Remote sensing of wet lands in irrigated areas

NASA Technical Reports Server (NTRS)

Ham, H. H.

1972-01-01

The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

Sensitive Precise p H Measurement with Large-Area Graphene Field-Effect Transistors at the Quantum-Capacitance Limit

NASA Astrophysics Data System (ADS)

Fakih, Ibrahim; Mahvash, Farzaneh; Siaj, Mohamed; Szkopek, Thomas

2017-10-01

A challenge for p H sensing is decreasing the minimum measurable p H per unit bandwidth in an economical fashion. Minimizing noise to reach the inherent limit imposed by charge fluctuation remains an obstacle. We demonstrate here graphene-based ion-sensing field-effect transistors that saturate the physical limit of sensitivity, defined here as the change in electrical response with respect to p H , and achieve a precision limited by charge-fluctuation noise at the sensing layer. We present a model outlining the necessity for maximizing the device carrier mobility, active sensing area, and capacitive coupling in order to minimize noise. We encapsulate large-area graphene with an ultrathin layer of parylene, a hydrophobic polymer, and deposit an ultrathin, stoichiometric p H -sensing layer of either aluminum oxide or tantalum pentoxide. With these structures, we achieve gate capacitances ˜0.6 μ F /cm2 , approaching the quantum-capacitance limit inherent to graphene, along with a near-Nernstian p H response of ˜55 ±2 mV /p H . We observe field-effect mobilities as high as 7000 cm2 V-1 s-1 with minimal hysteresis as a result of the parylene encapsulation. A detection limit of 0.1 m p H in a 60-Hz electrical bandwidth is observed in optimized graphene transistors.

Development of monitoring method of coffee leaf rust fungus (Hemileia vastatrix) infected area using satellite remote sensing

NASA Astrophysics Data System (ADS)

Katsuhama, N.; Ikeda, K.; Imai, M.; Watanabe, K.; Marpaung, F.; Yoshii, T.; Naruse, N.; Takahashi, Y.

2016-12-01

Since 2008, coffee leaf rust fungus (Hemileia vastatrix) has expanded its infection in Latin America, and early trimming and burning infected trees have been only effective countermeasures to prevent spreading infection. Although some researchers reported a case about the monitoring of coffee leaf rust using satellite remote sensing in 1970s, the spatial resolution was unsatisfied, and therefore, further technological development has been required. The purpose of this research is to develop effective method of discovering coffee leaf rust infected areas using satellite remote sensing. Annual changes of vegetation indices, i.e. Normalized Difference Vegetation Index (NDVI) and Modified Structure Insensitive Pigment Index (MSIPI), around Cuchumatanes Mountains, Republic of Guatemala, were analyzed by Landsat 7 images. Study fields in the research were limited by the coffee farm areas based on a previous paper about on site surveys in different damage areas. As the result of the analysis, the annual change of NDVI at the coffee farm areas with damages tended to be lower than those without damages. Moreover, the decline of NDVI appear from 2008 before the damage was reported. On the other hand, the change of MSIPI had no significant difference. NDVI and MSIPI are mainly related to the amount of chlorophyll and carotenoid in the leaves respectively. This means that the infected coffee leaves turned yellow without defoliation. This situation well matches the symptom of coffee leaf rust. The research concluded that the property of infected leaves turning yellow is effective to monitoring of infection areas by satellite remote sensing.

EPA REMOTE SENSING RESEARCH

EPA Science Inventory

The 2006 transgenic corn imaging research campaign has been greatly assisted through a cooperative effort with several Illinois growers who provided planting area and crop composition. This research effort was designed to evaluate the effectiveness of remote sensed imagery of var...

Data and techniques for studying the urban heat island effect in Johannesburg

NASA Astrophysics Data System (ADS)

Hardy, C. H.; Nel, A. L.

2015-04-01

The city of Johannesburg contains over 10 million trees and is often referred to as an urban forest. The intra-urban spatial variability of the levels of vegetation across Johannesburg's residential regions has an influence on the urban heat island effect within the city. Residential areas with high levels of vegetation benefit from cooling due to evapo-transpirative processes and thus exhibit weaker heat island effects; while their impoverished counterparts are not so fortunate. The urban heat island effect describes a phenomenon where some urban areas exhibit temperatures that are warmer than that of surrounding areas. The factors influencing the urban heat island effect include the high density of people and buildings and low levels of vegetative cover within populated urban areas. This paper describes the remote sensing data sets and the processing techniques employed to study the heat island effect within Johannesburg. In particular we consider the use of multi-sensorial multi-temporal remote sensing data towards a predictive model, based on the analysis of influencing factors.

Remote sensing techniques to assess active fire characteristics and post-fire effects

Treesearch

Leigh B. Lentile; Zachary A. Holden; Alistair M. S. Smith; Michael J. Falkowski; Andrew T. Hudak; Penelope Morgan; Sarah A. Lewis; Paul E. Gessler; Nate C. Benson

2006-01-01

Space and airborne sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Confusion about fire intensity, fire severity, burn severity, and related terms can result in the potential misuse of the inferred information by land managers and remote sensing practitioners who require unambiguous...

VLSI Technology for Cognitive Radio

NASA Astrophysics Data System (ADS)

VIJAYALAKSHMI, B.; SIDDAIAH, P.

2017-08-01

One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.

Discrimination of fluoride and phosphate contamination in central Florida for analyses of environmental effects

NASA Technical Reports Server (NTRS)

Coker, A. E.; Marshall, R.; Thomson, F.

1972-01-01

A study was made of the spatial registration of fluoride and phosphate pollution parameters in central Florida by utilizing remote sensing techniques. Multispectral remote sensing data were collected over the area and processed to produce multispectral recognition maps. These processed data were used to map land areas and waters containing concentrations of fluoride and phosphate. Maps showing distribution of affected and unaffected vegetation were produced. In addition, the multispectral data were processed by single band radiometric slicing to produce radiometric maps used to delineate areas of high ultraviolet radiance, which indicates high fluoride concentrations. The multispectral parameter maps and radiometric maps in combination showed distinctive patterns, which are correlated with areas known to be affected by fluoride and phosphate contamination. These remote sensing techniques have the potential for regional use to assess the environmental impact of fluoride and phosphate wastes in central Florida.

Detection of geothermal anomalies in Tengchong, Yunnan Province, China from MODIS multi-temporal night LST imagery

NASA Astrophysics Data System (ADS)

Li, H.; Kusky, T. M.; Peng, S.; Zhu, M.

2012-12-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using multi-temporal MODIS LST (Land Surface Temperature). The monthly night MODIS LST data from Mar. 2000 to Mar. 2011 of the study area were collected and analyzed. The 132 month average LST map was derived and three geothermal anomalies were identified. The findings of this study agree well with the results from relative geothermal gradient measurements. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect geothermal anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Factors related to sense of coherence in adult patients with Type 2 diabetes.

PubMed

Odajima, Yuki; Sumi, Naomi

2018-02-01

The influence of a diabetic person's sense of burden and blood sugar control through sense of coherence (SOC) on self-management has yet to be sufficiently clarified. The purpose of this study was to examine the utility of salutogenesis, which has sense of coherence at its core, for the self-management of patients with type 2 diabetes. A total of 258 questionnaires were distributed to patients who were seen at one of three hospitals in an urban area in Japan, after obtaining consent from the patient. They were between 20 and 75 years old and regularly received care. Of the 185 responses, 177 were valid. The responses were analyzed by referring to the framework of salutogenesis, and the relationship between patient characteristics, SOC, the Problem Areas In Diabetes survey (PAID), and glycosylated hemoglobin (HbA1c) were studied with structural equation modeling (SEM). SOC had a main effect on PAID scores and an indirect effect on HbA1c. Moreover, age influenced SOC positively. The SOC of patients with type 2 diabetes in the present study was comparatively high. These observations suggest a direct effect of SOC on reducing the sense of burden from having diabetes and an indirect effect on decreasing HbA1c. This research suggested the possibility that diabetes can be controlled by improving SOC.

Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis—A case study in Tengchong, China

NASA Astrophysics Data System (ADS)

Qin, Qiming; Zhang, Ning; Nan, Peng; Chai, Leilei

2011-08-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. Based on radiometric calibration, atmospheric correction and emissivity calculation, a simple but efficient single channel algorithm with acceptable precision is applied to retrieve the land surface temperature (LST) of study area. The LST anomalous areas with temperature about 4-10 K higher than background area are discovered. Four geothermal areas are identified with the discussion of geothermal mechanism and the further analysis of regional geologic structure. The research reveals that the distribution of geothermal areas is consistent with the fault development in study area. Magmatism contributes abundant thermal source to study area and the faults provide thermal channels for heat transfer from interior earth to land surface and facilitate the present of geothermal anomalies. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect LST anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia

NASA Astrophysics Data System (ADS)

Tweed, Sarah O.; Leblanc, Marc; Webb, John A.; Lubczynski, Maciek W.

2007-02-01

Identifying groundwater recharge and discharge areas across catchments is critical for implementing effective strategies for salinity mitigation, surface-water and groundwater resource management, and ecosystem protection. In this study, a synergistic approach has been developed, which applies a combination of remote sensing and geographic information system (GIS) techniques to map groundwater recharge and discharge areas. This approach is applied to an unconfined basalt aquifer, in a salinity and drought prone region of southeastern Australia. The basalt aquifer covers ~11,500 km2 in an agriculturally intensive region. A review of local hydrogeological processes allowed a series of surface and subsurface indicators of groundwater recharge and discharge areas to be established. Various remote sensing and GIS techniques were then used to map these surface indicators including: terrain analysis, monitoring of vegetation activity, and mapping of infiltration capacity. All regions where groundwater is not discharging to the surface were considered potential recharge areas. This approach, applied systematically across a catchment, provides a framework for mapping recharge and discharge areas. A key component in assigning surface and subsurface indicators is the relevance to the dominant recharge and discharge processes occurring and the use of appropriate remote sensing and GIS techniques with the capacity to identify these processes.

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Remote sensing study of Maumee River effects of Lake Erie

NASA Technical Reports Server (NTRS)

Svehla, R.; Raquet, C.; Shook, D.; Salzman, J.; Coney, T.; Wachter, D.; Gedney, R.

1975-01-01

The effects of river inputs on boundary waters were studied in partial support of the task to assess the significance of river inputs into receiving waters, dispersion of pollutants, and water quality. The effects of the spring runoff of the Maumee River on Lake Erie were assessed by a combination of ship survey and remote sensing techniques. The imagery obtained from a multispectral scanner of the west basin of Lake Erie is discussed: this clearly showed the distribution of particulates throughout the covered area. This synoptic view, in addition to its qualitative value, is very useful in selecting sampling stations for shipboard in situ measurements, and for extrapolating these quantitative results throughout the area of interest.

Active microwave users working group program planning

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Bare, J.; Brown, W. E., Jr.; Childs, L. F.; Dellwig, L. F.; Heighway, J. E.; Joosten, R.; Lewis, A. J.; Linlor, W.; Lundien, J. R.

1978-01-01

A detailed programmatic and technical development plan for active microwave technology was examined in each of four user activities: (1) vegetation; (2) water resources and geologic applications, and (4) oceanographic applications. Major application areas were identified, and the impact of each application area in terms of social and economic gains were evaluated. The present state of knowledge of the applicability of active microwave remote sensing to each application area was summarized and its role relative to other remote sensing devices was examined. The analysis and data acquisition techniques needed to resolve the effects of interference factors were reviewed to establish an operational capability in each application area. Flow charts of accomplished and required activities in each application area that lead to operational capability were structured.

In and out of control: brain mechanisms linking fluency of action selection to self-agency in patients with schizophrenia.

PubMed

Voss, Martin; Chambon, Valérian; Wenke, Dorit; Kühn, Simone; Haggard, Patrick

2017-08-01

Sense of agency refers to the feeling of control over one's actions, and their consequences. It involves both predictive processes linked to action control, and retrospective 'sense-making' causal inferences. Schizophrenia has been associated with impaired predictive processing, but the underlying mechanisms that impair patients' sense of agency remain unclear. We introduce a new 'prospective' aspect of agency and show that subliminally priming an action not only influences response times, but also influences reported sense of agency over subsequent action outcomes. This effect of priming was associated with altered connectivity between frontal areas and the angular gyrus. The effects on response times and on frontal action selection mechanisms were similar in patients with schizophrenia and in healthy volunteers. However, patients showed no effects of priming on sense of agency, no priming-related activation of angular gyrus, and no priming-related changes in fronto-parietal connectivity. We suggest angular gyrus activation reflects the experiences of agency, or non-agency, in part by processing action selection signals generated in the frontal lobes. The altered action awareness that characterizes schizophrenia may be due to impaired communication between these areas. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Identification of Land Utilization in Coastal Reclamation Areas in Tianjin Using High Resolution Remote Sensing Images

NASA Astrophysics Data System (ADS)

Meng, Y.; Cao, Y.; Tian, H.; Han, Z.

2018-04-01

In recent decades, land reclamation activities have been developed rapidly in Chinese coastal regions, especially in Bohai Bay. The land reclamation areas can effectively alleviate the contradiction between land resources shortage and human needs, but some idle lands that left unused after the government making approval the usage of sea areas are also supposed to pay attention to. Due to the particular features of land coverage identification in large regions, traditional monitoring approaches are unable to perfectly meet the needs of effectively and quickly land use classification. In this paper, Gaofen-1 remotely sensed satellite imagery data together with sea area usage ownership data were used to identify the land use classifications and find out the idle land resources. It can be seen from the result that most of the land use types and idle land resources can be identified precisely.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Large area graphene ion sensitive field effect transistors with tantalum pentoxide sensing layers for pH measurement at the Nernstian limit

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

Fakih, Ibrahim, E-mail: ibrahim.fakih@mail.mcgill.ca; Sabri, Shadi; Szkopek, Thomas, E-mail: thomas.szkopek@mcgill.ca

2014-08-25

We have fabricated and characterized large area graphene ion sensitive field effect transistors (ISFETs) with tantalum pentoxide sensing layers and demonstrated pH sensitivities approaching the Nernstian limit. Low temperature atomic layer deposition was used to deposit tantalum pentoxide atop large area graphene ISFETs. The charge neutrality point of graphene, inferred from quantum capacitance or channel conductance, was used to monitor surface potential in the presence of an electrolyte with varying pH. Bare graphene ISFETs exhibit negligible response, while graphene ISFETs with tantalum pentoxide sensing layers show increased sensitivity reaching up to 55 mV/pH over pH 3 through pH 8. Applying themore » Bergveld model, which accounts for site binding and a Guoy-Chapman-Stern picture of the surface-electrolyte interface, the increased pH sensitivity can be attributed to an increased buffer capacity reaching up to 10{sup 14} sites/cm{sup 2}. ISFET response was found to be stable to better than 0.05 pH units over the course of two weeks.« less

Large area graphene ion sensitive field effect transistors with tantalum pentoxide sensing layers for pH measurement at the Nernstian limit

NASA Astrophysics Data System (ADS)

Fakih, Ibrahim; Sabri, Shadi; Mahvash, Farzaneh; Nannini, Matthieu; Siaj, Mohamed; Szkopek, Thomas

2014-08-01

We have fabricated and characterized large area graphene ion sensitive field effect transistors (ISFETs) with tantalum pentoxide sensing layers and demonstrated pH sensitivities approaching the Nernstian limit. Low temperature atomic layer deposition was used to deposit tantalum pentoxide atop large area graphene ISFETs. The charge neutrality point of graphene, inferred from quantum capacitance or channel conductance, was used to monitor surface potential in the presence of an electrolyte with varying pH. Bare graphene ISFETs exhibit negligible response, while graphene ISFETs with tantalum pentoxide sensing layers show increased sensitivity reaching up to 55 mV/pH over pH 3 through pH 8. Applying the Bergveld model, which accounts for site binding and a Guoy-Chapman-Stern picture of the surface-electrolyte interface, the increased pH sensitivity can be attributed to an increased buffer capacity reaching up to 1014 sites/cm2. ISFET response was found to be stable to better than 0.05 pH units over the course of two weeks.

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.

Comparison of geostatistical interpolation and remote sensing techniques for estimating long-term exposure to ambient PM2.5 concentrations across the continental United States.

PubMed

Lee, Seung-Jae; Serre, Marc L; van Donkelaar, Aaron; Martin, Randall V; Burnett, Richard T; Jerrett, Michael

2012-12-01

A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from monitor-based data. We evaluated and compared the predictive capabilities of remote sensing and geostatistical interpolation. We developed a space-time geostatistical kriging model to predict PM2.5 over the continental United States and compared resulting predictions to estimates derived from satellite retrievals. The kriging estimate was more accurate for locations that were about 100 km from a monitoring station, whereas the remote sensing estimate was more accurate for locations that were > 100 km from a monitoring station. Based on this finding, we developed a hybrid map that combines the kriging and satellite-based PM2.5 estimates. We found that for most of the populated areas of the continental United States, geostatistical interpolation produced more accurate estimates than remote sensing. The differences between the estimates resulting from the two methods, however, were relatively small. In areas with extensive monitoring networks, the interpolation may provide more accurate estimates, but in the many areas of the world without such monitoring, remote sensing can provide useful exposure estimates that perform nearly as well.

Remote sensing for mined area reclamation: Application inventory

NASA Technical Reports Server (NTRS)

1971-01-01

Applications of aerial remote sensing to coal mined area reclamation are documented, and information concerning available data banks for coal producing areas in the east and midwest is given. A summary of mined area information requirements to which remote sensing methods might contribute is included.

Machine processing of remotely sensed data; Proceedings of the Fifth Annual Symposium, Purdue University, West Lafayette, Ind., June 27-29, 1979

NASA Technical Reports Server (NTRS)

Tendam, I. M. (Editor); Morrison, D. B.

1979-01-01

Papers are presented on techniques and applications for the machine processing of remotely sensed data. Specific topics include the Landsat-D mission and thematic mapper, data preprocessing to account for atmospheric and solar illumination effects, sampling in crop area estimation, the LACIE program, the assessment of revegetation on surface mine land using color infrared aerial photography, the identification of surface-disturbed features through a nonparametric analysis of Landsat MSS data, the extraction of soil data in vegetated areas, and the transfer of remote sensing computer technology to developing nations. Attention is also given to the classification of multispectral remote sensing data using context, the use of guided clustering techniques for Landsat data analysis in forest land cover mapping, crop classification using an interactive color display, and future trends in image processing software and hardware.

Biogeochemical cycling in terrestrial ecosystems - Modeling, measurement, and remote sensing

NASA Technical Reports Server (NTRS)

Peterson, D. L.; Matson, P. A.; Lawless, J. G.; Aber, J. D.; Vitousek, P. M.

1985-01-01

The use of modeling, remote sensing, and measurements to characterize the pathways and to measure the rate of biogeochemical cycling in forest ecosystems is described. The application of the process-level model to predict processes in intact forests and ecosystems response to disturbance is examined. The selection of research areas from contrasting climate regimes and sites having a fertility gradient in that regime is discussed, and the sites studied are listed. The use of remote sensing in determining leaf area index and canopy biochemistry is analyzed. Nitrous oxide emission is investigated by using a gas measurement instrument. Future research projects, which include studying the influence of changes on nutrient cycling in ecosystems and the effect of pollutants on the ecosystems, are discussed.

Negative measurement sensitivity values of planar capacitive imaging probes

NASA Astrophysics Data System (ADS)

Yin, Xiaokang; Chen, Guoming; Li, Wei; Hutchins, David

2014-02-01

The measurement sensitivity distribution of planar capacitive imaging (CI) probes describes how effectively each region in the sensing area is contributing to the measured charge signal on the sensing electrode. It can be used to determine the imaging ability of a CI probe. It is found in previous work that, there are regions in the sensing area where the change of the charge output and the change of targeting physical parameter are of opposite trends. This opposite correlation implies that the measurement sensitivity values in such regions are negative. In this work, the cause of negative sensitivity is discussed. Experiments are also designed and performed so as to verify the existence of negative sensitivity and study the factors that may affect the negative sensitivity distributions.

Broadening the Earthscan Industry

NASA Technical Reports Server (NTRS)

1994-01-01

Law Environmental, Inc. is a professional engineering and Earth sciences consulting firm. When a client, who operates an electricity generating plant required assistance in evaluating the effects of a heated water discharge on aquatic life, Law proposed a Visiting Investigator Program (VIP) to Stennis Space Center (SSC). The VIP is directed toward small companies who could use remote sensing profitably, but do not have the money to explore new technologies. SSC provided remote sensing data to Law enabling it to produce images of the thermal "plume," the water area affected by the discharge. After comparisons of plant and animal life with similar life in an unaffected control area, Law concluded that the discharge effect was not significant.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Metal nanostructures for non-enzymatic glucose sensing.

PubMed

Tee, Si Yin; Teng, Choon Peng; Ye, Enyi

2017-01-01

This review covers the recent development of metal nanostructures in electrochemical non-enzymatic glucose sensing. It highlights a variety of nanostructured materials including noble metals, other transition metals, bimetallic systems, and their hybrid with carbon-based nanomaterials. Particularly, attention is devoted to numerous approaches that have been implemented for improving the sensors performance by tailoring size, shape, composition, effective surface area, adsorption capability and electron-transfer properties. The correlation of the metal nanostructures to the glucose sensing performance is addressed with respect to the linear concentration range, sensitivity and detection limit. In overall, this review provides important clues from the recent scientific achievements of glucose sensor nanomaterials which will be essentially useful in designing better and more effective electrocatalysts for future electrochemical sensing industry. Copyright © 2016 Elsevier B.V. All rights reserved.

The relationship of multispectral satellite imagery to immediate fire effects

Treesearch

Andrew T. Hudak; Penelope Morgan; Michael J. Bobbitt; Allstair M. S. Smith; Sarah A. Lewis; Leigh B. Lentile; Peter R. Robichaud; Jess T. Clark; Randy A. McKinley

2007-01-01

The Forest Service Remote Sensing Applications Center (RSAC) and the U.S. Geological Survey Earth Resources Observation and Science (EROS) Data Center produce Burned Area Reflectance Classification (BARC) maps for use by Burned Area Emergency Response (BAER) teams in rapid response to wildfires. BAER teams desire maps indicative of fire effects on soils, but green and...

Assessment and prediction of land ecological environment quality change based on remote sensing-a case study of the Dongting lake area in China

NASA Astrophysics Data System (ADS)

Hu, Wenmin; Wang, Zhongcheng; Li, Chunhua; Zhao, Jin; Li, Yi

2018-02-01

Multi-source remote sensing data is rarely used for the comprehensive assessment of land ecologic environment quality. In this study, a digital environmental model was proposed with the inversion algorithm of land and environmental factors based on the multi-source remote sensing data, and a comprehensive index (Ecoindex) was applied to reconstruct and predict the land environment quality of the Dongting Lake Area to assess the effect of human activities on the environment. The main finding was that with the decrease of Grade I and Grade II quality had a decreasing tendency in the lake area, mostly in suburbs and wetlands. Atmospheric water vapour, land use intensity, surface temperature, vegetation coverage, and soil water content were the main driving factors. The cause of degradation was the interference of multi-factor combinations, which led to positive and negative environmental agglomeration effects. Positive agglomeration, such as increased rainfall and vegetation coverage and reduced land use intensity, could increase environmental quality, while negative agglomeration resulted in the opposite. Therefore, reasonable ecological restoration measures should be beneficial to limit the negative effects and decreasing tendency, improve the land ecological environment quality and provide references for macroscopic planning by the government.

Practical applications of remote sensing technology

NASA Technical Reports Server (NTRS)

Whitmore, Roy A., Jr.

1990-01-01

Land managers increasingly are becoming dependent upon remote sensing and automated analysis techniques for information gathering and synthesis. Remote sensing and geographic information system (GIS) techniques provide quick and economical information gathering for large areas. The outputs of remote sensing classification and analysis are most effective when combined with a total natural resources data base within the capabilities of a computerized GIS. Some examples are presented of the successes, as well as the problems, in integrating remote sensing and geographic information systems. The need to exploit remotely sensed data and the potential that geographic information systems offer for managing and analyzing such data continues to grow. New microcomputers with vastly enlarged memory, multi-fold increases in operating speed and storage capacity that was previously available only on mainframe computers are a reality. Improved raster GIS software systems have been developed for these high performance microcomputers. Vector GIS systems previously reserved for mini and mainframe systems are available to operate on these enhanced microcomputers. One of the more exciting areas that is beginning to emerge is the integration of both raster and vector formats on a single computer screen. This technology will allow satellite imagery or digital aerial photography to be presented as a background to a vector display.

Modeling residential lawn fertilization practices: integrating high resolution remote sensing with socioeconomic data.

PubMed

Zhou, Weiqi; Troy, Austin; Grove, Morgan

2008-05-01

This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman's Run, in Baltimore County, Maryland, USA. Parcel lawn area and lawn greenness were derived from high-resolution aerial imagery using an object-oriented classification approach. Four indicators of household characteristics, including lot size, square footage of the house, housing value, and housing age were obtained from a property database. Residential lawn care survey data combined with remotely sensed parcel lawn area and greenness data were used to estimate two measures of household lawn fertilization practices, household annual fertilizer nitrogen application amount (N_yr) and household annual fertilizer nitrogen application rate (N_ha_yr). Using multiple regression with multi-model inferential procedures, we found that a combination of parcel lawn area and parcel lawn greenness best predicts N_yr, whereas a combination of parcel lawn greenness and lot size best predicts variation in N_ha_yr. Our analyses show that household fertilization practices can be effectively predicted by remotely sensed lawn indices and household characteristics. This has significant implications for urban watershed managers and modelers.

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 for the sustainable management and conservation of forest environments biodiversity: the conservation managers perspective.

NASA Astrophysics Data System (ADS)

Aguilar-Amuchas, N.; Henebry, G. M.; Blanchard, J.; Sutter, R.

2008-12-01

The potential use of remote sensing for the design and implementation of sustainable management, conservation, and monitoring of forest biodiversity has been well documented in the scientific literature. However, when we look into how often remote sensing is actually being used in the decision making processes affecting biodiversity conservation and sustainable management, we find that, apart from specific study cases, its use is not as widespread as we know it should. There is an enormous gap between our scientific achievements and their use in the real world towards the preservation of a rapidly vanishing biodiversity. Conservation managers understand the potential remote sensing has. However, logistical constraints and high technical skills requirements render the use of remote sensing data difficult. Sound and easy approaches need to be developed and implemented. We present two study cases that illustrate 1st. How the interaction between tropical forest managers and remote sensing specialist allowed developing a simple method for the identification of priority areas for field surveys of tropical forests management ecological sustainability indicators and, 2nd. How remote sensing is being used by The Nature Conservancy as a first level approach towards the assessment of forest conservation strategies effectiveness in for areas located in 11 states, covering different forest types and a variety of conservation objectives.

LOCATING AREAS OF CONCERN

EPA Science Inventory

A simple method to locate changes in vegetation cover, which can be used to identify areas under stress. The method only requires inexpensive NDVI data. The use of remotely sensed data is far more cost-effective than field studies and can be performed more quickly. Local knowledg...

The use of high altitude aerial photography to inventory wildlife habitat in Kansas: An initial evaluation

NASA Technical Reports Server (NTRS)

Merchant, J. W.; Waddell, B. H.

1974-01-01

The use of aerial photography as a method for determining the wildlife conditions of an area is discussed. Color infrared photography is investigated as the most effective type of remote sensor. The characteristics of the remote sensing systems are described. Examples of the remote sensing operation and the method for reducing the data are presented.

Effects of annealing temperature on the H2-sensing properties of Pd-decorated WO3 nanorods

NASA Astrophysics Data System (ADS)

Lee, Sangmin; Lee, Woo Seok; Lee, Jae Kyung; Hyun, Soong Keun; Lee, Chongmu; Choi, Seungbok

2018-03-01

The temperature of the post-annealing treatment carried out after noble metal deposition onto semiconducting metal oxides (SMOs) must be carefully optimized to maximize the sensing performance of the metal-decorated SMO sensors. WO3 nanorods were synthesized by thermal evaporation of WO3 powders and decorated with Pd nanoparticles using a sol-gel method, followed by an annealing process. The effects of the annealing temperature on the hydrogen gas-sensing properties of the Pd-decorated WO3 nanorods were then examined; the optimal annealing temperature, leading to the highest response of the WO3 nanorod sensor to H2, was determined to be 600 °C. Post-annealing at 600 °C resulted in nanorods with the highest surface area-to-volume ratio, as well as in the optimal size and the largest number of deposited Pd nanoparticles, leading to the highest response and the shortest response/recovery times toward H2. The improved H2-sensing performance of the Pd-decorated WO3 nanorod sensor, compared to a sensor based on pristine WO3 nanorods, is attributed to the enhanced catalytic activity, increased surface area-to-volume ratio, and higher amounts of surface defects.

