartographic data covering the United States.

Watermarking-based protection of remote sensing images: requirements and possible solutions

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella

2001-12-01

Earth observation missions have recently attracted ag rowing interest form the scientific and industrial communities, mainly due to the large number of possible applications capable to exploit remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products from non-authorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred means of data exchange. A crucial issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: i) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection ii) analysis of the state-of-the-art, and performance evaluation of existing algorithms in terms of the requirements at the previous point.

Remote-sensing supported monitoring of global biodiversity change

NASA Astrophysics Data System (ADS)

Jetz, W.; Tuanmu, M. N.; W, A.; Melton, F. S.; Parmentier, B.; Amatulli, G.; Guzman, A.

2016-12-01

Remote sensing combined with biodiversity observation offers an unrivalled tool for understanding and predicting species distributions and their changes at the planetary scale. I will illustrate recently developed high-resolution remote-sensing based layers targeted for spatiotemporal biodiversity modeling, addressing climate, environment, topography, and habitat heterogeneity. In particular, I will illustrate the development and use of global MODIS-derived environmental layers for biodiversity assessment and change monitoring. Remote-sensing based capture of these putative predictors of biodiversity dynamics provides more a reliable signal than spatially interpolated layers and avoids inflated spatial autocorrelation. The layers result in more accurate models of species occurrence and are more readily able to address the scale of processes underpinning species distributions, e.g. when combined with emerging hierarchical, cross-scale models. I illustrate the multiple ways in which this type of information, based on continuously collected data, supports the prediction of not just spatial but also temporal variation in biodiversity. Using implementations in the Map of Life infrastructure I will showcase new indicators of species distribution and change that demonstrate these new opportunities.

Remote sensing of a coupled carbon-water-energy-radiation balances from the Globe to plot scales

NASA Astrophysics Data System (ADS)

Ryu, Y.; Jiang, C.; Huang, Y.; Kim, J.; Hwang, Y.; Kimm, H.; Kim, S.

2016-12-01

Advancements in near-surface and satellite remote sensing technologies have enabled us to monitor the global terrestrial ecosystems at multiple spatial and temporal scales. An emergent challenge is how to formulate a coupled water, carbon, energy, radiation, and nitrogen cycles from remote sensing. Here, we report Breathing Earth System Simulator (BESS), which coupled radiation (shortwave, longwave, PAR, diffuse PAR), carbon (gross primary productivity, ecosystem respiration, net ecosystem exchange), water (evaporation), and energy (latent and sensible heat) balances across the global land at 1 km resolution, 8 daily between 2000 and 2015 using multiple satellite remote sensing. The performance of BESS was tested against field observations (FLUXNET, BSRN) and other independent products (MPI-BGC, MODIS, GLASS). We found that the coupled model, BESS showed on par with, or better performance than the other products which computed land surface fluxes individually. Lastly, we show one plot-level study conducted in a paddy rice to demonstrate how to couple radiation, carbon, water, nitrogen balances with a series of near-surface spectral sensors.

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data

NASA Astrophysics Data System (ADS)

Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin

2018-03-01

The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With detailed analysis, we show that the error of the retrieval mainly arises from the difference between the modeled and the observed (SMOS) L-band brightness temperature (TB). The narrow swath and the limited coverage of the sea ice cover by altimetry is the potential source of error associated with the modeling of L-band TB and retrieval. The proposed retrieval methodology can be applied to the basin-scale retrieval of sea ice thickness and snow depth, using concurrent passive remote sensing and active laser altimetry based on satellites such as ICESat-2 and WCOM.

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

NASA Technical Reports Server (NTRS)

Kiang, Richard; Adimi, Farida; Kempler, Steven

2008-01-01

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Remote sensing in operational range management programs in Western Canada

NASA Technical Reports Server (NTRS)

Thompson, M. D.

1977-01-01

A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.

Applications of the SWOT Mission to Reservoirs in the Mekong River Basin

NASA Astrophysics Data System (ADS)

Bonnema, M.; Hossain, F.

2017-12-01

The forthcoming Surface Water and Ocean Topography (SWOT) mission has the potential to significantly improve our ability to observe artificial reservoirs globally from a remote sensing perspective. By providing simultaneous estimates of reservoir water surface extent and elevation with near global coverage, reservoir storage changes can be estimated. Knowing how reservoir storage changes over time is critical for understanding reservoir impacts on river systems. In data limited regions, remote sensing is often the only viable method of retrieving such information about reservoir operations. When SWOT launches in 2021, it will join an array of satellite sensors with long histories of reservoir observation and monitoring capabilities. There are many potential synergies in the complimentary use of future SWOT observations with observations from current satellite sensors. The work presented here explores the potential benefits of utilizing SWOT observations over 20 reservoirs in the Mekong River Basin. The SWOT hydrologic simulator, developed by NASA Jet Propulsion Laboratory, is used to generate realistic SWOT observations, which are then inserted into a previously established remote sensing modeling framework of the 20 Mekong Basin reservoirs. This framework currently combines data from Landsat missions, Jason radar altimeters, and the Shuttle Radar and Topography Mission (SRTM), to provide monthly estimates of reservoir storage change. The incorporation of SWOT derived reservoir surface area and elevation into the model is explored in an effort to improve both accuracy and temporal resolution of observed reservoir operations.

Evaluating ESA CCI soil moisture in East Africa.

PubMed

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R; Wang, Shugong; Peters-Lidard, Christa D; Verdin, James P

2016-06-01

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R>0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

SENSOR: a tool for the simulation of hyperspectral remote sensing systems

NASA Astrophysics Data System (ADS)

Börner, Anko; Wiest, Lorenz; Keller, Peter; Reulke, Ralf; Richter, Rolf; Schaepman, Michael; Schläpfer, Daniel

The consistent end-to-end simulation of airborne and spaceborne earth remote sensing systems is an important task, and sometimes the only way for the adaptation and optimisation of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software Environment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray-tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. The third part consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimisation requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and first examples of its use are given. The verification of SENSOR is demonstrated. This work is closely related to the Airborne PRISM Experiment (APEX), an airborne imaging spectrometer funded by the European Space Agency.

Investigating the thermophysical properties of indurated materials on Mars

NASA Astrophysics Data System (ADS)

Murphy, Nathaniel William

Indurated materials have been observed on the surface of Mars at every landing site and inferred from orbital remote-sensing data by the Viking, Mars Global Surveyor, and Mars Odyssey spacecraft. However, indurated materials on Mars are poorly understood because there is no ground truth for the indurated surfaces inferred from thermal remote-sensing data. I adopted two approaches to investigate indurated materials on Mars: (1) remote-sensing analysis of the Isidis basin, which shows some of the highest thermal inertia values derived from TES 1 observations, and (2) laboratory analyses of terrestrial indurated materials. To characterize the surface of the Isidis basin, I combined a variety of remote-sensing datasets, including thermal inertia data derived from TES and MO-THEMIS, TES albedo, THEMIS thermal and visible imaging, and Earth-based radar observations. From these observations I concluded that the thermal inertia values in the Isidis basin are likely the result of variations in the degree of cementation of indurated materials. To examine the thermophysical properties of indurated materials I collected four examples of terrestrial indurated materials. These included two types of gypcrete collected from a gypcrete deposit near Upham Hills, NM, clay-materials from Lunar Lake Playa, NV, and a pyroclastic material from the Bandelier Tuff near Los Alamos, NM. Despite significant differences in their physical properties and origins, all of these materials have thermal inertia values consistent with inferred indurated surfaces on Mars. There are no strong correlations between the thermal and physical properties of the collected samples due to thermal effects of the fabrics of the indurated materials. 1 Thermal Emission Spectrometer onboard the Mars Global Surveyor spacecraft. 2 Thermal Emission Imaging System onboard the Mars Odyssey spacecraft

NASA's NI-SAR Observing Strategy and Data Availability for Agricultural Monitoring and Assessment

NASA Astrophysics Data System (ADS)

Siqueira, P.; Dubayah, R.; Kellndorfer, J. M.; Saatchi, S. S.; Chapman, B. D.

2014-12-01

The monitoring and characterization of global crop development by remote sensing is a complex task, in part, because of the time varying nature of the target and the diversity of crop types and agricultural practices that vary worldwide. While some of these difficulties are overcome with the availability of national and market-derived resources (e.g. publication of crop statistics by the USDA and FAO), monitoring by remote sensing has the ability of augmenting those resources to better identify changes over time, and to provide timely assessments for the current year's production. Of the remote sensing techniques that are used for agricultural applications, optical observations of NDVI from Landsat, AVHRR, MODIS and similar sensors have historically provided the majority of data that is used by the community. In addition, radiometer and radar sensors, are often used for estimating soil moisture and structural information for these agricultural regions. The combination of these remote sensing datasets and national resources constitutes the state of the art for crop monitoring and yield forecasts. To help improve these crop monitoring efforts in the future, the joint NASA-ISRO SAR mission known as NI-SAR is being planned for launch in 2020, and will have L- and S-band fully polarimetric radar systems, a fourteen day repeat period, and a swath width on the order of several hundred kilometers. To address the needs of the science and applications communities that NI-SAR will support, the systems observing strategy is currently being planned such that data rate and the system configuration will address the needs of the community. In this presentation, a description of the NI-SAR system will be given along with the currently planned observing strategy and derived products that will be relevant to the overall GEOGLAM initiative.

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

NASA Technical Reports Server (NTRS)

Gregg, W. W.; Behrenfield, M. J.; Hoge, F. E.; Esaias, W. E.; Huang, N. E.; Long, S. R.; McClain, C. R.

2000-01-01

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance

PubMed Central

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2017-01-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), Scdm (units: nm−1), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving Scdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360–500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of Scdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors. PMID:29201583

Remote-sensing reflectance determinations in the coastal ocean environment: impact of instrumental characteristics and environmental variability.

PubMed

Toole, D A; Siegel, D A; Menzies, D W; Neumann, M J; Smith, R C

2000-01-20

Three independent ocean color sampling methodologies are compared to assess the potential impact of instrumental characteristics and environmental variability on shipboard remote-sensing reflectance observations from the Santa Barbara Channel, California. Results indicate that under typical field conditions, simultaneous determinations of incident irradiance can vary by 9-18%, upwelling radiance just above the sea surface by 8-18%, and remote-sensing reflectance by 12-24%. Variations in radiometric determinations can be attributed to a variety of environmental factors such as Sun angle, cloud cover, wind speed, and viewing geometry; however, wind speed is isolated as the major source of uncertainty. The above-water approach to estimating water-leaving radiance and remote-sensing reflectance is highly influenced by environmental factors. A model of the role of wind on the reflected sky radiance measured by an above-water sensor illustrates that, for clear-sky conditions and wind speeds greater than 5 m/s, determinations of water-leaving radiance at 490 nm are undercorrected by as much as 60%. A data merging procedure is presented to provide sky radiance correction parameters for above-water remote-sensing reflectance estimates. The merging results are consistent with statistical and model findings and highlight the importance of multiple field measurements in developing quality coastal oceanographic data sets for satellite ocean color algorithm development and validation.

Water Quality Analysis Tool (WQAT) | Science Inventory | US ...

EPA Pesticide Factsheets

The purpose of the Water Quality Analysis Tool (WQAT) software is to provide a means for analyzing and producing useful remotely sensed data products for an entire estuary, a particular point or area of interest (AOI or POI) in estuaries, or water bodies of interest where pre-processed and geographically gridded remotely sensed images are available. A graphical user interface (GUI), was created to enable the user to select and display imagery from a variety of remote sensing data sources. The user can select a date (or date range) and location to extract pixels from the remotely sensed imagery. The GUI is used to obtain all available pixel values (i.e. pixel from all available bands of all available satellites) for a given location on a given date and time. The resultant data set can be analyzed or saved to a file for future use. The WQAT software provides users with a way to establish algorithms between remote sensing reflectance (Rrs) and any available in situ parameters, as well as statistical and regression analysis. The combined data sets can be used to improve water quality research and studies. Satellites provide spatially synoptic data at high frequency (daily to weekly). These characteristics are desirable for supplementing existing water quality observations and for providing information for large aquatic ecosystems that are historically under-sampled by field programs. Thus, the Water Quality Assessment Tool (WQAT) software tool was developed to suppo

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water.

PubMed

Rodriguez, Jenna; Ustin, Susan; Sandoval-Solis, Samuel; O'Geen, Anthony Toby

2016-09-15

Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate post-earthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management. Copyright © 2016 Elsevier B.V. All rights reserved.

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance.

PubMed

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2016-03-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), S cdm (units: nm -1 ), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving S cdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360-500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of S cdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors.

Geomorphic Processes and Remote Sensing Signatures of Alluvial Fans in the Kun Lun Mountains, China

NASA Technical Reports Server (NTRS)

Farr, Tom G.; Chadwick, Oliver A.

1996-01-01

The timing of alluvial deposition in arid and semiarid areas is tied to land-surface instability caused by regional climate changes. The distribution pattern of dated deposits provides maps of regional land-surface response to past climate change. Sensitivity to differences in surface roughness and composition makes remote sensing techniques useful for regional mapping of alluvial deposits. Radar images from the Spaceborne Radar Laboratory and visible wavelength images from the French SPOT satellite were used to determine remote sensing signatures of alluvial fan units for an area in the Kun Lun Mountains of northwestern China. These data were combined with field observations to compare surface processes and their effects on remote sensing signatures in northwestern China and the southwestern United States. Geomorphic processes affecting alluvial fans in the two areas include aeolian deposition, desert varnish, and fluvial dissection. However, salt weathering is a much more important process in the Kun Lun than in the southwestern United States. This slows the formation of desert varnish and prevents desert pavement from forming. Thus the Kun Lun signatures are characteristic of the dominance of salt weathering, while signatures from the southwestern United States are characteristic of the dominance of desert varnish and pavement processes. Remote sensing signatures are consistent enough in these two regions to be used for mapping fan units over large areas.

PROCEEDINGS OF THE FOURTH SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT; 12, 13, 14 APRIL 1966.

DTIC Science & Technology

The symposium was conducted as part of a continuing program investigating the field of remote sensing , its potential in scientific research and...information on all aspects of remote sensing , with special emphasis on such topics as needs for remotely sensed data, data management, and the special... remote sensing programs, data acquisition, data analysis and application, and equipment design, were presented. (Author)

Remote sensing and image interpretation

NASA Technical Reports Server (NTRS)

Lillesand, T. M.; Kiefer, R. W. (Principal Investigator)

1979-01-01

A textbook prepared primarily for use in introductory courses in remote sensing is presented. Topics covered include concepts and foundations of remote sensing; elements of photographic systems; introduction to airphoto interpretation; airphoto interpretation for terrain evaluation; photogrammetry; radiometric characteristics of aerial photographs; aerial thermography; multispectral scanning and spectral pattern recognition; microwave sensing; and remote sensing from space.

Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands

USGS Publications Warehouse

Kustas, William P.; Moran, M.S.; Humes, K.S.; Stannard, D.I.; Pinter, P. J.; Hipps, L.E.; Swiatek, E.; Goodrich, D.C.

1994-01-01

Remotely sensed data in the visible, near-infrared, and thermal-infrared wave bands were collected from a low-flying aircraft during the Monsoon '90 field experiment. Monsoon '90 was a multidisciplinary experiment conducted in a semiarid watershed. It had as one of its objectives the quantification of hydrometeorological fluxes during the “monsoon” or wet season. The remote sensing observations along with micrometeprological and atmospheric boundary layer (ABL) data were used to compute the surface energy balance over a range of spatial scales. The procedure involved averaging multiple pixels along transects flown over the meteorological and flux (METFLUX) stations. Average values of the spectral reflectance and thermal-infrared temperatures were computed for pixels of order 10−1 to 101 km in length and were used with atmospheric data for evaluating net radiation (Rn), soil heat flux (G), and sensible (H) and latent (LE) heat fluxes at these same length scales. The model employs a single-layer resistance approach for estimating H that requires wind speed and air temperature in the ABL and a remotely sensed surface temperature. The values of Rn and G are estimated from remote sensing information together with near-surface observations of air temperature, relative humidity, and solar radiation. Finally, LE is solved as the residual term in the surface energy balance equation. Model calculations were compared to measurements from the METFLUX network for three days having different environmental conditions. Average percent differences for the three days between model and the METFLUX estimates of the local fluxes were about 5% for Rn, 20% for Gand H, and 15% for LE. Larger differences occurred during partly cloudy conditions because of errors in interpreting the remote sensing data and the higher spatial and temporal variation in the energy fluxes. Minor variations in modeled energy fluxes were observed when the pixel size representing the remote sensing inputs changed from 0.2 to 2 km. Regional scale estimates of the surface energy balance using bulk ABL properties for the model parameters and input variables and the 10-km pixel data differed from the METFLUX network averages by about 4% for Rn, 10% for G and H, and 15% for LE. Model sensitivity in calculating the turbulent fluxes H and LE to possible variations in key model parameters (i.e., the roughness lengths for heat and momentum) was found to be fairly significant. Therefore the reliability of the methods for estimating key model parameters and potential errors needs further testing over different ecosystems and environmental conditions.

Impact of spatial inhomogeneities on stratospheric species vertical profiles from remote-sensing balloon-borne instruments

NASA Astrophysics Data System (ADS)

Berthet, Gwenael; Renard, Jean-Baptiste; Catoire, Valery; Huret, Nathalie; Lefevre, Franck; Hauchecorne, Alain; Chartier, Michel; Robert, Claude

Remote-sensing balloon observations have recurrently revealed high concentrations of polar stratospheric NO2 in particular in the lower stratosphere as can be seen in various published vertical profiles. A balloon campaign dedicated to the investigation of this problem through comparisons between remote-sensing (SALOMON) and in situ (SPIRALE) measurements of NO2 inside the polar vortex was conducted in January 2006. The published results show unexpected strong enhancements in the slant column densities of NO2 with respect to the elevation angle and displacement of the balloon. These fluctuations result from NO2 spatial inhomogeneities located above the balloon float altitude resulting from mid-latitude air intrusion as revealed by Potential Vorticity (PV) maps. The retrieval of the NO2 vertical profile is subsequently biased in the form of artificial excesses of NO2 concentrations. A direct implication is that the differences previously observed between measurements of NO2 and OClO and model results are probably mostly due to the improper inversion of NO2 in presence of either perturbed dynamical conditions or when mesospheric production events occur as recently highlighted from ENVISAT data. Through the occurrence of such events, we propose to re-examine formerly published high-latitude profiles from the remote-sensing instruments AMON and SALOMON using in parallel PV maps from the MIMOSA advection contour model and the REPROBUS CTM outputs. Mid-latitude profiles of NO2 will also be investigated since they are likely to be biased if presence of air from other latitudes was present at the time of the observations.

Remote Sensing of Suspended Sediment Dynamics in the Mississippi Sound

NASA Astrophysics Data System (ADS)

Merritt, D. N.; Skarke, A. D.; Silwal, S.; Dash, P.

2016-02-01

The Mississippi Sound is a semi-enclosed estuary between the coast of Mississippi and a chain of offshore barrier islands with relatively shallow water depths and high marine biodiversity that is wildly utilized for commercial fishing and public recreation. The discharge of sediment-laden rivers into the Mississippi Sound and the adjacent Northern Gulf of Mexico creates turbid plumes that can extend hundreds of square kilometers along the coast and persist for multiple days. The concentration of suspended sediment in these coastal waters is an important parameter in the calculation of regional sediment budgets as well as analysis of water-quality factors such as primary productivity, nutrient dynamics, and the transport of pollutants as well as pathogens. The spectral resolution, sampling frequency, and regional scale spatial domain associated with satellite based sensors makes remote sensing an ideal tool to monitor suspended sediment dynamics in the Northern Gulf of Mexico. Accordingly, the presented research evaluates the validity of published models that relate remote sensing reflectance with suspended sediment concentrations (SSC), for similar environmental settings, with 51 in situ observations of SSC from the Mississippi Sound. Additionally, regression analysis is used to correlate additional in situ observations of SSC in Mississippi Sound with coincident observations of visible and near-infrared band reflectance collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Aqua satellite, in order to develop a site-specific empirical predictive model for SSC. Finally, specific parameters of the sampled suspended sediment such as grain size and mineralogy are analyzed in order to quantify their respective contributions to total remotely sensed reflectance.

Passive Microwave Remote Sensing of Soil Moisture

NASA Technical Reports Server (NTRS)

Njoku, Eni G.; Entekhabi, Dara

1996-01-01

Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

Mapping the impact of river regulation on carbon dynamics using coupled field surveys and remotely-sensed optical properties

NASA Astrophysics Data System (ADS)

Kuhn, C.; Butman, D. E.

2016-12-01

Many river-reservoir networks are already managed for ecological targets such as stream temperature regulation, but less is known about how management choices alter the quantity and composition of dissolved organic carbon as well as the concentration of dissolved carbon gases. Understanding these ecological impacts is critical to informing water resources management, especially in light of the global hydropower boom and the increased interest in dam removal in the United States. Here we present results from a field survey and remote sensing imagery analysis quantifying a suite of water quality variables. With this approach, we evaluate spatial differences in carbon signals above, and below eight mainstem dams located on the Columbia and Snake Rivers. Dissolved methane and carbon dioxide concentrations were in excess of atmospheric levels with occasional carbon dioxide undersaturation being observed in the Snake River. CH4 and CO2 δ13C values shifted between the mainstem and the tributaries reflecting changes in carbon sources and processes. Satellite-retrieved estimates of CDOM and chlorophyll-a were compared to in situ measurements to enable surface mapping of concentrations at broader spatial scales. Our technical approach blends cloud-based data fusion techniques and machine learning to link ground-collected observations to remote sensing imagery in order to produce spatially-explicit, cross-scale estimates of carbon dynamics in a large, highly regulated river system. These findings test the feasibility of coupling remote sensing with field-based measurements to observe the complex impacts of run-of-the river impoundments to aquatic carbon cycling.

Geotechnical applications of remote sensing and remote data transmission; Proceedings of the Symposium, Cocoa Beach, FL, Jan. 31-Feb. 1, 1986

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, A.I.; Pettersson, C.B.

1988-01-01

Papers and discussions concerning the geotechnical applications of remote sensing and remote data transmission, sources of remotely sensed data, and glossaries of remote sensing and remote data transmission terms, acronyms, and abbreviations are presented. Aspects of remote sensing use covered include the significance of lineaments and their effects on ground-water systems, waste-site use and geotechnical characterization, the estimation of reservoir submerging losses using CIR aerial photographs, and satellite-based investigation of the significance of surficial deposits for surface mining operations. Other topics presented include the location of potential ground subsidence and collapse features in soluble carbonate rock, optical Fourier analysis ofmore » surface features of interest in geotechnical engineering, geotechnical applications of U.S. Government remote sensing programs, updating the data base for a Geographic Information System, the joint NASA/Geosat Test Case Project, the selection of remote data telemetry methods for geotechnical applications, the standardization of remote sensing data collection and transmission, and a comparison of airborne Goodyear electronic mapping system/SAR with satelliteborne Seasat/SAR radar imagery.« less

Education in Environmental Remote Sensing: Potentials and Problems.

ERIC Educational Resources Information Center

Kiefer, Ralph W.; Lillesand, Thomas M.

1983-01-01

Discusses remote sensing principles and applications and the status and needs of remote sensing education in the United States. A summary of the fundamental policy issues that will determine remote sensing's future role in environmental and resource managements is included. (Author/BC)

THE EPA REMOTE SENSING ARCHIVE

EPA Science Inventory

What would you do if you were faced with organizing 30 years of remote sensing projects that had been haphazardly stored at two separate locations for years then combined? The EPA Remote Sensing Archive, currently located in Las Vegas, Nevada. contains the remote sensing data and...

Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar

NASA Astrophysics Data System (ADS)

Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani

2017-07-01

Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002-2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.

Research on remote sensing image pixel attribute data acquisition method in AutoCAD

NASA Astrophysics Data System (ADS)

Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui

2013-07-01

The remote sensing image has been widely used in AutoCAD, but AutoCAD lack of the function of remote sensing image processing. In the paper, ObjectARX was used for the secondary development tool, combined with the Image Engine SDK to realize remote sensing image pixel attribute data acquisition in AutoCAD, which provides critical technical support for AutoCAD environment remote sensing image processing algorithms.

Bibliography of Remote Sensing Techniques Used in Wetland Research.

DTIC Science & Technology

1993-01-01

remote sensing technology for detecting changes in wetland environments. This report documents a bibliographic search conducted as part of that work unit on applications of remote sensing techniques in wetland research. Results were used to guide research efforts on the use of remote sensing technology for wetland change detection and assessment. The citations are presented in three appendixes, organized by wetland type, sensor type, and author.... Change detection, Wetland assessment, Remote sensing ,

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

NASA Astrophysics Data System (ADS)

Kustas, William P.; Alfieri, Joseph G.; Anderson, Martha C.; Colaizzi, Paul D.; Prueger, John H.; Evett, Steven R.; Neale, Christopher M. U.; French, Andrew N.; Hipps, Lawrence E.; Chávez, José L.; Copeland, Karen S.; Howell, Terry A.

2012-12-01

Application and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of Norman et al. (1995) [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by Evett et al. (2012) [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint.

Illumination invariant feature point matching for high-resolution planetary remote sensing images

NASA Astrophysics Data System (ADS)

Wu, Bo; Zeng, Hai; Hu, Han

2018-03-01

Despite its success with regular close-range and remote-sensing images, the scale-invariant feature transform (SIFT) algorithm is essentially not invariant to illumination differences due to the use of gradients for feature description. In planetary remote sensing imagery, which normally lacks sufficient textural information, salient regions are generally triggered by the shadow effects of keypoints, reducing the matching performance of classical SIFT. Based on the observation of dual peaks in a histogram of the dominant orientations of SIFT keypoints, this paper proposes an illumination-invariant SIFT matching method for high-resolution planetary remote sensing images. First, as the peaks in the orientation histogram are generally aligned closely with the sub-solar azimuth angle at the time of image collection, an adaptive suppression Gaussian function is tuned to level the histogram and thereby alleviate the differences in illumination caused by a changing solar angle. Next, the suppression function is incorporated into the original SIFT procedure for obtaining feature descriptors, which are used for initial image matching. Finally, as the distribution of feature descriptors changes after anisotropic suppression, and the ratio check used for matching and outlier removal in classical SIFT may produce inferior results, this paper proposes an improved matching procedure based on cross-checking and template image matching. The experimental results for several high-resolution remote sensing images from both the Moon and Mars, with illumination differences of 20°-180°, reveal that the proposed method retrieves about 40%-60% more matches than the classical SIFT method. The proposed method is of significance for matching or co-registration of planetary remote sensing images for their synergistic use in various applications. It also has the potential to be useful for flyby and rover images by integrating with the affine invariant feature detectors.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

PubMed Central

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Remote sensing for detecting and mapping whitefly (Bemisia tabaci) infestations

USDA-ARS?s Scientific Manuscript database

Remote sensing technology has long been used for detecting insect infestations on agricultural crops. With recent advances in remote sensing sensors and other spatial information technologies such as Global Position Systems (GPS) and Geographic Information Systems (GIS), remote sensing is finding mo...

Reflections on Earth--Remote-Sensing Research from Your Classroom.

ERIC Educational Resources Information Center

Campbell, Bruce A.

2001-01-01

Points out the uses of remote sensing in different areas, and introduces the program "Reflections on Earth" which provides access to basic and instructional information on remote sensing to students and teachers. Introduces students to concepts related to remote sensing and measuring distances. (YDS)

Remote-Sensing Practice and Potential

DTIC Science & Technology

1974-05-01

Six essential processes that must be accomplished if use of a remote - sensing system is to result in useful information are defined as problem...to be useful in remote - sensing projects are described. An overview of the current state-of-the-art of remote sensing is presented.

History and future of remote sensing technology and education

NASA Technical Reports Server (NTRS)

Colwell, R. N.

1980-01-01

A historical overview of the discovery and development of photography, related sciences, and remote sensing technology is presented. The role of education to date in the development of remote sensing is discussed. The probable future and potential of remote sensing and training is described.

High-Frequency Observation of Water Spectrum and Its Application in Monitoring of Dynamic Variation of Suspended Materials in the Hangzhou Bay.

PubMed

Dai, Qian; Pan, De-lu; He, Xian-qiang; Zhu, Qian-kun; Gong, Fang; Huang, Hai-qing

2015-11-01

In situ measurement of water spectrum is the basis of the validation of the ocean color remote sensing. The traditional method to obtain the water spectrum is based on the shipboard measurement at limited stations, which is difficult to meet the requirement of validation of ocean color remote sensing in the highly dynamic coastal waters. To overcome this shortage, continuously observing systems of water spectrum have been developed in the world. However, so far, there are still few high-frequency observation systems of the water spectrum in coastal waters, especially in the highly turbid and high-dynamic waters. Here, we established a high-frequency water-spectrum observing system based on tower in the Hangzhou Bay. The system measures the water spectrum at a step of 3 minutes, which can fully match the satellite observation. In this paper, we primarily developed a data processing method for the tower-based high-frequency water spectrum data, to realize automatic judgment of clear sky, sun glint, platform shadow, and weak illumination, etc. , and verified the processing results. The results show that the normalized water-leaving radiance spectra obtained through tower observation have relatively high consistency with the shipboard measurement results, with correlation coefficient of more than 0. 99, and average relative error of 9.96%. In addition, the long-term observation capability of the tower-based high-frequency water-spectrum observing system was evaluated, and the results show that although the system has run for one year, the normalized water-leaving radiance obtained by this system have good consistency with the synchronously measurement by Portable spectrometer ASD in respect of spectral shape and value, with correlation coefficient of more than 0.90 and average relative error of 6.48%. Moreover, the water spectra from high-frequency observation by the system can be used to effectively monitor the rapid dynamic variation in concentration of suspended materials with tide. The tower-based high-frequency water-spectrum observing system provided rich in situ spectral data for the validation of ocean color remote sensing in turbid waters, especially for validation of the high temporal-resolution geostationary satellite ocean color remote sensing.

CME Plasma Dynamics Using In-situ and Remote-sensing Observations

NASA Astrophysics Data System (ADS)

Kocher, Manan; Lepri, Susan; Landi, Enrico

2017-04-01

The thermal and kinetic energy of Coronal Mass Ejections [CMEs] can be best reconstructed if the plasma density, temperature and dynamics of each of their components are known. During periods of quadrature, we use a combination of in-situ measurements from ACE/SWICS and remote sensing observations from SDO/AIA and STEREO/EUVI to present several case studies of geo-effective halo-CMEs. We carry out density diagnostics and Differential Emission Measure [DEM] profile calculations to reconstruct a 3D picture of the CME plasma for the selected cases in the low solar corona. We then discuss these results in the context of models of CME initiation and release.

Program on Earth Observation Data Management Systems (EODMS), appendixes

NASA Technical Reports Server (NTRS)

Eastwood, L. F., Jr.; Gohagan, J. K.; Hill, C. T.; Morgan, R. P.; Bay, S. M.; Foutch, T. K.; Hays, T. R.; Ballard, R. J.; Makin, K. P.; Power, M. A.

1976-01-01

The needs of state, regional, and local agencies involved in natural resources management in Illinois, Iowa, Minnesota, Missouri, and Wisconsin are investigated to determine the design of satellite remotely sensed derivable information products. It is concluded that an operational Earth Observation Data Management System (EODMS) will be most beneficial if it provides a full range of services - from raw data acquisition to interpretation and dissemination of final information products. Included is a cost and performance analysis of alternative processing centers, and an assessment of the impacts of policy, regulation, and government structure on implementing large scale use of remote sensing technology in this community of users.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Huilin; Zhang, Shuai; Fu, Rong

Land surface temperatures (LSTs) within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS), providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability ofmore » cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Lastly, the differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP) reanalysis data).« less

Future opportunities and challenges in remote sensing of drought

USGS Publications Warehouse

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.

2012-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Future Opportunities and Challenges in Remote Sensing of Drought

NASA Technical Reports Server (NTRS)

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt

2011-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Role of remote sensing in documenting living resources

NASA Technical Reports Server (NTRS)

Wagner, P. E.; Anderson, R. R.; Brun, B.; Eisenberg, M.; Genys, J. B.; Lear, D. W., Jr.; Miller, M. H.

1978-01-01

Specific cases of known or potentially useful applications of remote sensing in assessing biological resources are discussed. It is concluded that the more usable remote sensing techniques relate to the measurement of population fluctuations in aquatic systems. Sensing of the flora and the fauna of the Bay is considered with emphasis on direct sensing of aquatic plant populations and of water quality. Recommendations for remote sensing projects are given.

Commercial future: making remote sensing a media event

NASA Astrophysics Data System (ADS)

Lurie, Ian

1999-12-01

The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.

Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Aber, John D.; Peterson, David L.; Melillo, Jerry M.

1988-01-01

The use of images acquired by the Airborne Imaging Spectrometer, an experimental high-spectral resolution imaging sensor developed by NASA, to estimate the lignin concentration of whole forest canopies in Wisconsin is reported. The observed strong relationship between canopy lignin concentration and nitrogen availability in seven undisturbed forest ecosystems on Blackhawk Island, Wisconsin, suggests that canopy lignin may serve as an index for site nitrogen status. This predictive relationship presents the opportunity to estimate nitrogen-cycling rates across forested landscapes through remote sensing.