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.

[Research progress on remote sensing of ecological and environmental changes in the Three Gorges Reservoir area, China].

PubMed

Teng, Ming-jun; Zeng, Li-xiong; Xiao, Wen-fa; Zhou, Zhi-xiang; Huang, Zhi-lin; Wang, Peng-cheng; Dian, Yuan-yong

2014-12-01

The Three Gorges Reservoir area (TGR area) , one of the most sensitive ecological zones in China, has dramatically changes in ecosystem configurations and services driven by the Three Gorges Engineering Project and its related human activities. Thus, understanding the dynamics of ecosystem configurations, ecological processes and ecosystem services is an attractive and critical issue to promote regional ecological security of the TGR area. The remote sensing of environment is a promising approach to the target and is thus increasingly applied to and ecosystem dynamics of the TGR area on mid- and macro-scales. However, current researches often showed controversial results in ecological and environmental changes in the TGR area due to the differences in remote sensing data, scale, and land-use/cover classification. Due to the complexity of ecological configurations and human activities, challenges still exist in the remote-sensing based research of ecological and environmental changes in the TGR area. The purpose of this review was to summarize the research advances in remote sensing of ecological and environmental changes in the TGR area. The status, challenges and trends of ecological and environmental remote-sensing in the TGR area were further discussed and concluded in the aspect of land-use/land-cover, vegetation dynamics, soil and water security, ecosystem services, ecosystem health and its management. The further researches on the remote sensing of ecological and environmental changes were proposed to improve the ecosystem management of the TGR area.

a Hyperspectral Based Method to Detect Cannabis Plantation in Inaccessible Areas

NASA Astrophysics Data System (ADS)

Houmi, M.; Mohamadi, B.; Balz, T.

2018-04-01

The increase in drug use worldwide has led to sophisticated illegal planting methods. Most countries depend on helicopters, and local knowledge to identify such illegal plantations. However, remote sensing techniques can provide special advantages for monitoring the extent of illegal drug production. This paper sought to assess the ability of the Satellite remote sensing to detect Cannabis plantations. This was achieved in two stages: 1- Preprocessing of Hyperspectral data EO-1, and testing the capability to collect the spectral signature of Cannabis in different sites of the study area (Morocco) from well-known Cannabis plantation fields. 2- Applying the method of Spectral Angle Mapper (SAM) based on a specific angle threshold on Hyperion data EO-1 in well-known Cannabis plantation sites, and other sites with negative Cannabis plantation in another study area (Algeria), to avoid any false Cannabis detection using these spectra. This study emphasizes the benefits of using hyperspectral remote sensing data as an effective detection tool for illegal Cannabis plantation in inaccessible areas based on SAM classification method with a maximum angle (radians) less than 0.03.

PIXELS: Using field-based learning to investigate students' concepts of pixels and sense of scale

NASA Astrophysics Data System (ADS)

Pope, A.; Tinigin, L.; Petcovic, H. L.; Ormand, C. J.; LaDue, N.

2015-12-01

Empirical work over the past decade supports the notion that a high level of spatial thinking skill is critical to success in the geosciences. Spatial thinking incorporates a host of sub-skills such as mentally rotating an object, imagining the inside of a 3D object based on outside patterns, unfolding a landscape, and disembedding critical patterns from background noise. In this study, we focus on sense of scale, which refers to how an individual quantified space, and is thought to develop through kinesthetic experiences. Remote sensing data are increasingly being used for wide-reaching and high impact research. A sense of scale is critical to many areas of the geosciences, including understanding and interpreting remotely sensed imagery. In this exploratory study, students (N=17) attending the Juneau Icefield Research Program participated in a 3-hour exercise designed to study how a field-based activity might impact their sense of scale and their conceptions of pixels in remotely sensed imagery. Prior to the activity, students had an introductory remote sensing lecture and completed the Sense of Scale inventory. Students walked and/or skied the perimeter of several pixel types, including a 1 m square (representing a WorldView sensor's pixel), a 30 m square (a Landsat pixel) and a 500 m square (a MODIS pixel). The group took reflectance measurements using a field radiometer as they physically traced out the pixel. The exercise was repeated in two different areas, one with homogenous reflectance, and another with heterogeneous reflectance. After the exercise, students again completed the Sense of Scale instrument and a demographic survey. This presentation will share the effects and efficacy of the field-based intervention to teach remote sensing concepts and to investigate potential relationships between students' concepts of pixels and sense of scale.

Rotation Sensing with Trapped Ions

DTIC Science & Technology

2016-09-01

Sagnac effect can be used to measure the rotational velocity Ω of a reference frame by observing the phase shift of an interferometer in that frame whose...sensitivity of interferometric gyroscopes. For photons, optical fibers (or ring laser cavities) allow many effective round-trips through the Sagnac...interferometer, thereby increasing the effective area A by 2 times the number of round trips (M) without increasing the actual area of the apparatus. This

Stretchable Electronic Sensors of Nanocomposite Network Films for Ultrasensitive Chemical Vapor Sensing.

PubMed

Yan, Hong; Zhong, Mengjuan; Lv, Ze; Wan, Pengbo

2017-11-01

A stretchable, transparent, and body-attachable chemical sensor is assembled from the stretchable nanocomposite network film for ultrasensitive chemical vapor sensing. The stretchable nanocomposite network film is fabricated by in situ preparation of polyaniline/MoS 2 (PANI/MoS 2 ) nanocomposite in MoS 2 suspension and simultaneously nanocomposite deposition onto prestrain elastomeric polydimethylsiloxane substrate. The assembled stretchable electronic sensor demonstrates ultrasensitive sensing performance as low as 50 ppb, robust sensing stability, and reliable stretchability for high-performance chemical vapor sensing. The ultrasensitive sensing performance of the stretchable electronic sensors could be ascribed to the synergistic sensing advantages of MoS 2 and PANI, higher specific surface area, the reliable sensing channels of interconnected network, and the effectively exposed sensing materials. It is expected to hold great promise for assembling various flexible stretchable chemical vapor sensors with ultrasensitive sensing performance, superior sensing stability, reliable stretchability, and robust portability to be potentially integrated into wearable electronics for real-time monitoring of environment safety and human healthcare. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Airborne Detection of Cosmic-Ray Albedo Neutrons for Regional-Scale Surveys of Root-Zone Soil Water on Earth

NASA Astrophysics Data System (ADS)

Schrön, M.; Bannehr, L.; Köhli, M.; Zreda, M. G.; Weimar, J.; Zacharias, S.; Oswald, S. E.; Bumberger, J.; Samaniego, L. E.; Schmidt, U.; Zieger, P.; Dietrich, P.

2017-12-01

While the detection of albedo neutrons from cosmic rays became a standard method in planetary space science, airborne neutron sensing has never been conceived for hydrological research on Earth. We assessed the applicability of atmospheric neutrons to sense root-zone soil moisture averaged over tens of hectares using neutron detectors on an airborne vehicle. Large-scale quantification of near-surface water content is an urgent challenge in hydrology. Information about soil and plant water is crucial to accurately assess the risks for floods and droughts, to adjust regional weather forecasts, and to calibrate and validate the corresponding models. However, there is a lack of data at scales relevant for these applications. Most conventional ground-based geophysical instruments provide root-zone soil moisture only within a few tens of m2, while electromagnetic signals from conventional remote-sensing instruments can only penetrate the first few centimeters below surface, though at larger spatial areas.In the last couple of years, stationary and roving neutron detectors have been used to sense the albedo component of cosmic-ray neutrons, which represents the average water content within 10—15 hectares and 10—50 cm depth. However, the application of these instruments is limited by inaccessible terrain and interfering local effects from roads. To overcome these limitations, we have pioneered first simulations and experiments of such sensors in the field of airborne geophysics. Theoretical investigations have shown that the footprint increases substantially with height above ground, while local effects smooth out throughout the whole area. Campaigns with neutron detectors mounted on a lightweight gyrocopter have been conducted over areas of various landuse types including agricultural fields, urban areas, forests, flood plains, and lakes. The neutron signal showed influence of soil moisture patterns in heights of up to 180 m above ground. We found correlation with ground-truthing data, using mobile cosmic-ray neutron sensors, local soil samples, TDR, and buried wireless soil moisture monitoring networks. The work opens the path towards further systematic assessment of airborne neutron sensing, which could become a valuable addition - or even an alternative - to conventional remote-sensing methods.

Using Remote Sensing Mapping and Growth Response to Environmental Variability to Aide Aquatic Invasive Plant Management

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Schlick, Greg; Genovese, Vanessa; Wilson, Kenneth D.

2018-01-01

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta.

Throughput assurance of wireless body area networks coexistence based on stochastic geometry

PubMed Central

Wang, Yinglong; Shu, Minglei; Wu, Shangbin

2017-01-01

Wireless body area networks (WBANs) are expected to influence the traditional medical model by assisting caretakers with health telemonitoring. Within WBANs, the transmit power of the nodes should be as small as possible owing to their limited energy capacity but should be sufficiently large to guarantee the quality of the signal at the receiving nodes. When multiple WBANs coexist in a small area, the communication reliability and overall throughput can be seriously affected due to resource competition and interference. We show that the total network throughput largely depends on the WBANs distribution density (λp), transmit power of their nodes (Pt), and their carrier-sensing threshold (γ). Using stochastic geometry, a joint carrier-sensing threshold and power control strategy is proposed to meet the demand of coexisting WBANs based on the IEEE 802.15.4 standard. Given different network distributions and carrier-sensing thresholds, the proposed strategy derives a minimum transmit power according to varying surrounding environment. We obtain expressions for transmission success probability and throughput adopting this strategy. Using numerical examples, we show that joint carrier-sensing thresholds and transmit power strategy can effectively improve the overall system throughput and reduce interference. Additionally, this paper studies the effects of a guard zone on the throughput using a Matern hard-core point process (HCPP) type II model. Theoretical analysis and simulation results show that the HCPP model can increase the success probability and throughput of networks. PMID:28141841

On multidisciplinary research on the application of remote sensing to water resources problems. [Wisconsin

NASA Technical Reports Server (NTRS)

Clapp, J. L.

1973-01-01

Research objectives during 1972-73 were to: (1) Ascertain the extent to which special aerial photography can be operationally used in monitoring water pollution parameters. (2) Ascertain the effectiveness of remote sensing in the investigation of nearshore mixing and coastal entrapment in large water bodies. (3) Develop an explicit relationship of the extent of the mixing zone in terms of the outfall, effluent and water body characteristics. (4) Develop and demonstrate the use of the remote sensing method as an effective legal implement through which administrative agencies and courts can not only investigate possible pollution sources but also legally prove the source of water pollution. (5) Evaluate the field potential of remote sensing techniques in monitoring algal blooms and aquatic macrophytes, and the use of these as indicators of lake eutrophication level. (6) Develop a remote sensing technique for the determination of the location and extent of hydrologically active source areas in a watershed.

Assessment of practicality of remote sensing techniques for a study of the effects of strip mining in Alabama

NASA Technical Reports Server (NTRS)

Hughes, T. H.; Dillion, A. C., III; White, J. R., Jr.; Drummond, S. E., Jr.; Hooks, W. G.

1975-01-01

Because of the volume of coal produced by strip mining, the proximity of mining operations, and the diversity of mining methods (e.g. contour stripping, area stripping, multiple seam stripping, and augering, as well as underground mining), the Warrior Coal Basin seemed best suited for initial studies on the physical impact of strip mining in Alabama. Two test sites, (Cordova and Searles) representative of the various strip mining techniques and environmental problems, were chosen for intensive studies of the correlation between remote sensing and ground truth data. Efforts were eventually concentrated in the Searles Area, since it is more accessible and offers a better opportunity for study of erosional and depositional processes than the Cordova Area.

Introduction. [usefulness of modern remote sensing techniques for studying components of California water resources

NASA Technical Reports Server (NTRS)

Colwell, R. N.

1973-01-01

Since May 1970, personnel on several campuses of the University of California have been conducting investigations which seek to determine the usefulness of modern remote sensing techniques for studying various components of California's earth resources complex. Emphasis has been given to California's water resources as exemplified by the Feather River project and other aspects of the California Water Plan. This study is designed to consider in detail the supply, demand, and impact relationships. The specific geographic areas studied are the Feather River drainage in northern California, the Chino-Riverside Basin and Imperial Valley areas in southern California, and selected portions of the west side of San Joaquin Valley in central California. An analysis is also given on how an effective benefit-cost study of remote sensing in relation to California's water resources might best be made.

Sea Ice Thickness Measurement by Ground Penetrating Radar for Ground Truth of Microwave Remote Sensing Data

NASA Astrophysics Data System (ADS)

Matsumoto, M.; Yoshimura, M.; Naoki, K.; Cho, K.; Wakabayashi, H.

2018-04-01

Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR) can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately) aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation.

Multi-electrode stimulation in somatosensory cortex increases probability of detection

NASA Astrophysics Data System (ADS)

Zaaimi, Boubker; Ruiz-Torres, Ricardo; Solla, Sara A.; Miller, Lee E.

2013-10-01

Objective. Brain machine interfaces (BMIs) that decode control signals from motor cortex have developed tremendously in the past decade, but virtually all rely exclusively on vision to provide feedback. There is now increasing interest in developing an afferent interface to replace natural somatosensation, much as the cochlear implant has done for the sense of hearing. Preliminary experiments toward a somatosensory neuroprosthesis have mostly addressed the sense of touch, but proprioception, the sense of limb position and movement, is also critical for the control of movement. However, proprioceptive areas of cortex lack the precise somatotopy of tactile areas. We showed previously that there is only a weak tendency for neighboring neurons in area 2 to signal similar directions of hand movement. Consequently, stimulation with the relatively large currents used in many studies is likely to activate a rather heterogeneous set of neurons. Approach. Here, we have compared the effect of single-electrode stimulation at subthreshold levels to the effect of stimulating as many as seven electrodes in combination. Main results. We found a mean enhancement in the sensitivity to the stimulus (d‧) of 0.17 for pairs compared to individual electrodes (an increase of roughly 30%), and an increase of 2.5 for groups of seven electrodes (260%). Significance. We propose that a proprioceptive interface made up of several hundred electrodes may yield safer, more effective sensation than a BMI using fewer electrodes and larger currents.

Cholesterol homeostasis: How do cells sense sterol excess?

PubMed

Howe, Vicky; Sharpe, Laura J; Alexopoulos, Stephanie J; Kunze, Sarah V; Chua, Ngee Kiat; Li, Dianfan; Brown, Andrew J

2016-09-01

Cholesterol is vital in mammals, but toxic in excess. Consequently, elaborate molecular mechanisms have evolved to maintain this sterol within narrow limits. How cells sense excess cholesterol is an intriguing area of research. Cells sense cholesterol, and other related sterols such as oxysterols or cholesterol synthesis intermediates, and respond to changing levels through several elegant mechanisms of feedback regulation. Cholesterol sensing involves both direct binding of sterols to the homeostatic machinery located in the endoplasmic reticulum (ER), and indirect effects elicited by sterol-dependent alteration of the physical properties of membranes. Here, we examine the mechanisms employed by cells to maintain cholesterol homeostasis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A coactive interdisciplinary research program with NASA

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr.

1972-01-01

The applications area of the Texas A&M University remote sensing program consists of a series of coactive projects with NASA/MSC personnel. In each case, the Remote Sensing Center has served to complement and enhance the research capability within the Manned Spacecraft Center. In addition to the applications study area, the Texas A&M University program includes coordinated projects in sensors and data analysis. Under the sensors area, an extensive experimental study of microwave radiometry for soil moisture determination established the effect of soil moisture on the measured brightness temperature for several different soil types. The data analysis area included a project which ERTS-A and Skylab data were simulated using aircraft multispectral scanner measurements at two altitudes. This effort resulted in development of a library of computer programs which provides an operational capability in classification analysis of multispectral data.

Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas

NASA Astrophysics Data System (ADS)

Sun, X. F.; Lin, X. G.

2017-09-01

As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.

The Effectiveness of Hydrothermal Alteration Mapping based on Hyperspectral Data in Tropical Region

NASA Astrophysics Data System (ADS)

Muhammad, R. R. D.; Saepuloh, A.

2016-09-01

Hyperspectral remote sensing could be used to characterize targets at earth's surface based on their spectra. This capability is useful for mapping and characterizing the distribution of host rocks, alteration assemblages, and minerals. Contrary to the multispectral sensors, the hyperspectral identifies targets with high spectral resolution. The Wayang Windu Geothermal field in West Java, Indonesia was selected as the study area due to the existence of surface manifestation and dense vegetation environment. Therefore, the effectiveness of hyperspectral remote sensing in tropical region was targeted as the study objective. The Spectral Angle Mapper (SAM) method was used to detect the occurrence of clay minerals spatially from Hyperion data. The SAM references of reflectance spectra were obtained from field observation at altered materials. To calculate the effectiveness of hyperspectral data, we used multispectral data from Landsat-8. The comparison method was conducted by comparing the SAM's rule images from Hyperion and Landsat-8, resulting that hyperspectral was more accurate than multispectral data. Hyperion SAM's rule images showed lower value compared to Landsat-8, the significant number derived from using Hyperion was about 24% better. This inferred that the hyperspectral remote sensing is preferable for mineral mapping even though vegetation covered study area.

3D Architectured Graphene/Metal Oxide Hybrids for Gas Sensors: A Review

PubMed Central

Xia, Yi; Li, Ran; Chen, Ruosong; Wang, Jing; Xiang, Lan

2018-01-01

Graphene/metal oxide-based materials have been demonstrated as promising candidates for gas sensing applications due to the enhanced sensing performance and synergetic effects of the two components. Plenty of metal oxides such as SnO2, ZnO, WO3, etc. have been hybridized with graphene to improve the gas sensing properties. However, graphene/metal oxide nanohybrid- based gas sensors still have several limitations in practical application such as the insufficient sensitivity and response rate, and long recovery time in some cases. To achieve higher sensing performances of graphene/metal oxides nanocomposites, many recent efforts have been devoted to the controllable synthesis of 3D graphene/metal oxides architectures owing to their large surface area and well-organized structure for the enhanced gas adsorption/diffusion on sensing films. This review summarizes recent advances in the synthesis, assembly, and applications of 3D architectured graphene/metal oxide hybrids for gas sensing. PMID:29735951

Sea Surface Signature of Tropical Cyclones Using Microwave Remote Sensing

DTIC Science & Technology

2013-01-01

due to the ionosphere and troposphere, which have to be compensated for, and components due to the galactic and cosmic background radiation those...and corrections for sun glint, galactic and cosmic background radiation, and Stokes effects of the ionosphere. The accuracy of a given retrieval...RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) Sea surface signature of tropical cyclones using microwave remote sensing Bumjun Kil

Method For Detecting The Presence Of A Ferromagnetic Object

DOEpatents

Roybal, Lyle G.

2000-11-21

A method for detecting a presence or an absence of a ferromagnetic object within a sensing area may comprise the steps of sensing, during a sample time, a magnetic field adjacent the sensing area; producing surveillance data representative of the sensed magnetic field; determining an absolute value difference between a maximum datum and a minimum datum comprising the surveillance data; and determining whether the absolute value difference has a positive or negative sign. The absolute value difference and the corresponding positive or negative sign thereof forms a representative surveillance datum that is indicative of the presence or absence in the sensing area of the ferromagnetic material.

A Polygon Model for Wireless Sensor Network Deployment with Directional Sensing Areas

PubMed Central

Wu, Chun-Hsien; Chung, Yeh-Ching

2009-01-01

The modeling of the sensing area of a sensor node is essential for the deployment algorithm of wireless sensor networks (WSNs). In this paper, a polygon model is proposed for the sensor node with directional sensing area. In addition, a WSN deployment algorithm is presented with topology control and scoring mechanisms to maintain network connectivity and improve sensing coverage rate. To evaluate the proposed polygon model and WSN deployment algorithm, a simulation is conducted. The simulation results show that the proposed polygon model outperforms the existed disk model and circular sector model in terms of the maximum sensing coverage rate. PMID:22303159

Urban heat island impacts on plant phenology: intra-urban variability and response to land cover

NASA Astrophysics Data System (ADS)

Zipper, Samuel C.; Schatz, Jason; Singh, Aditya; Kucharik, Christopher J.; Townsend, Philip A.; Loheide, Steven P., II

2016-05-01

Despite documented intra-urban heterogeneity in the urban heat island (UHI) effect, little is known about spatial or temporal variability in plant response to the UHI. Using an automated temperature sensor network in conjunction with Landsat-derived remotely sensed estimates of start/end of the growing season, we investigate the impacts of the UHI on plant phenology in the city of Madison WI (USA) for the 2012-2014 growing seasons. Median urban growing season length (GSL) estimated from temperature sensors is ˜5 d longer than surrounding rural areas, and UHI impacts on GSL are relatively consistent from year-to-year. Parks within urban areas experience a subdued expression of GSL lengthening resulting from interactions between the UHI and a park cool island effect. Across all growing seasons, impervious cover in the area surrounding each temperature sensor explains >50% of observed variability in phenology. Comparisons between long-term estimates of annual mean phenological timing, derived from remote sensing, and temperature-based estimates of individual growing seasons show no relationship at the individual sensor level. The magnitude of disagreement between temperature-based and remotely sensed phenology is a function of impervious and grass cover surrounding the sensor, suggesting that realized GSL is controlled by both local land cover and micrometeorological conditions.

Estimating reforestation by means of remote sensing

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.

1981-01-01

LANDSAT imagery at the scale of 1:250.000 and obtained from bands 5 and 7 as well as computer compatible tapes were used to evaluate the effectiveness of remotely sensed orbital data in inventorying forests in a 462,100 area of Brazil emcompassing the cities of Ribeirao, Altinopolis Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Santa Rita do Passa Quatro, and Santa Rosa do Viterbo. Visual interpretation of LANDSAT imagery shows that 37,766 hectares (1977) and 38,003.75 hectares (1979) were reforested areas of pine and eucalyptus species. An increment of 237.5 hectares was found during this two-year time lapse.

Ten ways remote sensing can contribute to conservation

USGS Publications Warehouse

Rose, Robert A.; Byler, Dirck; Eastman, J. Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A.; Laporte, Nadine; Leidner, Allison K.; Leimgruber, Peter; Morisette, Jeffrey T.; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C.; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

2014-01-01

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?

Ten ways remote sensing can contribute to conservation.

PubMed

Rose, Robert A; Byler, Dirck; Eastman, J Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A; Laporte, Nadine; Leidner, Allison; Leimgruber, Peter; Morisette, Jeffrey; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

2015-04-01

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions? © 2014 Society for Conservation Biology.

Nonlinear Photonic Systems for V- and W-Band Antenna Remoting Applications

DTIC Science & Technology

2016-10-22

for commercial, academic, and military purposes delivering microwaves through fibers to remote areas for wireless sensing , imaging, and detection...academic, and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and...and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and detection

Surface-area-controlled synthesis of porous TiO2 thin films for gas-sensing applications

NASA Astrophysics Data System (ADS)

Park, Jae Young; Kim, Ho-hyoung; Rana, Dolly; Jamwal, Deepika; Katoch, Akash

2017-03-01

Surface-area-controlled porous TiO2 thin films were prepared via a simple sol-gel chemical route, and their gas-sensing properties were thoroughly investigated in the presence of typical oxidizing NO2 gas. The surface area of TiO2 thin films was controlled by developing porous TiO2 networked by means of controlling the TiO2-to-TTIP (titanium isopropoxide, C12H28O4Ti) molar ratio, where TiO2 nanoparticles of size ˜20 nm were used. The sensor’s response was found to depend on the surface area of the TiO2 thin films. The porous TiO2 thin-film sensor with greater surface area was more sensitive than those of TiO2 thin films with lesser surface area. The improved sensing ability was ascribed to the porous network formed within the thin films by TiO2 sol. Our results show that surface area is a key parameter for obtaining superior gas-sensing performance; this provides important guidelines for preparing and using porous thin films for gas-sensing applications.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application.

PubMed

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-06-06

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

PubMed Central

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-01-01

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information’s relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection. PMID:28587299

Comparison of Effects of a Proprioceptive Exercise Program in Water and on Land the Balance of Chronic Stroke Patients

PubMed Central

Han, Seul Ki; Kim, Myung Chul; An, Chang Sik

2013-01-01

[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exercise group used wonder boards in a pool (depth 1.1m, water temperature 33.5 °C, air temperature 27 °C) dedicated to underwater exercise, and the land exercise group used balance mats. [Result] The joint position sense, sway area, Berg Balance Scale showed significant improvements in both groups. However, the joint position sense test, sway area, and Berg Balance Scale showed there was more improvement in the underwater exercise group than in the land exercise group. [Conclusion] The results suggest that underwater exercise is more effective than land exercise at improving the joint position sense and balance of stroke patients. PMID:24259761

Comparison of effects of a proprioceptive exercise program in water and on land the balance of chronic stroke patients.

PubMed

Han, Seul Ki; Kim, Myung Chul; An, Chang Sik

2013-10-01

[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exercise group used wonder boards in a pool (depth 1.1m, water temperature 33.5 °C, air temperature 27 °C) dedicated to underwater exercise, and the land exercise group used balance mats. [Result] The joint position sense, sway area, Berg Balance Scale showed significant improvements in both groups. However, the joint position sense test, sway area, and Berg Balance Scale showed there was more improvement in the underwater exercise group than in the land exercise group. [Conclusion] The results suggest that underwater exercise is more effective than land exercise at improving the joint position sense and balance of stroke patients.

Thermal anomaly before earthquake and damage assessment using remote sensing data for 2014 Yutian earthquake

NASA Astrophysics Data System (ADS)

Zhang, Yanmei; Huang, Haiying; Jiang, Zaisen; Fang, Ying; Cheng, Xiao

2014-12-01

Thermal anomaly appears to be a significant precursor of some strong earthquakes. In this study, time series of MODIS Land Surface Temperature (LST) products from 2001 to 2014 are processed and analyzed to locate possible anomalies prior to the Yutian earthquake (12 February 2014, Xinjiang, CHINA). In order to reduce the seasonal or annual effects from the LST variations, also to avoid the rainy and cloudy weather in this area, a background mean of ten-day nighttime LST are derived using averaged MOD11A2 products from 2001 to 2012. Then the ten-day LST data from Jan 2014 to FebJanuary 2014 were differenced using the above background. Abnormal LST increase before the earthquake is quite obvious from the differential images, indicating that this method is useful in such area with high mountains and wide-area deserts. Also, in order to assess the damage to infrastructure, China's latest civilian high-resolution remote sensing satellite - GF-1 remote sensed data are applied to the affected counties in this area. The damaged infrastructures and ground surface could be easily interpreted in the fused pan-chromatic and multi-spectral images integrating both texture and spectral information.

Expanding the Detection of Traversable Area with RealSense for the Visually Impaired

PubMed Central

Yang, Kailun; Wang, Kaiwei; Hu, Weijian; Bai, Jian

2016-01-01

The introduction of RGB-Depth (RGB-D) sensors into the visually impaired people (VIP)-assisting area has stirred great interest of many researchers. However, the detection range of RGB-D sensors is limited by narrow depth field angle and sparse depth map in the distance, which hampers broader and longer traversability awareness. This paper proposes an effective approach to expand the detection of traversable area based on a RGB-D sensor, the Intel RealSense R200, which is compatible with both indoor and outdoor environments. The depth image of RealSense is enhanced with IR image large-scale matching and RGB image-guided filtering. Traversable area is obtained with RANdom SAmple Consensus (RANSAC) segmentation and surface normal vector estimation, preliminarily. A seeded growing region algorithm, combining the depth image and RGB image, enlarges the preliminary traversable area greatly. This is critical not only for avoiding close obstacles, but also for allowing superior path planning on navigation. The proposed approach has been tested on a score of indoor and outdoor scenarios. Moreover, the approach has been integrated into an assistance system, which consists of a wearable prototype and an audio interface. Furthermore, the presented approach has been proved to be useful and reliable by a field test with eight visually impaired volunteers. PMID:27879634

Application of remote sensing and geographical information system in mapping forest fire risk zone at Bhadra wildlife sanctuary, India.

PubMed

Sowmya, S V; Somashekar, R K

2010-11-01

Fire is the most spectacular natural disturbance that affects the forest ecosystem composition and diversity. Fire has a devastating effect on the landscape and its impact is felt at every level of the ecosystem and it is possible to map forest fire risk zone and thereby minimize the frequency of fire. There is a need for supranational approaches that analyze wide scenarios of factors involved and global fire effects. Fires can be monitored and analyzed over large areas in a timely and cost effective manner by using satellite imagery. Also Geographical Information System (GIS) can be used effectively to demarcate the fire risk zone map. Bhadra wildlife Sanctuary located in Kamataka, India was selected for this study. Vegetation, slope, distance from roads, settlements parameters were derived for a study area using topographic maps and field information. The Remote Sensing (RS) and Geographical Information System (GIS)-based forest fire risk model of the study area appeared to be highly compatible with the actual fire-affected sites. The temporal satellite data from 1989 to2006 have been analyzed to map the burnt areas. These classes were weighted according to their influence on forest fire. Four categories of fire risk regions such as Low, Moderate, High and Very high fire intensity zones were identified. It is predicted that around 10.31% of the area falls undermoderate risk zone.

Earth Survey Applications Division. [a bibliography

NASA Technical Reports Server (NTRS)

Carpenter, L. (Editor)

1981-01-01

Accomplishments of research and data analysis conducted to study physical parameters and processes inside the Earth and on the Earth's surface, to define techniques and systems for remotely sensing the processes and measuring the parameters of scientific and applications interest, and the transfer of promising operational applications techniques to the user community of Earth resources monitors, managers, and decision makers are described. Research areas covered include: geobotany, magnetic field modeling, crustal studies, crustal dynamics, sea surface topography, land resources, remote sensing of vegetation and soils, and hydrological sciences. Major accomplishments include: production of global maps of magnetic anomalies using Magsat data; computation of the global mean sea surface using GEOS-3 and Seasat altimetry data; delineation of the effects of topography on the interpretation of remotely-sensed data; application of snowmelt runoff models to water resources management; and mapping of snow depth over wheat growing areas using Nimbus microwave data.

Aligned hierarchical Ag/ZnO nano-heterostructure arrays via electrohydrodynamic nanowire template for enhanced gas-sensing properties.

PubMed

Yin, Zhouping; Wang, Xiaomei; Sun, Fazhe; Tong, Xiaohu; Zhu, Chen; Lv, Qiying; Ye, Dong; Wang, Shuai; Luo, Wei; Huang, YongAn

2017-09-22

Gas sensing performance can be improved significantly by the increase in both the effective gas exposure area and the surface reactivitiy of ZnO nanorods. Here, we propose aligned hierarchical Ag/ZnO nano-heterostructure arrays (h-Ag/ZnO-NAs) via electrohydrodynamic nanowire template, together with a subsequent hydrothermal synthesis and photoreduction reaction. The h-Ag/ZnO-NAs scatter at top for higher specific surface areas with the air, simultaneously contact at root for the electrical conduction. Besides, the ZnO nanorods are uniformly coated with dispersed Ag nanoparticles, resulting in a tremendous enhancement of the surface reactivity. Compared with pure ZnO, such h-Ag/ZnO-NAs exhibit lower electrical resistance and faster responses. Moreover, they demonstrate enhanced NO 2 gas sensing properties. Self-assembly via electrohydrodynamic nanowire template paves a new way for the preparation of high performance gas sensors.

A framework for farmland parcels extraction based on image classification

NASA Astrophysics Data System (ADS)

Liu, Guoying; Ge, Wenying; Song, Xu; Zhao, Hongdan

2018-03-01

It is very important for the government to build an accurate national basic cultivated land database. In this work, farmland parcels extraction is one of the basic steps. However, during the past years, people had to spend much time on determining an area is a farmland parcel or not, since they were bounded to understand remote sensing images only from the mere visual interpretation. In order to overcome this problem, in this study, a method was proposed to extract farmland parcels by means of image classification. In the proposed method, farmland areas and ridge areas of the classification map are semantically processed independently and the results are fused together to form the final results of farmland parcels. Experiments on high spatial remote sensing images have shown the effectiveness of the proposed method.

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.

Remote sensing of wetlands

NASA Technical Reports Server (NTRS)

Roller, N. E. G.

1977-01-01

The concept of using remote sensing to inventory wetlands and the related topics of proper inventory design and data collection are discussed. The material presented shows that aerial photography is the form of remote sensing from which the greatest amount of wetlands information can be derived. For extensive, general-purpose wetlands inventories, however, the use of LANDSAT data may be more cost-effective. Airborne multispectral scanners and radar are, in the main, too expensive to use - unless the information that these sensors alone can gather remotely is absolutely required. Multistage sampling employing space and high altitude remote sensing data in the initial stages appears to be an efficient survey strategy for gathering non-point specific wetlands inventory data over large areas. The operational role of remote sensing insupplying inventory data for application to several typical wetlands management problems is illustrated by summary descriptions of past ERIM projects.

Integrated photonics for fiber optic based temperature sensing

NASA Astrophysics Data System (ADS)

Evenblij, R. S.; van Leest, T.; Haverdings, M. B.

2017-09-01

One of the promising space applications areas for fibre sensing is high reliable thermal mapping of metrology structures for effects as thermal deformation, focal plane distortion, etc. Subsequently, multi-point temperature sensing capability for payload panels and instrumentation instead of, or in addition to conventional thermo-couple technology will drastically reduce electrical wiring and sensor materials to minimize weight and costs. Current fiber sensing technologies based on solid state ASPIC (Application Specific Photonic Integrated Circuits) technology, allow significant miniaturization of instrumentation and improved reliability. These imperative aspects make the technology candidate for applications in harsh environments such as space. One of the major aspects in order to mature ASPIC technology for space is assessment on radiation hardness. This paper describes the results of radiation hardness experiments on ASPIC including typical multipoint temperature sensing and thermal mapping capabilities.

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.

Evaluation of impact of earthquake on agriculture in Nepal based on remote sensing

NASA Astrophysics Data System (ADS)

Sekiyama, Ayako; Shimada, Sawahiko; Okazawa, Hiromu; Mihara, Machito; Kuo, Kuang Ting

2016-07-01

The big earthquake happening on April, 2015 killed over than 8000 people in Nepal. The effect of earthquake not only affected safety of local people but also agricultural field. Agricultural economy dominates income of local people. Therefore, restoration of agricultural areas are required for improving life of local people. However, lack of information about agricultural areas is main problem for local government to assess and restore damaged agricultural areas. Remote sensing was applied for accessing damaged agricultural field due to its advantages in observing responds of environment without temporal and spatial restriction. Accordingly, the objective of the study is to evaluate impact of earthquake on agriculture in Nepal based on remote sensing. The experimental procedure includes conducting the impact of earthquake on changes of total agricultural area, and analysis of response of greenness affected by earthquake in agricultural land. For conducting agricultural land changes, land use map was first created and classified into four categories: road, city, forest, and agricultural land. Changes before and after earthquake in total area of agricultural land were analyzed by GIS. Moreover, vegetation index was used as indicator for evaluating greenness responds in agricultural land and computed based on high-resolution satellite imagery such as World view-3. Finally, the conclusion of the study and suggestions will be made and provided for helping local government in Nepal restore agricultural areas.

Toward irrigation retrieval by combining multi-sensor remote sensing data into a land surface model over a semi-arid region

NASA Astrophysics Data System (ADS)

Malbéteau, Y.; Lopez, O.; Houborg, R.; McCabe, M.

2017-12-01

Agriculture places considerable pressure on water resources, with the relationship between water availability and food production being critical for sustaining population growth. Monitoring water resources is particularly important in arid and semi-arid regions, where irrigation can represent up to 80% of the consumptive uses of water. In this context, it is necessary to optimize on-farm irrigation management by adjusting irrigation to crop water requirements throughout the growing season. However, in situ point measurements are not routinely available over extended areas and may not be representative at the field scale. Remote sensing approaches present as a cost-effective technique for mapping and monitoring broad areas. By taking advantage of multi-sensor remote sensing methodologies, such as those provided by MODIS, Landsat, Sentinel and Cubesats, we propose a new method to estimate irrigation input at pivot-scale. Here we explore the development of crop-water use estimates via these remote sensing data and integrate them into a land surface modeling framework, using a farm in Saudi Arabia as a demonstration of what can be achieved at larger scales.

Integrated waveguide and nanostructured sensor platform for surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Pearce, Stuart J.; Pollard, Michael E.; Oo, SweZin; Chen, Ruiqi; Kalsi, Sumit; Charlton, Martin D. B.

2014-01-01

Limitations of current sensors include large dimensions, sometimes limited sensitivity and inherent single-parameter measurement capability. Surface-enhanced Raman spectroscopy can be utilized for environment and pharmaceutical applications with the intensity of the Raman scattering enhanced by a factor of 10. By fabricating and characterizing an integrated optical waveguide beneath a nanostructured precious metal coated surface a new surface-enhanced Raman spectroscopy sensing arrangement can be achieved. Nanostructured sensors can provide both multiparameter and high-resolution sensing. Using the slab waveguide core to interrogate the nanostructures at the base allows for the emission to reach discrete sensing areas effectively and should provide ideal parameters for maximum Raman interactions. Thin slab waveguide films of silicon oxynitride were etched and gold coated to create localized nanostructured sensing areas of various pitch, diameter, and shape. These were interrogated using a Ti:Sapphire laser tuned to 785-nm end coupled into the slab waveguide. The nanostructured sensors vertically projected a Raman signal, which was used to actively detect a thin layer of benzyl mercaptan attached to the sensors.

Integrated analysis of remote sensing products from basic geological surveys. [Brazil

NASA Technical Reports Server (NTRS)

Dasilvafagundesfilho, E. (Principal Investigator)

1984-01-01

Recent advances in remote sensing led to the development of several techniques to obtain image information. These techniques as effective tools in geological maping are analyzed. A strategy for optimizing the images in basic geological surveying is presented. It embraces as integrated analysis of spatial, spectral, and temporal data through photoptic (color additive viewer) and computer processing at different scales, allowing large areas survey in a fast, precise, and low cost manner.

Finely Tuned SnO2 Nanoparticles for Efficient Detection of Reducing and Oxidizing Gases: The Influence of Alkali Metal Cation on Gas-Sensing Properties.

PubMed

Lee, Szu-Hsuan; Galstyan, Vardan; Ponzoni, Andrea; Gonzalo-Juan, Isabel; Riedel, Ralf; Dourges, Marie-Anne; Nicolas, Yohann; Toupance, Thierry

2018-03-28

Tin dioxide (SnO 2 ) nanoparticles were straightforwardly synthesized using an easily scaled-up liquid route that involves the hydrothermal treatment, either under acidic or basic conditions, of a commercial tin dioxide particle suspension including potassium counterions. After further thermal post-treatment, the nanomaterials have been thoroughly characterized by Fourier transform infrared and Raman spectroscopy, powder X-ray diffraction, transmission electron microscopy, X-ray photoelectron spectroscopy, and nitrogen sorption porosimetry. Varying pH conditions and temperature of the thermal treatment provided cassiterite SnO 2 nanoparticles with crystallite sizes ranging from 7.3 to 9.7 nm and Brunauer-Emmett-Teller surface areas ranging from 61 to 106 m 2 ·g -1 , acidic conditions favoring potassium cation removal. Upon exposure to a reducing gas (H 2 , CO, and volatile organic compounds such as ethanol and acetone) or oxidizing gas (NO 2 ), layers of these SnO 2 nanoparticles led to highly sensitive, reversible, and reproducible responses. The sensing results were discussed in regard to the crystallite size, specific area, valence band energy, Debye length, and chemical composition. Results highlight the impact of the counterion residuals, which affect the gas-sensing performance to an extent much higher than that of size and surface area effects. Tin dioxide nanoparticles prepared under acidic conditions and calcined in air showed the best sensing performances because of lower amount of potassium cations and higher crystallinity, despite the lower surface area.

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.

A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

NASA Astrophysics Data System (ADS)

Guo, H., II

2016-12-01

Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

Stochastic frequency signature for chemical sensing using noninvasive neuronelectronic interface.

PubMed

Yang, Mo; Zhang, Xuan; Zhang, Yu; Ozkan, Cengiz S

2005-05-01

The detection of chemical agents is important in many areas including environmental pollutants, toxins, biological and chemical pollutants. As "smart" cells, with strong information encoding ability, neurons can be treated as independent sensing elements. A hybrid circuit of a semiconductor chip with dissociated neurons formed both sensors and transducers. Stochastic frequency spectrum was used to differentiate a mixture of chemical agents with effect on the opening of different ion channels. The frequency of spike trains revealed the concentration of the chemical agent, where the characteristic tuning curve revealed the identity. "Fatigue" experiment was performed to explore the "refreshing" ability and "memory" effect of neurons by cyclic and cascaded sensing. "Neuronelectronic noses" such as this should have wide potential applications, most notably in environmental and medical monitoring.

Performance enhanced piezoelectric-based crack detection system for high temperature I-beam SHM

NASA Astrophysics Data System (ADS)

Zhang, Chen; Zhang, Haifeng

2017-04-01

This paper proposes an innovative sensing system for high temperature (up to 150°C) I-beam crack detection. The proposed system is based on the piezoelectric effect and laser sensing mechanisms, which is proved to be effective at high temperature environment (up to 150°C). Different from other high temperature SHM approaches, the proposed sensing system is employing a piezoelectric disk as an actuator and a laser vibrometer as a sensor for remote detection. Lab tests are carried out and the vibrational properties are studied to characterize the relationship between crack depth and sensor responses by analyzing the RMS of sensor responses. Instead of utilizing a pair of piezoelectric actuator and sensor, using the laser vibrometer will enable 1) a more flexible detection, which will not be limited to specific area or dimension, 2) wireless sensing, which lowers the risk of operating at high temperature/harsh environment. The proposed sensing system can be applied to engineering structures such as in nuclear power plant reactor vessel and heat pipe structures/systems.

Levee Health Monitoring With Radar Remote Sensing

NASA Astrophysics Data System (ADS)

Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.

2012-12-01

Remote sensing offers the potential to augment current levee monitoring programs by providing rapid and consistent data collection over large areas irrespective of the ground accessibility of the sites of interest, at repeat intervals that are difficult or costly to maintain with ground-based surveys, and in rapid response to emergency situations. While synthetic aperture radar (SAR) has long been used for subsidence measurements over large areas, applying this technique directly to regional levee monitoring is a new endeavor, mainly because it requires both a wide imaging swath and fine spatial resolution to resolve individual levees within the scene, a combination that has not historically been available. Application of SAR remote sensing directly to levee monitoring has only been attempted in a few pilot studies. Here we describe how SAR remote sensing can be used to assess levee conditions, such as seepage, drawing from the results of two levee studies: one of the Sacramento-San Joaquin Delta levees in California that has been ongoing since July 2009 and a second that covered the levees near Vicksburg, Mississippi, during the spring 2011 floods. These studies have both used data acquired with NASA's UAVSAR L-band synthetic aperture radar, which has the spatial resolution needed for this application (1.7 m single-look), sufficiently wide imaging swath (22 km), and the longer wavelength (L-band, 0.238 m) required to maintain phase coherence between repeat collections over levees, an essential requirement for applying differential interferometry (DInSAR) to a time series of repeated collections for levee deformation measurement. We report the development and demonstration of new techniques that employ SAR polarimetry and differential interferometry to successfully assess levee health through the quantitative measurement of deformation on and near levees and through detection of areas experiencing seepage. The Sacramento-San Joaquin Delta levee study, which covers the entire network of more than 1100 miles of levees in the area, has used several sets of in situ data to validate the results. This type of levee health status information acquired with radar remote sensing could provide a cost-effective method to significantly improve the spatial and temporal coverage of levee systems and identify areas of concern for targeted levee maintenance, repair, and emergency response in the future. Our results show, for example, that during an emergency, when time is of the essence, SAR remote sensing offers the potential of rapidly providing levee status information that is effectively impossible to obtain over large areas using conventional monitoring, e.g., through high precision measurements of subcentimeter-scale levee movement prior to failure. The research described here was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

HCMM hydrological analysis in Utah

NASA Technical Reports Server (NTRS)

Miller, A. W. (Principal Investigator)

1982-01-01

The feasibility of applying a linear model to HCMM data in hopes of obtaining an accurate linear correlation was investigated. The relationship among HCMM sensed data surface temperature and red reflectivity on Utah Lake and water quality factors including algae concentrations, algae type, and nutrient and turbidity concentrations was established and evaluated. Correlation (composite) images of day infrared and reflectance imagery were assessed to determine if remote sensing offers the capability of using masses of accurate and comprehensive data in calculating evaporation. The effects of algae on temperature and evaporation were studied and the possibility of using satellite thermal data to locate areas within Utah Lake where significant thermal sources exist and areas of near surface groundwater was examined.

Earthquake Hazard Analysis Methods: A Review

NASA Astrophysics Data System (ADS)

Sari, A. M.; Fakhrurrozi, A.

2018-02-01

One of natural disasters that have significantly impacted on risks and damage is an earthquake. World countries such as China, Japan, and Indonesia are countries located on the active movement of continental plates with more frequent earthquake occurrence compared to other countries. Several methods of earthquake hazard analysis have been done, for example by analyzing seismic zone and earthquake hazard micro-zonation, by using Neo-Deterministic Seismic Hazard Analysis (N-DSHA) method, and by using Remote Sensing. In its application, it is necessary to review the effectiveness of each technique in advance. Considering the efficiency of time and the accuracy of data, remote sensing is used as a reference to the assess earthquake hazard accurately and quickly as it only takes a limited time required in the right decision-making shortly after the disaster. Exposed areas and possibly vulnerable areas due to earthquake hazards can be easily analyzed using remote sensing. Technological developments in remote sensing such as GeoEye-1 provide added value and excellence in the use of remote sensing as one of the methods in the assessment of earthquake risk and damage. Furthermore, the use of this technique is expected to be considered in designing policies for disaster management in particular and can reduce the risk of natural disasters such as earthquakes in Indonesia.

Effects of land use/cover change and harvests on forest carbon dynamics in northern states of the United States from remote sensing and inventory data: 1992-2001

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2011-01-01

We examined spatial patterns of changes in forest area and nonsoil carbon (C) dynamics affected by land use/cover change (LUC) and harvests in 24 northern states of the United States using an integrated methodology combining remote sensing and ground inventory data between 1992 and 2001. We used the Retrofit Change Product from the Multi-Resolution Land Characteristics...

Fiber Optic-Based Refractive Index Sensing at INESC Porto

PubMed Central

Jorge, Pedro A. S.; Silva, Susana O.; Gouveia, Carlos; Tafulo, Paula; Coelho, Luis; Caldas, Paulo; Viegas, Diana; Rego, Gaspar; Baptista, José M.; Santos, José L.; Frazão, Orlando

2012-01-01

A review of refractive index measurement based on different types of optical fiber sensor configurations and techniques is presented. It addresses the main developments in the area, with particular focus on results obtained at INESC Porto, Portugal. The optical fiber sensing structures studied include those based on Bragg and long period gratings, on micro-interferometers, on plasmonic effects in fibers and on multimode interference in a large spectrum of standard and microstructured optical fibers. PMID:22969405

Enhanced acoustic sensing through wave compression and pressure amplification in anisotropic metamaterials.

PubMed

Chen, Yongyao; Liu, Haijun; Reilly, Michael; Bae, Hyungdae; Yu, Miao

2014-10-15

Acoustic sensors play an important role in many areas, such as homeland security, navigation, communication, health care and industry. However, the fundamental pressure detection limit hinders the performance of current acoustic sensing technologies. Here, through analytical, numerical and experimental studies, we show that anisotropic acoustic metamaterials can be designed to have strong wave compression effect that renders direct amplification of pressure fields in metamaterials. This enables a sensing mechanism that can help overcome the detection limit of conventional acoustic sensing systems. We further demonstrate a metamaterial-enhanced acoustic sensing system that achieves more than 20 dB signal-to-noise enhancement (over an order of magnitude enhancement in detection limit). With this system, weak acoustic pulse signals overwhelmed by the noise are successfully recovered. This work opens up new vistas for the development of metamaterial-based acoustic sensors with improved performance and functionalities that are highly desirable for many applications.

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...

Hyperspectral sensing of forests

NASA Astrophysics Data System (ADS)

Goodenough, David G.; Dyk, Andrew; Chen, Hao; Hobart, Geordie; Niemann, K. Olaf; Richardson, Ash

2007-11-01

Canada contains 10% of the world's forests covering an area of 418 million hectares. The sustainable management of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of new and improved information products to resource managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory, forest health, foliar biochemistry, biomass, and aboveground carbon than are currently available. This paper surveys recent methods and results in hyperspectral sensing of forests and describes space initiatives for hyperspectral sensing.

a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification

NASA Astrophysics Data System (ADS)

Zhang, C.; Pan, X.; Zhang, S. Q.; Li, H. P.; Atkinson, P. M.

2017-09-01

Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

Detecting the red tide based on remote sensing data in optically complex East China Sea

NASA Astrophysics Data System (ADS)

Xu, Xiaohui; Pan, Delu; Mao, Zhihua; Tao, Bangyi; Liu, Qiong

2012-09-01

Red tide not only destroys marine fishery production, deteriorates the marine environment, affects coastal tourist industry, but also causes human poison, even death by eating toxic seafood contaminated by red tide organisms. Remote sensing technology has the characteristics of large-scale, synchronized, rapid monitoring, so it is one of the most important and most effective means of red tide monitoring. This paper selects the high frequency red tides areas of the East China Sea as study area, MODIS/Aqua L2 data as the data source, analysis and compares the spectral differences in the red tide water bodies and non-red tide water bodies of many historical events. Based on the spectral differences, this paper develops the algorithm of Rrs555/Rrs488> 1.5 to extract the red tide information. Apply the algorithm on red tide event happened in the East China Sea on May 28, 2009 to extract the information of red tide, and found that the method can determine effectively the location of the occurrence of red tide; there is a good corresponding relationship between red tide extraction result and chlorophyll a concentration extracted by remote sensing, shows that these algorithm can determine effectively the location and extract the red tide information.

Developing a Satellite Based Automatic System for Crop Monitoring: Kenya's Great Rift Valley, A Case Study

NASA Astrophysics Data System (ADS)

Lucciani, Roberto; Laneve, Giovanni; Jahjah, Munzer; Mito, Collins

2016-08-01

The crop growth stage represents essential information for agricultural areas management. In this study we investigate the feasibility of a tool based on remotely sensed satellite (Landsat 8) imagery, capable of automatically classify crop fields and how much resolution enhancement based on pan-sharpening techniques and phenological information extraction, useful to create decision rules that allow to identify semantic class to assign to an object, can effectively support the classification process. Moreover we investigate the opportunity to extract vegetation health status information from remotely sensed assessment of the equivalent water thickness (EWT). Our case study is the Kenya's Great Rift valley, in this area a ground truth campaign was conducted during August 2015 in order to collect crop fields GPS measurements, leaf area index (LAI) and chlorophyll samples.

Paper as a platform for sensing applications and other devices: a review.

PubMed

Mahadeva, Suresha K; Walus, Konrad; Stoeber, Boris

2015-04-29

Paper is a ubiquitous material that has various applications in day to day life. A sheet of paper is produced by pressing moist wood cellulose fibers together. Paper offers unique properties: paper allows passive liquid transport, it is compatible with many chemical and biochemical moieties, it exhibits piezoelectricity, and it is biodegradable. Hence, paper is an attractive low-cost functional material for sensing devices. In recent years, researchers in the field of science and engineering have witnessed an exponential growth in the number of research contributions that focus on the development of cost-effective and scalable fabrication methods and new applications of paper-based devices. In this review article, we highlight recent advances in the development of paper-based sensing devices in the areas of electronics, energy storage, strain sensing, microfluidic devices, and biosensing, including piezoelectric paper. Additionally, this review includes current limitations of paper-based sensing devices and points out issues that have limited the commercialization of some of the paper-based sensing devices.

Improving Aquatic Plant Management in the California Sacramento-San Joaquin Delta

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Potter, Chris

2018-01-01

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass), direct operations, and assess management impacts on plant communities. Archived satellite records going are used to review results from previous climate and management events and aide in developing long-term strategies. Modeling at local and watershed scales provides insight into land-use effects on water quality. Plant growth models informed by remote sensing are being applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments, phenology, environmental regulations, and economics in selection of management practices. Initial utilization of remote sensing tools developed for mapping of aquatic invasive weeds improved operational efficiency by focusing limited chemical use to strategic areas with high plant-control impact and incorporating mechanical harvesting when chemical use is restricted. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta, both spatial and temporal, informed by ecological understanding with the objective of improving management and assessment effectiveness.

Road Extraction from AVIRIS Using Spectral Mixture and Q-Tree Filter Techniques

NASA Technical Reports Server (NTRS)

Gardner, Margaret E.; Roberts, Dar A.; Funk, Chris; Noronha, Val

2001-01-01

Accurate road location and condition information are of primary importance in road infrastructure management. Additionally, spatially accurate and up-to-date road networks are essential in ambulance and rescue dispatch in emergency situations. However, accurate road infrastructure databases do not exist for vast areas, particularly in areas with rapid expansion. Currently, the US Department of Transportation (USDOT) extends great effort in field Global Positioning System (GPS) mapping and condition assessment to meet these informational needs. This methodology, though effective, is both time-consuming and costly, because every road within a DOT's jurisdiction must be field-visited to obtain accurate information. Therefore, the USDOT is interested in identifying new technologies that could help meet road infrastructure informational needs more effectively. Remote sensing provides one means by which large areas may be mapped with a high standard of accuracy and is a technology with great potential in infrastructure mapping. The goal of our research is to develop accurate road extraction techniques using high spatial resolution, fine spectral resolution imagery. Additionally, our research will explore the use of hyperspectral data in assessing road quality. Finally, this research aims to define the spatial and spectral requirements for remote sensing data to be used successfully for road feature extraction and road quality mapping. Our findings will facilitate the USDOT in assessing remote sensing as a new resource in infrastructure studies.

Strategies for using remotely sensed data in hydrologic models

NASA Technical Reports Server (NTRS)

Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

1981-01-01

Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

Portable Apparatus for Electrochemical Sensing of Ethylene

NASA Technical Reports Server (NTRS)

Manoukian, Mourad; Tempelman, Linda A.; Forchione, John; Krebs, W. Michael; Schmitt, Edwin W.

2007-01-01

A small, lightweight, portable apparatus based on an electrochemical sensing principle has been developed for monitoring low concentrations of ethylene in air. Ethylene has long been known to be produced by plants and to stimulate the growth and other aspects of the development of plants (including, notably, ripening of fruits and vegetables), even at concentrations as low as tens of parts per billion (ppb). The effects are magnified in plant-growth and -storage chambers wherein ethylene can accumulate. There is increasing recognition in agriculture and related industries that it is desirable to monitor and control ethylene concentrations in order to optimize the growth, storage, and ripening of plant products. Hence, there are numerous potential uses for the present apparatus in conjunction with equipment for controlling ethylene concentrations. The ethylene sensor is of a thick-film type with a design optimized for a low detection limit. The sensor includes a noble metal sensing electrode on a chip and a hydrated solid-electrolyte membrane that is held in contact with the chip. Also located on the sensor chip are a counter electrode and a reference electrode. The sensing electrode is held at a fixed potential versus the reference electrode. Detection takes place at active-triple-point areas where the sensing electrode, electrolyte, and sample gas meet. These areas are formed by cutting openings in the electrolyte membrane. The electrode current generated from electrochemical oxidation of ethylene at the active triple points is proportional to the concentration of ethylene. An additional film of the solid-electrolyte membrane material is deposited on the sensing electrode to increase the effective triple-point areas and thereby enhance the detection signal. The sensor chip is placed in a holder that is part of a polycarbonate housing. When fully assembled, the housing holds the solid-electrolyte membrane in contact with the chip (see figure). The housing includes a water reservoir for keeping the solid-electrolyte membrane hydrated. The housing also includes flow channels for circulating a sample stream of air over the chip: ethylene is brought to the sensing surface predominately by convection in this sample stream. The sample stream is generated by a built-in sampling pump. The forced circulation of sample air contributes to the attainment of a low detection limit.

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

NASA Astrophysics Data System (ADS)

Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

A patch-based convolutional neural network for remote sensing image classification.

PubMed

Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

2017-11-01

Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Remote sensing techniques in monitoring areas affected by forest fire

NASA Astrophysics Data System (ADS)

Karagianni, Aikaterini Ch.; Lazaridou, Maria A.

2017-09-01

Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.

Using High Resolution Remotely Sensed Data to Predict Territory Occupancy and Mircrorefugia for a Habitat Specialist, the American Pika (Ochotona princeps)

NASA Astrophysics Data System (ADS)

Beers, A.; Ray, C.