Identification of Terrestrial Reflectance From Remote Sensing

NASA Technical Reports Server (NTRS)

Alter-Gartenberg, Rachel; Nolf, Scott R.; Stacy, Kathryn (Technical Monitor)

2000-01-01

Correcting for atmospheric effects is an essential part of surface-reflectance recovery from radiance measurements. Model-based atmospheric correction techniques enable an accurate identification and classification of terrestrial reflectances from multi-spectral imagery. Successful and efficient removal of atmospheric effects from remote-sensing data is a key factor in the success of Earth observation missions. This report assesses the performance, robustness and sensitivity of two atmospheric-correction and reflectance-recovery techniques as part of an end-to-end simulation of hyper-spectral acquisition, identification and classification.

Mapping products of Titan's surface

USGS Publications Warehouse

Stephan, Katrin; Jaumann, Ralf; Karkoschka, Erich; Barnes, Jason W.; Tomasko, Martin G.; Turtle, Elizabeth P.; Le Corre, Lucille; Langhans, Mirjam; Le Mouelic, Stephane; Lorenz, Ralf D.; Perry, Jason; Brown, Robert H.; Lebreton, Jean-Pierre

2009-01-01

Remote sensing instruments aboard the Cassini spacecraft have been observed the surface of Titan globally in the infrared and radar wavelength ranges as well as locally by the Huygens instruments revealing a wealth of new morphological features indicating a geologically active surface. We present a summary of mapping products of Titan's surface derived from data of the remote sensing instruments onboard the Cassini spacecraft (ISS, VIMS, RADAR) as well as the Huygens probe (DISR) that were achieved during the nominal Cassini mission including an overview of Titan's recent nomenclature.

Experimental validation of a millimeter wave radar technique to remotely sense atmospheric pressure at the Earth's surface

NASA Technical Reports Server (NTRS)

Flower, D. A.; Peckham, G. E.; Bradford, W. J.

1984-01-01

Experiments with a millimeter wave radar operating on the NASA CV-990 aircraft which validate the technique for remotely sensing atmospheric pressure at the Earth's surface are described. Measurements show that the precise millimeter wave observations needed to deduce pressure from space with an accuracy of 1 mb are possible, that sea surface reflection properties agree with theory and that the measured variation of differential absorption with altitude corresponds to that expected from spectroscopic models.

Viking Landers and remote sensing

NASA Technical Reports Server (NTRS)

Moore, H. J.; Jakosky, B. M.; Christensen, P. R.

1987-01-01

Thermal and radar remote sensing signatures of the materials in the lander sample fields can be crudely estimated from evaluations of their physical-mechanical properties, laboratory data on thermal conductivities and dielectric constants, and theory. The estimated thermal inertias and dielectric constants of some of the materials in the sample field are close to modal values estimated from orbital and earth-based observations. This suggests that the mechanical properties of the surface materials of much of Mars will not be significantly different that those of the landing sites.

Acquisition of Earth Science Remote Sensing Observations from Commercial Sources: Lessons Learned from the Space Imaging IKONOS Example

NASA Technical Reports Server (NTRS)

Goward, Samuel N.; Townshend, John R.; Zanoni, Vicki; Policelli, Fritz; Stanley, Tom; Ryan, Robert; Holekamp, Kara; Underwood, Lauren; Pagnutti, Mary; Fletcher, Rose

2003-01-01

In an effort to more full explore the potential of commercial remotely sensed land data sources, the NASA Earth Science Enterprise (ESE) implemented an experimental Scientific Data Purchase (SDP) that solicited bids from the private sector to meet ESE-user data needs. The images from the Space Imaging IKONOS system provided a particularly good match to the current ESE missions such as Terra and Landsat 7 and therefore serve as a focal point in this analysis.

Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

DTIC Science & Technology

2003-09-30

We are developing an integrated rapid environmental assessment capability that will be used to feed an ocean nowcast/forecast system. The goal is to develop a capacity for predicting the dynamics in inherent optical properties in coastal waters. This is being accomplished by developing an integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to calibrate hyperspectral remote sensing sensors in optically complex nearshore coastal waters.

Special section introduction on MicroMars to MegaMars

USGS Publications Warehouse

Bridges, Nathan T.; Dundas, Colin M.; Edgar, Lauren

2016-01-01

The study of Earth's surface and atmosphere evolved from local investigations to the incorporation of remote sensing on a global scale. The study of Mars has followed the opposite progression, beginning with telescopic observations, followed by flyby and orbital missions, landers, and finally rover missions in the last ∼20 years. This varied fleet of spacecraft (seven of which are currently operating as of this writing) provides a rich variety of datasets at spatial scales ranging from microscopic images to synoptic orbital remote sensing.

Introduction to AIRS and CrIS

NASA Technical Reports Server (NTRS)

Susskind, Joel

2004-01-01

"Introduction to AIRS and CrIS" is a chapter in a book dealing with various aspects of remote sensing. AIRS and CrIS are both high spectral resolution IR sounding instruments, which were recently launched (AIRS) or will soon be launched (CrIS). The chapter explains the general principles of infra-red remote sensing, and explains the significance and information content of high spectral resolution IR measurements. The chapter shows results obtained using AIRS observations, and explains why similar quality results should be obtainable from CrIS data.

77 FR 39220 - Advisory Committee on Commercial Remote Sensing (ACCRES); Charter Renewal

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-02

... Commercial Remote Sensing (ACCRES); Charter Renewal AGENCY: National Oceanic and Atmospheric Administration... Committee on Commercial Remote Sensing (ACCRES) was renewed on March 14, 2012. SUPPLEMENTARY INFORMATION: In... Commercial Remote Sensing (ACCRES) is in the public interest in connection with the performance of duties...

76 FR 66042 - Advisory Committee on Commercial Remote Sensing (ACCRES); Request for Nominations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

... Commercial Remote Sensing (ACCRES); Request for Nominations ACTION: Notice requesting nominations for the Advisory Committee on Commercial Remote Sensing (ACCRES). SUMMARY: The Advisory Committee on Commercial Remote Sensing (ACCRES) was established to advise the Secretary of Commerce, through the Under Secretary...

An introduction to quantitative remote sensing. [data processing

NASA Technical Reports Server (NTRS)

Lindenlaub, J. C.; Russell, J.

1974-01-01

The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.

Calibration of a distributed hydrologic model for six European catchments using remote sensing data

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

2017-12-01

While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

Mixed-phase altocumulus clouds over Leipzig: Remote sensing measurements and spectral cloud microphysics simulations

NASA Astrophysics Data System (ADS)

Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

2015-04-01

The present work combines remote sensing observations and detailed microphysics cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6°C. For comparison, a second mixed phase case at about -25°C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Temperature and humidity profiles are taken either from observation (radiosonde) or GDAS reanalysis. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to dynamical as well as ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

Utility of Satellite Remote Sensing for Land-Atmosphere Coupling and Drought Metrics

NASA Technical Reports Server (NTRS)

Roundy, Joshua K.; Santanello, Joseph A.

2017-01-01

Feedbacks between the land and the atmosphere can play an important role in the water cycle and a number of studies have quantified Land-Atmosphere (L-A) interactions and feedbacks through observations and prediction models. Due to the complex nature of L-A interactions, the observed variables are not always available at the needed temporal and spatial scales. This work derives the Coupling Drought Index (CDI) solely from satellite data and evaluates the input variables and the resultant CDI against in-situ data and reanalysis products. NASA's AQUA satellite and retrievals of soil moisture and lower tropospheric temperature and humidity properties are used as input. Overall, the AQUA-based CDI and its inputs perform well at a point, spatially, and in time (trends) compared to in-situ and reanalysis products. In addition, this work represents the first time that in-situ observations were utilized for the coupling classification and CDI. The combination of in-situ and satellite remote sensing CDI is unique and provides an observational tool for evaluating models at local and large scales. Overall, results indicate that there is sufficient information in the signal from simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information for applications of drought monitoring and coupling metrics.

Utility of Satellite Remote Sensing for Land-Atmosphere Coupling and Drought Metrics

PubMed Central

Roundy, Joshua K.; Santanello, Joseph A.

2018-01-01

Feedbacks between the land and the atmosphere can play an important role in the water cycle and a number of studies have quantified Land-Atmosphere (L-A) interactions and feedbacks through observations and prediction models. Due to the complex nature of L-A interactions, the observed variables are not always available at the needed temporal and spatial scales. This work derives the Coupling Drought Index (CDI) solely from satellite data and evaluates the input variables and the resultant CDI against in-situ data and reanalysis products. NASA’s AQUA satellite and retrievals of soil moisture and lower tropospheric temperature and humidity properties are used as input. Overall, the AQUA-based CDI and its inputs perform well at a point, spatially, and in time (trends) compared to in-situ and reanalysis products. In addition, this work represents the first time that in-situ observations were utilized for the coupling classification and CDI. The combination of in-situ and satellite remote sensing CDI is unique and provides an observational tool for evaluating models at local and large scales. Overall, results indicate that there is sufficient information in the signal from simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information for applications of drought monitoring and coupling metrics. PMID:29645012

Vegetation shifts observed in arctic tundra 17 years after fire

USGS Publications Warehouse

Barrett, Kirsten; Rocha, Adrian V.; van de Weg, Martine Janet; Shaver, Gaius

2012-01-01

With anticipated climate change, tundra fires are expected to occur more frequently in the future, but data on the long-term effects of fire on tundra vegetation composition are scarce. This study addresses changes in vegetation structure that have persisted for 17 years after a tundra fire on the North Slope of Alaska. Fire-related shifts in vegetation composition were assessed from remote-sensing imagery and ground observations of the burn scar and an adjacent control site. Early-season remotely sensed imagery from the burn scar exhibits a low vegetation index compared with the control site, whereas the late-season signal is slightly higher. The range and maximum vegetation index are greater in the burn scar, although the mean annual values do not differ among the sites. Ground observations revealed a greater abundance of moss in the unburned site, which may account for the high early growing season normalized difference vegetation index (NDVI) anomaly relative to the burn. The abundance of graminoid species and an absence of Betula nana in the post-fire tundra sites may also be responsible for the spectral differences observed in the remotely sensed imagery. The partial replacement of tundra by graminoid-dominated ecosystems has been predicted by the ALFRESCO model of disturbance, climate and vegetation succession.

Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

PubMed Central

Wang, Kai; Franklin, Steven E.; Guo, Xulin; Cattet, Marc

2010-01-01

Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS). PMID:22163432

Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists.

PubMed

Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc

2010-01-01

Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).

Remote Sensing and Reflectance Profiling in Entomology.

PubMed

Nansen, Christian; Elliott, Norman

2016-01-01

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

The use of remotely sensed data for operational fisheries oceanography

NASA Technical Reports Server (NTRS)

Fiuza, Armando F. G.

1992-01-01

Satellite remote sensing data are used under two contexts in fisheries: as a tool for fisheries research and as a means to provide operational support to fishing activities. Fishing operations need synoptic data provided timely; fisheries research needs that type of data and, also, good short-term climatologies. A description is given of several experiences conducted around the world which have employed or are using satellite data for operational fisheries problems. An overview is included of the Portuguese program for fisheries support using remotely sensed data provided by satellites and in situ observations conducted by fishermen. Environmental products useful for fisheries necessarily combine satellite and in situ data. The role of fishermen as a source of good, near-real-time in situ environmental data is stressed; so far, this role seems to have been largely overlooked.

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Current Insights and Trends. Chapter 3

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

2014-01-01

NASA or NOAA Earth-observing satellites are not the only space-based TIR platforms. The European Space Agency (ESA), the Chinese, and other countries have in orbit or plan to launch TIR remote sensing systems. Satellite remote sensing provides an excellent opportunity to study land-atmosphere energy exchanges at the regional scale. A predominant application of TIR data has been in inferring evaporation, evapotranspiration (ET), and soil moisture. In addition to using TIR data for ET and soil moisture analysis over vegetated surfaces, there is also a need for using these data for assessment of drought conditions. The concept of ecological thermodynamics provides a quantification of surface energy fluxes for landscape characterization in relation to the overall amount of energy input and output from specific land cover types.

Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios.

PubMed

Doxaran, David; Froidefond, Jean-Marie; Castaing, Patrice

2003-05-20

Variations of sediment type (grain size and refractive index) and changing illumination conditions affect the reflectance signal of coastal waters and limit the accuracy of sediment-concentration estimations from remote-sensing measurements. These effects are analyzed from numerous in situ remote-sensing measurements carried out in the Gironde and Loire Estuaries and then reduced and partly eliminated when reflectance ratios between the near infrared and the visible are considered. These ratios showed high correlation with the sediment concentration. On the basis of the obtained relationships, performing correspondence functions were established that allow an accurate estimation of suspended sediments in the estuaries from Système Probatoire d'Observation de la Terre, Landsat, and Sea-Viewing Wide Field-of-View Sensor data, independently of the date of acquisition.

Problems in merging Earth sensing satellite data sets

NASA Technical Reports Server (NTRS)

Smith, Paul H.; Goldberg, Michael J.

1987-01-01

Satellite remote sensing systems provide a tremendous source of data flow to the Earth science community. These systems provide scientists with data of types and on a scale previously unattainable. Looking forward to the capabilities of Space Station and the Earth Observing System (EOS), the full realization of the potential of satellite remote sensing will be handicapped by inadequate information systems. There is a growing emphasis in Earth science research to ask questions which are multidisciplinary in nature and global in scale. Many of these research projects emphasize the interactions of the land surface, the atmosphere, and the oceans through various physical mechanisms. Conducting this research requires large and complex data sets and teams of multidisciplinary scientists, often working at remote locations. A review of the problems of merging these large volumes of data into spatially referenced and manageable data sets is presented.

Verification of retail food outlet location data from a local health department using ground-truthing and remote-sensing technology: assessing differences by neighborhood characteristics.

PubMed

Rossen, Lauren M; Pollack, Keshia M; Curriero, Frank C

2012-09-01

Obtaining valid and accurate data on community food environments is critical for research evaluating associations between the food environment and health outcomes. This study utilized ground-truthing and remote-sensing technology to validate a food outlet retail list obtained from an urban local health department in Baltimore, Maryland in 2009. Ten percent of outlets (n=169) were assessed, and differences in accuracy were explored by neighborhood characteristics (96 census tracts) to determine if discrepancies were differential or non-differential. Inaccuracies were largely unrelated to a variety of neighborhood-level variables, with the exception of number of vacant housing units. Although remote-sensing technologies are a promising low-cost alternative to direct observation, this study demonstrated only moderate levels of agreement with ground-truthing. Published by Elsevier Ltd.

Middle Term Achievements of Project 5322: Retrieval Of Key Eco-Hydrological Parameters From Remote Sensing In The Watershed Allied Telemetry Experimental Research (Water)

NASA Astrophysics Data System (ADS)

Li, Xin; Menenti, Massimo

2010-10-01

The general objective of project 5322 in the Dragon 2 programme is to quantitatively retrieve some key eco- hydrological parameters by using remote sensed data, especially from ESA, Chinese, and the Third Party Mission (TPM). To achieve this goal, a comprehensive observation experiment, Watershed Allied Telemetry Experimental Research (WATER) was carried out. WARER is a simultaneously airborne, satellite-borne, and ground-based remote sensing experiment took place in the Heihe River Basin, a typical inland river basin in the northwest of China. This paper introduces the background and implementation of WATER. Data have been obtained so far are described in details. After a period of data analysis for two years, numerous results have also been achieved. This paper presents some early results of WATER as well.

Remote Sensing in Geography in the New Millennium: Prospects, Challenges, and Opportunities

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Jensen, John R.; Morain, Stanley A.; Walsh, Stephen J.; Ridd, Merrill K.

1999-01-01

Remote sensing science contributes greatly to our understanding of the Earth's ecosystems and cultural landscapes. Almost all the natural and social sciences, including geography, rely heavily on remote sensing to provide quantitative, and indispensable spatial information. Many geographers have made significant contributions to remote sensing science since the 1970s, including the specification of advanced remote sensing systems, improvements in analog and digital image analysis, biophysical modeling, and terrain analysis. In fact, the Remote Sensing Specialty Group (RSSG) is one of the largest specialty groups within the AAG with over 500 members. Remote sensing in concert with a geographic information systems, offers much value to geography as both an incisive spatial-analytical tool and as a scholarly pursuit that adds to the body of geographic knowledge on the whole. The "power" of remote sensing as a research endeavor in geography lies in its capabilities for obtaining synoptic, near-real time data at many spatial and temporal scales, and in many regions of the electromagnetic spectrum - from microwave, to RADAR, to visible, and reflective and thermal infrared. In turn, these data present a vast compendium of information for assessing Earth attributes and characte6stics that are at the very core of geography. Here we revisit how remote sensing has become a fundamental and important tool for geographical research, and how with the advent of new and improved sensing systems to be launched in the near future, remote sensing will further advance geographical analysis in the approaching New Millennium.