2015-12-01

Climate change is likely to affect mountainous areas unevenly due to the complex interactions between topography, vegetation, and the accumulation of snow and ice. This heterogeneity will complicate relationships between species presence and large-scale drivers such as precipitation and make predicting habitat extent and connectivity much more difficult. We studied the potential for fine-scale variation in climate and habitat use throughout the year in the American pika (Ochotona princeps), a talus specialist of mountainous western North America known for strong microhabitat affiliation. Not all areas of talus are likely to be equally hospitable, which may reduce connectivity more than predicted by large-scale occupancy drivers. We used high resolution remotely sensed data to create metrics of the terrain and land cover in the Niwot Ridge (NWT) LTER site in Colorado. We hypothesized that pikas preferentially use heterogeneous terrain, as it might foster greater snow accumulation, and used radio telemetry to test this with radio-collared pikas. Pikas use heterogeneous terrain during snow covered periods and less heterogeneous area during the summer. This suggests that not all areas of talus habitat are equally suitable as shelter from extreme conditions but that pikas need more than just shelter from winter cold. With those results we created a predictive map using the same habitat metrics to model the extent of suitable habitat across the NWT area. These strong effects of terrain on pika habitat use and territory occupancy show the great utility that high resolution remotely sensed data can have in ecological applications. With increasing effects of climate change in mountainous regions, this modeling approach is crucial for quantifying habitat connectivity at both small and large scales and to identify potential refugia for threatened or isolated species.

Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China

NASA Astrophysics Data System (ADS)

Wu, Hao; Ye, Lu-Ping; Shi, Wen-Zhong; Clarke, Keith C.

2014-10-01

Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.

Exploring and Describing the Spatial & Temporal Dynamics of Medushead in the Channeled Scablands of Eastern Washington Using Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Bateman, Timothy M.

Medusahead is a harmful weed that is invading public lands in the West. The invasion is a serious concern to the public because it can reduce forage for livestock and wildlife, increase fire frequency, alter important ecosystem cycles (like water), reduce recreational activities, and produce landscapes that are aesthetically unpleasing. Invasions can drive up costs that generally require taxpayer's dollars. Medusahead seedlings typically spread to new areas by attaching itself to passing objects (e.g. vehicles, animals, clothing) where it can quickly begin to affect plants communities. To be effective, management plans need to be sustainable, informed, and considerate to invasion levels across large landscapes. Ecological remote sensing analysis is a method that uses airborne imagery, taken from drones, aircrafts, or satellites, to gather information about ecological systems. This Thesis strived to use remote sensing techniques to identify medusahead in the landscape and its changes through time. This was done for an extensive area of rangelands in the Channel Scabland region of eastern ashington. This Thesis provided results that would benefit land managers that include: 1) a dispersal map of medusahead, 2) a time line of medusahead cover through time, 3) 'high risk' dispersal areas, 4) climatic factors showing an influence on the time line of medusahead, 5) a strategy map that can be utilized by land managers to direct management needs. This Thesis shows how remote sensing applications can be used to detect medusahead in the landscape and understand its invasiveness through time. This information can help create sustainable and effective management plans so land managers can continue to protect and improve western public lands threatened by the invasion of medusahead.

Revealing livestock effects on bunchgrass vegetation with Landsat ETM+ data across a grazing season

NASA Astrophysics Data System (ADS)

Jansen, Vincent S.

Remote sensing provides monitoring solutions for more informed grazing management. To investigate the ability to detect the effects of cattle grazing on bunchgrass vegetation with Landsat Enhanced Thematic Mapper Plus (ETM+) data, we conducted a study on the Zumwalt Prairie in northeastern Oregon across a gradient of grazing intensities. Biophysical vegetation data was collected on vertical structure, biomass, and cover at three different time periods during the grazing season: June, August, and October 2012. To relate these measures to the remotely sensed Landsat ETM+ data, Pearson's correlations and multiple regression models were computed. Using the best models, predicted vegetation metrics were then mapped across the study area. Results indicated that models using common vegetation indices had the ability to discern different levels of grazing across the study area. Results can be distributed to land managers to help guide grassland conservation by improving monitoring of bunchgrass vegetation for sustainable livestock management.

Natural and environmental vulnerability analysis through remote sensing and GIS techniques: a case study of Indigirka River basin, Eastern Siberia, Russia

NASA Astrophysics Data System (ADS)

Boori, Mukesh S.; Choudhary, Komal; Kupriyanov, Alexander; Sugimoto, Atsuko; Evers, Mariele

2016-10-01

The aim of this research work is to understand natural and environmental vulnerability situation and its cause such as intensity, distribution and socio-economic effect in the Indigirka River basin, Eastern Siberia, Russia. This paper identifies, assess and classify natural and environmental vulnerability using landscape pattern from multidisciplinary approach, based on remote sensing and Geographical Information System (GIS) techniques. A model was developed by following thematic layers: land use/cover, vegetation, wetland, geology, geomorphology and soil in ArcGIS 10.2 software. According to numerical results vulnerability classified into five levels: low, sensible, moderate, high and extreme vulnerability by mean of cluster principal. Results are shows that in natural vulnerability maximum area covered by moderate (29.84%) and sensible (38.61%) vulnerability and environmental vulnerability concentrated by moderate (49.30%) vulnerability. So study area has at medial level vulnerability. The results found that the methodology applied was effective enough in the understanding of the current conservation circumstances of the river basin in relation to their environment with the help of remote sensing and GIS. This study is helpful for decision making for eco-environmental recovering and rebuilding as well as predicting the future development.

Polycrystalline silicon ion sensitive field effect transistors

NASA Astrophysics Data System (ADS)

Yan, F.; Estrela, P.; Mo, Y.; Migliorato, P.; Maeda, H.; Inoue, S.; Shimoda, T.

2005-01-01

We report the operation of polycrystalline silicon ion sensitive field effect transistors. These devices can be fabricated on inexpensive disposable substrates such as glass or plastics and are, therefore, promising candidates for low cost single-use intelligent multisensors. In this work we have developed an extended gate structure with a Si3N4 sensing layer. Nearly ideal pH sensitivity (54mV /pH) and stable operation have been achieved. Temperature effects have been characterized. A penicillin sensor has been fabricated by functionalizing the sensing area with penicillinase. The sensitivity to penicillin G is about 10mV/mM, in solutions with concentration lower than the saturation value, which is about 7 mM.

Air pollution impacts of speed limitation measures in large cities: The need for improving traffic data in a metropolitan area

NASA Astrophysics Data System (ADS)

Baldasano, José M.; Gonçalves, María; Soret, Albert; Jiménez-Guerrero, Pedro

2010-08-01

Assessing the effects of air quality management strategies in urban areas is a major concern worldwide because of the large impacts on health caused by the exposure to air pollution. In this sense, this work analyses the changes in urban air quality due to the introduction of a maximum speed limit to 80 km h -1 on motorways in a large city by using a novel methodology combining traffic assimilation data and modelling systems implemented in a supercomputing facility. Albeit the methodology has been non-specifically developed and can be extrapolated to any large city or megacity, the case study of Barcelona is presented here. Hourly simulations take into account the entire year 2008 (when the 80 km h -1 limit has been introduced) vs. the traffic conditions for the year 2007. The data has been assimilated in an emission model, which considers hourly variable speeds and hourly traffic intensity in the affected area, taken from long-term measurement campaigns for the aforementioned years; it also permits to take into account the traffic congestion effect. Overall, the emissions are reduced up to 4%; however the local effects of this reduction achieve an important impact for the adjacent area to the roadways, reaching 11%. In this sense, the speed limitation effects assessed represent enhancements in air quality levels (5-7%) of primary pollutants over the area, directly improving the welfare of 1.35 million inhabitants (over 41% of the population of the Metropolitan Area) and affecting 3.29 million dwellers who are potentially benefited from this strategy for air quality management (reducing 0.6% the mortality rates in the area).

Color difference threshold of chromostereopsis induced by flat display emission.

PubMed

Ozolinsh, Maris; Muizniece, Kristine

2015-01-01

The study of chromostereopsis has gained attention in the backdrop of the use of computer displays in daily life. In this context, we analyze the illusory depth sense using planar color images presented on a computer screen. We determine the color difference threshold required to induce an illusory sense of depth psychometrically using a constant stimuli paradigm. Isoluminant stimuli are presented on a computer screen, which stimuli are aligned along the blue-red line in the computer display CIE xyY color space. Stereo disparity is generated by increasing the color difference between the central and surrounding areas of the stimuli with both areas consisting of random dots on a black background. The observed altering of illusory depth sense, thus also stereo disparity is validated using the "center-of-gravity" model. The induced illusory sense of the depth effect undergoes color reversal upon varying the binocular lateral eye pupil covering conditions (lateral or medial). Analysis of the retinal image point spread function for the display red and blue pixel radiation validates the altering of chromostereopsis retinal disparity achieved by increasing the color difference, and also the chromostereopsis color reversal caused by varying the eye pupil covering conditions.

A framework for nowcasting and forecasting of rainfall-triggered landslide activity using remotely sensed data

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas

2016-04-01

Remote sensing data offers the unique perspective to provide situational awareness of hydrometeorological hazards over large areas in a way that is impossible to achieve with in situ data. Recent work has shown that rainfall-triggered landslides, while typically local hazards that occupy small spatial areas, can be approximated over regional or global scales in near real-time. This work presents a regional and global approach to approximating potential landslide activity using the landslide hazard assessment for situational awareness (LHASA) model. This system couples remote sensing data, including Global Precipitation Measurement rainfall data, Shuttle Radar Topography Mission and other surface variables to estimate where and when landslide activity may be likely. This system also evaluates the effectiveness of quantitative precipitation estimates from the Goddard Earth Observing System Model, Version 5 to provide a 24 forecast of potential landslide activity. Preliminary results of the LHASA model and implications for are presented for a regional version of this system in Central America as well as a prototype global approach.

Application of phase-diverse phase retrieval to wavefront sensing in non-connected complicated pupil optics

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2007-07-01

Baseline algorithm, as a tool in wavefront sensing (WFS), incorporates the phase-diverse phase retrieval (PDPR) method with hybrid-unwrapping approach to ensure a unique pupil phase estimate with high WFS accuracy even in the case of high dynamic range aberration, as long as the pupil shape is of a convex set. However, for a complicated pupil, such as that in obstructed pupil optics, the said unwrapping approach would fail owing to the fake values at points located in obstructed areas of the pupil. Thus a modified unwrapping approach that can minimize the negative effects of the obstructed areas is proposed. Simulations have shown the validity of this unwrapping approach when it is embedded in Baseline algorithm.

[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.

Assessments of urban growth in the Tampa Bay watershed using remote sensing data

USGS Publications Warehouse

Xian, G.; Crane, M.

2005-01-01

Urban development has expanded rapidly in the Tampa Bay area of west-central Florida over the past century. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. This research utilizes an innovative approach for mapping urban extent and its changes through determining impervious surfaces from Landsat satellite remote sensing data. By 2002, areas with subpixel impervious surface greater than 10% accounted for approximately 1800 km2, or 27 percent of the total watershed area. The impervious surface area increases approximately three-fold from 1991 to 2002. The resulting imperviousness data are used with a defined suite of geospatial data sets to simulate historical urban development and predict future urban and suburban extent, density, and growth patterns using SLEUTH model. Also examined is the increasingly important influence that urbanization and its associated imperviousness extent have on the individual drainage basins of the Tampa Bay watershed.

Remote sensing monitoring study of ecological environment change in Qingtu Lake

NASA Astrophysics Data System (ADS)

Han, Tao; Wang, Dawei; Jiang, Youyan; Qian, Li; Chen, Lei; Hao, Xiaocui

2018-03-01

Based on the Environmental Mitigation Satellite (HJ-1) data, this paper has carried on the remote sensing monitoring to change of the surrounding vegetation and water area of the Qingtu Lake since 2009. The result shows that the average area of water has increased by 3.59 square kilometres annually since the reappearance of the waters with the Qingtu Lake in 2010. The area of Qingtu Lake and surrounding vegetation cover has presented an average increase of 1.09 square kilometres per year. Since 2010, the precipitation of the Qingtu Lake and its surrounding area in Minqin county have a significant increase in the trend, the average increase rate of 6.0 mm/year. Compared to 2010 years ago, the average precipitation increased 36.4 mm. And it shows that the change of the Qingtu Lake underlying surface has a positive feedback effect to local heavy rainfall according to the comparative analysis of the precipitation observation in the surrounding weather station.

The application of remote sensing image sea ice monitoring method in Bohai Bay based on C4.5 decision tree algorithm

NASA Astrophysics Data System (ADS)

Ye, Wei; Song, Wei

2018-02-01

In The Paper, the remote sensing monitoring of sea ice problem was turned into a classification problem in data mining. Based on the statistic of the related band data of HJ1B remote sensing images, the main bands of HJ1B images related with the reflectance of seawater and sea ice were found. On the basis, the decision tree rules for sea ice monitoring were constructed by the related bands found above, and then the rules were applied to Liaodong Bay area seriously covered by sea ice for sea ice monitoring. The result proved that the method is effective.

California's transition from conventional snowpack measurements to a developing remote sensing capability for water supply forecasting

NASA Technical Reports Server (NTRS)

Brown, A. J.; Peterson, N.

1980-01-01

California's Snow Survey Program and water supply forecasting procedures are described. A review is made of current activities and program direction on such matters as: the growing statewide network of automatic snow sensors; restrictions on the gathering hydrometeorological data in areas designated as wilderness; the use of satellite communications, which both provides a flexible network without mountaintop repeaters and satisfies the need for unobtrusiveness in wilderness areas; and the increasing operational use of snow covered area (SCA) obtained from satellite imagery, which, combined with water equivalent from snow sensors, provides a high correlation to the volumes and rates of snowmelt runoff. Also examined are the advantages of remote sensing; the anticipated effects of a new input of basin wide index of water equivalent, such as the obtained through microwave techniques, on future forecasting opportunities; and the future direction and goals of the California Snow Surveys Program.

Mobile Sensing Systems

PubMed Central

Macias, Elsa; Suarez, Alvaro; Lloret, Jaime

2013-01-01

Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high. PMID:24351637

Mobile sensing systems.

PubMed

Macias, Elsa; Suarez, Alvaro; Lloret, Jaime

2013-12-16

Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high.

Basic Investigations for Remote Sensing of Coastal Areas.

DTIC Science & Technology

for the delineation and analysis of bottom features in coastal areas. The focus is on the development of remote sensing techniques for delineating and classifying bottom features in the nearshore zone.

The Human Operator in Advanced Aerospace Systems

DTIC Science & Technology

1981-12-15

a very effective 6.1 program. The neuropsychological area is another area currently showing considerable promise. Research in this area should not...Things are not well in the world today in the most diLect and simple sense of the word. Hunger and death threaten the majority of men. That is why the...people from hunger and disease cannot contradict the source of active good, that which is most humane in man. I believe that mankind will find a rational

Predicting Post-Fire Severity Effects in Coast Redwood Forests Using FARSITE

Treesearch

Hugh Scanlon; Yana Valachovic

2006-01-01

Assessing post-fire impacts in coast redwood (Sequoia sempervirens) forests can be difficult due to rough terrain, limited roads, and dense canopies. Remote sensing techniques can identify overstory damage, locating high intensity damage areas, although this can underestimate the effects on the understory vegetation and soils. To accurately assess...

Hydrogen gas sensing feature of polyaniline/titania (rutile) nanocomposite at environmental conditions

NASA Astrophysics Data System (ADS)

Milani Moghaddam, Hossain; Nasirian, Shahruz

2014-10-01

The resistance-based sensors of polyaniline/titania (rutile) nanocomposite (TPNC) were prepared by spin coating technique onto an epoxy glass substrate with Cu-interdigited electrodes to study their hydrogen (H2) gas sensing features. Our findings are that the change of the surface morphology, porosity and wt% of titania in TPNCs have a significant effect on H2 gas sensing of sensors. All of the sensors had a reproducibility response toward 0.8 vol% H2 gas at room temperature, air pressure and 50% relative humidity. A sensor with 40 wt% of titania nanoparticles had better response/recovery time and the response than other sensors. Moreover, H2 gas sensing mechanism of TPNC sensors based contact areas and the correlation of energy levels between PANI chains and the titania grains were studied.

Monitoring spatial variations in soil organic carbon using remote sensing and geographic information systems

NASA Astrophysics Data System (ADS)

Jaber, Salahuddin M.

Soil organic carbon (SOC) sequestration is a component of larger strategies to control the accumulation of greenhouse gases that may be causing global warming. To implement this approach, it is necessary to improve the methods of measuring SOC content. Among these methods are indirect remote sensing and geographic information systems (GIS) techniques that are required to provide non-intrusive, low cost, and spatially continuous information that cover large areas on a repetitive basis. The main goal of this study is to evaluate the effects of using Hyperion hyperspectral data on improving the existing remote sensing and GIS-based methodologies for rapidly, efficiently, and accurately measuring SOC content on farmland. The study area is Big Creek Watershed (BCW) in Southern Illinois. The methodology consists of compiling a GIS database (consisting of remote sensing and soil variables) for 303 composite soil samples collected from representative pixels along the Hyperion coverage area of the watershed. Stepwise procedures were used to calibrate and validate linear multiple regression models where SOC was regarded as the response and the other remote sensing and soil variables as the predictors. Two models were selected. The first was the best all variables model and the second was the best only raster variables model. Map algebra was implemented to extrapolate the best only raster variables model and produce a SOC map for the BGW. This study concluded that Hyperion data marginally improved the predictability of the existing SOC statistical models based on multispectral satellite remote sensing sensors with correlation coefficient of 0.37 and root mean square error of 3.19 metric tons/hectare to a 15-cm depth. The total SOC pool of the study area is about 225,232 metric tons to 15-cm depth. The nonforested wetlands contained the highest SOC density (34.3 metric tons/hectare/15cm) with total SOC content of about 2,003.5 metric tons to 15-cm depth, where croplands had the lowest SOC density (21.6 metric tons/hectare/15cm) with total SOC content of about 44,571.2 metric tons to 15-cm depth.

Remote sensing of geobotanical relations in Georgia

NASA Technical Reports Server (NTRS)

Arden, D. D., Jr.; Westra, R. N.

1977-01-01

The application of remote sensing to geological investigations, with special attention to geobotanical factors, was evaluated. The general areas of investigation included: (1) recognition of mineral deposits; (2) geological mapping; (3) delineation of geological structure, including areas of complex tectonics; and (4) limestone areas where ground withdrawal had intensified surface collapse.

Construction of a remotely sensed area sampling frame for Southern Brazil

NASA Technical Reports Server (NTRS)

Fecso, R.; Gardner, W.; Hale, B.; Johnson, V.; Pavlasek, S. (Principal Investigator)

1982-01-01

A remotely sensed area sampling frame was constructed for selected areas in Southern Brazil. The sampling unit information was stored in digital form in a latitudinal/longitudinal characterized population. Computerized sampling procedures were developed which allow for flexibility in sample unit specifications and sampling designs.

Sensing sheets based on large area electronics for fatigue crack detection

NASA Astrophysics Data System (ADS)

Yao, Yao; Glisic, Branko

2015-03-01

Reliable early-stage damage detection requires continuous structural health monitoring (SHM) over large areas of structure, and with high spatial resolution of sensors. This paper presents the development stage of prototype strain sensing sheets based on Large Area Electronics (LAE), in which thin-film strain gauges and control circuits are integrated on the flexible electronics and deposited on a polyimide sheet that can cover large areas. These sensing sheets were applied for fatigue crack detection on small-scale steel plates. Two types of sensing-sheet interconnects were designed and manufactured, and dense arrays of strain gauge sensors were assembled onto the interconnects. In total, four (two for each design type) strain sensing sheets were created and tested, which were sensitive to strain at virtually every point over the whole sensing sheet area. The sensing sheets were bonded to small-scale steel plates, which had a notch on the boundary so that fatigue cracks could be generated under cyclic loading. The fatigue tests were carried out at the Carleton Laboratory of Columbia University, and the steel plates were attached through a fixture to the loading machine that applied cyclic fatigue load. Fatigue cracks then occurred and propagated across the steel plates, leading to the failure of these test samples. The strain sensor that was close to the notch successfully detected the initialization of fatigue crack and localized the damage on the plate. The strain sensor that was away from the crack successfully detected the propagation of fatigue crack based on the time history of measured strain. Overall, the results of the fatigue tests validated general principles of the strain sensing sheets for crack detection.

Effect of Annealing Temperature on Bi3.25La0.75Ti3O12 Powders for Humidity Sensing Properties

NASA Astrophysics Data System (ADS)

Zhang, Yong; He, Jinping; Yuan, Mengjiao; Jiang, Bin; Li, Peiwen; Tong, Yexing; Zheng, Xuejun

2017-01-01

Bi3.25La0.75Ti3O12 (BLT) powders have been synthesized via the metal-organic decomposition method with annealing of the BLT precursor solution at 350°C, 450°C, 550°C, 650°C or 750°C. The crystalline structure and morphology of the BLT powders were characterized by x-ray diffraction analysis, field-emission scanning electron microscopy, energy-dispersive x-ray spectroscopy, and specific surface and pore size analyses. The humidity sensing properties of the BLT powders annealed at the five temperatures were investigated to determine the effect of annealing temperature. The annealing temperature strongly influenced the grain size, pore size distribution, and specific surface area of the BLT powders, being largely correlated to their humidity sensing properties. The specific surface area of the BLT powder annealed at 550°C was 68.2 m2/g, much larger than for the other annealing temperatures, and the majority of the pores in the BLT powder annealed at 550°C were mesoporous, significantly increasing the adsorption efficiency of water vapor onto the surface of the material. The impedance of the BLT powder annealed at 550°C varied by more than five orders of magnitude over the whole humidity range at working frequency of 100 Hz, being approximately five times greater than for BLT powders annealed at other temperatures. The response time was about 8 s, with maximum hysteresis of around 3% relative humidity. The BLT powder annealed at 550°C exhibited the best humidity sensing properties compared with the other annealing temperatures. We expect that these results will offer useful guidelines for preparation of humidity sensing materials.

Detection of Steel Fatigue Cracks with Strain Sensing Sheets Based on Large Area Electronics

PubMed Central

Yao, Yao; Glisic, Branko

2015-01-01

Reliable early-stage damage detection requires continuous monitoring over large areas of structure, and with sensors of high spatial resolution. Technologies based on Large Area Electronics (LAE) can enable direct sensing and can be scaled to the level required for Structural Health Monitoring (SHM) of civil structures and infrastructure. Sensing sheets based on LAE contain dense arrangements of thin-film strain sensors, associated electronics and various control circuits deposited and integrated on a flexible polyimide substrate that can cover large areas of structures. This paper presents the development stage of a prototype strain sensing sheet based on LAE for crack detection and localization. Two types of sensing-sheet arrangements with size 6 × 6 inch (152 × 152 mm) were designed and manufactured, one with a very dense arrangement of sensors and the other with a less dense arrangement of sensors. The sensing sheets were bonded to steel plates, which had a notch on the boundary, so the fatigue cracks could be generated under cyclic loading. The sensors within the sensing sheet that were close to the notch tip successfully detected the initialization of fatigue crack and localized the damage on the plate. The sensors that were away from the crack successfully detected the propagation of fatigue cracks based on the time history of the measured strain. The results of the tests have validated the general principles of the proposed sensing sheets for crack detection and identified advantages and challenges of the two tested designs. PMID:25853407

Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.

2014-12-01

Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to improve the hydrological model through higher resolution products and parameterization of variables that have previously been largely unknown.

Extraction of Rice Heavy Metal Stress Signal Features Based on Long Time Series Leaf Area Index Data Using Ensemble Empirical Mode Decomposition

PubMed Central

Liu, Xiangnan; Zhang, Biyao; Liu, Ming; Wu, Ling

2017-01-01

The use of remote sensing technology to diagnose heavy metal stress in crops is of great significance for environmental protection and food security. However, in the natural farmland ecosystem, various stressors could have a similar influence on crop growth, therefore making heavy metal stress difficult to identify accurately, so this is still not a well resolved scientific problem and a hot topic in the field of agricultural remote sensing. This study proposes a method that uses Ensemble Empirical Mode Decomposition (EEMD) to obtain the heavy metal stress signal features on a long time scale. The method operates based on the Leaf Area Index (LAI) simulated by the Enhanced World Food Studies (WOFOST) model, assimilated with remotely sensed data. The following results were obtained: (i) the use of EEMD was effective in the extraction of heavy metal stress signals by eliminating the intra-annual and annual components; (ii) LAIdf (The first derivative of the sum of the interannual component and residual) can preferably reflect the stable feature responses to rice heavy metal stress. LAIdf showed stability with an R2 of greater than 0.9 in three growing stages, and the stability is optimal in June. This study combines the spectral characteristics of the stress effect with the time characteristics, and confirms the potential of long-term remotely sensed data for improving the accuracy of crop heavy metal stress identification. PMID:28878147

The detection and mapping of oil on a marshy area by a remote luminescent sensor

USGS Publications Warehouse

McFarlane, C.; Watson, R.D.

2005-01-01

Airborne remote sensing can be a cost-effective method for monitoring pollutants in large areas such as occur in oil spills. An opportunity to test a particular method arose when a well ruptured and for 23 days spewed a 90-meter fountain of oil into the air, dispersing the oil over a wide area. The method tested was an airborne luminescence detector with a Fraunhofer Line Discriminator (FLD) which was flown over the affected area 41 days after the well was capped to obtain a map or the deposition pattern. To calibrate the system, samples of Spartina (wire grass) and Phragmites (common reed) were collected from the contaminated area and the oil residues were eluted in cyclohexane and quantitatively analyzed in a fluorescence photometer. Good correlation was observed between the remote sensor (FLD) and the laboratory analysis. Isopleths defining the deposition pattern of oil were drawn from the remote sensing information. A discussion will be presented on the feasibility of using this instrument for similar contamination incidents for cleanup and damage assessment.

Mapping ground cover using hyperspectral remote sensing after the 2003 Simi and Old wildfires in southern California

Treesearch

Sarah A. Lewis; Leigh B. Lentile; Andrew T. Hudak; Peter R. Robichaud; Penelope Morgan; Michael J. Bobbitt

2007-01-01

Wildfire effects on the ground surface are indicative of the potential for post-fire watershed erosion response. Areas with remaining organic ground cover will likely experience less erosion than areas of complete ground cover combustion or exposed mineral soil. The Simi and Old fires burned ~67,000 ha in southern California in 2003. Burn severity indices calculated...

Assessing Green Infrastructure Performance Using Remote Hydologic Monitoring Measures

EPA Science Inventory

Two locations in Cincinnati were instrumented with level sensing technologies to measure stormwater flow in porous pavement and bioretention areas. Results indicate good performance of porous pavement and a cost effective application of technology to measure those flows. Result...

Integrated single-walled carbon nanotube/microfluidic devices for the study of the sensing mechanism of nanotube sensors.

PubMed

Fu, Qiang; Liu, Jie

2005-07-21

A method to fabricate integrated single-walled carbon nanotube/microfluidic devices was developed. This simple process could be used to directly prepare nanotube thin film transistors within the microfluidic channel and to register SWNT devices with the microfludic channel without the need of an additional alignment step. The microfluidic device was designed to have several inlets that deliver multiple liquid flows to a single main channel. The location and width of each flow in the main channel could be controlled by the relative flow rates. This capability enabled us to study the effect of the location and the coverage area of the liquid flow that contained charged molecules on the conduction of the nanotube devices, providing important information on the sensing mechanism of carbon nanotube sensors. The results showed that in a sensor based on a nanotube thin film field effect transistor, the sensing signal came from target molecules absorbed on or around the nanotubes. The effect from adsorption on metal electrodes was weak.

Sensing sheet: the response of full-bridge strain sensors to thermal variations for detecting and characterizing cracks

NASA Astrophysics Data System (ADS)

Tung, S.-T.; Glisic, B.

2016-12-01

Sensing sheets based on large-area electronics consist of a dense array of unit strain sensors. This new technology has potential for becoming an effective and affordable monitoring tool that can identify, localize and quantify surface damage in structures. This research contributes to their development by investigating the response of full-bridge unit strain sensors to thermal variations. Overall, this investigation quantifies the effects of temperature on thin-film full-bridge strain sensors monitoring uncracked and cracked concrete. Additionally, an empirical formula is developed to estimate crack width given an observed strain change and a measured temperature change. This research led to the understanding of the behavior of full-bridge strain sensors installed on cracked concrete and exposed to temperature variations. It proves the concept of the sensing sheet and its suitability for application in environments with variable temperature.