Agricultural Production Monitoring in the Sahel Using Remote Sensing: Present Possibilities and Research Needs

DTIC Science & Technology

1993-01-01

during the agricultural season. Satellite remote sensing can contribute significantly to such a system by collecting information on crops and on...well as techniques to derive biophysical variables from remotely-sensed data. Finally, the integration of these remote - sensing techniques with crop

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

Recent Progresses of Microwave Marine Remote Sensing

NASA Astrophysics Data System (ADS)

Yang, Jingsong; Ren, Lin; Zheng, Gang; Wang, He; He, Shuangyan; Wang, Juan; Li, Xiaohui

2016-08-01

It is presented in this paper the recent progresses of Dragon 3 Program (ID. 10412) in the field of microwave marine remote sensing including (1) ocean surface wind fields from full polarization synthetic aperture radars (SAR), (2) joint retrieval of directional ocean wave spectra from SAR and wave spectrometer, (3) error analysis on ENVISAT ASAR wave mode significant wave height (SWH) retrievals using triple collocation model, (4) typhoon observation from SAR and optical sensors, (5) ocean internal wave observation from SAR and optical sensors, (6) ocean eddy observation from SAR and optical sensors, (7) retrieval models of water vapor and wet tropospheric path delay for the HY-2A calibration microwave radiometer, (8) calibration of SWH from HY-2A satellite altimeter.

Method of determining forest production from remotely sensed forest parameters

DOEpatents

Corey, J.C.; Mackey, H.E. Jr.

1987-08-31

A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

Removal of Surface-Reflected Light for the Measurement of Remote-Sensing Reflectance from an Above-Surface Platform

DTIC Science & Technology

2010-12-01

remote - sensing reflectance) can be highly inaccurate if a spectrally constant value is applied (although errors can be reduced by carefully filtering measured raw data). To remove surface-reflected light in field measurements of remote sensing reflectance, a spectral optimization approach was applied, with results compared with those from remote sensing models and from direct measurements. The agreement from different determinations suggests that reasonable results for remote sensing reflectance of clear

Removal of Surface-Reflected Light for the Measurement of Remote-Sensing Reflectance from an Above-Surface Platform

DTIC Science & Technology

2010-12-06

remote - sensing reflectance) can be highly inaccurate if a spectrally constant value is applied (although errors can be reduced by carefully filtering measured raw data). To remove surface-reflected light in field measurements of remote sensing reflectance, a spectral optimization approach was applied, with results compared with those from remote sensing models and from direct measurements. The agreement from different determinations suggests that reasonable results for remote sensing reflectance of clear

Submillimeter Remote Sensing of Planetary and Cometary Atmospheres and LRO/LCROSS Observations of the Moon

NASA Technical Reports Server (NTRS)

Chin, Gordon

2011-01-01

Submillimeter remote sensing of planetary and cometary atmospheres have been proposed for Venus and Mars while MIRO on Rosetta will observe the coma of Comet 67P/Churyumov - Cierasimenko in December 2015, UARS and AURA MLS have observed millimeter and submillimeter molecule emissions in the Earth's stratosphere for many decades, Observations of submillimeter wave molecular emissions provide a wealth of information not obtainable by alternative techniques. Submillimeter line emissions exhibit linear temperature dependence, insensitivity to aerosol scattering, extinction, and have separated transitions with well determined line-shapes. These observations have high sensitivities to trace chemical species and can; 1) Fully resolve the line profiles of molecules with high resolution, 2) Provide deterministic retrievals of species abundance, temperature, and pressure, and 3) Measure Doppler shifts of detected molecules for wind velocities.

Estimation of Regional Evapotranspiration Using Remotely Sensed Land Surface Temperature. Part 1: Measurement of Evapotranspiration at the Environmental Research Center and Determination of Priestley-taylor Parameter

NASA Technical Reports Server (NTRS)

Kotada, K.; Nakagawa, S.; Kai, K.; Yoshino, M. M.; Takeda, K.; Seki, K.

1985-01-01

In order to study the distribution of evapotranspiration in the humid region using remote sensing technology, the parameter (alpha) in the Priestley-Taylor model was determined. The daily means of the parameter alpha = 1.14 can be available from summer to autumn and alpha = to approximately 2.0 in winter. The results of the satellite and the airborne sensing done on 21st and 22nd January, 1983, are described. Using the vegetation distribution in the Tsukuba Academic New Town, as well as the radiation temperature obtained by remote sensing and the radiation data observed at the ground surface, the evapotranspiration was calculated for each vegetation type by the Priestley-Taylor method. The daily mean evapotranspiration on 22nd January, 1983, was approximately 0.4 mm/day. The differences in evapotranspiration between the vegetation types were not detectable, because the magnitude of evapotranspiration is very little in winter.

Field Data Collection: an Essential Element in Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Pettinger, L. R.

1971-01-01

Field data collected in support of remote sensing projects are generally used for the following purposes: (1) calibration of remote sensing systems, (2) evaluation of experimental applications of remote sensing imagery on small test sites, and (3) designing and evaluating operational regional resource studies and inventories which are conducted using the remote sensing imagery obtained. Field data may be used to help develop a technique for a particular application, or to aid in the application of that technique to a resource evaluation or inventory problem for a large area. Scientists at the Forestry Remote Sensing Laboratory have utilized field data for both purposes. How meaningful field data has been collected in each case is discussed.

Remote sensing and eLearning 2.0 for school education

NASA Astrophysics Data System (ADS)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2010-10-01

The "Remote Sensing in Schools" project aims at improving the integration of "Satellite remote sensing" into school teaching. Therefore, it is the project's overall objective to teach students in primary and secondary schools the basics and fields of application of remote sensing. Existing results show that many teachers are interested in remote sensing and at same time motivated to integrate it into their teaching. Despite the good intention, in the end, the implementation often fails due to the complexity and poor set-up of the information provided. Therefore, a comprehensive and well-structured learning platform on the topic of remote sensing is developed. The platform shall allow a structured introduction to the topic.

Controlling Malaria and Other Diseases Using Remote Sensing

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Wharton, Stephen W. (Technical Monitor)

2001-01-01

Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.

Airborne and satellite remote sensing of the mid-infrared water vapour continuum.

PubMed

Newman, Stuart M; Green, Paul D; Ptashnik, Igor V; Gardiner, Tom D; Coleman, Marc D; McPheat, Robert A; Smith, Kevin M

2012-06-13

Remote sensing of the atmosphere from space plays an increasingly important role in weather forecasting. Exploiting observations from the latest generation of weather satellites relies on an accurate knowledge of fundamental spectroscopy, including the water vapour continuum absorption. Field campaigns involving the Facility for Airborne Atmospheric Measurements research aircraft have collected a comprehensive dataset, comprising remotely sensed infrared radiance observations collocated with accurate measurements of the temperature and humidity structure of the atmosphere. These field measurements have been used to validate the strength of the infrared water vapour continuum in comparison with the latest laboratory measurements. The recent substantial changes to self-continuum coefficients in the widely used MT_CKD (Mlawer-Tobin-Clough-Kneizys-Davies) model between 2400 and 3200 cm(-1) are shown to be appropriate and in agreement with field measurements. Results for the foreign continuum in the 1300-2000 cm(-1) band suggest a weak temperature dependence that is not currently included in atmospheric models. A one-dimensional variational retrieval experiment is performed that shows a small positive benefit from using new laboratory-derived continuum coefficients for humidity retrievals.

Airborne remote sensing and in situ measurements of atmospheric CO2 to quantify point source emissions

NASA Astrophysics Data System (ADS)

Krings, Thomas; Neininger, Bruno; Gerilowski, Konstantin; Krautwurst, Sven; Buchwitz, Michael; Burrows, John P.; Lindemann, Carsten; Ruhtz, Thomas; Schüttemeyer, Dirk; Bovensmann, Heinrich

2018-02-01

Reliable techniques to infer greenhouse gas emission rates from localised sources require accurate measurement and inversion approaches. In this study airborne remote sensing observations of CO2 by the MAMAP instrument and airborne in situ measurements are used to infer emission estimates of carbon dioxide released from a cluster of coal-fired power plants. The study area is complex due to sources being located in close proximity and overlapping associated carbon dioxide plumes. For the analysis of in situ data, a mass balance approach is described and applied, whereas for the remote sensing observations an inverse Gaussian plume model is used in addition to a mass balance technique. A comparison between methods shows that results for all methods agree within 10 % or better with uncertainties of 10 to 30 % for cases in which in situ measurements were made for the complete vertical plume extent. The computed emissions for individual power plants are in agreement with results derived from emission factors and energy production data for the time of the overflight.

Deriving Leaf Area Index (LAI) from multiple lidar remote sensing systems

NASA Astrophysics Data System (ADS)

Tang, H.; Dubayah, R.; Zhao, F.

2012-12-01

LAI is an important biophysical variable linking biogeochemical cycles of earth systems. Observations with passive optical remote sensing are plagued by saturation and results from different passive and active sensors are often inconsistent. Recently lidar remote sensing has been applied to derive vertical canopy structure including LAI and its vertical profile. In this research we compare LAI retrievals from three different types of lidar sensors. The study areas include the La Selva Biological Station in Costa Rica and Sierra Nevada Forest in California. We first obtain independent LAI estimates from different lidar systems including airborne lidar (LVIS), spaceborne lidar (GLAS) and ground lidar (Echidna). LAI retrievals are then evaluated between sensors as a function of scale, land cover type and sensor characteristics. We also assess the accuracy of these LAI products against ground measurements. By providing a link between ground observations, ground lidar, aircraft and space-based lidar we hope to demonstrate a path for deriving more accurate estimates of LAI on a global basis, and to provide a more robust means of validating passive optical estimates of this important variable.

Remote sensing requirements as suggested by watershed model sensitivity analyses

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Rango, A.; Ormsby, J. P.; Ambaruch, R.

1975-01-01

A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.

Data Quality in Remote Sensing

NASA Astrophysics Data System (ADS)

Batini, C.; Blaschke, T.; Lang, S.; Albrecht, F.; Abdulmutalib, H. M.; Barsi, Á.; Szabó, G.; Kugler, Zs.

2017-09-01

The issue of data quality (DQ) is of growing importance in Remote Sensing (RS), due to the widespread use of digital services (incl. apps) that exploit remote sensing data. In this position paper a body of experts from the ISPRS Intercommission working group III/IVb "DQ" identifies, categorises and reasons about issues that are considered as crucial for a RS research and application agenda. This ISPRS initiative ensures to build on earlier work by other organisations such as IEEE, CEOS or GEO, in particular on the meritorious work of the Quality Assurance Framework for Earth Observation (QA4EO) which was established and endorsed by the Committee on Earth Observation Satellites (CEOS) but aims to broaden the view by including experts from computer science and particularly database science. The main activities and outcomes include: providing a taxonomy of DQ dimensions in the RS domain, achieving a global approach to DQ for heterogeneous-format RS data sets, investigate DQ dimensions in use, conceive a methodology for managing cost effective solutions on DQ in RS initiatives, and to address future challenges on RS DQ dimensions arising in the new era of the big Earth data.

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

NASA Astrophysics Data System (ADS)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

Satellites as Sentinels for Environment & Health

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.

2002-01-01

Satellites as Sentinels for Environment & Health Remotely-sensed data and observations are providing powerful new tools for addressing human and ecosystem health by enabling improved understanding of the relationships and linkages between health-related environmental parameters and society as well as techniques for early warning of potential health problems. NASA Office of Earth Science Applications Program has established a new initiative to utilize its data, expertise, and observations of the Earth for public health applications. In this initiative, lead by Goddard Space Flight Center, remote sensing, geographic information systems, improved computational capabilities, and interdisciplinary research between the Earth and health science communities are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global health issues. This presentation provides a number of recent examples of applications of advanced remote sensing and other technologies to health.and security issues related to the following: infectious and vector-borne diseases; urban, regional and global air pollution; African and Asian airborne dust; heat stress; UV radiation; water-borne disease; extreme weather; contaminant pathways (ocean, atmosphere, ice)

Remote sensing programs and courses in engineering and water resources

NASA Technical Reports Server (NTRS)

Kiefer, R. W.

1981-01-01

The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

ESTUARINE PHYTOPLANKTON PRIMARY PRODUCTION AND SIZE AS DETERMINED REMOTELY FROM AIRCRAFT AND COASTAL OBSERVATION

EPA Science Inventory

We used remotely sensed estimates of chlorophyll a and sea surface temperature, incorporated into the Chesapeake Bay Productivity Model (Harding et al., 2002), to estimate the spatial and temporal variation of phytoplankton net primary production and species size in the Narragans...

Interplanetary Propagation of Coronal Mass Ejections

NASA Technical Reports Server (NTRS)

Gopalswamy, Nat

2011-01-01

Although more than ten thousand coronal mass ejections (CMEs) are produced during each solar cycle at the Sun, only a small fraction hits the Earth. Only a small fraction of the Earth-directed CMEs ultimately arrive at Earth depending on their interaction with the solar wind and other large-scale structures such as coronal holes and CMEs. The interplanetary propagation is essentially controlled by the drag force because the propelling force and the solar gravity are significant only near the Sun. Combined remote-sensing and in situ observations have helped us estimate the influence of the solar wind on the propagation of CMEs. However, these measurements have severe limitations because the remote-sensed and in-situ observations correspond to different portions of the CME. Attempts to overcome this problem are made in two ways: the first is to model the CME and get the space speed of the CME, which can be compared with the in situ speed. The second method is to use stereoscopic observation so that the remote-sensed and in-situ observations make measurements on the Earth-arriving part of CMEs. The Solar Terrestrial Relations Observatory (STEREO) mission observed several such CMEs, which helped understand the interplanetary evolution of these CMEs and to test earlier model results. This paper discusses some of these issues and updates the CME/shock travel time estimates for a number of CMEs.

Unmanned aerial vehicle: A unique platform for low-altitude remote sensing for crop management

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...

Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

Treesearch

Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan

2016-01-01

Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...

75 FR 32360 - Proposed Information Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-08

... Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems AGENCY: National Oceanic and.... Abstract NOAA has established requirements for the licensing of private operators of remote-sensing space... Land Remote- Sensing Policy Act of 1992 and with the national security and international obligations of...

78 FR 44536 - Proposed Information Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-24

... Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems AGENCY: National Oceanic and... for the licensing of private operators of remote-sensing space systems. The information in applications and subsequent reports is needed to ensure compliance with the Land Remote- Sensing Policy Act of...

Advancement of China’s Visible Light Remote Sensing Technology In Aerospace,

DTIC Science & Technology

1996-03-19

Aerospace visible light film systems were among the earliest space remote sensing systems to be developed in China. They have been applied very well...makes China the third nation in the world to master space remote sensing technology, it also puts recoverable remote sensing satellites among the first

Review: advances in in situ and satellite phenological observations in Japan

NASA Astrophysics Data System (ADS)

Nagai, Shin; Nasahara, Kenlo Nishida; Inoue, Tomoharu; Saitoh, Taku M.; Suzuki, Rikie

2016-04-01

To accurately evaluate the responses of spatial and temporal variation of ecosystem functioning (evapotranspiration and photosynthesis) and services (regulating and cultural services) to the rapid changes caused by global warming, we depend on long-term, continuous, near-surface, and satellite remote sensing of phenology over wide areas. Here, we review such phenological studies in Japan and discuss our current knowledge, problems, and future developments. In contrast with North America and Europe, Japan has been able to evaluate plant phenology along vertical and horizontal gradients within a narrow area because of the country's high topographic relief. Phenological observation networks that support scientific studies and outreach activities have used near-surface tools such as digital cameras and spectral radiometers. Differences in phenology among ecosystems and tree species have been detected by analyzing the seasonal variation of red, green, and blue digital numbers (RGB values) extracted from phenological images, as well as spectral reflectance and vegetation indices. The relationships between seasonal variations in RGB-derived indices or spectral characteristics and the ecological and CO2 flux measurement data have been well validated. In contrast, insufficient satellite remote-sensing observations have been conducted because of the coarse spatial resolution of previous datasets, which could not detect the heterogeneous plant phenology that results from Japan's complex topography and vegetation. To improve Japanese phenological observations, multidisciplinary analysis and evaluation will be needed to link traditional phenological observations with "index trees," near-surface and satellite remote-sensing observations, "citizen science" (observations by citizens), and results published on the Internet.

Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong

NASA Astrophysics Data System (ADS)

Huang, Yuhan; Organ, Bruce; Zhou, John L.; Surawski, Nic C.; Hong, Guang; Chan, Edward F. C.; Yam, Yat Shing

2018-06-01

Vehicle emissions are a major contributor to air pollution in cities and have serious health impacts to their inhabitants. On-road remote sensing is an effective and economic tool to monitor and control vehicle emissions. In this review, the mechanism, accuracy, advantages and limitations of remote sensing were introduced. Then the applications and major findings of remote sensing were critically reviewed. It was revealed that the emission distribution of on-road vehicles was highly skewed so that the dirtiest 10% vehicles accounted for over half of the total fleet emissions. Such findings highlighted the importance and effectiveness of using remote sensing for in situ identification of high-emitting vehicles for further inspection and maintenance programs. However, the accuracy and number of vehicles affected by screening programs were greatly dependent on the screening criteria. Remote sensing studies showed that the emissions of gasoline and diesel vehicles were significantly reduced in recent years, with the exception of NOx emissions of diesel vehicles in spite of greatly tightened automotive emission regulations. Thirdly, the experience and issues of using remote sensing for identifying high-emitting vehicles in Hong Kong (where remote sensing is a legislative instrument for enforcement purposes) were reported. That was followed by the first time ever identification and discussion of the issue of frequent false detection of diesel high-emitters using remote sensing. Finally, the challenges and future research directions of on-road remote sensing were elaborated.