Public health applications of remote sensing of the environment, an evaluation

NASA Technical Reports Server (NTRS)

1972-01-01

The available techniques were examined in the field of remote sensing (including aerial photography, infrared detection, radar, etc.) and applications to a number of problems in the wide field of public health determined. The specific areas of public health examined included: air pollution, water pollution, communicable disease, and the combined problems of urban growth and the effect of disasters on human communities. The assessment of the possible applications of remote sensing to these problems was made primarily by examination of the available literature in each field, and by interviews with health authorities, physicists, biologists, and other interested workers. Three types of programs employing remote sensors were outlined in the air pollution field: (1) proving ability of sensors to monitor pollutants at three levels of interest - point source, ambient levels in cities, and global patterns; (2) detection of effects of pollutants on the environment at local and global levels; and (3) routine monitoring.

A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area

USDA-ARS?s Scientific Manuscript database

Although conventional high-altitude airborne remote sensing and low-altitude unmanned aerial system (UAS) based remote sensing share many commonalities, one of the major differences between the two remote sensing platforms is that the latter has much smaller image footprint. To cover the same area o...

Enhanced clear sky reflectance near clouds: What can be learned from it about aerosol properties?

NASA Astrophysics Data System (ADS)

Marshak, A.; Varnai, T.; Wen, G.; Chiu, J.

2009-12-01

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 radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. The cloud adjacency effect is well observed in MODIS clear-sky data in the vicinity of clouds. Comparing with CALIPSO clear-sky backscatterer measurements, we show that this effect may be responsible for a large portion of the enhanced clear-sky reflectance observed by MODIS. Finally, 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.

Facile Synthesis of Wormhole-Like Mesoporous Tin Oxide via Evaporation-Induced Self-Assembly and the Enhanced Gas-Sensing Properties

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Peng, Kang; Dou, Yewei; Chen, Jiasheng; Zhang, Yue; An, Gai

2018-01-01

Wormhole-like mesoporous tin oxide was synthesized via a facile evaporation-induced self-assembly (EISA) method, and the gas-sensing properties were evaluated for different target gases. The effect of calcination temperature on gas-sensing properties of mesoporous tin oxide was investigated. The results demonstrate that the mesoporous tin oxide sensor calcined at 400 °C exhibits remarkable selectivity to ethanol vapors comparison with other target gases and has a good performance in the operating temperature and response/recovery time. This might be attributed to their high specific surface area and porous structure, which can provide more active sites and generate more chemisorbed oxygen spices to promote the diffusion and adsorption of gas molecules on the surface of the gas-sensing material. A possible formation mechanism of the mesoporous tin oxide and the enhanced gas-sensing mechanism are proposed. The mesoporous tin oxide shows prospective detecting application in the gas sensor fields.

Flexible and self-powered temperature-pressure dual-parameter sensors using microstructure-frame-supported organic thermoelectric materials.

PubMed

Zhang, Fengjiao; Zang, Yaping; Huang, Dazhen; Di, Chong-an; Zhu, Daoben

2015-09-21

Skin-like temperature- and pressure-sensing capabilities are essential features for the next generation of artificial intelligent products. Previous studies of e-skin and smart elements have focused on flexible pressure sensors, whereas the simultaneous and sensitive detection of temperature and pressure with a single device remains a challenge. Here we report developing flexible dual-parameter temperature-pressure sensors based on microstructure-frame-supported organic thermoelectric (MFSOTE) materials. The effective transduction of temperature and pressure stimuli into two independent electrical signals permits the instantaneous sensing of temperature and pressure with an accurate temperature resolution of <0.1 K and a high-pressure-sensing sensitivity of up to 28.9 kPa(-1). More importantly, these dual-parameter sensors can be self-powered with outstanding sensing performance. The excellent sensing properties of MFSOTE-based devices, together with their unique advantages of low cost and large-area fabrication, make MFSOTE materials possess promising applications in e-skin and health-monitoring elements.

The role of satellite remote sensing in structured ecosystem risk assessments.

PubMed

Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

2018-04-01

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

Flexible and self-powered temperature-pressure dual-parameter sensors using microstructure-frame-supported organic thermoelectric materials

NASA Astrophysics Data System (ADS)

Zhang, Fengjiao; Zang, Yaping; Huang, Dazhen; di, Chong-An; Zhu, Daoben

2015-09-01

Skin-like temperature- and pressure-sensing capabilities are essential features for the next generation of artificial intelligent products. Previous studies of e-skin and smart elements have focused on flexible pressure sensors, whereas the simultaneous and sensitive detection of temperature and pressure with a single device remains a challenge. Here we report developing flexible dual-parameter temperature-pressure sensors based on microstructure-frame-supported organic thermoelectric (MFSOTE) materials. The effective transduction of temperature and pressure stimuli into two independent electrical signals permits the instantaneous sensing of temperature and pressure with an accurate temperature resolution of <0.1 K and a high-pressure-sensing sensitivity of up to 28.9 kPa-1. More importantly, these dual-parameter sensors can be self-powered with outstanding sensing performance. The excellent sensing properties of MFSOTE-based devices, together with their unique advantages of low cost and large-area fabrication, make MFSOTE materials possess promising applications in e-skin and health-monitoring elements.

A low-cost sensing system for cooperative air quality monitoring in urban areas.

PubMed

Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo

2015-05-26

Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.

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.

The Large Area Crop Inventory Experiment (LACIE). Part 3: A systematic approach to the practical application of remote-sensing technology

NASA Technical Reports Server (NTRS)

Murphy, J. D.; Dideriksen, R. I.

1975-01-01

The application of remote sensing technology by the U.S. Department of Agriculture (USDA) is examined. The activities of the USDA Remote-Sensing User Requirement Task Force which include cataloging USDA requirements for earth resources data, determining those requirements that would return maximum benefits by using remote sensing technology and developing a plan for acquiring, processing, analyzing, and distributing data to satisfy those requirements are described. Emphasis is placed on the large area crop inventory experiment and its relationship to the task force.

[Study on extraction method of Panax notoginseng plots in Wenshan of Yunnan province based on decision tree model].

PubMed

Shi, Ting-Ting; Zhang, Xiao-Bo; Guo, Lan-Ping; Huang, Lu-Qi

2017-11-01

The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level. Copyright© by the Chinese Pharmaceutical Association.

Social capital and sense of insecurity in the neighbourhood: a population-based multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Merlo, Juan; Ostergren, Per Olof

2003-03-01

The aim of this study was to investigate the influence of social capital on self-reported sense of insecurity in the neighbourhood. The public health survey in Malmö, Sweden in 1994 was a cross-sectional study. A total of 5600 individuals aged 20-80 years were asked to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of individual (social participation) and neighbourhood social capital (electoral participation in the 1994 municipal election) on sense of insecurity after adjustment for compositional factors. Neighbourhood factors accounted for 7.2% of the total variance in individual insecurity. This effect was marginally reduced when the individual factors were included in the model. In contrast, it was reduced by 70% by the introduction of the contextual variable. This study suggests that social capital, measured as electoral participation, may partly explain the individual's sense of insecurity in the neighbourhood.

Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

NASA Astrophysics Data System (ADS)

Ding, Hua; Li, Ru Ren; Shuang Sun, Li; Wang, Xin; Liu, Yu Mei

2018-05-01

Taking Landsat remote sensing image as the main data source, the research on land use changes in Panjin City in 2005 to 2015 is made with the support of remote sensing platform and GIS platform in this paper; the range of land use changes and change rate are analyzed through the classification of remote sensing image; the dynamic analysis on land changes is made with the help of transfer matrix of land use type; the quantitative calculation on all kinds of dynamic change features of land changes is made by utilizing mathematical model; and the analysis on driving factors of land changes of image is made at last. The research results show that, in recent ten years, the area of cultivated land in Panjin City decreased, the area of vegetation increased, and meanwhile the area of road increased drastically, the settlement place decreased than ever, and water area changed slightly.

Validation of a remote sensing model to identify Simulium damnosum s.l. breeding sites in Sub-Saharan Africa.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent D; Sanfo, Moussa; Griffith, Daniel A; Lakwo, Thomson L; Habomugisha, Peace; Katabarwa, Moses N; Unnasch, Thomas R

2013-01-01

Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement.

Validation of a Remote Sensing Model to Identify Simulium damnosum s.l. Breeding Sites in Sub-Saharan Africa

PubMed Central

Jacob, Benjamin G.; Novak, Robert J.; Toe, Laurent D.; Sanfo, Moussa; Griffith, Daniel A.; Lakwo, Thomson L.; Habomugisha, Peace; Katabarwa, Moses N.; Unnasch, Thomas R.

2013-01-01

Background Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Methodology/Principal Findings Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. Conclusions/Significance This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement. PMID:23936571

Remote sensing of Northern mines: supporting operation and environmental monitoring in cold conditions

NASA Astrophysics Data System (ADS)

Tuomela, Anne; Davids, Corine; Knutsson, Sven; Knutsson, Roger; Rauhala, Anssi; Rossi, Pekka M.; Rouyet, Line

2017-04-01

Northern areas of Finland, Sweden and Norway have mineral-rich deposits. There are several active mines in the area but also closed ones and deposits with plans for future mining. With increasing demand for environmental protection in the sensitive Northern conditions, there is a need for more comprehensive monitoring of the mining environment. In our study, we aim to develop new opportunities to use remote sensing data from satellites and unmanned aerial vehicles (UAVs) in improving mining safety and monitoring, for example in the case of mine waste storage facilities. Remote sensing methods have evolved fast, and could in many cases enable precise, reliable, and cost-efficient data collection over large areas. The study has focused on four mining areas in Northern Fennoscandia. Freely available medium-resolution (e.g. Sentinel-1), commercial high-resolution (e.g. TerraSAR-X) and Synthetic Aperture Radar (SAR) data has been collected during 2015-2016 to study how satellite remote sensing could be used e.g. for displacement monitoring using SAR Interferometry (InSAR). Furthermore, UAVs have been utilized in similar data collection in a local scale, and also in collection of thermal infrared data for hydrological monitoring of the areas. The development and efficient use of the methods in mining areas requires experts from several fields. In addition, the Northern conditions with four distinct seasons bring their own challenges for the efficient use of remote sensing, and further complicate their integration as standardised monitoring methods for mine environments. Based on the initial results, remote sensing could especially enhance the monitoring of large-scale structures in mine areas such as tailings impoundments.

Integrative freight demand management in the New York City metropolitan area.

DOT National Transportation Integrated Search

2010-09-01

This project is one of the first in the world that has successfully integrated the use of remote sensing : technologyin this case Global Positioning System (GPS) enabled cell phonesas part of a system that : effectively reduces truck traffic in...

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya.

PubMed

Sewe, Maquins Odhiambo; Ahlm, Clas; Rocklöv, Joacim

2016-01-01

Malaria is an important cause of morbidity and mortality in malaria endemic countries. The malaria mosquito vectors depend on environmental conditions, such as temperature and rainfall, for reproduction and survival. To investigate the potential for weather driven early warning systems to prevent disease occurrence, the disease relationship to weather conditions need to be carefully investigated. Where meteorological observations are scarce, satellite derived products provide new opportunities to study the disease patterns depending on remotely sensed variables. In this study, we explored the lagged association of Normalized Difference Vegetation Index (NVDI), day Land Surface Temperature (LST) and precipitation on malaria mortality in three areas in Western Kenya. The lagged effect of each environmental variable on weekly malaria mortality was modeled using a Distributed Lag Non Linear Modeling approach. For each variable we constructed a natural spline basis with 3 degrees of freedom for both the lag dimension and the variable. Lag periods up to 12 weeks were considered. The effect of day LST varied between the areas with longer lags. In all the three areas, malaria mortality was associated with precipitation. The risk increased with increasing weekly total precipitation above 20 mm and peaking at 80 mm. The NDVI threshold for increased mortality risk was between 0.3 and 0.4 at shorter lags. This study identified lag patterns and association of remote- sensing environmental factors and malaria mortality in three malaria endemic regions in Western Kenya. Our results show that rainfall has the most consistent predictive pattern to malaria transmission in the endemic study area. Results highlight a potential for development of locally based early warning forecasts that could potentially reduce the disease burden by enabling timely control actions.

Design and implementation of sensor systems for control of a closed-loop life support system

NASA Technical Reports Server (NTRS)

Alnwick, Leslie; Clark, Amy; Debs, Patricia; Franczek, Chris; Good, Tom; Rodrigues, Pedro

1989-01-01

The sensing and controlling needs for a Closed-Loop Life Support System (CLLSS) were investigated. The sensing needs were identified in five particular areas and the requirements were defined for workable sensors. The specific areas of interest were atmosphere and temperature, nutrient delivery, plant health, plant propagation and support, and solids processing. The investigation of atmosphere and temperature control focused on the temperature distribution within the growth chamber as well as the possibility for sensing other parameters such as gas concentration, pressure, and humidity. The sensing needs were studied for monitoring the solution level in a porous membrane material along with the requirements for measuring the mass flow rate in the delivery system. The causes and symptoms of plant disease were examined and the various techniques for sensing these health indicators were explored. The study of sensing needs for plant propagation and support focused on monitoring seed viability and measuring seed moisture content as well as defining the requirements for drying and storing the seeds. The areas of harvesting, food processing, and resource recycling, were covered with a main focus on the sensing possibilities for regulating the recycling process.

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.

The variability of winds over the ocean

NASA Technical Reports Server (NTRS)

Pierson, W. J.

1981-01-01

The present state of knowledge of the synoptic scale, the mesoscale, and the microscale in describing the winds, especially over the ocean, is summarized both in terms of conventional data and remotely sensed properties and effects of the winds. A description is then given of some of the areas posing problems in modeling each scale and interpreting the various kinds of measurements that are made. It is noted that not much is known about the wind, especially in the mesoscale, that affects the ability to use remotely sensed data in an optimum way.

Recent advances in remote sensing; Proceedings of the First International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981

NASA Technical Reports Server (NTRS)

Mcintosh, R.

1982-01-01

The state of the art in remote sensing of the earth and the planets was discussed in terms of sensor performance, signal processing, and data interpretation. Particular attention was given to lidar for characterizing atmospheric particulates, the modulation of short waves by long ocean gravity waves, and runoff modeling for snow-covered areas. The use of NOAA-6 spacecraft AVHRR data to explore hydrologic land surface features, the effects of soil moisture and vegetation canopies on microwave and thermal microwave emissions, and regional scale evapotranspiration rate determination through satellite IR data are examined. A Shuttle experiment to demonstrate high accuracy global time and frequency transfer is described, along with features of the proposed Gravsat, radar image processing for rock-type discrimination, and passive microwave sensing of temperature and salinity in coastal zones.

Highly Sensitive and Selective Ethanol Sensor Fabricated with In-Doped 3DOM ZnO.

PubMed

Wang, Zhihua; Tian, Ziwei; Han, Dongmei; Gu, Fubo

2016-03-02

ZnO is an important n-type semiconductor sensing material. Currently, much attention has been attracted to finding an effective method to prepare ZnO nanomaterials with high sensing sensitivity and excellent selectivity. A three-dimensionally ordered macroporous (3DOM) ZnO nanostructure with a large surface area is beneficial to gas and electron transfer, which can enhance the gas sensitivity of ZnO. Indium (In) doping is an effective way to improve the sensing properties of ZnO. In this paper, In-doped 3DOM ZnO with enhanced sensitivity and selectivity has been synthesized by using a colloidal crystal templating method. The 3DOM ZnO with 5 at. % of In-doping exhibits the highest sensitivity (∼88) to 100 ppm ethanol at 250 °C, which is approximately 3 times higher than that of pure 3DOM ZnO. The huge improvement to the sensitivity to ethanol was attributed to the increase in the surface area and the electron carrier concentration. The doping by In introduces more electrons into the matrix, which is helpful for increasing the amount of adsorbed oxygen, leading to high sensitivity. The In-doped 3DOM ZnO is a promising material for a new type of ethanol sensor.

Utilizing multisource remotely sensed data to dynamically monitor drought in China

NASA Astrophysics Data System (ADS)

Liu, Sanchao; Li, Wenbo

2011-12-01

Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.

Application of remote sensing to land and water resource planning: The Pocomoke River Basin, Maryland

NASA Technical Reports Server (NTRS)

Wildesen, S. E.; Phillips, E. P.

1981-01-01

Because of the size of the Pocomoke River Basin, the inaccessibility of certain areas, and study time constraints, several remote sensing techniques were used to collect base information on the river corridor, (a 23.2 km channel) and on a 1.2 km wooded floodplain. This information provided an adequate understanding of the environment and its resources, thus enabling effective management options to be designed. The remote sensing techniques used for assessment included manual analysis of high altitude color-infrared photography, computer-assisted analysis of LANDSAT-2 imagery, and the application of airborne oceanographic Lidar for topographic mapping. Results show that each techniques was valuable in providing the needed base data necessary for resource planning.

Remote sensing in Michigan for land resource management

NASA Technical Reports Server (NTRS)

Lowe, D. S.; Istvan, L. B.; Roller, N. E. G.; Sellman, A. N.; Wagner, T. W.

1975-01-01

The utilization of NASA earth resource survey technology as an important aid in the solution of current problems in resource management and environmental protection in Michigan is discussed. Remote sensing techniques to aid Michigan government agencies were used to achieve the following results: (1) provide data on Great Lakes beach recession rates to establish shoreline zoning ordinances; (2) supply technical justification for public acquisition of land to establish the St. John's Marshland Recreation Area; (3) establish economical and effective methods for performing a statewide wetlands survey; (4) accomplish a variety of regional resource management actions in the Upper Peninsula; and (5) demonstrate improved soil survey methods. The project disseminated information on remote sensing technology and provided advice and assistance to a number of users in Michigan.

Evapotranspiration and remote sensing

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Gurney, R.

1982-01-01

There are three things required for evapotranspiration to occur: (1) energy (580 cal/gm) for the change of phase of the water; (2) a source of the water, i.e., adequate soil moisture in the surface layer or in the root zone of the plant; and (3) a sink for the water, i.e., a moisture deficit in the air above the ground. Remote sensing can contribute information to the first two of these conditions by providing estimates of solar insolation, surface albedo, surface temperature, vegetation cover, and soil moisture content. In addition there have been attempts to estimate precipitation and shelter air temperature from remotely sensed data. The problem remains to develop methods for effectively using these sources of information to make large area estimates of evapotranspiration.

Functional Connectivity Analysis of NIRS Data under Rubber Hand Illusion to Find a Biomarker of Sense of Ownership.

PubMed

Arizono, Naoki; Ohmura, Yuji; Yano, Shiro; Kondo, Toshiyuki

2016-01-01

The self-identification, which is called sense of ownership, has been researched through methodology of rubber hand illusion (RHI) because of its simple setup. Although studies with neuroimaging technique, such as fMRI, revealed that several brain areas are associated with the sense of ownership, near-infrared spectroscopy (NIRS) has not yet been utilized. Here we introduced an automated setup to induce RHI, measured the brain activity during the RHI with NIRS, and analyzed the functional connectivity so as to understand dynamical brain relationship regarding the sense of ownership. The connectivity was evaluated by multivariate Granger causality. In this experiment, the peaks of oxy-Hb on right frontal and right motor related areas during the illusion were significantly higher compared with those during the nonillusion. Furthermore, by analyzing the NIRS recordings, we found a reliable connectivity from the frontal to the motor related areas during the illusion. This finding suggests that frontal cortex and motor related areas communicate with each other when the sense of ownership is induced. The result suggests that the sense of ownership is related to neural mechanism underlying human motor control, and it would be determining whether motor learning (i.e., neural plasticity) will occur. Thus RHI with the functional connectivity analysis will become an appropriate biomarker for neurorehabilitation.

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Problems of urban development and growth

NASA Technical Reports Server (NTRS)

Gerlach, A. C.; Wray, J. R.

1972-01-01

The increase in the density of human population in urban areas and the effects on various aspects of the environment are discussed. The application of remote sensors to measure, analyze, and predict urban changes and their environmental impact is described. Examples of urban area mapping by aerial photography are included. The methods which have been developed to acquire, analyze, utilize, and preserve remotely sensed data on urban development are presented.

Determination of the Electrochemical Area of Screen-Printed Electrochemical Sensing Platforms.

PubMed

García-Miranda Ferrari, Alejandro; Foster, Christopher W; Kelly, Peter J; Brownson, Dale A C; Banks, Craig E

2018-06-08

Screen-printed electrochemical sensing platforms, due to their scales of economy and high reproducibility, can provide a useful approach to translate laboratory-based electrochemistry into the field. An important factor when utilising screen-printed electrodes (SPEs) is the determination of their real electrochemical surface area, which allows for the benchmarking of these SPEs and is an important parameter in quality control. In this paper, we consider the use of cyclic voltammetry and chronocoulometry to allow for the determination of the real electrochemical area of screen-printed electrochemical sensing platforms, highlighting to experimentalists the various parameters that need to be diligently considered and controlled in order to obtain useful measurements of the real electroactive area.

Integration of remote sensing based surface information into a three-dimensional microclimate model

NASA Astrophysics Data System (ADS)

Heldens, Wieke; Heiden, Uta; Esch, Thomas; Mueller, Andreas; Dech, Stefan

2017-03-01

Climate change urges cities to consider the urban climate as part of sustainable planning. Urban microclimate models can provide knowledge on the climate at building block level. However, very detailed information on the area of interest is required. Most microclimate studies therefore make use of assumptions and generalizations to describe the model area. Remote sensing data with area wide coverage provides a means to derive many parameters at the detailed spatial and thematic scale required by urban climate models. This study shows how microclimate simulations for a series of real world urban areas can be supported by using remote sensing data. In an automated process, surface materials, albedo, LAI/LAD and object height have been derived and integrated into the urban microclimate model ENVI-met. Multiple microclimate simulations have been carried out both with the dynamic remote sensing based input data as well as with manual and static input data to analyze the impact of the RS-based surface information and the suitability of the applied data and techniques. A valuable support of the integration of the remote sensing based input data for ENVI-met is the use of an automated processing chain. This saves tedious manual editing and allows for fast and area wide generation of simulation areas. The analysis of the different modes shows the importance of high quality height data, detailed surface material information and albedo.

Making Sense of Principal Leadership in Content Areas: The Case of Secondary Math and Science Instruction

ERIC Educational Resources Information Center

Lochmiller, Chad R.; Acker-Hocevar, Michele

2016-01-01

We drew upon sense making and leadership content knowledge to explore how high school administrators' understanding of content areas informed their leadership. We used math and science to illustrate our interpretations, noting that other content areas may pose different challenges. We found that principals' limited understanding of these content…

Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing

NASA Astrophysics Data System (ADS)

Ya'acob, Norsuzila; Mohd Azize, Aziean Binti; Anis Mahmon, Nur; Laily Yusof, Azita; Farhana Azmi, Nor; Mustafa, Norfazira

2014-03-01

This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.

Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel

2011-01-01

Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.

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)

The effect of flight altitude to data quality of fixed-wing UAV imagery: case study in Murcia, Spain

NASA Astrophysics Data System (ADS)

Anders, Niels; Keesstra, Saskia; Cammeraat, Erik

2014-05-01

Unmanned Aerial System (UAS) are becoming popular tools in the geosciences due to improving technology and processing techniques. They can potentially fill the gap between spaceborne or manned aircraft remote sensing and terrestrial remote sensing, both in terms of spatial and temporal resolution. In this study we tested a fixed-wing Unmanned Aerial System (UAS) for the application of digital landscape analysis. The focus was to analyze the effect of flight altitude and the effect to accuracy and detail of the produced digital elevation models, derived terrain properties and orthophotos. The aircraft was equipped with a Panasonic GX1 16MP pocket camera with 20 mm lens to capture normal JPEG RGB images. Images were processed using Agisoft Photoscan Pro which includes the structure-from-motion and multiview stereopsis algorithms. The test area consisted of small abandoned agricultural fields in semi-arid Murcia in southeastern Spain. The area was severely damaged after a destructive rainfall event, including damaged check dams, rills, deep gully incisions and piping. Results suggest that careful decisions on flight altitude are essential to find a balance between the area coverage, ground sampling distance, UAS ground speed, camera processing speed and the accurate registration of specific soil erosion features of interest.

Research and Practice of Uav Remote Sensing in the Monitoring and Management of Construction Projects in Riparian Areas

NASA Astrophysics Data System (ADS)

Yu, J.; Gan, Z.; Zhong, L.; Deng, L.

2018-04-01

The objective of this paper is to investigate the use of UAV remote sensing in the monitoring and management of construction projects in riparian areas through the case study of embankment construction projects' monitoring in the Three Gorges Reservoir area. A three-step approach is proposed to address the problem: data acquisition with UAV, data processing, and monitoring information extraction. The results of the case study demonstrate that UAV remote sensing is capable of providing fast and accurate measurements and calculations for the needs of monitoring of riparian constructions.

Method and apparatus for detecting concealed weapons

DOEpatents

Kotter, Dale K.; Fluck, Frederick D.

2006-03-14

Apparatus for classifying a ferromagnetic object within a sensing area may include a magnetic field sensor that produces magnetic field data. A signal processing system operatively associated with the magnetic field sensor includes a neural network. The neural network compares the magnetic field data with magnetic field data produced by known ferromagnetic objects to make a probabilistic determination as to the classification of the ferromagnetic object within the sensing area. A user interface operatively associated with the signal processing system produces a user-discernable output indicative of the probabilistic determination of the classification of the ferromagnetic object within a sensing area.

Mapping irrigated areas of Ghana using fusion of 30 m and 250 m resolution remote-sensing data

USGS Publications Warehouse

Gumma, M.K.; Thenkabail, P.S.; Hideto, F.; Nelson, A.; Dheeravath, V.; Busia, D.; Rala, A.

2011-01-01

Maps of irrigated areas are essential for Ghana's agricultural development. The goal of this research was to map irrigated agricultural areas and explain methods and protocols using remote sensing. Landsat Enhanced Thematic Mapper (ETM+) data and time-series Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to map irrigated agricultural areas as well as other land use/land cover (LULC) classes, for Ghana. Temporal variations in the normalized difference vegetation index (NDVI) pattern obtained in the LULC class were used to identify irrigated and non-irrigated areas. First, the temporal variations in NDVI pattern were found to be more consistent in long-duration irrigated crops than with short-duration rainfed crops due to more assured water supply for irrigated areas. Second, surface water availability for irrigated areas is dependent on shallow dug-wells (on river banks) and dug-outs (in river bottoms) that affect the timing of crop sowing and growth stages, which was in turn reflected in the seasonal NDVI pattern. A decision tree approach using Landsat 30 m one time data fusion with MODIS 250 m time-series data was adopted to classify, group, and label classes. Finally, classes were tested and verified using ground truth data and national statistics. Fuzzy classification accuracy assessment for the irrigated classes varied between 67 and 93%. An irrigated area derived from remote sensing (32,421 ha) was 20-57% higher than irrigated areas reported by Ghana's Irrigation Development Authority (GIDA). This was because of the uncertainties involved in factors such as: (a) absence of shallow irrigated area statistics in GIDA statistics, (b) non-clarity in the irrigated areas in its use, under-development, and potential for development in GIDA statistics, (c) errors of omissions and commissions in the remote sensing approach, and (d) comparison involving widely varying data types, methods, and approaches used in determining irrigated area statistics using GIDA and remote sensing. Extensive field campaigns to help in better classification and validation of irrigated areas using high (30 m ) to very high (<5 m) resolution remote sensing data that are fused with multi temporal data like MODIS are the way forward. This is especially true in accounting for small yet contiguous patches of irrigated areas from dug-wells and dug-outs. ?? 2011 by the authors.

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.

The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish

NASA Technical Reports Server (NTRS)

Savastano, K. J.; Leming, T. D.

1975-01-01

An investigation was conducted to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. The data from the test area was jointly acquired by NASA, the Navy, the Air Force and NOAA/NMFS elements and private and professional fishermen in the northeastern Gulf of Mexico. The data collected has made it possible to identify fisheries significant environmental parameters for white marlin. Prediction models, based on catch data and surface truth information, were developed and demonstrated a potential for significantly reducing search by identifying areas that have a high probability of productivity. Three of the parameters utilized by the models, chlorophyll-a, sea surface temperature, and turbidity were inferred from aircraft sensor data and were tested. Effective use of Skylab data was inhibited by cloud cover and delayed delivery. Initial efforts toward establishing the feasibility of utilizing remotely sensed data to assess and monitor the distribution of oceanic gamefish has successfully identified fisheries significant oceanographic parameters and demonstrated the capability of remotely measuring most of the parameters.

Gulf Coast Disaster Management: Forest Damage Detection and Carbon Flux Estimation

NASA Astrophysics Data System (ADS)

Maki, A. E.; Childs, L. M.; Jones, J.; Matthews, C.; Spindel, D.; Batina, M.; Malik, S.; Allain, M.; Brooks, A. O.; Brozen, M.; Chappell, C.; Frey, J. W.

2008-12-01

Along the Gulf Coast and Eastern Seaboard, tropical storms and hurricanes annually cause defoliation and deforestation amongst coastal forests. After a severe storm clears, there is an urgent need to assess impacts on timber resources for targeting state and national resources to assist in recovery. It is important to identify damaged areas following the storm, due to their increased probability of fire risk, as well as the effect upon the carbon budget. Better understanding and management of the immediate and future effects on the carbon cycle in the coastal forest ecosystem is especially important. Current methods of detection involve assessment through ground-based field surveys, aerial surveys, computer modeling of meteorological data, space-borne remote sensing, and Forest Inventory and Analysis field plots. Introducing remotely-sensed data from NASA and NASA-partnered Earth Observation Systems (EOS), this project seeks to improve the current methodology and focuses on a need for methods that are more synoptic than field surveys and more closely linked to the phenomenology of tree loss and damage than passive remote sensing methods. The primary concentration is on the utilization of Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) data products to detect changes in forest canopy height as an indicator of post-hurricane forest disturbances. By analyzing ICESat data over areas affected by Hurricane Katrina, this study shows that ICESsat is a useful method of detecting canopy height change, though further research is needed in mixed forest areas. Other EOS utilized in this study include Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and the NASA verified and validated international Advanced Wide Field Sensor (AWiFS) sensor. This study addresses how NASA could apply ICESat data to contribute to an improved method of detecting hurricane-caused forest damage in coastal areas; thus to pinpoint areas more susceptible to fire damage and subsequent loss of carbon sequestration.

Operational monitoring of land-cover change using multitemporal remote sensing data

NASA Astrophysics Data System (ADS)

Rogan, John

2005-11-01

Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation techniques. Finally, the land-cover modification maps generated for three time intervals (1985--1990--1996--2000), with nine change-classes revealed important variations in land-cover gain and loss between northern and southern California study areas.

A hotspot model for leaf canopies

NASA Technical Reports Server (NTRS)

Jupp, David L. B.; Strahler, Alan H.

1991-01-01

The hotspot effect, which provides important information about canopy structure, is modeled using general principles of environmental physics as driven by parameters of interest in remote sensing, such as leaf size, leaf shape, leaf area index, and leaf angle distribution. Specific examples are derived for canopies of horizontal leaves. The hotspot effect is implemented within the framework of the model developed by Suits (1972) for a canopy of leaves to illustrate what might occur in an agricultural crop. Because the hotspot effect arises from very basic geometrical principles and is scale-free, it occurs similarly in woodlands, forests, crops, rough soil surfaces, and clouds. The scaling principles advanced are also significant factors in the production of image spatial and angular variance and covariance which can be used to assess land cover structure through remote sensing.

City of Flagstaff Project: Ground Water Resource Evaluation, Remote Sensing Component

USGS Publications Warehouse

Chavez, Pat S.; Velasco, Miguel G.; Bowell, Jo-Ann; Sides, Stuart C.; Gonzalez, Rosendo R.; Soltesz, Deborah L.

1996-01-01

Many regions, cities, and towns in the Western United States need new or expanded water resources because of both population growth and increased development. Any tools or data that can help in the evaluation of an area's potential water resources must be considered for this increasingly critical need. Remotely sensed satellite images and subsequent digital image processing have been under-utilized in ground water resource evaluation and exploration. Satellite images can be helpful in detecting and mapping an area's regional structural patterns, including major fracture and fault systems, two important geologic settings for an area's surface to ground water relations. Within the United States Geological Survey's (USGS) Flagstaff Field Center, expertise and capabilities in remote sensing and digital image processing have been developed over the past 25 years through various programs. For the City of Flagstaff project, this expertise and these capabilities were combined with traditional geologic field mapping to help evaluate ground water resources in the Flagstaff area. Various enhancement and manipulation procedures were applied to the digital satellite images; the results, in both digital and hardcopy format, were used for field mapping and analyzing the regional structure. Relative to surface sampling, remotely sensed satellite and airborne images have improved spatial coverage that can help study, map, and monitor the earth surface at local and/or regional scales. Advantages offered by remotely sensed satellite image data include: 1. a synoptic/regional view compared to both aerial photographs and ground sampling, 2. cost effectiveness, 3. high spatial resolution and coverage compared to ground sampling, and 4. relatively high temporal coverage on a long term basis. Remotely sensed images contain both spectral and spatial information. The spectral information provides various properties and characteristics about the surface cover at a given location or pixel (that is, vegetation and/or soil type). The spatial information gives the distribution, variation, and topographic relief of the cover types from pixel to pixel. Therefore, the main characteristics that determine a pixel's brightness/reflectance and, consequently, the digital number (DN) assigned to the pixel, are the physical properties of the surface and near surface, the cover type, and the topographic slope. In this application, the ability to detect and map lineaments, especially those related to fractures and faults, is critical. Therefore, the extraction of spatial information from the digital images was of prime interest in this project. The spatial information varies among the different spectral bands available; in particular, a near infrared spectral band is better than a visible band when extracting spatial information in highly vegetated areas. In this study, both visible and near infrared bands were analyzed and used to extract the desired spatial information from the images. The wide swath coverage of remotely sensed satellite digital images makes them ideal for regional analysis and mapping. Since locating and mapping highly fractured and faulted areas is a major requirement for ground water resource evaluation and exploration this aspect of satellite images was considered critical; it allowed us to stand back (actually up about 440 miles), look at, and map the regional structural setting of the area. The main focus of the remote sensing and digital image processing component of this project was to use both remotely sensed digital satellite images and a Digital Elevation Model (DEM) to extract spatial information related to the structural and topographic patterns in the area. The data types used were digital satellite images collected by the United States' Landsat Thematic Mapper (TM) and French Systeme Probatoire d'Observation de laTerre (SPOT) imaging systems, along with a DEM of the Flagstaff region. The USGS Mini Image Processing Sy

Assessment of rockfall hazard at Al-Noor Mountain, Makkah city (Saudi Arabia) using spatio-temporal remote sensing data and field investigation

NASA Astrophysics Data System (ADS)

Youssef, Ahmed M.; Pradhan, Biswajeet; Al-Kathery, Mohamed; Bathrellos, George D.; Skilodimou, Hariklia D.

2015-01-01

Rockfall is one of the major concerns along different urban areas and highways all over the world. Al-Noor Mountain is one of the areas that threaten rockfalls to the Al-Noor escarpment track road and the surrounding urban areas. Thousands of visitors and tourisms use the escarpment track road to visit Hira cave which is located at the top of Al-Noor Mountain. In addition, the surrounding urban areas of Al-Noor Mountain are continuously spreading over the recent years. The escarpment track road and the surrounding urban areas are highly vulnerable and suffers from recurrent rockfall mostly in the rainy season. The steep and highly jointed slope along the different faces of the mountain makes these zones prone to failure due to different actions such as weathering, erosion and anthropogenic effect. Therefore, an attempt has been made in this study to determine the Al-Noor cliff stability, by identifying the unstable areas, and to apply the rockfall simulations. A combination of remote sensing, field study and 2D computer simulation rockfall program were performed to assess surface characteristics of the cliff faces. Bounce height, total and translational kinetic energy, translational velocity, and number of blocks have been estimated. Different unstable zones along the Al-Noor Mountain and escarpment track road were determined using filed investigation and remote sensing based image analysis. In addition the rockfall simulation analysis indicated that rockfall in zone 1 and zone 2 of the Al-Noor Mountain may reach the urban areas, whereas rockfall in zone 3 will not reach the urban areas, and rockfalls along the Al-Noor escarpment track road will have highly impact on the tourists. Proper preventive measures are also suggested to arrest the movement of falling rocks before reaching the urban areas and the Al-Noor escarpment track road. If proper care is taken, then further uncertain rockfall hazards can be prevented.

Temperature and acidity effects on WO{sub 3} nanostructures and gas-sensing properties of WO{sub 3} nanoplates

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

Zhang, Huili; Liu, Zhifang; Yang, Jiaqin

2014-09-15

Graphical abstract: Generally, large acid quantity and high temperature are beneficial to the formation of anhydrous WO3, but the acidity effect on the crystal phase is weaker than that of temperature. Large acid quantity is found helpful to the oriented growth of tungsten oxides, forming a nanoplate-like product. - Highlights: • Large acid quantity is propitious to the oriented growth of a WO{sub 3} nanoplate. • Effect of acid quantity on crystal phases of products is weaker than that of temperature. • One step hydrothermal synthesis of WO{sub 3} is facile and can be easily scaled up. • A WO{submore » 3} nanoplate shows a fast response and distinct sensing selectivity to acetone gas. - Abstract: WO{sub 3} nanostructures were successfully synthesized by a facile hydrothermal method using Na{sub 2}WO{sub 4}·2H{sub 2}O and HNO{sub 3} as raw materials. They are characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). The specific surface area was obtained from N{sub 2} adsorption–desorption isotherm. The effects of the amount of HNO{sub 3}, hydrothermal temperature and reaction time on the crystal phases and morphologies of the WO{sub 3} nanostructures were investigated in detail, and the reaction mechanism was discussed. Large amount of acid is found for the first time to be helpful to the oriented growth of tungsten oxides, forming nanoplate-like products, while hydrothermal temperature has more influence on the crystal phase of the product. Gas-sensing properties of the series of as-prepared WO{sub 3} nanoplates were tested by means of acetone, ethanol, formaldehyde and ammonia. One of the WO{sub 3} nanoplates with high specific surface area and high crystallinity displays high sensitivity, fast response and distinct sensing selectivity to acetone gas.« less

"A remote sensing approach to determining susceptibility of national park forest areas to forecasted changes in precipitation and temperature"

NASA Astrophysics Data System (ADS)

Finley, T.; Griffin, R.

2016-12-01

The United States designates 59 protected areas around the country as national parks, totaling around 51.9 million acres. With the exception of a few, the majority of these parks feature forested areas of biological and/or historical importance. Depending on their location, these forested areas are threatened by climate change in the form of decreasing precipitation and/or increasing temperatures, which can result in significant drying resulting in increased susceptibility to threats and resultant tree mortality. This study aims to survey the forested areas of America's national parks and determine their susceptibility to climate-induced drying. Land cover derived from remotely sensed multispectral data was used to characterize forested areas within national parks. Multiple climate change scenarios to end of century were taken from the NASA Earth Exchange Downscaled Climate Projections (DEX _DCP30) dataset and were compared with the forested areas. Forests projected to experience both an increase in temperature and decrease in precipitation were considered most at risk. A susceptibility analysis was performed to develop an index that would identify these areas most prone to negative effects from climate change in low (B1), medium (A1B), and high (A2) emissions scenarios. With this information, park officials can better focus efforts to monitor and preserve their forested areas.

The Feasibility Evaluation of Land Use Change Detection Using GAOFEN-3 Data

NASA Astrophysics Data System (ADS)

Huang, G.; Sun, Y.; Zhao, Z.

2018-04-01

GaoFen-3 (GF-3) satellite, is the first C band and multi-polarimetric Synthetic Aperture Radar (SAR) satellite in China. In order to explore the feasibility of GF-3 satellite in remote sensing interpretation and land-use remote sensing change detection, taking Guangzhou, China as a study area, the full polarimetric image of GF-3 satellite with 8 m resolution of two temporal as the data source. Firstly, the image is pre-processed by orthorectification, image registration and mosaic, and the land-use remote sensing digital orthophoto map (DOM) in 2017 is made according to the each county. Then the classification analysis and judgment of ground objects on the image are carried out by means of ArcGIS combining with the auxiliary data and using artificial visual interpretation, to determine the area of changes and the category of change objects. According to the unified change information extraction principle to extract change areas. Finally, the change detection results are compared with 3 m resolution TerraSAR-X data and 2 m resolution multi-spectral image, and the accuracy is evaluated. Experimental results show that the accuracy of the GF-3 data is over 75 % in detecting the change of ground objects, and the detection capability of new filling soil is better than that of TerraSAR-X data, verify the detection and monitoring capability of GF-3 data to the change information extraction, also, it shows that GF-3 can provide effective data support for the remote sensing detection of land resources.

Remote sensing and geographic information system for appraisal of salt-affected soils in India.

PubMed

Singh, Gurbachan; Bundela, D S; Sethi, Madhurama; Lal, Khajanchi; Kamra, S K

2010-01-01

Quantification of the nature, extent, and spatial distribution of salt-affected soils (SAS) for India and the world is essential for planning and implementing reclamation programs in a timely and cost-effective manner for sustained crop production. The national extent of SAS for India over the last four decades was assessed by conventional and remote sensing approaches using diverse methodologies and class definitions and ranged from 6.0 to 26.1 million hectares (Mha) and 1.2 to 10.1 Mha, respectively. In 1966, an area of 6 Mha under SAS was first reported using the former approach. Three national estimates, obtained using remote sensing, were reconciled using a geographic information system, resulting in an acceptable extent of 6.73 Mha. Moderately and severely salt-encrusted lands having large contiguous area have been correctly mapped, but slightly salt-encrusted land having smaller affected areas within croplands has not been accurately mapped. Recent satellite sensors (e.g., Resourcesat-1, Cartosat-2, IKONOS-II, and RISAT-2), along with improved image processing techniques integrated with terrain and other spatial data using a geographic information system, are enabling mapping at large scale. Significant variations in salt encrustation at the surface caused by soil moisture, waterlogging conditions, salt-tolerant crops, and dynamics of subsurface salts present constraints in appraisal, delineation, and mapping efforts. The article provides an overview of development, identification, characterization, and delineation of SAS, past and current national scenarios of SAS using conventional and remote sensing approaches, reconciliation of national estimates, issues of SAS mapping, and future scope.

Composite polymer systems with control of local substrate elasticity and their effect on cytoskeletal and morphological characteristics of adherent cells.

PubMed

Chou, Szu-Yuan; Cheng, Chao-Min; LeDuc, Philip R

2009-06-01

At the interface between extracellular substrates and biological materials, substrate elasticity strongly influences cell morphology and function. The associated biological ramifications comprise a diversity of critical responses including apoptosis, differentiation, and motility, which can affect medical devices such as stents. The interactions of the extracellular environment with the substrate are also affected by local properties wherein cells sense and respond to different physical inputs. To investigate the effects of having localized elasticity control of substrate microenvironments on cell response, we have developed a method to control material interface interactions with cells by dictating local substrate elasticity. This system is created by generating a composite material system with alternating, linear regions of polymers that have distinct stiffness characteristics. This approach was used to examine cytoskeletal and morphological changes in NIH 3T3 fibroblasts with emphasis on both local and global properties, noting that cells sense and respond to distinct material elasticities. Isolated cells sense and respond to these local differences in substrate elasticity by extending processes along the interface. Also, cells grown on softer elastic regions at higher densities (in contact with each other) have a higher projected area than isolated cells. Furthermore, when using chemical agents such as cytochalasin-D to disrupt the actin cytoskeleton, there is a significant increase in projected area for cells cultured on softer elastic regions This method has the potential to promote understanding of biomaterial-affected responses in a diversity of areas including morphogenesis, mechanotransduction, stents, and stem cell differentiation.

Integrated Use of Remote Sensing, GIS and GPS Technology for Monitoring the Environmental Problem of Shyamnagar

NASA Astrophysics Data System (ADS)

Akbar, M. S.; Sarker, M. H.; Sattar, M. A.; Sarwar, G. M.; Rahman, S. M. M.; Rahman, M. M.; Khan, Z. U.

2017-05-01

Cultivation of shrimp mostly in unplanned way has been considered as one of the major environmental disasters of Shamnagar. Villagers surrounding the rivers are mainly involved with fish (shrimp) cultivation. So, fertile agriculture land has been converted to shrimp cultivation. Conversion of agriculture land to other usage is a common but acute problem for land resources of the country like Bangladesh. Conventional methods for collecting this information are relatively costly and time consuming. Contrarily, Remote Sensing satellite observation with its unique capability to provide cost-effective support in compiling the latest information about the natural resource. Remote sensing, in conjunction with GIS, has been widely applied and been recognized as a powerful and effective tool in detecting land use and land cover changes. RapidEye, Landsat8 images were used to identify land use and land cover of the area during the period 2008 and 2015. Google images were used to identify the micro-level land use features of the same period. Multi-spectral classifications using unsupervised and supervised classification were done and results have been compared based on the field investigation. The study reveals that during the period 2008 to 2015 agricultural practice has been reduced from 35 % to 21 % and shrimp cultivation area increased from 38 % to 50 %. Due to the impact of high salinity and salt water intrusion caused by natural disaster, agricultural activities is reduced and farmers have been converted to other practices, as a result shrimp farming is gaining popularity in the area.

Design of Weft Detection System in The Stenter Machine

NASA Astrophysics Data System (ADS)

Gu, Minming; Xu, Xianju; Dai, Wenzhan

2017-12-01

In order to build an effective automatic weft-straightening system, it is important for the sensing device to detect most the possible fabric styles, designs, colours and structures, an optical sensing system that detects the angular orientation of weft threads in a moving web of a textile has been built. It contains an adjustable light source, two lens systems and photodiode sensor array. The sensor array includes 13 radial pattern of photosensitive areas that each generate an electrical signal proportional to the total intensity of the light incident on the area. The moving shadow of a weft thread passing over the area will modulate the output signal. A signal processed circuit was built to do the I/V conversion, amplifying, hardware filtering. An embed micro control system then deals with the information of these signals, calculates the angle of the weft drew. Finally, the experiments were done, the results showed that the weft detection system can deal with the fabric weft skew up to 30° and has achieved good results in the application.

Assessment of the Impact of the California Water Project in the West Side of the San Joaquin Valley

NASA Technical Reports Server (NTRS)

Estes, J. E.; Kuhn, M.; Golomb, B.; Senger, L. W.; Wester, L.; Fortune, P.; Viellenave, J.

1971-01-01

The ability of remote sensing techniques to effectively monitor, on a continuing basis, the impact of a change in the water supply of an arid area is considered. Research involves the collection of a substantial body of information relative to both physical and biological phenomena or systems operative within the study area by concentrating on the accumulation of library materials, and field data.

Atmospheric effects on cluster analyses. [for remote sensing application

NASA Technical Reports Server (NTRS)

Kiang, R. K.

1979-01-01

Ground reflected radiance, from which information is extracted through techniques of cluster analyses for remote sensing application, is altered by the atmosphere when it reaches the satellite. Therefore it is essential to understand the effects of the atmosphere on Landsat measurements, cluster characteristics and analysis accuracy. A doubling model is employed to compute the effective reflectivity, observed from the satellite, as a function of ground reflectivity, solar zenith angle and aerosol optical thickness for standard atmosphere. The relation between the effective reflectivity and ground reflectivity is approximately linear. It is shown that for a horizontally homogeneous atmosphere, the classification statistics from a maximum likelihood classifier remains unchanged under these transforms. If inhomogeneity is present, the divergence between clusters is reduced, and correlation between spectral bands increases. Radiance reflected by the background area surrounding the target may also reach the satellite. The influence of background reflectivity on effective reflectivity is discussed.

Predicting risk of invasive species occurrence - remote-sesning strategies

USDA-ARS?s Scientific Manuscript database

Remote sensing is a means to describe characteristics of an area without physically sampling the area. Remote sensors can be mounted on a satellite, plane, or other airborne structure. Remotely sensed data allow for landscape perspectives on management issues. Sensors measure the electromagnetic ene...

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

Identification of Potential High-Risk Habitats within the Transmission Reach of Oncomelania hupensis after Floods Based on SAR Techniques in a Plane Region in China

PubMed Central

Shi, Yuanyuan; Qiu, Juan; Li, Rendong; Shen, Qiang; Huang, Duan

2017-01-01

Schistosomiasis japonica is an infectious disease caused by Schistosoma japonicum, and it remains endemic in China. Flooding is the main hazard factor, as it causes the spread of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum, thereby triggering schistosomiasis outbreaks. Based on multi-source real-time remote sensing data, we used remote sensing (RS) technology, especially synthetic aperture radar (SAR), and geographic information system (GIS) techniques to carry out warning research on potential snail habitats within the snail dispersal range following flooding. Our research result demonstrated: (1) SAR data from Sentinel-1A before and during a flood were used to identify submerged areas rapidly and effectively; (2) the likelihood of snail survival was positively correlated with the clay proportion, core area standard deviation, and ditch length but negatively correlated with the wetness index, NDVI (normalized difference vegetation index), elevation, woodland area, and construction land area; (3) the snail habitats were most abundant near rivers and ditches in paddy fields; (4) the rivers and paddy irrigation ditches in the submerged areas must be the focused of mitigation efforts following future floods. PMID:28867814

Identification of Potential High-Risk Habitats within the Transmission Reach of Oncomelania hupensis after Floods Based on SAR Techniques in a Plane Region in China.

PubMed

Shi, Yuanyuan; Qiu, Juan; Li, Rendong; Shen, Qiang; Huang, Duan

2017-08-30

Schistosomiasis japonica is an infectious disease caused by Schistosoma japonicum , and it remains endemic in China. Flooding is the main hazard factor, as it causes the spread of Oncomelania hupensis , the only intermediate host of Schistosoma japonicum , thereby triggering schistosomiasis outbreaks. Based on multi-source real-time remote sensing data, we used remote sensing (RS) technology, especially synthetic aperture radar (SAR), and geographic information system (GIS) techniques to carry out warning research on potential snail habitats within the snail dispersal range following flooding. Our research result demonstrated: (1) SAR data from Sentinel-1A before and during a flood were used to identify submerged areas rapidly and effectively; (2) the likelihood of snail survival was positively correlated with the clay proportion, core area standard deviation, and ditch length but negatively correlated with the wetness index, NDVI (normalized difference vegetation index), elevation, woodland area, and construction land area; (3) the snail habitats were most abundant near rivers and ditches in paddy fields; (4) the rivers and paddy irrigation ditches in the submerged areas must be the focused of mitigation efforts following future floods.

Land movement monitoring at the Mavropigi lignite mine using spaceborne D-InSAR

NASA Astrophysics Data System (ADS)

Papadaki, Eirini; Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis; Schilizzi, Pavlos

2013-08-01

This paper examines the capability of remote sensing radar interferometry to monitor land movements, as it varies with time, in areas close to open pit lignite mines. The study area is the "Mavropigi" lignite mine in Ptolemais, Northern Greece; whose continuous operation is of vital importance to the electric power supply of Greece. The mine is presently 100-120m deep while horizontal and vertical movements have been measured in the vicinity of the pit. Within the mine, ground geodetic monitoring has revealed an average rate of movement amounting to 10-20mm/day at the southeast slopes. In this work, differential interferometry (DInSAR), using 19 Synthetic Aperture Radar (SAR) images of ALOS satellite, has been applied to monitor progression of land movement caused my mining within the greater area of "Mavropigi" region. The results of this work show that DInSAR can be used effectively to capture ground movement information, well before signs of movements can be observed visually in the form of imminent fissures and tension cracks. The advantage of remote sensing interferometry is that it can be applied even in inaccessible areas where monitoring with ground equipment is either impossible or of high-cost (large areas).

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.

Functional Connectivity Analysis of NIRS Data under Rubber Hand Illusion to Find a Biomarker of Sense of Ownership

PubMed Central

Arizono, Naoki

2016-01-01

The self-identification, which is called sense of ownership, has been researched through methodology of rubber hand illusion (RHI) because of its simple setup. Although studies with neuroimaging technique, such as fMRI, revealed that several brain areas are associated with the sense of ownership, near-infrared spectroscopy (NIRS) has not yet been utilized. Here we introduced an automated setup to induce RHI, measured the brain activity during the RHI with NIRS, and analyzed the functional connectivity so as to understand dynamical brain relationship regarding the sense of ownership. The connectivity was evaluated by multivariate Granger causality. In this experiment, the peaks of oxy-Hb on right frontal and right motor related areas during the illusion were significantly higher compared with those during the nonillusion. Furthermore, by analyzing the NIRS recordings, we found a reliable connectivity from the frontal to the motor related areas during the illusion. This finding suggests that frontal cortex and motor related areas communicate with each other when the sense of ownership is induced. The result suggests that the sense of ownership is related to neural mechanism underlying human motor control, and it would be determining whether motor learning (i.e., neural plasticity) will occur. Thus RHI with the functional connectivity analysis will become an appropriate biomarker for neurorehabilitation. PMID:27413556

Analysis of Urban Expansion of the Resort City of Al Ain Using Remote Sensing and GIS

NASA Astrophysics Data System (ADS)

Issa, S.; Al Shuwaihi, A.

2009-12-01

The urban growth of AL Ain city has been investigated using remote sensing data for three different dates, 1972, 1990 and 2000. We used three Landsat images together with socio-economic data in a post-classification analysis to map the spatial dynamics of land use/cover changes and identify the urbanization process in Al Ain resort city, United Arab Emirates. Land use/cover statistics, extracted from Landsat Multi-spectral Scanner (MSS). Thematic Mapper (TM) and Enhanced Thematic Mapper plus (ETM +) images for 1972. 1990 and 2000 respectively, revealed that the built-up area has expanded by about 170.53km2. The city was found to have a tendency for major expansion in four different directions: along the Abu Dhabi highway, along Dubai highway, Myziad direction and Hafeet recreational area. Expansion in any direction was found to be governed by the availability of road network, suitability for construction, utilities, economic activities, geographical constraints, and legal factors (boundary with Sultanate of Oman). The road network in particular has influenced the spatial patterns and structure of urban development, so that the expansion of the built-up areas has assumed an accretive as well as linear growth along the major roads. The research concludes that the development is based on conservation of agricultural areas (oases) and reclamation of the desert for farming and agricultural activities. The integration of remote sensing and GIS was found to be effective in monitoring LULC changes and providing valuable information necessary for planning and research.

Dancing with Gravity—Why the Sense of Balance Is (the) Fundamental

PubMed Central

2018-01-01

The sense of balance, which is usually barely noticeable in the background of each of our movements, only becomes manifest in its function during intense stimulation or in the event of illness, which may quite literally turn your world upside down. While it is true that balance is becoming a bigger issue, that is mainly because people are losing it more frequently. So why is balance not as commonly talked about in psychology, medicine or the arts as the other five traditional senses? This is partly due to its unusual multi-modal nature, whereby three sensory inputs are coordinated and integrated by the central nervous system. Without it, however, we might not have much use for the other senses. The sense of balance encompasses the bodily experience in its entirety. Not only do we act with the body, we may also think and feel through it and with it. Bodily states are not simply effects of cognition; they cause it as well. Equilibrioception is an essential sense and it is interconnected with a wide range of other areas, including cognition, perception, embodiment, the autonomic nervous system, aesthetics, the arts, and education. PMID:29303967

Dancing with Gravity-Why the Sense of Balance Is (the) Fundamental.

PubMed

Fuchs, Dominik

2018-01-05

The sense of balance, which is usually barely noticeable in the background of each of our movements, only becomes manifest in its function during intense stimulation or in the event of illness, which may quite literally turn your world upside down. While it is true that balance is becoming a bigger issue, that is mainly because people are losing it more frequently. So why is balance not as commonly talked about in psychology, medicine or the arts as the other five traditional senses? This is partly due to its unusual multi-modal nature, whereby three sensory inputs are coordinated and integrated by the central nervous system. Without it, however, we might not have much use for the other senses. The sense of balance encompasses the bodily experience in its entirety. Not only do we act with the body, we may also think and feel through it and with it. Bodily states are not simply effects of cognition; they cause it as well. Equilibrioception is an essential sense and it is interconnected with a wide range of other areas, including cognition, perception, embodiment, the autonomic nervous system, aesthetics, the arts, and education.

Cluster Method Analysis of K. S. C. Image

NASA Technical Reports Server (NTRS)

Rodriguez, Joe, Jr.; Desai, M.

1997-01-01

Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

Improving alpine-region spectral unmixing with optimal-fit snow endmembers

NASA Technical Reports Server (NTRS)

Painter, Thomas H.; Roberts, Dar A.; Green, Robert O.; Dozier, Jeff

1995-01-01

Surface albedo and snow-covered-area (SCA) are crucial inputs to the hydrologic and climatologic modeling of alpine and seasonally snow-covered areas. Because the spectral albedo and thermal regime of pure snow depend on grain size, areal distribution of snow grain size is required. Remote sensing has been shown to be an effective (and necessary) means of deriving maps of grain size distribution and snow-covered-area. Developed here is a technique whereby maps of grain size distribution improve estimates of SCA from spectral mixture analysis with AVIRIS data.