Evaluating ESA CCI Soil Moisture in East Africa

NASA Technical Reports Server (NTRS)

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R.; Wang, Shugong; Peters-Lidard, Christa D.; Verdin, James P.

2016-01-01

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASAs Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R greater than 0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

Monitoring crop coefficient of orange orchards using energy balance and the remote sensed NDVI

NASA Astrophysics Data System (ADS)

Consoli, Simona; Cirelli, Giuseppe Luigi; Toscano, Attilio

2006-09-01

The structure of vegetation is paramount in regulating the exchange of mass and energy across the biosphereatmosphere interface. In particular, changes in vegetation density affected the partitioning of incoming solar energy into sensible and latent heat fluxes that may result in persistent drought through reductions in agricultural productivity and in the water resources availability. Limited research with citrus orchards has shown improvements to irrigation scheduling due to better water-use estimation and more appropriate timing of irrigation when crop coefficient (Kc) estimate, derived from remotely sensed multispectral vegetation indices (VIs), are incorporated into irrigation-scheduling algorithms. The purpose of this article is the application of an empirical reflectance-based model for the estimation of Kc and evapotranspiration fluxes (ET) using ground observations on climatic data and high-resolution VIs from ASTER TERRA satellite imagery. The remote sensed Kc data were used in developing the relationship with the normalized difference vegetation index (NDVI) for orange orchards during summer periods. Validation of remote sensed data on ET, Kc and vegetation features was deal through ground data observations and the resolution of the energy balance to derive latent heat flux density (λE), using measures of net radiation (Rn) and soil heat flux density (G) and estimate of sensible heat flux density (H) from high frequency temperature measurements (Surface Renewal technique). The chosen case study is that of an irrigation area covered by orange orchards located in Eastern Sicily, Italy) during the irrigation seasons 2005 and 2006.

FerryBox and MERIS Assessment of coastal and shelf sea ecosystems by combining in situ and remotely sensed data

NASA Astrophysics Data System (ADS)

Petersen, W.; Wehde, H.; Krasemann, H.; Colijn, F.; Schroeder, F.

2008-04-01

An automatic measuring system called " FerryBox" was installed in the North Sea on a ferry travelling between Germany (Cuxhaven) and Great Britain (Harwich), enabling online oceanographic and biological measurements such as salinity, temperature, fluorescence, turbidity, oxygen, pH, and nutrient concentrations. Observations made along the ferry transect reveal characteristic phenomena such as high salinity inflow through the Channel into the Southern Bight, algal bloom dynamics and related oxygen and pH changes. Combination of these online observations with remote sensing enhances the spatial resolution of the transect related measurements. Several examples of the synergy between these two measuring strategies are shown, both for large-scale algal blooms in the North Sea as well as for local intense but short-term blooms in the German Bight. Coherence of the data sets can be gained and improved by using water transport models in order to obtain synoptic overviews of the remotely sensed and FerryBox related parameters. Limitations of the currently used algorithms for deriving chlorophyll- a from remote sensing images for coastal and shelf seas (Case-2 water) are discussed, as well as depth related processes which cannot be properly resolved on the basis of water intake at a fixed point. However, in unstratified coastal waters under normal conditions FerryBox data represent average conditions. The importance of future applications of this combination of methods for monitoring of coastal waters is emphasized.

Discharge prediction in the Upper Senegal River using remote sensing data

NASA Astrophysics Data System (ADS)

Ceccarini, Iacopo; Raso, Luciano; Steele-Dunne, Susan; Hrachowitz, Markus; Nijzink, Remko; Bodian, Ansoumana; Claps, Pierluigi

2017-04-01

The Upper Senegal River, West Africa, is a poorly gauged basin. Nevertheless, discharge predictions are required in this river for the optimal operation of the downstream Manantali reservoir, flood forecasting, development plans for the entire basin and studies for adaptation to climate change. Despite the need for reliable discharge predictions, currently available rainfall-runoff models for this basin provide only poor performances, particularly during extreme regimes, both low-flow and high-flow. In this research we develop a rainfall-runoff model that combines remote-sensing input data and a-priori knowledge on catchment physical characteristics. This semi-distributed model, is based on conceptual numerical descriptions of hydrological processes at the catchment scale. Because of the lack of reliable input data from ground observations, we use the Tropical Rainfall Measuring Mission (TRMM) remote-sensing data for precipitation and the Global Land Evaporation Amsterdam Model (GLEAM) for the terrestrial potential evaporation. The model parameters are selected by a combination of calibration, by match of observed output and considering a large set of hydrological signatures, as well as a-priori knowledge on the catchment. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to choose the most likely range in which the parameter sets belong. Analysis of different experiments enhances our understanding on the added value of distributed remote-sensing data and a-priori information in rainfall-runoff modelling. Results of this research will be used for decision making at different scales, contributing to a rational use of water resources in this river.

Remote sensing of natural resources: Quarterly literature review

NASA Technical Reports Server (NTRS)

1976-01-01

A quarterly review of technical literature concerning remote sensing techniques is presented. The format contains indexed and abstracted materials with emphasis on data gathering techniques performed or obtained remotely from space, aircraft, or ground-based stations. Remote sensor applications including the remote sensing of natural resources are presented.

Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data

NASA Astrophysics Data System (ADS)

Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar

2012-10-01

Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.

Meta Data Mining in Earth Remote Sensing Data Archives

NASA Astrophysics Data System (ADS)

Davis, B.; Steinwand, D.

2014-12-01

Modern search and discovery tools for satellite based remote sensing data are often catalog based and rely on query systems which use scene- (or granule-) based meta data for those queries. While these traditional catalog systems are often robust, very little has been done in the way of meta data mining to aid in the search and discovery process. The recently coined term "Big Data" can be applied in the remote sensing world's efforts to derive information from the vast data holdings of satellite based land remote sensing data. Large catalog-based search and discovery systems such as the United States Geological Survey's Earth Explorer system and the NASA Earth Observing System Data and Information System's Reverb-ECHO system provide comprehensive access to these data holdings, but do little to expose the underlying scene-based meta data. These catalog-based systems are extremely flexible, but are manually intensive and often require a high level of user expertise. Exposing scene-based meta data to external, web-based services can enable machine-driven queries to aid in the search and discovery process. Furthermore, services which expose additional scene-based content data (such as product quality information) are now available and can provide a "deeper look" into remote sensing data archives too large for efficient manual search methods. This presentation shows examples of the mining of Landsat and Aster scene-based meta data, and an experimental service using OPeNDAP to extract information from quality band from multiple granules in the MODIS archive.

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

An Adaptive Web-Based Learning Environment for the Application of Remote Sensing in Schools

NASA Astrophysics Data System (ADS)

Wolf, N.; Fuchsgruber, V.; Riembauer, G.; Siegmund, A.

2016-06-01

Satellite images have great educational potential for teaching on environmental issues and can promote the motivation of young people to enter careers in natural science and technology. Due to the importance and ubiquity of remote sensing in science, industry and the public, the use of satellite imagery has been included into many school curricular in Germany. However, its implementation into school practice is still hesitant, mainly due to lack of teachers' know-how and education materials that align with the curricula. In the project "Space4Geography" a web-based learning platform is developed with the aim to facilitate the application of satellite imagery in secondary school teaching and to foster effective student learning experiences in geography and other related subjects in an interdisciplinary way. The platform features ten learning modules demonstrating the exemplary application of original high spatial resolution remote sensing data (RapidEye and TerraSAR-X) to examine current environmental issues such as droughts, deforestation and urban sprawl. In this way, students will be introduced into the versatile applications of spaceborne earth observation and geospatial technologies. The integrated web-based remote sensing software "BLIF" equips the students with a toolset to explore, process and analyze the satellite images, thereby fostering the competence of students to work on geographical and environmental questions without requiring prior knowledge of remote sensing. This contribution presents the educational concept of the learning environment and its realization by the example of the learning module "Deforestation of the rainforest in Brasil".

An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

NASA Astrophysics Data System (ADS)

Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

2018-01-01

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

An ecological assessment of pasturelands in the Balkhash area of Kazakhstan with remote sensing and models

NASA Astrophysics Data System (ADS)

Lebed, L.; Qi, J.; Heilman, P.

2012-06-01

The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation’s economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation.

Proxies for soil organic carbon derived from remote sensing

NASA Astrophysics Data System (ADS)

Rasel, S. M. M.; Groen, T. A.; Hussin, Y. A.; Diti, I. J.

2017-07-01

The possibility of carbon storage in soils is of interest because compared to vegetation it contains more carbon. Estimation of soil carbon through remote sensing based techniques can be a cost effective approach, but is limited by available methods. This study aims to develop a model based on remotely sensed variables (elevation, forest type and above ground biomass) to estimate soil carbon stocks. Field observations on soil organic carbon, species composition, and above ground biomass were recorded in the subtropical forest of Chitwan, Nepal. These variables were also estimated using LiDAR data and a WorldView 2 image. Above ground biomass was estimated from the LiDAR image using a novel approach where the image was segmented to identify individual trees, and for these trees estimates of DBH and Height were made. Based on AIC (Akaike Information Criterion) a regression model with above ground biomass derived from LiDAR data, and forest type derived from WorldView 2 imagery was selected to estimate soil organic carbon (SOC) stocks. The selected model had a coefficient of determination (R2) of 0.69. This shows the scope of estimating SOC with remote sensing derived variables in sub-tropical forests.

Review of FEWS NET Biophysical Monitoring Requirements

NASA Technical Reports Server (NTRS)

Ross, K. W.; Brown, Molly E.; Verdin, J.; Underwood, L. W.

2009-01-01

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users: it focused upon operational requirements to determine additional useful remote sensing data and; subsequently, beneficial FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world, enabling a robust set of professional perspectives to be gathered and analyzed rapidly. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard: that high resolution remote sensing products continue to be in demand, and that rainfall and vegetation products were valued as data that provide actionable food security information.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

Preliminary data for the 20 May 1974, simultaneous evaluation of remote sensors experiment. [water pollution monitoring

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Batten, C. E.; Bowker, D. E.; Bressette, W. E.; Grew, G. W.

1975-01-01

Several remote sensors were simultaneously used to collect data over the tidal James River from Hopewell to Norfolk, Virginia. Sensors evaluated included the Multichannel-Ocean Color Sensor, multispectral scanners, and multispectral photography. Ground truth measurements and remotely sensed data are given. Preliminary analysis indicates that suspended sediment and concentrated industrial effluent are observable from all sensors.

Modeling river discharge and sediment transport in the Wax Lake-Atchafalaya basin with remote sensing parametrization.

NASA Astrophysics Data System (ADS)

Simard, M.; Liu, K.; Denbina, M. W.; Jensen, D.; Rodriguez, E.; Liao, T. H.; Christensen, A.; Jones, C. E.; Twilley, R.; Lamb, M. P.; Thomas, N. A.

2017-12-01

Our goal is to estimate the fluxes of water and sediments throughout the Wax Lake-Atchafalaya basin. This was achieved by parametrization of a set of 1D (HEC-RAS) and 2D (DELFT3D) hydrology models with state of the art remote sensing measurements of water surface elevation, water surface slope and total suspended sediment (TSS) concentrations. The model implementations are spatially explicit, simulating river currents, lateral flows to distributaries and marshes, and spatial variations of sediment concentrations. Three remote sensing instruments were flown simultaneously to collect data over the Wax Lake-Atchafalaya basin, and along with in situ field data. A Riegl Lidar was used to measure water surface elevation and slope, while the UAVSAR L-band radar collected data in repeat-pass interferometric mode to measure water level change within adjacent marshes and islands. These data were collected several times as the tide rose and fell. AVRIS-NG instruments measured water surface reflectance spectra, used to estimate TSS. Bathymetry was obtained from sonar transects and water level changes were recorded by 19 water level pressure transducers. We used several Acoustic Doppler Current Profiler (ADCP) transects to estimate river discharge. The remotely sensed measurements of water surface slope were small ( 1cm/km) and varied slightly along the channel, especially at the confluence with bayous and the intra-coastal waterway. The slope also underwent significant changes during the tidal cycle. Lateral fluxes to island marshes were mainly observed by UAVSAR close to the distributaries. The extensive remote sensing measurements showed significant disparity with the hydrology model outputs. Observed variations in water surface slopes were unmatched by the model and tidal wave propagation was much faster than gauge measurements. The slope variations were compensated for in the models by tuning local lateral fluxes, bathymetry and riverbed friction. Overall, the simpler 1D model could best simulate observed tidal wave propagation and water surface slope. The complexity of the 2D model requires further quantification of parameter sensitivity and improvement of the parametrization routine.

Research activity of the greenhouse gas measurements using optical remote sensing in Japan (Invited)

NASA Astrophysics Data System (ADS)

Asai, K.

2009-12-01

Japan might be one of the most active countries dedicating themselves to studying the greenhouse gas (GHG) measurements using optical remote sensing not only on the ground but also from space. There are two reasons; one of them ascends to the Kyoto Protocol, agreed in December 1997 in Kyoto, an ancient city of Japan until 19th centuries, was designed to address the international response to serious climate change due to greenhouse gases. The other reason is due to a revision of the Basic Environment Law of Japan in order to meet the Kyoto Protocol in 1998. The State makes efforts to ensure international collaboration so as to effectively promote the monitoring, observation and measurement of the environmental situation with regard to global warming. Main activities are listed in a Table1. They are divided into two categories, i.e. the Greenhouse gases Observing SATellite (GOSAT), launched on Jan.23, 2009 and active remote sensing using lidar technology. In case of GOSAT, an initial analysis of carbon dioxide and methane concentrations was obtained for clear-sky scenes over land. In the future, after further calibration and validation of the data, observation data and corresponding analyzed products will be made available. On the other hand, studies of the laser remote sensing for measuring GHG have been actively carrying out to achieve reliable data with a higher accuracy at wavelengths of 1.6micron meter (Tokyo Metropolitan University, JAXA, Mitsubishi Electric Co.) and 2 micron meter (National Institute of Information and Communications Technology). As well-known, one of the most interests regarding atmospheric CO2 measurements is that carbon dioxide molecule measured are due to anthropological emission from fossil fuel burning or due to natural one from forest fires etc. We proposed a newly advanced CO2/CO DIAL using a hybrid of pulsed Tm,Ho:YLF and pulsed OPO pumped by it for better understanding them. Now, our effort is directed to find out the most suitable wavelength pairs to be selected.Activities of optical remote sensing for GHG in Japan

Monitoring vegetation dynamics in the Amazon with RapidScat

NASA Astrophysics Data System (ADS)

van Emmerik, Tim; Steele-Dunne, Susan; Paget, Aaron C.; van de Giesen, Nick

2017-04-01

Several studies affiliated diurnal variations in radar backscatter over the Amazon [1,2] with vegetation water stress. Recent studies on tree and corn canopies [3,4] have demonstrated that during periods of low soil moisture availability, the total radar backscatter is primarily sensitive to changes in leaf water content, highlighting the potential of radar for water stress detection. The RapidScat mission (Ku-band, 13.4GHz), mounted on the International Space Station, observes the Earth in a non-sun-synchronous orbit [5]. This unique orbit allows for reconstructing diurnal cycles of radar backscatter. We hypothesize that the state of the canopy is a significant portion of the diurnal variations observed in the radar backscatter. Recent, yet inconclusive, analyses support the theory of the impact of vegetation water content on diurnal variation in RapidScat radar backscatter over the Amazon and Congo. Linking ground measurements of canopy dynamics to radar backscatter will allow further exploration of the possibilities for monitoring vegetation dynamics. Our presentation focuses of two parts. First, we reconstruct diurnal cycles of RapidScat backscatter over the Amazon, and study its variation over time. Second, we analyze the pre-dawn backscatter over time. The water content at this time of day is a measure of water stress, and might therefore be visible in the backscatter time series. References [1] Frolking, S., et al.: "Tropical forest backscatter anomaly evident in SeaWinds scatterometer morning overpass data during 2005 drought in Amazonia", Remote Sensing of Environment, 2011. [2] Jaruwatanadilok, S., and B. Stiles: "Trends and variation in Ku-band backscatter of natural targets on land observed in QuikSCAT data", IEEE Transactions on Geoscience and Remote Sensing , 2014. [3] Steele-Dunne, S., et al.: "Using diurnal variation in backscatter to detect vegetation water stress", IEEE Transactions on Geoscience and Remote Sensing, 2012. [4] van Emmerik, T., et al.: "Impact of diurnal variation in vegetation water content on radar backscatter from maize during water stress", IEEE Transactions on Geoscience and Remote Sensing, 2015. [5] Paget, A., et al.: "RapidScat Diurnal Cycles Over Land", IEEE Transactions on Geoscience and Remote Sensing, 2016.

Scaling forest phenology from trees to the landscape using an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Klosterman, S.; Melaas, E. K.; Martinez, A.; Richardson, A. D.

2013-12-01

Vegetation phenology monitoring has yielded a decades-long archive documenting the impacts of global change on the biosphere. However, the coarse spatial resolution of remote sensing obscures the organismic level processes driving phenology, while point measurements on the ground limit the extent of observation. Unmanned aerial vehicles (UAVs) enable low altitude remote sensing at higher spatial and temporal resolution than available from space borne platforms, and have the potential to elucidate the links between organism scale processes and landscape scale analyses of terrestrial phenology. This project demonstrates the use of a low cost multirotor UAV, equipped with a consumer grade digital camera, for observation of deciduous forest phenology and comparison to ground- and tower-based data as well as remote sensing. The UAV was flown approximately every five days during the spring green-up period in 2013, to obtain aerial photography over an area encompassing a 250m resolution MODIS (Moderate Resolution Imaging Spectroradiometer) pixel at Harvard Forest in central Massachusetts, USA. The imagery was georeferenced and tree crowns were identified using a detailed species map of the study area. Image processing routines were used to extract canopy 'greenness' time series, which were used to calculate phenology transition dates corresponding to early, middle, and late stages of spring green-up for the dominant canopy trees. Aggregated species level phenology estimates from the UAV data, including the mean and variance of phenology transition dates within species in the study area, were compared to model predictions based on visual assessment of a smaller sample size of individual trees, indicating the extent to which limited ground observations represent the larger landscape. At an intermediate scale, the UAV data was compared to data from repeat digital photography, integrating over larger portions of canopy within and near the study area, as a validation step and to see how well tower-based approaches characterize the surrounding landscape. Finally, UAV data was compared to MODIS data to determine how tree crowns within a remote sensing pixel combine to create the aggregate landscape phenology measured by remote sensing, using an area weighted average of the phenology of all dominant crowns.

Data-intensive multispectral remote sensing of the nighttime Earth for environmental monitoring and emergency response

NASA Astrophysics Data System (ADS)

Zhizhin, M.; Poyda, A.; Velikhov, V.; Novikov, A.; Polyakov, A.

2016-02-01

All Most of the remote sensing applications rely on the daytime visible and infrared images of the Earth surface. Increase in the number of satellites, their spatial resolution as well as the number of the simultaneously observed spectral bands ensure a steady growth of the data volumes and computational complexity in the remote sensing sciences. Recent advance in the night time remote sensing is related to the enhanced sensitivity of the on-board instruments and to the unique opportunity to observe “pure” emitters in visible infrared spectra without contamination from solar heat and reflected light. A candidate set of the night-time emitters observable from the low-orbiting and geostationary satellites include steady state and temporal changes in the city and traffic electric lights, fishing boats, high-temperature industrial objects such as steel mills, oil cracking refineries and power plants, forest and agricultural fires, gas flares, volcanic eruptions and similar catastrophic events. Current satellite instruments can detect at night 10 times more of such objects compared to daytime. We will present a new data-intensive workflow of the night time remote sensing algorithms for map-reduce processing of visible and infrared images from the multispectral radiometers flown by the modern NOAA/NASA Suomi NPP and the USGS Landsat 8 satellites. Similar radiometers are installed on the new generation of the US geostationary GOES-R satellite to be launched in 2016. The new set of algorithms allows us to detect with confidence and track the abrupt changes and long-term trends in the energy of city lights, number of fishing boats, as well as the size, geometry, temperature of gas flares and to estimate monthly and early flared gas volumes by site or by country. For real-time analysis of the night time multispectral satellite images with global coverage we need gigabit network, petabyte data storage and parallel compute cluster with more than 20 nodes. To meet the processing requirements, we have used the supercomputer at the Kurchatov Institute in Moscow.

Neural Network-Based Retrieval of Surface and Root Zone Soil Moisture using Multi-Frequency Remotely-Sensed Observations

NASA Astrophysics Data System (ADS)

Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre

2017-04-01

Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.

The Chinese FY-1 Meteorological Satellite Application in Observation on Oceanic Environment

NASA Astrophysics Data System (ADS)

Weimin, S.

meteorological satellite is stated in this paper. exploration of the ocean resources has been a very important question of global strategy in the world. The exploration of the ocean resources includes following items: Making full use of oceanic resources and space, protecting oceanic environment. to observe the ocean is by using of satellite. In 1978, US successfully launched the first ocean observation satellite in the world --- Sea Satellite. It develops ancient oceanography in to advanced space-oceanography. FY-1 B and FY- IC respectively. High quality data were acquired at home and abroad. FY-1 is Chinese meteorological satellite, but with 0.43 ~ 0.48 μm ,0.48 ~ 0.53 μm and 0.53 ~ 0.58 μm three ocean color channels, actually it is a multipurpose remote sensing satellite of meteorology and oceanography. FY-1 satellite's capability of observation on ocean partly, thus the application field is expanded and the value is increased. With the addition of oceanic channels on FY-1, the design of the satellite is changed from the original with meteorological observation as its main purpose into remote sensing satellite possessing capability of observing meteorology and ocean as well. Thus, the social and economic benefit of FY-1 is increased. the social and economic benefit of the development of the satellite is the key technique in the system design of the satellite. technically feasible but also save the funds in researching and manufacturing of the satellite, quicken the tempo of researching and manufacturing satellite. the scanning radiometer for FY-1 is conducted an aviation experiment over Chinese ocean. This experiment was of vital importance to the addition of oceanic observation channel on FY-1. FY-1 oceanic channels design to be correct. detecting ocean color. This is the unique character of Chinese FY-1 meteorological satellite. meteorological remote sensing channel on FY-1 to form detecting capability of three visible channels: red, yellow and blue spectrum bands. Thus FY-1 satellite can be used for observation on ocean color experiment. This experiment is successful, a lot of data were acquired. Good application results were obtained in the field of oceanic science research. Therefore, it makes FY-1 a remote sensing satellite used for observation on meteorology and ocean. This is the unique character of Chinese FY-1 meteorological satellite, it is widely noticed all over the world. Chinese meteorological satellite has been realized the aim of using one satellite for multipurpose applications and brought more and more social and economic benefit. oceanic channel in Chinese meteorological satellites is also foreseen to expand the application field in Chinese meteorological satellites. Key Word : Meteorological Satellite Oceanic Remote Sensing

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Jackson, Thomas J.; Manu, Andrew; Tsegaye, Teferi D.; Soman, V.; Arnold, James E. (Technical Monitor)

2001-01-01

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

Evaluation of 3-D Air Quality System Remotely-Sensed Aerosol Optical Depth for the Baltimore/Washington Metropolitan Air Shed

NASA Astrophysics Data System (ADS)

Weber, S. A.; Engel-Cox, J. A.; Hoff, R. M.; Prados, A.; Zhang, H.

2008-12-01

Integrating satellite- and ground-based aerosol optical depth (AOD) observations with surface total fine particulate (PM2.5) and sulfate concentrations allows for a more comprehensive understanding of local- and urban-scale air quality. This study evaluates the utility of integrated databases being developed for NOAA and EPA through the 3D-AQS project by examining the relationship between remotely-sensed AOD and PM2.5 concentrations for each platform for the summer of 2004 and the entire year of 2005. We compare results for the Baltimore, MD/Washington, DC metropolitan air shed, incorporating AOD products from the Terra and GOES-12 satellites, AERONET sunphotometer, and ground-based lidar, and PM2.5 concentrations from five surface monitoring sites. The satellite-derived products include AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR), as well as the GOES Aerosol/Smoke Product (GASP). The vertical profile of lidar backscatter is used to retrieve the planetary boundary layer (PBL) height in an attempt to capture only that fraction of the AOD arising from near surface aerosols. Adjusting the AOD data using platform- and season-specific ratios, calculated using the parameters of the regression equations, for two case studies resulted in a more accurate representation of surface PM2.5 concentrations when compared to a constant ratio that is currently being used in the NOAA IDEA product. This work demonstrates that quantitative relationships between remotely-sensed and in-situ aerosol observations in an integrated database can be computed and applied to improve the use of remotely-sensed observations for estimating surface concentrations.

Simulating Canopy-Level Solar Induced Fluorescence with CLM-SIF 4.5 at a Sub-Alpine Conifer Forest in the Colorado Rockies

NASA Astrophysics Data System (ADS)

Raczka, B. M.; Bowling, D. R.; Lin, J. C.; Lee, J. E.; Yang, X.; Duarte, H.; Zuromski, L.

2017-12-01

Forests of the Western United States are prone to drought, temperature extremes, forest fires and insect infestation. These disturbance render carbon stocks and land-atmosphere carbon exchanges highly variable and vulnerable to change. Regional estimates of carbon exchange from terrestrial ecosystem models are challenged, in part, by a lack of net ecosystem exchange observations (e.g. flux towers) due to the complex mountainous terrain. Alternatively, carbon estimates based on light use efficiency models that depend upon remotely-sensed greenness indices are challenged due to a weak relationship with GPP during the winter season. Recent advances in the retrieval of remotely sensed solar induced fluorescence (SIF) have demonstrated a strong seasonal relationship between GPP and SIF for deciduous, grass and, to a lesser extent, conifer species. This provides an important opportunity to use remotely-sensed SIF to calibrate terrestrial ecosystem models providing a more accurate regional representation of biomass and carbon exchange across mountainous terrain. Here we incorporate both leaf-level fluorescence and leaf-to-canopy radiative transfer represented by the SCOPE model into CLM 4.5 (CLM-SIF). We simulate canopy level fluorescence at a sub-alpine forest site (Niwot Ridge, Colorado) and test whether these simulations reproduce remotely-sensed SIF from a satellite (GOME2). We found that the average peak SIF during the growing season (yrs 2007-2013) was similar between the model and satellite observations (within 15%); however, simulated SIF during the winter season was significantly greater than the satellite observations (5x higher). This implies that the fluorescence yield is overestimated by the model during the winter season. It is important that the modeled representation of seasonal fluorescence yield is improved to provide an accurate seasonal representation of SIF across the Western United States.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1987-01-01

The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.

Forest mensuration with remote sensing: A retrospective and a vision for the future

Treesearch

Randolph H. Wynne

2004-01-01

Remote sensing, while occasionally oversold, has clear potential to reduce the overall cost of traditional forest inventories. Perhaps most important, some of the information needed for more intensive, rather than extensive, forest management is available from remote sensing. These new information needs may justify increased use and the increased cost of remote sensing...

15 CFR 960.12 - Data policy for remote sensing space systems.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...

Remote Sensing: Analyzing Satellite Images to Create Higher Order Thinking Skills.

ERIC Educational Resources Information Center

Marks, Steven K.; And Others

1996-01-01

Presents a unit that uses remote-sensing images from satellites and other spacecraft to provide new perspectives of the earth and generate greater global awareness. Relates the levels of Bloom's hierarchy to different aspects of the remote sensing unit to confirm that the concepts and principles of remote sensing and related images belong in…

15 CFR 960.12 - Data policy for remote sensing space systems.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 15 Commerce and Foreign Trade 3 2011-01-01 2011-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...

15 CFR 960.12 - Data policy for remote sensing space systems.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 15 Commerce and Foreign Trade 3 2012-01-01 2012-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...

15 CFR 960.12 - Data policy for remote sensing space systems.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 15 Commerce and Foreign Trade 3 2014-01-01 2014-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...

15 CFR 960.12 - Data policy for remote sensing space systems.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 15 Commerce and Foreign Trade 3 2013-01-01 2013-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...

Annotated bibliography of remote sensing methods for monitoring desertification

USGS Publications Warehouse

Walker, A.S.; Robinove, Charles J.

1981-01-01

Remote sensing techniques are valuable for locating, assessing, and monitoring desertification. Remotely sensed data provide a permanent record of the condition of the land in a format that allows changes in land features and condition to be measured. The annotated bibliography of 118 items discusses remote sensing methods that may be applied to desertification studies.

Applied Remote Sensing Program (ARSP)

NASA Technical Reports Server (NTRS)

Johnson, J. D.; Foster, K. E.; Mouat, D. A.; Miller, D. A.; Conn, J. S.

1976-01-01

The activities and accomplishments of the Applied Remote Sensing Program during FY 1975-1976 are reported. The principal objective of the Applied Remote Sensing Program continues to be designed projects having specific decision-making impacts as a principal goal. These projects are carried out in cooperation and collaboration with local, state and federal agencies whose responsibilities lie with planning, zoning and environmental monitoring and/or assessment in the application of remote sensing techniques. The end result of the projects is the use by the involved agencies of remote sensing techniques in problem solving.

Communicating remote sensing concepts in an interdisciplinary environment

NASA Technical Reports Server (NTRS)

Chung, R.

1981-01-01

Although remote sensing is currently multidisciplinary in its applications, many of its terms come from the engineering sciences, particularly from the field of pattern recognition. Scholars from fields such as the social sciences, botany, and biology, may experience initial difficulty with remote sensing terminology, even though parallel concepts exist in their own fields. Some parallel concepts and terminologies from nonengineering fields, which might enhance the understanding of remote sensing concepts in an interdisciplinary situation are identified. Feedbacks which this analogue strategy might have on remote sensing itself are explored.

Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, northwest China

NASA Astrophysics Data System (ADS)

Wu, X.; Shen, Y.; Wang, N.; Pan, X.; Zhang, W.; He, J.; Wang, G.

2017-12-01

Snowmelt water is an important freshwater resource in the Altay Mountains in northwest China, and it is also crucial for local ecological system, economic and social sustainable development; however, warming climate and rapid spring snowmelt can cause floods that endanger both eco-environment and public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature-index model based on remote sensing coupled with high-resolution meteorological data obtained from NCEP reanalysis fields that were downscaled using Weather Research Forecasting model, then bias-corrected using a statistical downscaled model. Validation of the forcing data revealed that the high-resolution meteorological fields derived from downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of temperature-index model based on remote sensing were calibrated for spring 2014, and model performance was validated using MODIS snow cover and snow observations from spring 2012. The results show that the temperature-index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash-Sutchliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt runoff was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt runoff accounts for 72% of spring runoff and 21% of annual runoff. Snowmelt is the main source of runoff for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt runoff predictions, so as to prevent snowmelt-induced floods, and also provide a generalizable approach that can be applied to other remote locations where high-density, long-term observational data is lacking.

People, Places and Pixels: Remote Sensing in the Service of Society

NASA Technical Reports Server (NTRS)

Lulla, Kamlesh

2003-01-01

What is the role of Earth remote sensing and other geospatial technologies in our society? Recent global events have brought into focus the role of geospatial science and technology such as remote sensing, GIS, GPS in assisting the professionals who are responsible for operations such as rescue and recovery of sites after a disaster or a terrorist act. This paper reviews the use of recent remote sensing products from satellites such as IKONOS in these efforts. Aerial and satellite imagery used in land mine detection has been evaluated and the results of this evaluation will be discussed. Synopsis of current and future ISS Earth Remote Sensing capabilities will be provided. The role of future missions in humanitarian use of remote sensing will be explored.

Inland and coastal waters

NASA Astrophysics Data System (ADS)

Mouw, Colleen; Greb, Steven

2012-09-01

Workshop for Remote Sensing of Coastal and Inland Waters;Madison, Wisconsin, 20-22 June 2012 Coastal and inland water bodies, which have great value for recreation, food supply, commerce, transportation, and human health, have been experiencing external pressure from direct human activities and climate change. Given their societal and economic value, understanding issues of water quality, water quantity, and the impact of environmental change on the ecological and biogeochemical functioning of these water bodies is of interest to a broad range of communities. Remote sensing offers one of the most spatially and temporally comprehensive tools for observing these waters. While there has been some success with remotely observing these water bodies, many challenges still remain, including algorithm performance, atmospheric correction, the relationships between optical properties and biogeochemical parameters, sufficient spatial and spectral resolution, and a lack of uncertainty estimates over the wide range of environmental conditions encountered across these coastal and inland water bodies.

Remote sensing monitoring and driving force analysis to forest and greenbelt in Zhuhai

NASA Astrophysics Data System (ADS)

Yuliang Qiao, Pro.