[Olfactory sensory perception].

PubMed

Fuentes, Aler; Fresno, María Javiera; Santander, Hugo; Valenzuela, Saúl; Gutiérrez, Mario Felipe; Miralles, Rodolfo

2011-03-01

The five senses have had a fundamental importance for survival and socialization of human beings. From an evolutionary point of view the sense of smell is the oldest. This sense has a strong representation within the genome, allowing the existence of many types of receptors that allow us to capture multiple volatile odor producing molecules, sending electrical signals to higher centers to report the outside world. Several cortical areas are activated in the brain, which are interconnected to form an extensive and complex neural network, linking for example, areas involved with memory and emotions, thus giving this sense of perceptual richness. While the concept of flavor is largely related to the sense of taste, smell provides the necessary integration with the rest of the senses and higher functions. Fully understanding the sense of smell is relevant to health professionals. Knowing the characteristics of the receptors, the transduction processes and convergence of information in the higher centers involved, we can properly detect olfactory disorders in our patients.

Natural resource inventory for urban planning utilizing remote sensing techniques

NASA Technical Reports Server (NTRS)

Foster, K. E.; Mackey, P. F.; Bonham, C. D.

1972-01-01

Remote sensing techniques were applied to the lower Pantano Wash area to acquire data for planning an ecological balance between the expanding Tucson metropolitan area and its environment. The types and distribution of vegetation are discussed along with the hydrologic aspects of the Wash.

A comparison between active and passive sensing of soil moisture from vegetated terrains

NASA Technical Reports Server (NTRS)

Fung, A. K.; Eom, H. J.

1985-01-01

A comparison between active and passive sensing of soil moisture over vegetated areas is studied via scattering models. In active sensing three contributing terms to radar backscattering can be identified: (1) the ground surface scatter term; (2) the volume scatter term representing scattering from the vegetation layer; and (3) the surface volume scatter term accounting for scattering from both surface and volume. In emission three sources of contribution can also be identified: (1) surface emission; (2) upward volume emission from the vegetation layer; and (3) downward volume emission scattered upward by the ground surface. As ground moisture increases, terms (1) and (3) increase due to increase in permittivity in the active case. However, in passive sensing, term (1) decreases but term (3) increases for the same reason. This self compensating effect produces a loss in sensitivity to change in ground moisture. Furthermore, emission from vegetation may be larger than that from the ground. Hence, the presence of vegetation layer causes a much greater loss of sensitivity to passive than active sensing of soil moisture.

A comparison between active and passive sensing of soil moisture from vegetated terrains

NASA Technical Reports Server (NTRS)

Fung, A. K.; Eom, H. J.

1984-01-01

A comparison between active and passive sensing of soil moisture over vegetated areas is studied via scattering models. In active sensing three contributing terms to radar backscattering can be identified: (1) the ground surface scatter term; (2) the volume scatter term representing scattering from the vegetation layer; and (3) the surface volume scatter term accounting for scattering from both surface and volume. In emission three sources of contribution can also be identified: (1) surface emission; (2) upward volume emission from the vegetation layer; and (3) downward volume emission scattered upward by the ground surface. As ground moisture increases, terms (1) and (3) increase due to increase in permittivity in the active case. However, in passive sensing, term (1) decreases but term (3) increases for the same reason. This self conpensating effect produces a loss in sensitivity to change in ground moisture. Furthermore, emission from vegetation may be larger than that from the ground. Hence, the presence of vegetation layer causes a much greater loss of sensitivity to passive than active sensing of soil moisture.

The construction, characterization, Hg(II)-sensing and removal behavior of magnetic core-shell nanospheres loaded with fluorescence "Off-On" probe

NASA Astrophysics Data System (ADS)

Tan, Jun; Wei, Xiaoyan; Chen, Jie; Sun, Ping; Ouyang, Yuxia; Fan, Juhong; Liu, Rui

2014-12-01

The present paper constructed and discussed core-shell structured nanospheres grafted with rhodamine based probe for Hg(II) sensing and removal. Electron microscopy images, XRD curves, thermogravimetric analysis and N2 adsorption/desorption isotherms were used to identify the core-shell structure. The inner core consisted of superparamagnetic Fe3O4 nanoparticles, which made the nanocomposite magnetically removable. The outer shell was constructed with silica molecular sieve which provided large surface area and ordered tunnels for the sensing probe, accelerating analyte adsorption and transportation. The rhodamine based sensing probe emission increased with the increasing Hg(II) concentration, showing emission "Off-On" effect, which could be explained by the structural transformation from a non-emissive one to a highly emissive one. The influence from various metal ions and pH values was also investigated, which suggested this structural transformation could only be triggered by Hg(II), showing high selectivity and linear response. The Hg(II) sensing nanocomposite could be regenerated after usage. The response time was slightly compromised and could be further improved.

Integrated amplifying nanowire FET for surface and bulk sensing

NASA Astrophysics Data System (ADS)

Chui, Chi On; Shin, Kyeong-Sik

2011-10-01

For over one decade, numerous research have been performed on field-effect transistor (FET) sensors with a quasi-onedimensional (1D) nanostructure channel demonstrating highly sensitive surface and bulk sensing. The high surface and bulk sensing sensitivity respectively arises from the inherently large surface area-to-volume ratio and tiny channel volume. The generic nanowire FET sensors, however, have limitations such as impractically low output current levels especially near the limit of detection (LOD) that would require downstream remote amplification with an appreciable amount of added noise. We have recently proposed and experimentally demonstrated an innovative amplifying nanowire FET sensor structure that seamlessly integrates therein a sensing nanowire and a nanowire FET amplifier. This novel sensor structure embraces the same geometrical advantage in quasi-1D nanostructure yet it offers unprecedented closeproximity signal amplification with the lowest possible added noise. In this paper, we review the device operating principle and amplification mechanism. We also present the prototype fabrication procedures, and surface and bulk sensing experimental results showing significantly enhanced output current level difference as predicted.

Urban land use: Remote sensing of ground-basin permeability

NASA Technical Reports Server (NTRS)

Tinney, L. R.; Jensen, J. R.; Estes, J. E.

1975-01-01

A remote sensing analysis of the amount and type of permeable and impermeable surfaces overlying an urban recharge basin is discussed. An effective methodology for accurately generating this data as input to a safe yield study is detailed and compared to more conventional alternative approaches. The amount of area inventoried, approximately 10 sq. miles, should provide a reliable base against which automatic pattern recognition algorithms, currently under investigation for this task, can be evaluated. If successful, such approaches can significantly reduce the time and effort involved in obtaining permeability data, an important aspect of urban hydrology dynamics.

Effect of metal stress on the thermal infrared emission of soybeans: A greenhouse experiment - Possible utility in remote sensing

NASA Technical Reports Server (NTRS)

Suresh, R.; Schwaller, M. R.; Foy, C. D.; Weidner, J. R.; Schnetzler, C. S.

1989-01-01

Manganese-sensitive forest and manganese-tolerant lee soybean cultivars were subjected to differential manganese stress in loring soil in a greenhouse experiment. Leaf temperature measurements were made using thermistors for forest and lee. Manganese-stressed plants had higher leaf temperatures than control plants in both forest and lee. Results of this experiment have potential applications in metal stress detection using remote sensing thermal infrared data over large areas of vegetation. This technique can be useful in reconnaissance mineral exploration in densely-vegetated regions where conventional ground-based methods are of little help.

Application of Remote Sensors in Mapping Rice Area and Forecasting Its Production: A Review

PubMed Central

Mosleh, Mostafa K.; Hassan, Quazi K.; Chowdhury, Ehsan H.

2015-01-01

Rice is one of the staple foods for more than three billion people worldwide. Rice paddies accounted for approximately 11.5% of the World's arable land area during 2012. Rice provided ∼19% of the global dietary energy in recent times and its annual average consumption per capita was ∼65 kg during 2010–2011. Therefore, rice area mapping and forecasting its production is important for food security, where demands often exceed production due to an ever increasing population. Timely and accurate estimation of rice areas and forecasting its production can provide invaluable information for governments, planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. The aim of this paper was to review the applicability of the remote sensing-based imagery for rice area mapping and forecasting its production. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the rice crop. For elaborative understanding of the application of remote sensing sensors, following issues were described: the rice area mapping and forecasting its production using optical and microwave imagery, synergy between remote sensing-based methods and other developments, and their implications as an operational one. The overview of the studies to date indicated that remote sensing-based methods using optical and microwave imagery found to be encouraging. However, there were having some limitations, such as: (i) optical remote sensing imagery had relatively low spatial resolution led to inaccurate estimation of rice areas; and (ii) radar imagery would suffer from speckles, which potentially would degrade the quality of the images; and also the brightness of the backscatters were sensitive to the interacting surface. In addition, most of the methods used in forecasting rice yield were empirical in nature, so thus it would require further calibration and validation prior to implement over other geographical locations. PMID:25569753

Application of remote sensors in mapping rice area and forecasting its production: a review.

PubMed

Mosleh, Mostafa K; Hassan, Quazi K; Chowdhury, Ehsan H

2015-01-05

Rice is one of the staple foods for more than three billion people worldwide. Rice paddies accounted for approximately 11.5% of the World's arable land area during 2012. Rice provided ~19% of the global dietary energy in recent times and its annual average consumption per capita was ~65 kg during 2010-2011. Therefore, rice area mapping and forecasting its production is important for food security, where demands often exceed production due to an ever increasing population. Timely and accurate estimation of rice areas and forecasting its production can provide invaluable information for governments, planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. The aim of this paper was to review the applicability of the remote sensing-based imagery for rice area mapping and forecasting its production. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the rice crop. For elaborative understanding of the application of remote sensing sensors, following issues were described: the rice area mapping and forecasting its production using optical and microwave imagery, synergy between remote sensing-based methods and other developments, and their implications as an operational one. The overview of the studies to date indicated that remote sensing-based methods using optical and microwave imagery found to be encouraging. However, there were having some limitations, such as: (i) optical remote sensing imagery had relatively low spatial resolution led to inaccurate estimation of rice areas; and (ii) radar imagery would suffer from speckles, which potentially would degrade the quality of the images; and also the brightness of the backscatters were sensitive to the interacting surface. In addition, most of the methods used in forecasting rice yield were empirical in nature, so thus it would require further calibration and validation prior to implement over other geographical locations.

STEM Integration: Solids, CAD, and 3D Printers

ERIC Educational Resources Information Center

Fujiwara, Yujiro

2018-01-01

While many students may struggle to make sense of a mathematical formula and its practical implications, they can benefit greatly from an intuitive visualization and the engineering application of the topic. Effective STEM programs create clear connections at least with two subject areas, which translates into an enhanced student learning…

The Hidden Toll

ERIC Educational Resources Information Center

Miles, Leonora

2008-01-01

Financial abuse is already one of the most prevalent areas of elder abuse. The effects of financial abuse can be as severe as physical abuse and, in this context, the infrequently used term "economic violence" conveys a more vivid sense of the devastating impact. The elder financial abuse project initiated by the National Institute of…

Periodical Microstructures Based on Novel Piezoelectric Material for Biomedical Applications.

PubMed

Janusas, Giedrius; Ponelyte, Sigita; Brunius, Alfredas; Guobiene, Asta; Prosycevas, Igoris; Vilkauskas, Andrius; Palevicius, Arvydas

2015-12-15

A novel cantilever type piezoelectric sensing element was developed. Cost-effective and simple fabrication design allows the use of this element for various applications in the areas of biomedicine, pharmacy, environmental analysis and biosensing. This paper proposes a novel piezoelectric composite material whose basic element is PZT and a sensing platform where this material was integrated. Results showed that a designed novel cantilever-type element is able to generate a voltage of up to 80 µV at 50 Hz frequency. To use this element for sensing purposes, a four micron periodical microstructure was imprinted. Silver nanoparticles were precipitated on the grating to increase the sensitivity of the designed element, i.e., Surface Plasmon Resonance (SPR) effect appears in the element. To tackle some issues (a lack of sensitivity, signal delays) the element must have certain electronic and optical properties. One possible solution, proposed in this paper, is a combination of piezoelectricity and SPR in a single element.

Remote sensing inputs to water demand modeling

NASA Technical Reports Server (NTRS)

Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

1975-01-01

In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

Needs and emerging trends of remote sensing

NASA Astrophysics Data System (ADS)

McNair, Michael

2014-06-01

From the earliest need to be able to see an enemy over a hill to sending semi-autonomous platforms with advanced sensor packages out into space, humans have wanted to know more about what is around them. Issues of distance are being minimized through advances in technology to the point where remote control of a sensor is useful but sensing by way of a non-collocated sensor is better. We are not content to just sense what is physically nearby. However, it is not always practical or possible to move sensors to an area of interest; we must be able to sense at a distance. This requires not only new technologies but new approaches; our need to sense at a distance is ever changing with newer challenges. As a result, remote sensing is not limited to relocating a sensor but is expanded into possibly deducing or inferring from available information. Sensing at a distance is the heart of remote sensing. Much of the sensing technology today is focused on analysis of electromagnetic radiation and sound. While these are important and the most mature areas of sensing, this paper seeks to identify future sensing possibilities by looking beyond light and sound. By drawing a parallel to the five human senses, we can then identify the existing and some of the future possibilities. A further narrowing of the field of sensing causes us to look specifically at robotic sensing. It is here that this paper will be directed.

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.

An analysis of the accuracy and cost-effectiveness of a cropland inventory utilizing remote sensing techniques

NASA Technical Reports Server (NTRS)

Jensen, J. R.; Tinney, L. R.; Estes, J. E.

1975-01-01

Cropland inventories utilizing high altitude and Landsat imagery were conducted in Kern County, California. It was found that in terms of the overall mean relative and absolute inventory accuracies, a Landsat multidate analysis yielded the most optimum results, i.e., 98% accuracy. The 1:125,000 CIR high altitude inventory is a serious alternative which can be very accurate (97% or more) if imagery is available for a specific study area. The operational remote sensing cropland inventories documented in this study are considered cost-effective. When compared to conventional survey costs of $62-66 per 10,000 acres, the Landsat and high-altitude inventories required only 3-5% of this amount, i.e., $1.97-2.98.

Field site selection

NASA Technical Reports Server (NTRS)

Schwarz, D. E.; Ellefsen, R. E.

1981-01-01

Several general guidelines should be kept in mind when considering the selection of field sites for teaching remote sensing fundamentals. Proximity and vantage point are two very practical considerations. Only through viewing a broad enough area to place the site in context can one make efficient use of a site. The effects of inclement weather when selecting sites should be considered. If field work is to be an effective tool to illustrate remote sensing principles, the following criteria are critical: (1) the site must represent the range of class interest; (2) the site must have a theme or add something no other site offers; (3) there should be intrasite variation within the theme; (4) ground resolution and spectral signature distinction should be illustrated; and (5) the sites should not be ordered sequentially.

Application of remote sensing to state and regional problems. [Mississippi

NASA Technical Reports Server (NTRS)

Miller, W. F.; Carter, B. D.; Solomon, J. L.; Williams, S. G.; Powers, J. S.; Clark, J. R. (Principal Investigator)

1980-01-01

Progress is reported in the following areas: remote sensing applications to land use planning Lowndes County, applications of LANDSAT data to strip mine inventory and reclamation, white tailed deer habitat evaluation using LANDSAT data, remote sensing data analysis support system, and discrimination of unique forest habitats in potential lignite areas of Mississippi. Other projects discussed include LANDSAT change discrimination in gravel operations, environmental impact modeling for highway corridors, and discrimination of fresh water wetlands for inventory and monitoring.

Monitoring of oil pollution in the Arabian Gulf based on medium resolution satellite imagery

NASA Astrophysics Data System (ADS)

Zhao, J.; Ghedira, H.

2013-12-01

A large number of inland and offshore oil fields are located in the Arabian Gulf where about 25% of the world's oil is produced by the countries surrounding the Arabian Gulf region. Almost all of this oil production is shipped by sea worldwide through the Strait of Hormuz making the region vulnerable to environmental and ecological threats that might arise from accidental or intentional oil spills. Remote sensing technologies have the unique capability to detect and monitor oil pollutions over large temporal and spatial scales. Synoptic satellite imaging can date back to 1972 when Landsat-1 was launched. Landsat satellite missions provide long time series of imagery with a spatial resolution of 30 m. MODIS sensors onboard NASA's Terra and Aqua satellites provide a wide and frequent coverage at medium spatial resolution, i.e. 250 m and 500, twice a day. In this study, the capability of medium resolution MODIS and Landsat data in detecting and monitoring oil pollutions in the Arabian Gulf was tested. Oil spills and slicks show negative or positive contrasts in satellite derived RGB images compared with surrounding clean waters depending on the solar/viewing geometry, oil thickness and evolution, etc. Oil-contaminated areas show different spectral characteristics compared with surrounding waters. Rayleigh-corrected reflectance at the seven medium resolution bands of MODIS is lower in oil affected areas. This is caused by high light absorption of oil slicks. 30-m Landsat image indicated the occurrence of oil spill on May 26 2000 in the Arabian Gulf. The oil spill showed positive contrast and lower temperature than surrounding areas. Floating algae index (FAI) images are also used to detect oil pollution. Oil-contaminated areas were found to have lower FAI values. To track the movement of oil slicks found on October 21 2007, ocean circulations from a HYCOM model were examined and demonstrated that the oil slicks were advected toward the coastal areas of United Arab Emirates (UAE). This can help to enable an early alarm for oil pollution and minimize the potential adverse effects. Remote sensing provides an effective tool for monitoring oil pollution. Medium resolution MODIS and Landsat data have shown to be effective in detecting oil pollution over small areas. Combined with remote sensing imagery, ocean circulation models demonstrate their unique value for developing a warning and forecasting system for oil pollution management.

Metal oxide nanostructures and their gas sensing properties: a review.

PubMed

Sun, Yu-Feng; Liu, Shao-Bo; Meng, Fan-Li; Liu, Jin-Yun; Jin, Zhen; Kong, Ling-Tao; Liu, Jin-Huai

2012-01-01

Metal oxide gas sensors are predominant solid-state gas detecting devices for domestic, commercial and industrial applications, which have many advantages such as low cost, easy production, and compact size. However, the performance of such sensors is significantly influenced by the morphology and structure of sensing materials, resulting in a great obstacle for gas sensors based on bulk materials or dense films to achieve highly-sensitive properties. Lots of metal oxide nanostructures have been developed to improve the gas sensing properties such as sensitivity, selectivity, response speed, and so on. Here, we provide a brief overview of metal oxide nanostructures and their gas sensing properties from the aspects of particle size, morphology and doping. When the particle size of metal oxide is close to or less than double thickness of the space-charge layer, the sensitivity of the sensor will increase remarkably, which would be called "small size effect", yet small size of metal oxide nanoparticles will be compactly sintered together during the film coating process which is disadvantage for gas diffusion in them. In view of those reasons, nanostructures with many kinds of shapes such as porous nanotubes, porous nanospheres and so on have been investigated, that not only possessed large surface area and relatively mass reactive sites, but also formed relatively loose film structures which is an advantage for gas diffusion. Besides, doping is also an effective method to decrease particle size and improve gas sensing properties. Therefore, the gas sensing properties of metal oxide nanostructures assembled by nanoparticles are reviewed in this article. The effect of doping is also summarized and finally the perspectives of metal oxide gas sensor are given.

Remote sensing utility in a disaster struck urban environment

NASA Technical Reports Server (NTRS)

Rush, M.; Holguin, A.

1976-01-01

Six major public health areas which might be affected by a natural disaster were identified. The functions and tasks associated with each area following a disaster, potential ways remote sensing could aid these functions, and the baseline data which would expedite problem solving associated with these functions are discussed.

Book Review: Book review

NASA Astrophysics Data System (ADS)

van der Linden, Sebastian

2016-05-01

Compiling a good book on urban remote sensing is probably as hard as the research in this disciplinary field itself. Urban areas comprise various environments and show high heterogeneity in many respects, they are highly dynamic in time and space and at the same time of greatest influence on connected and even tele-connected regions due to their great economic importance. Urban remote sensing is therefore of great importance, yet as manifold as its study area: mapping urban areas (or sub-categories thereof) plays an important (and challenging) role in land use and land cover (change) monitoring; the analysis of urban green and forests is by itself a specialization of ecological remote sensing; urban climatology asks for spatially and temporally highly resolved remote sensing products; the detection of artificial objects is not only a common and important remote sensing application but also a typical benchmark for image analysis techniques, etc. Urban analyses are performed with all available spaceborne sensor types and at the same time they are one of the most relevant fields for airborne remote sensing. Several books on urban remote sensing have been published during the past 10 years, each taking a different perspective. The book Global Urban Monitoring and Assessment through Earth Observation is motivated by the objectives of the Global Urban Observation and Information Task (SB-04) in the GEOSS (Global Earth Observation System of Systems) 2012-2015 workplan (compare Chapter 2) and wants to highlight the global aspects of state-of-the-art urban remote sensing.

Near-Real-Time Earth Observation Data Supporting Wildfire Management

NASA Astrophysics Data System (ADS)

Ambrosia, V. G.; Zajkowski, T.; Quayle, B.

2013-12-01

During disaster events, the most critical element needed by responding personnel and management teams is situational intelligence / awareness. During rapidly-evolving events such as wildfires, the need for timely information is critical to save lives, property and resources. The wildfire management agencies in the US rely heavily on remote sensing information both from airborne platforms as well as from orbital assets. The ability to readily have information from those systems, not just data, is critical to effective control and damage mitigation. NASA has been collaborating with the USFS to mature and operationalize various asset-information capabilities to effect improved knowledge of fire-prone areas, monitor wildfire events in real-time, assess effectiveness of fire management strategies, and provide rapid, post-fire assessment for recovery operations. Specific examples of near-real-time remote sensing asset utility include daily MODIS data employed to assess fire potential / wildfire hazard areas, and national-scale hot-spot detection, airborne thermal sensor collected during wildfire events to effect management strategies, EO-1 ALI 'pointable' satellite sensor data to assess fire-retardant application effectiveness, and Landsat 8 and other sensor data to derive burn severity indices for post-fire remediation work. These cases of where near-real-time data is used operationally during the previous few fire seasons will be presented.

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

Atmospheric Effects and Potential Climatic Impact of the 1980 Eruptions of Mount St. Helens

NASA Technical Reports Server (NTRS)

Deepak, A. (Editor)

1982-01-01

Measurements and studies of the 1980 Mount St. Helens volcanic eruptions and their atmospheric effects and climatic impact are addressed. Specific areas discussed include: (1) nature and impact of volcanic eruptions; (2) in situ measurements of effluents; (3) remote sensing measurements; (4) transport and dispersion of volcanic effluents; (5) chemistry of volcanic effluents; and (6) weather and potential climate impact.

Snowpack spatial variability: Towards understanding its effect on remote sensing measurements and snow slope stability

NASA Astrophysics Data System (ADS)

Marshall, Hans-Peter

The distribution of water in the snow-covered areas of the world is an important climate change indicator, and it is a vital component of the water cycle. At local and regional scales, the snow water equivalent (SWE), the amount of liquid water a given area of the snowpack represents, is very important for water resource management, flood forecasting, and prediction of available hydropower energy. Measurements from only a few automatic weather stations, such as the SNOTEL network, or sparse manual snowpack measurements are typically extrapolated for estimating SWE over an entire basin. Widespread spatial variability in the distribution of SWE and snowpack stratigraphy at local scales causes large errors in these basin estimates. Remote sensing measurements offer a promising alternative, due to their large spatial coverage and high temporal resolution. Although snow cover extent can currently be estimated from remote sensing data, accurately quantifying SWE from remote sensing measurements has remained difficult, due to a high sensitivity to variations in grain size and stratigraphy. In alpine snowpacks, the large degree of spatial variability of snowpack properties and geometry, caused by topographic, vegetative, and microclimatic effects, also makes prediction of snow avalanches very difficult. Ground-based radar and penetrometer measurements can quickly and accurately characterize snowpack properties and SWE in the field. A portable lightweight radar was developed, and allows a real-time estimate of SWE to within 10%, as well as measurements of depths of all major density transitions within the snowpack. New analysis techniques developed in this thesis allow accurate estimates of mechanical properties and an index of grain size to be retrieved from the SnowMicroPenetrometer. These two tools together allow rapid characterization of the snowpack's geometry, mechanical properties, and SWE, and are used to guide a finite element model to study the stress distribution on a slope. The ability to accurately characterize snowpack properties at much higher resolutions and spatial extent than previously possible will hopefully help lead to a more complete understanding of spatial variability, its effect on remote sensing measurements and snow slope stability, and result in improvements in avalanche prediction and accuracy of SWE estimates from space.

Decision Support Systems To Manage Water Resources At Irrigation District Level In Southern Italy Using Remote Sensing Information. An Integrated Project (AQUATER)

NASA Astrophysics Data System (ADS)

Rinaldi, M.; Castrignanò, A.; Mastrorilli, M.; Rana, G.; Ventrella, D.; Acutis, M.; D'Urso, G.; Mattia, F.

2006-08-01

An efficient management of water resources is crucial point for Italy and in particular for southern areas characterized by Mediterranean climate in order to improve the economical and environmental sustainability of the agricultural activity. A three-year Project (2005-2008) has been funded by the Italian Ministry of Agriculture and Forestry Policies; it involves four Italian research institutions: the Agricultural Research Council (ISA, Bari), the National Research Council (ISSIA, Bari) and two Universities (Federico II-Naples and Milan). It is focused on the remote sensing, the plant and the climate and, for interdisciplinary relationships, the project working group consists of agronomists, engineers and physicists. The aims of the Project are: a) to produce a Decision Support System (DSS) combining remote sensing information, spatial data and simulation models to manage water resources in irrigation districts; b) to simulate irrigation scenarios to evaluate the effects of water stress on crop yield using agro-ecological indicators; c) to identify the most sensitive areas to drought risk in Southern Italy. The tools used in this Project will be: 1. Remote sensing images, topographic maps, soil and land use maps; 2. Geographic Information Systems; 3. Geostatistic methodologies; 4. Ground truth measurements (land use, canopy and soil temperatures, soil and plant water status, Normalized Difference Vegetation Index, Crop Water Stress Index, Leaf Area Index, actual evapotranspiration, crop coefficients, crop yield, agro-ecological indicators); 5. Crop simulation models. The Project is structured in four work packages with specific objectives, high degree of interaction and information exchange: 1) Remote Sensing and Image Analysis; 2) Cropping Systems; 3) Modelling and Softwares Development; 4) Stakeholders. The final product will be a DSS with the purpose of integrating remote sensing images, to estimate crop and soil variables related to drought, to assimilate these variables into a simulation model at district scale and, finally, to estimate evapotranspiration, plant water status and drought indicators. A project Web home page, a technical course about DSS for the employers of irrigation authorities and dissemination of results (meetings, publications, reports), are also planned.

3D Modeling of Iran and Surrounding Areas from Simultaneous Inversion of Multiple Geophysical Datasets (Postprint). Annual Report 3

DTIC Science & Technology

2012-03-22

2003). This is particularly true at shallow depths where the shorter periods, which are primarily sensitive to upper crustal structures, are difficult...to measure, and especially true in tectonically and geologically complex areas. On the other hand, regional gravity inversions have the greatest...the slower deep crustal speeds into the Caspian region does not make sense geologically. These effects are driven by the simple Laplacian smoothness

Towards automatic lithological classification from remote sensing data using support vector machines

NASA Astrophysics Data System (ADS)

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

2010-05-01

Remote sensing data can be effectively used as a mean to build geological knowledge for poorly mapped terrains. Spectral remote sensing data from space- and air-borne sensors have been widely used to geological mapping, especially in areas of high outcrop density in arid regions. However, spectral remote sensing information by itself cannot be efficiently used for a comprehensive lithological classification of an area due to (1) diagnostic spectral response of a rock within an image pixel is conditioned by several factors including the atmospheric effects, spectral and spatial resolution of the image, sub-pixel level heterogeneity in chemical and mineralogical composition of the rock, presence of soil and vegetation cover; (2) only surface information and is therefore highly sensitive to the noise due to weathering, soil cover, and vegetation. Consequently, for efficient lithological classification, spectral remote sensing data needs to be supplemented with other remote sensing datasets that provide geomorphological and subsurface geological information, such as digital topographic model (DEM) and aeromagnetic data. Each of the datasets contain significant information about geology that, in conjunction, can potentially be used for automated lithological classification using supervised machine learning algorithms. In this study, support vector machine (SVM), which is a kernel-based supervised learning method, was applied to automated lithological classification of a study area in northwestern India using remote sensing data, namely, ASTER, DEM and aeromagnetic data. Several digital image processing techniques were used to produce derivative datasets that contained enhanced information relevant to lithological discrimination. A series of SVMs (trained using k-folder cross-validation with grid search) were tested using various combinations of input datasets selected from among 50 datasets including the original 14 ASTER bands and 36 derivative datasets (including 14 principal component bands, 14 independent component bands, 3 band ratios, 3 DEM derivatives: slope/curvatureroughness and 2 aeromagnetic derivatives: mean and variance of susceptibility) extracted from the ASTER, DEM and aeromagnetic data, in order to determine the optimal inputs that provide the highest classification accuracy. It was found that a combination of ASTER-derived independent components, principal components and band ratios, DEM-derived slope, curvature and roughness, and aeromagnetic-derived mean and variance of magnetic susceptibility provide the highest classification accuracy of 93.4% on independent test samples. A comparison of the classification results of the SVM with those of maximum likelihood (84.9%) and minimum distance (38.4%) classifiers clearly show that the SVM algorithm returns much higher classification accuracy. Therefore, the SVM method can be used to produce quick and reliable geological maps from scarce geological information, which is still the case with many under-developed frontier regions of the world.