As an important city in the southern part of Chu Chiang Delta, Zhuhai is one of the four special economic zones which are opening up to the outside at the earliest in China. With pure and fresh air and trees shading the street, Zhuhai is a famous beach port city which is near the mountain and by the sea. On the basis of Garden City, the government of Zhuhai decides to build National Forest City in 2011, which firstly should understand the situation of greenbelt in Zhuhai in short term. Traditional methods of greenbelt investigation adopt the combination of field surveying and statistics, whose efficiency is low and results are not much objective because of artificial influence. With the adventure of the information technology such as remote sensing to earth observation, especially the launch of many remote sensing satellites with high resolution for the past few years, kinds of urban greenbelt information extraction can be carried out by using remote sensing technology; and dynamic monitoring to spatial pattern evolvement of forest and greenbelt in Zhuhai can be achieved by the combination of remote sensing and GIS technology. Taking Landsat5 TM data in 1995, Landsat7 ETM+ data in 2002, CCD and HR data of CBERS-02B in 2009 as main information source, this research firstly makes remote sensing monitoring to dynamic change of forest and greenbelt in Zhuhai by using the combination of vegetation coverage index and three different information extraction methods, then does a driving force analysis to the dynamic change results in 3 months. The results show: the forest area in Zhuhai shows decreasing tendency from 1995 to 2002, increasing tendency from 2002 to 2009; overall, the forest area show a small diminution tendency from 1995 to 2009. Through the comparison to natural and artificial driving force, the artificial driving force is the leading factor to the change of forest and greenbelt in Zhuhai. The research results provide a timely and reliable scientific basis for the Zhuhai Government in building National Forest City. Keywords: forest and greenbelt; remote sensing; dynamic monitoring; driving force; vegetation coverage

NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

NASA Technical Reports Server (NTRS)

Giardino, Marco J.

2008-01-01

NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through the use of remote sensing. In 2007, NASA awarded six competitively chosen projects in Space Archaeology through an open solicitation whose purpose, among several, was to addresses the potential benefits to modern society that can be derived through a better understanding of how past cultures succeeded or failed to adapt to local, regional, and global change. A further objective of NASA's space archaeology is the protection and preservation of cultural heritage sites while planning for the sustainable development of cultural resources. NASA s archaeological approach through remote sensing builds on traditional methods of aerial archaeology (i.e. crop marks) and utilizes advanced technologies for collecting and analyzing archaeological data from digital imagery. NASA s archaeological research and application projects using remote sensing have been conducted throughout the world. In North America, NASA has imaged prehistoric mound sites in Mississippi; prehistoric shell middens in Louisiana, Puebloan sites in New Mexico and more recently the sites associated with the Lewis and Clark Corps of Discovery Expedition (1804-1806). In Central America, NASA archaeologists have researched Mayan sites throughout the region, including the Yucatan and Costa Rica, as well as Olmec localities in Veracruz. Other data has been collected over Angkor, Cambodia, Giza in Egypt, the lost city of Ubar on the Arabian Peninsula.

Integration of Remotely Sensed Data Into Geospatial Reference Information Databases. Un-Ggim National Approach

NASA Astrophysics Data System (ADS)

Arozarena, A.; Villa, G.; Valcárcel, N.; Pérez, B.

2016-06-01

Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the "skeleton" of any Spatial Data Infrastructure (SDI). Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.

International Space Station Data Collection for Disaster Response

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Evans, Cynthia A.

2015-01-01

Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous sensor systems in higher altitude polar orbits. NASA remote sensing assets on the station began collecting International Disaster Charter (IDC) response data in May 2012. The initial NASA ISS sensor systems responding to IDC activations included the ISS Agricultural Camera (ISSAC), mounted in the Window Observational Research Facility (WORF); the Crew Earth Observations (CEO) Facility, where the crew collects imagery using off-the-shelf handheld digital cameras; and the Hyperspectral Imager for the Coastal Ocean (HICO), a visible to near-infrared system mounted externally on the Japan Experiment Module Exposed Facility. The ISSAC completed its primary mission in January 2013. It was replaced by the very high resolution ISS SERVIR Environmental Research and Visualization System (ISERV) Pathfinder, a visible-wavelength digital camera, telescope, and pointing system. Since the start of IDC response in 2012 there have been 108 IDC activations; NASA sensor systems have collected data for thirty-two of these events. Of the successful data collections, eight involved two or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program.

Comprehensive studies of the dynamics of geosystems with the use of remote sensing techniques

NASA Astrophysics Data System (ADS)

Vasilev, L. N.; Kaczyński, R.; Ney, B. I.

The described research programme for comprehensive studies of changes occuring within geosystems is a part of scientific activity of INTERKOSMOS, which will be executed mainly with the use of remote sensing methods and techniques. The main aim of the programme is to get an insight into the seasonal rithm of environmental changes on both regional and global level. The work will consist of gathering systematized information concerning quantitative and qualitative relations between various components of the environment. The application of remote sensing methods enables the acquisition of such environmental data in dynamic setting. Research will be conducted for areas comprising distinct geosystems and will lead to the detection of diurnal, seasonal and yearly dynamics of geosystems as well as long-term trends. Except cognitive, the programme will also serve the methodological purpose. The first aim will be realized with respect to individual geosystems; the resulting sets of data will consist of matrixes of statistical data characterizing relations between various components of geosystems. The methodological aim will be achieved through the process of practical verification of the preliminary assumptions. Information will be collected from different data acquisition levels namely from satellite and aerial platforms and through ground measurements. Different types of data, such as multispectral photography (SALYUT, KOSMOS), multispectral scanner images (LANDSAT THEMATIC MAPPER, SPOT), infrared photography, radar imagery and spectrometric measurements will be gathered during simultaneous data acquisition projects. All types of observations will be timed in accordance with the natural rithm of the observed phenomena. The paper contains the description of geosystems under anthropogenic stress based on the previous research of the authors. The presented multifactor characteristics of soil and crops is a part of completed studies on agricultural geosystems. The results of comprehensive remote sensing experiments already completed within the framework of INTERKOSMOS programme on test sites in member countries fully support the approved programme for studying the dynamics of geosystems with the use of remote sensing.

Initial Scientific Assessment of the EOS Data and Information System (EOSDIS)

NASA Technical Reports Server (NTRS)

1989-01-01

Crucial to the success of the Earth Observing System (Eos) is the Eos Data and Information System (EosDIS). The goals of Eos depend not only on its instruments and science investigations, but also on how well EosDlS helps scientists integrate reliable, large-scale data sets of geophysical and biological measurements made from Eos data, and on how successfully Eos scientists interact with other investigations in Earth System Science. Current progress in the use of remote sensing for science is hampered by requirements that the scientist understand in detail the instrument, the electromagnetic properties of the surface, and a suite of arcane tape formats, and by the immaturity of some of the techniques for estimating geophysical and biological variables from remote sensing data. These shortcomings must be transcended if remote sensing data are to be used by a much wider population of scientists who study environmental change at regional and global scales.

Seasonality of a boreal forest: a remote sensing perspective

NASA Astrophysics Data System (ADS)

Rautiainen, Miina; Heiskanen, Janne; Lukes, Petr; Majasalmi, Titta; Mottus, Matti; Pisek, Jan

2016-04-01

Understanding the seasonal dynamics of boreal ecosystems through interpretation of satellite reflectance data is needed for efficient large-scale monitoring of northern vegetation dynamics and productivity trends. Satellite remote sensing enables continuous global monitoring of vegetation status and is not limited to single-date phenological metrics. Using remote sensing also enables gaining a wider perspective to the seasonality of vegetation dynamics. The seasonal reflectance cycles of boreal forests observed in optical satellite images are explained by changes in biochemical properties and geometrical structure of vegetation as well as seasonal variation in solar illumination. This poster provides a synthesis of a research project (2010-2015) dedicated to monitoring the seasonal cycle of boreal forests. It is based on satellite and field data collected from the Hyytiälä Forestry Field Station in Finland. The results highlight the role understory vegetation has in forming the forest reflectance measured by satellite instruments.

Japan's efforts to promote global health using satellite remote sensing data from the Japan Aerospace Exploration Agency for prediction of infectious diseases and air quality.

PubMed

Igarashi, Tamotsu; Kuze, Akihiko; Sobue, Shinichi; Yamamoto, Aya; Yamamoto, Kazuhide; Oyoshi, Kei; Imaoka, Keiji; Fukuda, Toru

2014-12-01

In this paper we review the status of new applications research of the Japanese Aerospace Exploration Agency (JAXA) for global health promotion using information derived from Earth observation data by satellites in cooperation with inter-disciplinary collaborators. Current research effort at JAXA to promote global public health is focused primarily on the use of remote sensing to address two themes: (i) prediction models for malaria and cholera in Kenya, Africa; and (ii) air quality assessment of small, particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Respiratory and cardivascular diseases constitute cross-boundary public health risk issues on a global scale. The authors report here on results of current of a collaborative research to call attention to the need to take preventive measures against threats to public health using newly arising remote sensing information from space.

An Uncertainty Quantification Framework for Remote Sensing Retrievals

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Hobbs, J.

2017-12-01

Remote sensing data sets produced by NASA and other space agencies are the result of complex algorithms that infer geophysical state from observed radiances using retrieval algorithms. The processing must keep up with the downlinked data flow, and this necessitates computational compromises that affect the accuracies of retrieved estimates. The algorithms are also limited by imperfect knowledge of physics and of ancillary inputs that are required. All of this contributes to uncertainties that are generally not rigorously quantified by stepping outside the assumptions that underlie the retrieval methodology. In this talk we discuss a practical framework for uncertainty quantification that can be applied to a variety of remote sensing retrieval algorithms. Ours is a statistical approach that uses Monte Carlo simulation to approximate the sampling distribution of the retrieved estimates. We will discuss the strengths and weaknesses of this approach, and provide a case-study example from the Orbiting Carbon Observatory 2 mission.

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

USGS Publications Warehouse

Vierling, L.A.; Fersdahl, M.; Chen, X.; Li, Z.; Zimmerman, P.

2006-01-01

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Estimating population size of Pygoscelid Penguins from TM data

NASA Technical Reports Server (NTRS)

Olson, Charles E., Jr.; Schwaller, Mathew R.; Dahmer, Paul A.

1987-01-01

An estimate was made toward a continent wide population of penguins. The results indicate that Thematic Mapper data can be used to identify penguin rookeries due to the unique reflectance properties of guano. Strong correlations exist between nesting populations and rookery area occupied by the birds. These correlations allow estimation of the number of nesting pairs in colonies. The success of remote sensing and biometric analyses leads one to believe that a continent wide estimate of penguin populations is possible based on a timely sample employing ground based and remote sensing techniques. Satellite remote sensing along the coastline may well locate previously undiscovered penguin nesting sites, or locate rookeries which have been assumed to exist for over a half century, but never located. Observations which found that penguins are one of the most sensitive elements in the complex of Southern Ocean ecosystems motivated this study.

The Scientific and Societal Need for Accurate Global Remote Sensing of Marine Suspended Sediments

NASA Technical Reports Server (NTRS)

Acker, James G.

2006-01-01

Population pressure, commercial development, and climate change are expected to cause continuing alteration of the vital oceanic coastal zone environment. These pressures will influence both the geology and biology of the littoral, nearshore, and continental shelf regions. A pressing need for global observation of coastal change processes is an accurate remotely-sensed data product for marine suspended sediments. The concentration, delivery, transport, and deposition of sediments is strongly relevant to coastal primary production, inland and coastal hydrology, coastal erosion, and loss of fragile wetland and island habitats. Sediment transport and deposition is also related to anthropogenic activities including agriculture, fisheries, aquaculture, harbor and port commerce, and military operations. Because accurate estimation of marine suspended sediment concentrations requires advanced ocean optical analysis, a focused collaborative program of algorithm development and assessment is recommended, following the successful experience of data refinement for remotely-sensed global ocean chlorophyll concentrations.

Survey of in-situ and remote sensing methods for soil moisture determination

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

1981-01-01

General methods for determining the moisture content in the surface layers of the soil based on in situ or point measurements, soil water models and remote sensing observations are surveyed. In situ methods described include gravimetric techniques, nuclear techniques based on neutron scattering or gamma-ray attenuation, electromagnetic techniques, tensiometric techniques and hygrometric techniques. Soil water models based on column mass balance treat soil moisture contents as a result of meteorological inputs (precipitation, runoff, subsurface flow) and demands (evaporation, transpiration, percolation). The remote sensing approaches are based on measurements of the diurnal range of surface temperature and the crop canopy temperature in the thermal infrared, measurements of the radar backscattering coefficient in the microwave region, and measurements of microwave emission or brightness temperature. Advantages and disadvantages of the various methods are pointed out, and it is concluded that a successful monitoring system must incorporate all of the approaches considered.

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

USGS Publications Warehouse

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.

Clear-sky remote sensing in the vicinity of clouds: what can be learned about aerosol changes?

NASA Astrophysics Data System (ADS)

Marshak, Alexander; Varnai, Tamas; Wen, Guoyong

2010-05-01

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. The width and ubiquity of the transition zone near clouds imply that studies of aerosol-cloud interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for remote sensing challenges and thus allow for including the transition zone into the study. We describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent "bluing" of aerosols in remote sensing retrievals.

Clear-sky remote sensing in the vicinity of clouds: what we learned from MODIS and CALIPSO

NASA Astrophysics Data System (ADS)

Marshak, Alexander; Varnai, Tamas; Wen, Guoyong; Cahalan, Robert

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. The width and ubiquity of the transition zone near clouds imply that studies of aerosol-cloud interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for remote sensing challenges and thus allow for including the transition zone into the study. We describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent "bluing" of aerosols in remote sensing retrievals.

Ground observations and remote sensing data for integrated modelisation of water budget in the Merguellil catchment, Tunisia

NASA Astrophysics Data System (ADS)

Mougenot, Bernard

2016-04-01

The Mediterranean region is affected by water scarcity. Some countries as Tunisia reached the limit of 550 m3/year/capita due overexploitation of low water resources for irrigation, domestic uses and industry. A lot of programs aim to evaluate strategies to improve water consumption at regional level. In central Tunisia, on the Merguellil catchment, we develop integrated water resources modelisations based on social investigations, ground observations and remote sensing data. The main objective is to close the water budget at regional level and to estimate irrigation and water pumping to test scenarios with endusers. Our works benefit from French, bilateral and European projects (ANR, MISTRALS/SICMed, FP6, FP7…), GMES/GEOLAND-ESA) and also network projects as JECAM and AERONET, where the Merguellil site is a reference. This site has specific characteristics associating irrigated and rainfed crops mixing cereals, market gardening and orchards and will be proposed as a new environmental observing system connected to the OMERE, TENSIFT and OSR systems respectively in Tunisia, Morocco and France. We show here an original and large set of ground and remote sensing data mainly acquired from 2008 to present to be used for calibration/validation of water budget processes and integrated models for present and scenarios: - Ground data: meteorological stations, water budget at local scale: fluxes tower, soil fluxes, soil and surface temperature, soil moisture, drainage, flow, water level in lakes, aquifer, vegetation parameters on selected fieds/month (LAI, height, biomass, yield), land cover: 3 times/year, bare soil roughness, irrigation and pumping estimations, soil texture. - Remote sensing data: remote sensing products from multi-platform (MODIS, SPOT, LANDSAT, ASTER, PLEIADES, ASAR, COSMO-SkyMed, TerraSAR X…), multi-wavelength (solar, micro-wave and thermal) and multi-resolution (0.5 meters to 1 km). Ground observations are used (1) to calibrate soil-vegetation-atmosphere models at field scale on different compartment and irrigated and rainfed land during a limited time (seasons or set of dry and wet years), (2) to calibrate and validate particularly evapotranspiration derived from multi-wavelength satellite data at watershed level in relationships with the aquifer conditions: pumping and recharge rate. We will point out some examples.

Tracking greenhouse gas emissions from a U.S. megacity by remote sensing from a mountaintop site

NASA Astrophysics Data System (ADS)

Wong, Clare; Fu, Dejian; Pongetti, Thomas; Newman, Sally; Kort, Eric; Duren, Riley; Hsu, Ying-Kuang; Miller, Charles; Yung, Yuk; Sander, Stanley

2014-05-01

Cities, such as Los Angeles, are significant sources of anthropogenic greenhouse gases (GHGs). With the growth of populations in cities worldwide, GHG emissions will increase, and monitoring the temporal trends will provide crucial data for global climate models as well as assessments of the effectiveness of control policies. Currently, continuous GHG observations in the Los Angeles basin are limited to a few in situ measurements, which are shown to be sensitive to local emissions and do not represent the Los Angeles basin well. To quantify GHG emissions from the metropolitan area, which tend to have heterogeneous characteristics, it is important to perform measurements which provide both continuous temporal and spatial coverage of the domain. Here we present observations of the major greenhouse gases, CO2 and CH4, using a spectroscopic remote sensing technique from the California Laboratory for Atmospheric Remote Sensing (CLARS) at Mount Wilson, California (1.7 km elevation). A Fourier Transform Spectrometer (FTS) deployed at the CLARS site points downward at 28 selected land surfaces in the LA basin to measure the slant column abundances of CO2, CH4, N2¬O, CO and O2 using reflected sunlight in the near-infrared and short-wave infrared regions. This remote sensing technique provides continuous temporal and spatial measurements in the Los Angeles basin to achieve the goal of quantifying emissions of GHGs and CO. It also serves as a test-bed for future geostationary satellite missions to measure GHGs from space such as NASA JPL's Geostationary Carbon Process Investigation (GCPI). The path-averaged dry-air mixing ratio, XCO2 and XCH4, observed by the CLARS FTS, showed significant diurnal variability that arises from emissions in the Los Angeles basin and atmospheric transport processes. High-precision data have been collected since August 2011. We analyze the seasonal trends of the ratio XCH4:XCO2 and estimate the seasonal and annual CH4 emission in the Los Angeles basin observed by the CLARS FTS from August 2011 to present. This work demonstrates the ability to quantify and track GHG emissions in a megacity using ground-based remote sensing from an elevated platform and the potential for future geostationary satellite missions, such as GCPI, to monitor carbon fluxes in cities. Copyright 2014. California Institute of Technology. Government sponsorship acknowledged.

Remote sensing of trend and seasonal variability of greenhouse gas emissions from the Los Angeles basin using an FTS on Mount Wilson

NASA Astrophysics Data System (ADS)

Wong, C.; Fu, D.; Pongetti, T. J.; Newman, S.; Yung, Y. L.; Sander, S. P.

2013-12-01

Cities, such as Los Angeles, are significant sources of anthropogenic greenhouse gases (GHGs). With the growth of populations in cities worldwide, GHG emissions will increase, and monitoring the temporal trends will provide crucial data for global climate models as well as assessments of the effectiveness of control policies. Currently, continuous GHG observations in the Los Angeles basin are limited to a few in situ measurements, which are shown to be sensitive to local emissions and do not represent the Los Angeles basin well. To quantify GHG emissions from the metropolitan area, which tend to have heterogeneous characteristics, it is important to perform measurements which provide both continuous temporal and spatial coverage of the domain. Here we present observations of the major greenhouse gases, CO2 and CH4, using a spectroscopic remote sensing technique from the California Laboratory for Atmospheric Remote Sensing (CLARS) at Mount Wilson, California (1.7 km elevation). A Fourier Transform Spectrometer (FTS) deployed at the CLARS site points downward at 28 selected land surfaces in the Los Angeles basin to measure the slant column abundances of CO2, CH4, N2O, CO and O2 using reflected sunlight in the near-infrared and shortwave infrared regions. This remote sensing technique provides continuous temporal and spatial measurements in the Los Angeles basin to achieve the goal of quantifying emissions of GHGs and CO. It also serves as a test-bed for future geostationary satellite missions to measure GHGs from space such as JPL's Geostationary Carbon Process Investigation (GCPI). The path-averaged dry-air mixing ratio, XCO2 and XCH4, observed by the CLARS FTS, show significant diurnal variability that arises from emissions in the Los Angeles basin and atmospheric transport processes. High-precision data have been collected since August 2011. Here we analyze the annual and seasonal trend of the ratio XCH4:XCO2 in the Los Angeles basin observed by the CLARS FTS from August 2011 to present. This work demonstrates the ability to quantify and track GHG emissions in a megacity using ground-based remote sensing from an elevated platform and the potential for future geostationary satellite missions, such as GCPI, to monitor carbon fluxes in cities.

Remote Sensing of Crystal Shapes in Ice Clouds

NASA Technical Reports Server (NTRS)

van Diedenhoven, Bastiaan

2017-01-01

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.

DISCOVER-AQ: An Overview and Initial Comparisons of NO2 with OMI Observations

NASA Technical Reports Server (NTRS)

Pickering, Kenneth; Crawford, James; Krotkov, Nickolay; Bucsela, Eric; Lamsal, Lok; Celarier, Edward; Herman, Jay; Janz, Scott; Cohen, Ron; Weinheimer, Andrew

2011-01-01

The first deployment of the Earth Venture -1 DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) project was conducted during July 2011 in the Baltimore-Washington region. Two aircraft (a P-3B for in-situ sampling and a King Air for remote sensing) were used along with an extensive array of surface-based in-situ and remote sensing instrumentation. Fourteen flight days were accomplished by both aircraft and over 250 profiles of trace gases and aerosols were performed by the P-3B over surface air quality monitoring stations, which were specially outfitted with sunphotometers and Pandora UV/Vis spectrometers. The King Air flew with the High Spectral Resolution Lidar for aerosols and the ACAM UV/Vis spectrometer for trace gases. This suite of observations allows linkage of surface air quality with the vertical distributions of gases and aerosols, with remotely-sensed column amounts observed from the surface and from the King Air, and with satellite observations from Aura (OMI and TES), GOME-2, MODIS and GOES. The DISCOVER-AQ data will allow determination of under what conditions satellite retrievals are indicative of surface air quality, and they will be useful in planning new satellites. In addition to an overview of the project, a preliminary comparison of tropospheric column NO2 densities from the integration of in-situ P-3B observations, from the Pandoras and ACAM, and from the new Goddard OMI NO2 algorithm will be presented.

The application of remote sensing techniques to the study of ophiolites

NASA Astrophysics Data System (ADS)

Khan, Shuhab D.; Mahmood, Khalid

2008-08-01

Satellite remote sensing methods are a powerful tool for detailed geologic analysis, especially in inaccessible regions of the earth's surface. Short-wave infrared (SWIR) bands are shown to provide spectral information bearing on the lithologic, structural, and geochemical character of rock bodies such as ophiolites, allowing for a more comprehensive assessment of the lithologies present, their stratigraphic relationships, and geochemical character. Most remote sensing data are widely available for little or no cost, along with user-friendly software for non-specialists. In this paper we review common remote sensing systems and methods that allow for the discrimination of solid rock (lithologic) components of ophiolite complexes and their structural relationships. Ophiolites are enigmatic rock bodies which associated with most, if not all, plate collision sutures. Ophiolites are ideal for remote sensing given their widely recognized diversity of lithologic types and structural relationships. Accordingly, as a basis for demonstrating the utility of remote sensing techniques, we briefly review typical ophiolites in the Tethyan tectonic belt. As a case study, we apply integrated remote sensing studies of a well-studied example, the Muslim Bagh ophiolite, located in Balochistan, western Pakistan. On this basis, we attempt to demonstrate how remote sensing data can validate and reconcile existing information obtained from field studies. The lithologic and geochemical diversity of Muslim Bagh are representative of Tethyan ophiolites. Despite it's remote location it has been extensively mapped and characterized by structural and geochemical studies, and is virtually free of vegetative cover. Moreover, integrating the remote sensing data with 'ground truth' information thus offers the potential of an improved template for interpreting remote sensing data sets of other ophiolites for which little or no field information is available.

Developing A Model for Lake Ice Phenology Using Satellite Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Skoglund, S. K.; Weathers, K. C.; Norouzi, H.; Prakash, S.; Ewing, H. A.

2017-12-01

Many northern temperate freshwater lakes are freezing over later and thawing earlier. This shift in timing, and the resulting shorter duration of seasonal ice cover, is expected to impact ecological processes, negatively affecting aquatic species and the quality of water we drink. Long-term, direct observations have been used to analyze changes in ice phenology, but those data are sparse relative to the number of lakes affected. Here we develop a model to utilize remote sensing data in approximating the dates of ice-on and ice-off for many years over a variety of lakes. Day and night surface temperatures from MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra (MYD11A1 and MOD11A1 data products) for 2002-2017 were utilized in combination with observed ice-on and ice-off dates of Lake Auburn, Maine, to determine the ability of MODIS data to match ground-based observations. A moving average served to interpolate MODIS temperature data to fill data gaps from cloudy days. The nighttime data were used for ice-off, and the daytime measurements were used for ice-on predictions to avoid fluctuations between day and night ice/water status. The 0˚C intercepts of those data were used to mark approximate days of ice-on or ice-off. This revealed that approximations for ice-off dates were satisfactory (average ±8.2 days) for Lake Auburn as well as for Lake Sunapee, New Hampshire (average ±8.1 days), while approximations for Lake Auburn ice-on were less accurate and showed consistently earlier-than-observed ice-on dates (average -33.8 days). The comparison of observed and remotely sensed Lake Auburn ice cover duration showed relative agreement with a correlation coefficient of 0.46. Other remote sensing observations, such as the new GOES-R satellite, and further exploration of the ice formation process can improve ice-on approximation methods. The model shows promise for estimating ice-on, ice-off, and ice cover duration for northern temperate lakes.

Informing a hydrological model of the Ogooué with multi-mission remote sensing data

NASA Astrophysics Data System (ADS)

Kittel, Cecile M. M.; Nielsen, Karina; Tøttrup, Christian; Bauer-Gottwein, Peter

2018-02-01

Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall-runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine Early Warning System rainfall estimate) and the Tropical Rainfall Measuring Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from (1) historical in situ discharge observations from the period 1953-1984 at six locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE (Gravity Recovery and Climate Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR (synthetic aperture radar) imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and the river stage, with an RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the FEWS-RFE-forced model. The hydrological model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling with multi-mission remote sensing from 10 different satellite missions, we obtain new information on an otherwise unstudied basin. The proposed model is the best current baseline characterization of hydrological conditions in the Ogooué in light of the available observations.

Remote Sensing and Remote Control Activities in Europe and America: Part 2--Remote Sensing Ground Stations in Europe,

DTIC Science & Technology

1996-04-08

Development tasks and products of remote sensing ground stations in Europe are represented by the In-Sec Corporation and the Schlumberger Industries Corporation. The article presents the main products of these two corporations.

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

2017-01-01

Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

Representation of activity in images using geospatial temporal graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brost, Randolph; McLendon, III, William C.; Parekh, Ojas D.

Various technologies pertaining to modeling patterns of activity observed in remote sensing images using geospatial-temporal graphs are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Activity patterns may be discerned from the graphs by coding nodes representing persistent objects like buildings differently from nodes representing ephemeral objects like vehicles, and examining the geospatial-temporal relationships of ephemeral nodes within the graph.

Methods of satellite oceanography

NASA Technical Reports Server (NTRS)

Stewart, R. H.

1985-01-01

The theoretical basis for remote sensing measurements of climate and ocean dynamics is examined. Consideration is given to: the absorption of electromagnetic radiation in the atmosphere; scattering in the atmosphere; and satellite observations using visible light. Consideration is also given to: the theory of radio scatter from the sea; scatter of centimeter waves from the sea; and the theory of operation of synthetic aperture radars. Additional topics include: the coordinate systems of satellite orbits for oceanographic remote sensing applications; the operating features of the major U.S. satellite systems for viewing the ocean; and satellite altimetry.

Advancing Technologies for Climate Observation

NASA Technical Reports Server (NTRS)

Wu, D.; Esper, J.; Ehsan, N.; Johnson, T.; Mast, W.; Piepmeier, J.; Racette, P.

2014-01-01

Climate research needs Accurate global cloud ice measurements Cloud ice properties are fundamental controlling variables of radiative transfer and precipitation Cost-effective, sensitive instruments for diurnal and wide-swath coverage Mature technology for space remote sensing IceCube objectivesDevelop and validate a flight-qualified 883 GHz receiver for future use in ice cloud radiometer missions Raise TRL (57) of 883 GHz receiver technology Reduce instrument cost and risk by developing path to space for COTS sub-mm-wave receiver systems Enable remote sensing of global cloud ice with advanced technologies and techniques

AgRISTARS: Foreign commodity production forecasting. Country summary report, Australia

NASA Technical Reports Server (NTRS)

Henninger, D. L.; Reed, C. R. (Principal Investigator)

1981-01-01

Australia is one of the world's major growers and exporters of wheat and as such is one of the countries of interest in the AgRISTARS program which endeavors to develop technology to estimate crop production using aerospace remote sensing. A compilation of geographic, political, and agricultural information on Australia is presented. Also included is a summary of the aerospace remote sensing, meteorological, and ground-observed data which were collected with respect to Australia, as well as a summary of contacts between AgRISTARS and Australia personnel.

Mapping products of Titan's surface: Chapter 19

USGS Publications Warehouse

Stephan, Katrin; Jaumann, Ralf; Karkoschka, Erich; Kirk, Randolph L.; Barnes, Jason W.; Tomasko, Martin G.; Turtle, Elizabeth P.; Le Corre, Lucille; Langhans, Mirjam; Le Mouélic, Stéphane; Lorenz, Ralph D.; Perry, Jason; Brown, Robert; Lebreton, Jean-Pierre; Waite, J. Hunter

2010-01-01

Remote sensing instruments aboard the Cassini spacecraft have been observed the surface of Titan globally in the infrared and radar wavelength ranges as well as locally by the Huygens instruments revealing a wealth of new morphological features indicating a geologically active surface. We present a summary of mapping products of Titan's surface derived from data of the remote sensing instruments onboard the Cassini spacecraft (ISS, VIMS, RADAR) as well as the Huygens probe (DISR) that were achieved during the nominal Cassini mission including an overview of Titan's recent nomenclature.

AgRISTARS: Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing. Enumerator's manual, 1981 ground data survey

NASA Technical Reports Server (NTRS)

1981-01-01

General information and administrative instructions are provided for individuals gathering ground truth data to support research and development techniques for estimating crop acreage and production by remote sensing by satellite. Procedures are given for personal safety with regards to organophosphorus insecticides, for conducting interviews for periodic observations, for coding the crops identified and their growth stages, and for selecting sites for placing rain gages. Forms are included for those citizens agreeing to monitor the gages and record the rainfall. Segment selection is also considered.

On prediction and discovery of lunar ores

NASA Technical Reports Server (NTRS)

Haskin, Larry A.; Colson, Russell O.; Vaniman, David

1991-01-01

Sampling of lunar material and remote geochemical, mineralogical, and photogeologic sensing of the lunar surface, while meager, provide first-cut information about lunar composition and geochemical separation processes. Knowledge of elemental abundances in known lunar materials indicates which common lunar materials might serve as ores if there is economic demand and if economical extraction processes can be developed, remote sensing can be used to extend the understanding of the Moon's major geochemical separations and to locate potential ore bodies. Observed geochemical processes might lead to ores of less abundant elements under extreme local conditions.

Project Copernicus: An Earth observing system

NASA Technical Reports Server (NTRS)

1991-01-01

Hunsaker Aerospace Corporation is presenting this proposal for Project Copernicus to fulfill the need for space-based remote sensing of Earth. Concentration is on data acquisition. Copernicus is designed to be a flexible system of spacecraft in a low near-polar orbit. The goal is to acquire data so that the scientists may begin to understand many Earth processes and interactions. The mission objective of Copernicus is to provide a space-based, remote-sensing measurement data acquisition and transfer system for 15 years. A description of the design project is presented.

Feasibility of Using Remotely Sensed Data to Aid in Long-Term Monitoring of Biodiversity

NASA Technical Reports Server (NTRS)

Carroll, Mark L.; Brown, Molly E.; Elders, Akiko; Johnson, Kiersten

2014-01-01

Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.

Interfacing remote sensing and geographic information systems for global environmental change research

NASA Technical Reports Server (NTRS)

Lee, Jae K.; Randolph, J. C.; Lulla, Kamlesh P.; Helfert, Michael R.

1993-01-01

Because changes in the Earth's environment have become major global issues, continuous, longterm scientific information is required to assess global problems such as deforestation, desertification, greenhouse effects and climate variations. Global change studies require understanding of interactions of complex processes regulating the Earth system. Space-based Earth observation is an essential element in global change research for documenting changes in Earth environment. It provides synoptic data for conceptual predictive modeling of future environmental change. This paper provides a brief overview of remote sensing technology from the perspective of global change research.

The least-squares mixing models to generate fraction images derived from remote sensing multispectral data

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Smith, James A.

1991-01-01

Constrained-least-squares and weighted-least-squares mixing models for generating fraction images derived from remote sensing multispectral data are presented. An experiment considering three components within the pixels-eucalyptus, soil (understory), and shade-was performed. The generated fraction images for shade (shade image) derived from these two methods were compared by considering the performance and computer time. The derived shade images are related to the observed variation in forest structure, i.e., the fraction of inferred shade in the pixel is related to different eucalyptus ages.

Need for expanded environmental measurement capabilities in geosynchronous Earth orbit

NASA Technical Reports Server (NTRS)

Mercanti, Enrico P.

1991-01-01

The proliferation of environmental satellites in low altitude earth orbit (LEO) has demonstrated the usefulness of earth remote sensing from space. As use of the technology grows, the limitations of LEO missions become more apparent. Many inadequacies can be met by remote sensing from geosynchronous earth orbits (GEO) that can provide high temporal resolution, consistent viewing of specific earth targets, long sensing dwell times with varying sun angles, stereoscopic coverage, and correlative measurements with ground and LEO observations. An environmental platform in GEO is being studied by NASA. Small research satellite missions in GEO were studied (1990) at GSFC. Some recent independent assessments of NASA Earth Science Programs recommend accelerating the earlier deployment of smaller missions.