One-Dimensional Nanostructure Field-Effect Sensors for Gas Detection

PubMed Central

Zhao, Xiaoli; Cai, Bin; Tang, Qingxin; Tong, Yanhong; Liu, Yichun

2014-01-01

Recently; one-dimensional (1D) nanostructure field-effect transistors (FETs) have attracted much attention because of their potential application in gas sensing. Micro/nanoscaled field-effect sensors combine the advantages of 1D nanostructures and the characteristic of field modulation. 1D nanostructures provide a large surface area-volume ratio; which is an outstanding advantage for gas sensors with high sensitivity and fast response. In addition; the nature of the single crystals is favorable for the studies of the response mechanism. On the other hand; one main merit of the field-effect sensors is to provide an extra gate electrode to realize the current modulation; so that the sensitivity can be dramatically enhanced by changing the conductivity when operating the sensors in the subthreshold regime. This article reviews the recent developments in the field of 1D nanostructure FET for gas detection. The sensor configuration; the performance as well as their sensing mechanism are evaluated. PMID:25090418

Occupant traffic estimation through structural vibration sensing

NASA Astrophysics Data System (ADS)

Pan, Shijia; Mirshekari, Mostafa; Zhang, Pei; Noh, Hae Young

2016-04-01

The number of people passing through different indoor areas is useful in various smart structure applications, including occupancy-based building energy/space management, marketing research, security, etc. Existing approaches to estimate occupant traffic include vision-, sound-, and radio-based (mobile) sensing methods, which have placement limitations (e.g., requirement of line-of-sight, quiet environment, carrying a device all the time). Such limitations make these direct sensing approaches difficult to deploy and maintain. An indirect approach using geophones to measure floor vibration induced by footsteps can be utilized. However, the main challenge lies in distinguishing multiple simultaneous walkers by developing features that can effectively represent the number of mixed signals and characterize the selected features under different traffic conditions. This paper presents a method to monitor multiple persons. Once the vibration signals are obtained, features are extracted to describe the overlapping vibration signals induced by multiple footsteps, which are used for occupancy traffic estimation. In particular, we focus on analysis of the efficiency and limitations of the four selected key features when used for estimating various traffic conditions. We characterize these features with signals collected from controlled impulse load tests as well as from multiple people walking through a real-world sensing area. In our experiments, the system achieves the mean estimation error of +/-0.2 people for different occupant traffic conditions (from one to four) using k-nearest neighbor classifier.

Fundamental remote sensing science research program: The Scene Radiation and Atmospheric Effects Characterization Project

NASA Technical Reports Server (NTRS)

Deering, D. W.

1985-01-01

The Scene Radiation and Atmospheric Effects Characterization (SRAEC) Project was established within the NASA Fundamental Remote Sensing Science Research Program to improve our understanding of the fundamental relationships of energy interactions between the sensor and the surface target, including the effect of the atmosphere. The current studies are generalized into the following five subject areas: optical scene modeling, Earth-space radiative transfer, electromagnetic properties of surface materials, microwave scene modeling, and scatterometry studies. This report has been prepared to provide a brief overview of the SRAEC Project history and objectives and to report on the scientific findings and project accomplishments made by the nineteen principal investigators since the project's initiation just over three years ago. This annual summary report derives from the most recent annual principal investigators meeting held January 29 to 31, 1985.

Combining remote sensing image with DEM to identify ancient Minqin Oasis, northwest of China

NASA Astrophysics Data System (ADS)

Xie, Yaowen

2008-10-01

The developing and desertification process of Minqin oasis is representative in the whole arid area of northwest China. Combining Remote Sensing image with Digital Elevation Model (DEM) can produce the three-dimensional image of the research area which can give prominence to the spatial background of historical geography phenomenon's distribution, providing the conditions for extracting and analyzing historical geographical information thoroughly. This research rebuilds the ancient artificial Oasis based on the three-dimensional images produced by the TM digital Remote Sensing image and DEM created using 1:100000 topographic maps. The result indicates that the whole area of the ancient artificial oasis in Minqin Basin over the whole historical period reaches 321km2, in the form of discontinuous sheet, separated on the two banks of ancient Shiyang River and its branches, namely, Xishawo area, west to modern Minqin Basin and Zhongshawo area, in the center of the oasis. Except for a little of the ancient oasis unceasingly used by later people, most of it became desert. The combination of digital Remote Sensing image and DEM can integrate the advantages of both in identifying ancient oasis and improve the interpreting accuracy greatly.

Young Children's Number Sense Development: Age Related Complexity across Cases of Three Children

ERIC Educational Resources Information Center

Yilmaz, Zuhal

2017-01-01

Children start to develop number sense even well before they start the school. Developing number sense serves as an intermediate tool for learning conventional mathematics taught in schools. This number sense has three key areas: number knowledge, counting and arithmetic operations. As a result, the aim of this study was to examine aged related…

Rapid Assessment of Wave Height Transformation through a Tidal Inlet via Radar Remote Sensing

NASA Astrophysics Data System (ADS)

Díaz Méndez, G.; Haller, M. C.; Raubenheimer, B.; Elgar, S.; Honegger, D.

2014-12-01

Radar has the potential to enable temporally and spatially dense, continuous monitoring of waves and currents in nearshore environments. If quantitative relationships between the remote sensing signals and the hydrodynamic parameters of interest can be found, remote sensing techniques can mitigate the challenges of continuous in situ sampling and possibly enable a better understanding of wave transformation in areas with strongly inhomogeneous along and across-shore bathymetry, currents, and dissipation. As part of the DARLA experiment (New River Inlet, NC), the accuracy of a rapid assessment of wave height transformation via radar remote sensing is tested. Wave breaking events are identified in the radar image time series (Catalán et al. 2011). Once the total number of breaking waves (per radar collection) is mapped throughout the imaging domain, radar-derived bathymetry and wave frequency are used to compute wave breaking dissipation (Janssen and Battjes 2007). Given the wave breaking dissipation, the wave height transformation is calculated by finding an inverse solution to the 1D cross-shore energy flux equation (including the effect of refraction). The predicted wave height transformation is consistent (correlation R > 0.9 and rmse as low as 0.1 m) with the transformation observed with in situ sensors in an area of complex morphology and strong (> 1 m/s) tidal currents over a nine-day period. The wave forcing (i.e., radiation stress gradients) determined from the remote sensing methodology will be compared with values estimated with in situ sensors. Funded by ONR and ASD(R&E)

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

Research on Remote Sensing Geological Information Extraction Based on Object Oriented Classification

NASA Astrophysics Data System (ADS)

Gao, Hui

2018-04-01

The northern Tibet belongs to the Sub cold arid climate zone in the plateau. It is rarely visited by people. The geological working conditions are very poor. However, the stratum exposures are good and human interference is very small. Therefore, the research on the automatic classification and extraction of remote sensing geological information has typical significance and good application prospect. Based on the object-oriented classification in Northern Tibet, using the Worldview2 high-resolution remote sensing data, combined with the tectonic information and image enhancement, the lithological spectral features, shape features, spatial locations and topological relations of various geological information are excavated. By setting the threshold, based on the hierarchical classification, eight kinds of geological information were classified and extracted. Compared with the existing geological maps, the accuracy analysis shows that the overall accuracy reached 87.8561 %, indicating that the classification-oriented method is effective and feasible for this study area and provides a new idea for the automatic extraction of remote sensing geological information.

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.

An empirical model to estimate daily forest fire smoke exposure over a large geographic area using air quality, meteorological, and remote sensing data

PubMed Central

Yao, Jiayun; Henderson, Sarah B

2014-01-01

Exposure to forest fire smoke (FFS) is associated with a range of adverse health effects. The British Columbia Asthma Medication Surveillance (BCAMS) product was developed to detect potential impacts from FFS in British Columbia (BC), Canada. However, it has been a challenge to estimate FFS exposure with sufficient spatial coverage for the provincial population. We constructed an empirical model to estimate FFS-related fine particulate matter (PM2.5) for all populated areas of BC using data from the most extreme FFS days in 2003 through 2012. The input data included PM2.5 measurements on the previous day, remotely sensed aerosols, remotely sensed fires, hand-drawn tracings of smoke plumes from satellite images, fire danger ratings, and the atmospheric venting index. The final model explained 71% of the variance in PM2.5 observations. Model performance was tested in days with high, moderate, and low levels of FFS, resulting in correlations from 0.57 to 0.83. We also developed a method to assign the model estimates to geographical local health areas for use in BCAMS. The simplicity of the model allows easy application in time-constrained public health surveillance, and its sufficient spatial coverage suggests utility as an exposure assessment tool for epidemiologic studies on FFS exposure. PMID:24301352

Global response of the growing season to soil moisture and topography

NASA Astrophysics Data System (ADS)

Guevara, M.; Arroyo, C.; Warner, D. L.; Equihua, J.; Lule, A. V.; Schwartz, A.; Taufer, M.; Vargas, R.

2017-12-01

Soil moisture has a direct influence in plant productivity. Plant productivity and its greenness can be inferred by remote sensing with higher spatial detail than soil moisture. The objective was to improve the coarse scale of currently available satellite soil moisture estimates and identify areas of strong coupling between the interannual variability soil moisture and the maximum greenness vegetation fraction (MGVF) at the global scale. We modeled, cross-validated and downscaled remotely sensed soil moisture using machine learning and digital terrain analysis across 23 years (1991-2013) of available data. Improving the accuracy (0.69-0.87 % of cross-validated explained variance) and the spatial detail (from 27 to 15km) of satellite soil moisture, we filled temporal gaps of information across vegetated areas where satellite soil moisture does not work properly. We found that 7.57% of global vegetated area shows strong correlation with our downscaled product (R2>0.5, Fig. 1). We found a dominant positive response of vegetation greenness to topography-based soil moisture across water limited environments, however, the tropics and temperate environments of higher latitudes showed a sparse negative response. We conclude that topography can be used to effectively improve the spatial detail of globally available remotely sensed soil moisture, which is convenient to generate unbiased comparisons with global vegetation dynamics, and better inform land and crop modeling efforts.

View angle effects on relationships between leaf area index in wheat and vegetation indices

NASA Astrophysics Data System (ADS)

Chen, H.; Li, W.; Huang, W.; Niu, Z.

2016-12-01

The effects of plant types and view angles on the canopy-reflected spectrum can not be ignored in the estimation of leaf area index (LAI) using remote sensing vegetation indices. While vegetation indices derived from nadir-viewing remote sensors are insufficient in leaf area index (LAI) estimation because of its misinterpretation of structural characteristecs, vegetation indices derived from multi-angular remote sensors have potential to improve detection of LAI. However, view angle effects on relationships between these indices and LAI for low standing crops (i.e. wheat) has not been fully evaluated and thus limits them to applied for consistent and accurate monitoring of vegetation. View angles effects of two types of winter wheat (wheat 411, erectophile; and wheat 9507, planophile) on relationship between LAI and spectral reflectance are assessed and compared in this study. An evaluation is conducted with in-situ measurements of LAI and bidirectional reflectance in the principal plane from -60° (back-scattering direction ) ot 60° (forward scattering direction) in the growth cycle of winter wheat. A variety of vegetation indices (VIs) published are calculated by BRDF. Additionally, all combinations of the bands are used in order to calculate Normalized difference Spectral Indices (NDSI) and Simple Subtraction Indices (SSI). The performance of the above indices along with raw reflectance and reflectance derivatives on LAI estimation are examined based on a linearity comparison. The results will be helpful in further developing multi-angle remote sensing models for accurate LAI evaluation.

Remote sensing study of land use and sedimentation in the Ross Barnett Reservoir, Jackson, Mississippi area

NASA Technical Reports Server (NTRS)

Mealor, W. T., Jr.; Pinson, T. W.; Wertz, D. L.; Hoskin, C. M.; Williams, D. C.

1972-01-01

This multi-year study is aimed at focusing on the recognition of sediment and other affluents in a selected area of the Ross Barnett Reservoir. The principle objectives are the determination of land use types, effect of land use on erosion, and the correlation of sediment with land use in the area. The I2S multi-band imagery was employed in conjunction with ground truth data for both water and land use studies. The selected test site contains approximately forty square miles including forest, open land, and water in addition to residential and recreational areas.

Coupling Analysis of Heat Island Effects, Vegetation Coverage and Urban Flood in Wuhan

NASA Astrophysics Data System (ADS)

Liu, Y.; Liu, Q.; Fan, W.; Wang, G.

2018-04-01

In this paper, satellite image, remote sensing technique and geographic information system technique are main technical bases. Spectral and other factors comprehensive analysis and visual interpretation are main methods. We use GF-1 and Landsat8 remote sensing satellite image of Wuhan as data source, and from which we extract vegetation distribution, urban heat island relative intensity distribution map and urban flood submergence range. Based on the extracted information, through spatial analysis and regression analysis, we find correlations among heat island effect, vegetation coverage and urban flood. The results show that there is a high degree of overlap between of urban heat island and urban flood. The area of urban heat island has buildings with little vegetation cover, which may be one of the reasons for the local heavy rainstorms. Furthermore, the urban heat island has a negative correlation with vegetation coverage, and the heat island effect can be alleviated by the vegetation to a certain extent. So it is easy to understand that the new industrial zones and commercial areas which under constructions distribute in the city, these land surfaces becoming bare or have low vegetation coverage, can form new heat islands easily.

Effects of simultaneously elevated temperature and CO2 levels on Nicotiana benthamiana and its infection by different positive-sense RNA viruses are cumulative and virus type-specific.

PubMed

Del Toro, Francisco J; Rakhshandehroo, Farshad; Larruy, Beatriz; Aguilar, Emmanuel; Tenllado, Francisco; Canto, Tomás

2017-11-01

We have studied how simultaneously elevated temperature and CO 2 levels [climate change-related conditions (CCC) of 30°C, 970 parts-per-million (ppm) of CO 2 vs. standard conditions (SC) of 25°C, ~ 405ppm CO 2 ] affect physiochemical properties of Nicotiana benthamiana leaves, and also its infection by several positive-sense RNA viruses. In previous works we had studied effects of elevated temperature, CO 2 levels separately. Under CCC, leaves of healthy plants almost doubled their area relative to SC but contained less protein/unit-of-area, similarly to what we had found under conditions of elevated CO 2 alone. CCC also affected the sizes/numbers of different foliar cell types differently. Under CCC, infection outcomes in titers and symptoms were virus type-specific, broadly similar to those observed under elevated temperature alone. Under either condition, infections did not significantly alter the protein content of leaf discs. Therefore, effects of elevated temperature and CO 2 combined on properties of the pathosystems studied were overall cumulative. Copyright © 2017 Elsevier Inc. All rights reserved.

Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010.

PubMed

Qian, Xiaojin; Liang, Liang; Shen, Qiu; Sun, Qin; Zhang, Lianpeng; Liu, Zhixiao; Zhao, Shuhe; Qin, Zhihao

2016-11-01

Drought is a type of natural disaster that has the most significant impacts on agriculture. Regional drought monitoring based on remote sensing has become popular due to the development of remote sensing technology. In this study, vegetation condition index (VCI) data recorded from 1982 to 2010 in agricultural areas of China were obtained from advanced very high resolution radiometer (AVHRR) data, and the temporal and spatial variations in each drought were analyzed. The relationships between drought and climate factors were also analyzed. The results showed that from 1982 to 2010, the agricultural areas that experienced frequent and severe droughts were mainly concentrated in the northwestern areas and Huang-Huai Plain. Moreover, the VCI increased in the majority of agricultural areas, indicating that the drought frequency decreased over time, and the decreasing trend in the southern region was more notable than that in the northern region. A correlation analysis showed that temperature and wind velocity were the main factors that influenced drought in the agricultural areas of China. From a regional perspective, excluding precipitation, the climate factors had various effects on drought in different regions. However, the correlation between the VCI and precipitation was low, possibly due to the widespread use of artificial irrigation technology, which reduces the reliance of agricultural areas on precipitation.

Development of predictive mapping techniques for soil survey and salinity mapping

NASA Astrophysics Data System (ADS)

Elnaggar, Abdelhamid A.

Conventional soil maps represent a valuable source of information about soil characteristics, however they are subjective, very expensive, and time-consuming to prepare. Also, they do not include explicit information about the conceptual mental model used in developing them nor information about their accuracy, in addition to the error associated with them. Decision tree analysis (DTA) was successfully used in retrieving the expert knowledge embedded in old soil survey data. This knowledge was efficiently used in developing predictive soil maps for the study areas in Benton and Malheur Counties, Oregon and accessing their consistency. A retrieved soil-landscape model from a reference area in Harney County was extrapolated to develop a preliminary soil map for the neighboring unmapped part of Malheur County. The developed map had a low prediction accuracy and only a few soil map units (SMUs) were predicted with significant accuracy, mostly those shallow SMUs that have either a lithic contact with the bedrock or developed on a duripan. On the other hand, the developed soil map based on field data was predicted with very high accuracy (overall was about 97%). Salt-affected areas of the Malheur County study area are indicated by their high spectral reflectance and they are easily discriminated from the remote sensing data. However, remote sensing data fails to distinguish between the different classes of soil salinity. Using the DTA method, five classes of soil salinity were successfully predicted with an overall accuracy of about 99%. Moreover, the calculated area of salt-affected soil was overestimated when mapped using remote sensing data compared to that predicted by using DTA. Hence, DTA could be a very helpful approach in developing soil survey and soil salinity maps in more objective, effective, less-expensive and quicker ways based on field data.

Timing constraints on remote sensing of wildland fire burned area in the southeastern US

USGS Publications Warehouse

Picotte, J.J.; Robertson, K.

2011-01-01

Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78-90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy. ?? 2011 by the authors.

Timing constraints on remote sensing of wildland fire burned area in the southeastern US

USGS Publications Warehouse

Picotte, Joshua J.; Robertson, Kevin

2011-01-01

Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.

Gas-sensing enhancement methods for hydrothermal synthesized SnO2-based sensors

NASA Astrophysics Data System (ADS)

Zhao, Yalei; Zhang, Wenlong; Yang, Bin; Liu, Jingquan; Chen, Xiang; Wang, Xiaolin; Yang, Chunsheng

2017-11-01

Gas sensing for hydrothermal synthesized SnO2-based gas sensors can be enhanced in three ways: structural improvement, composition optimization, and processing improvement. There have been zero-dimensional, one-dimensional, and three-dimensional structures reported in the literature. Controllable synthesis of different structures has been deployed to increase specific surface area. Change of composition would intensively tailor the SnO2 structure, which affected the gas-sensing performance. Furthermore, doping and compounding methods have been adopted to promote gas-sensing performance by adjusting surface conditions of SnO2 crystals and constructing heterojunctions. As for processing area, it is very important to find the optimal reaction time and temperature. In this paper, a gas-solid reaction rate constant was proposed to evaluate gas-sensing properties and find an excellent hydrothermal synthesized SnO2-based gas sensor.

ANALYZING THE CONSEQUENCES OF ENVIRONMENTAL SPATIAL PATTERNS ON ENVIRONMENTAL RESOURCES: THE USE OF LANDSCAPE METRICS GENERATED FROM REMOTE SENSING DATA

EPA Science Inventory

A number of existing and new remote sensing data provide images of areas ranging from small communities to continents. These images provide views on a wide range of physical features in the landscape, including vegetation, road infrastructure, urban areas, geology, soils, and wa...

Optical and Physical Methods for Mapping Flooding with Satellite Imagery

NASA Technical Reports Server (NTRS)

Fayne, Jessica Fayne; Bolten, John; Lakshmi, Venkat; Ahamed, Aakash

2016-01-01

Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

Remote sensing analysis of Lake Livingston aquatic plants

NASA Technical Reports Server (NTRS)

Benton, A. R., Jr.; Newman, R. M.

1976-01-01

Results obtained during 1975 to monitor the growth of aquatic plants in the Lake Livingston area, using remote sensing photographic imagery, were described. Sequential total coverage was provided of the Jungle and White Rock Creek, plus coverage of smaller areas of localized infestation downlake, including Brushy Creek, KOA Kampground Marina, Penwaugh Slough, Memorial Point Marina, the Beacon Bay marinas and Pine Island. The imagery was generally good, photographic exposure being increased as the season progressed in order to obtain better pictures of the submerged vegetation. Some very significant differences in growth patterns, species interaction, and species dominance were observed when compared to 1974. Observation of the following plants was discussed: water hyacinth, hydrilla, coontail, potamageton. In general, the level of infestation was lower in 1975 than in 1974, due to the combined effect of more systematic application of herbicides and harsher intervening winter weather conditions.

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

NASA Technical Reports Server (NTRS)

Korram, S.

1977-01-01

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

Area-variable capacitive microaccelerometer with force-balancing electrodes

NASA Astrophysics Data System (ADS)

Ha, Byeoungju; Lee, Byeungleul; Sung, Sangkyung; Choi, Sangon; Shinn, Meenam; Oh, Yong-Soo; Song, Ci M.

1997-11-01

A surface micromachined accelerometer which senses an inertial motion with an area variation and a force balancing electrodes is developed. The grid-type planar mass of a 7 micrometers thick polysilicon is supported by four thin beams and suspended above a silicon substrate with a 1.5 micrometers air gap. The motion sensing electrodes are formed on the substrate. The sensor is designed as an interdigital rib structure that has a differential capacitor arrangement. The moveable electrodes are mounted on the mass and the pairs of the stationary electrodes are patterned on the substrate. In the accelerometer that has comb-type movable electrodes, the mechanical stress and the electrical pulling effects between a moveable electrodes and the fixed electrodes occur. However this grid-type structure can have a large area variation in a small area relatively without stress and pulling, high sensitivity can be achieved. In order to improve the dynamic rang and a linearity, a pair of comb shape force-balancing electrodes are implemented on both sides of the mass. The force-balancing electrodes are made of the same layer as the mass and anchored on a silicon substrate. When acceleration is applied in the lateral direction, the difference of capacitance results from the area variation between the two capacitors and is measured using a charge amplifier. As AC coupled complimentary pick- off signals are applied in paris of stationary electrodes, the undesirable effects due to temperature and electrical noise are reduced effectively. The accelerometer has a sensitivity of 28mV/g and a bandwidth of DC-120Hz. A resolution of 3mg and a non-linearity of 1.3 percent is achieved for a measurement range of +/- 9 g.

Chronology of Fabry-Perot Interferometer Fiber-Optic Sensors and Their Applications: A Review

PubMed Central

Islam, Md. Rajibul; Ali, Muhammad Mahmood; Lai, Man-Hong; Lim, Kok-Sing; Ahmad, Harith

2014-01-01

Optical fibers have been involved in the area of sensing applications for more than four decades. Moreover, interferometric optical fiber sensors have attracted broad interest for their prospective applications in sensing temperature, refractive index, strain measurement, pressure, acoustic wave, vibration, magnetic field, and voltage. During this time, numerous types of interferometers have been developed such as Fabry-Perot, Michelson, Mach-Zehnder, Sagnac Fiber, and Common-path interferometers. Fabry-Perot interferometer (FPI) fiber-optic sensors have been extensively investigated for their exceedingly effective, simple fabrication as well as low cost aspects. In this study, a wide variety of FPI sensors are reviewed in terms of fabrication methods, principle of operation and their sensing applications. The chronology of the development of FPI sensors and their implementation in various applications are discussed. PMID:24763250

A Merging Approach for Urban Boundary Correction Acquired By Remote Sensing Images

NASA Astrophysics Data System (ADS)

Zhang, P. L.; Shi, W. Z.; Wu, X. Y.

2014-11-01

Since reform and opening up to outside world, ever-growing economy and development of urbanization of China have caused expansion of the urban land scale. It's necessary to grasp the information about urban spatial form change, expansion situation and expanding regularity, in order to provide the scientific basis for urban management and planning. The traditional methods, like land supply cumulative method and remote sensing, to get the urban area, existed some defects. Their results always doesn't accord with the reality, and can't reflects the actual size of the urban area. Therefore, we propose a new method, making the best use of remote sensing, the population data, road data and other social economic statistic data. Because urban boundary not only expresses a geographical concept, also a social economic systems.It's inaccurate to describe urban area with only geographic areas. We firstly use remote sensing images, demographic data, road data and other data to produce urban boundary respectively. Then we choose the weight value for each boundary, and in terms of a certain model the ultimate boundary can be obtained by a series of calculations of previous boundaries. To verify the validity of this method, we design a set of experiments and obtained the preliminary results. The results have shown that this method can extract the urban area well and conforms with both the broad and narrow sense. Compared with the traditional methods, it's more real-time, objective and ornamental.

City-Level Adult Stroke Prevalence in Relation to Remote Sensing Derived PM2.5 Adjusting for Unhealthy Behaviors and Medical Risk Factors

NASA Astrophysics Data System (ADS)

Hu, Z.

2018-04-01

This research explores the use of PM2.5 gird derived from remote sensing for assessing the effect of long-term exposure to PM2.5 (ambient air pollution of particulate matter with an aerodynamic diameter of 2.5 μm or less) on stroke, adjusting for unhealthy behaviors and medical risk factors. Health data was obtained from the newly published CDC "500 Cities Project" which provides city- and census tract-level small area estimates for chronic disease risk factors, and clinical preventive service use for the largest 500 cities in the United States. PM2.5 data was acquired from the "The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), V1 (1998-2012)" datasets. Average PM2.5 were calculated for each city using a GIS zonal statistics function. Map data visualization and pattern comparison, univariate linear regression, and a multivariate linear regression model fitted using a generalized linear model via penalized maximum likelihood found that long-term exposure to ambient PM2.5 may increase the risk of stroke. Increasing physical activity, reducing smoking and body weight, enough sleeping, controlling diseases such as blood pressure, coronary heart disease, diabetes, and cholesterol, may mitigate the effect. PM2.5 grids derived from moderate resolution satellite remote sensing imagery may offer a unique opportunity to fill the data gap due to limited ground monitoring at broader scales. The evidence of raised stroke prevalence risk in high PM2.5 areas would support targeting of policy interventions on such areas to reduce pollution levels and protect human health.

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series.

PubMed

Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

2016-04-19

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series

PubMed Central

Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

2016-01-01

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. PMID:27104536

A GIS and statistical approach to identify variables that control water quality in hydrothermally altered and mineralized watersheds, Silverton, Colorado, USA

USGS Publications Warehouse

Yager, Douglas B.; Johnson, Raymond H.; Rockwell, Barnaby W.; Caine, Jonathan S.; Smith, Kathleen S.

2013-01-01

Hydrothermally altered bedrock in the Silverton mining area, southwest Colorado, USA, contains sulfide minerals that weather to produce acidic and metal-rich leachate that is toxic to aquatic life. This study utilized a geographic information system (GIS) and statistical approach to identify watershed-scale geologic variables in the Silverton area that influence water quality. GIS analysis of mineral maps produced using remote sensing datasets including Landsat Thematic Mapper, advanced spaceborne thermal emission and reflection radiometer, and a hybrid airborne visible infrared imaging spectrometer and field-based product enabled areas of alteration to be quantified. Correlations between water quality signatures determined at watershed outlets, and alteration types intersecting both total watershed areas and GIS-buffered areas along streams were tested using linear regression analysis. Despite remote sensing datasets having varying watershed area coverage due to vegetation cover and differing mineral mapping capabilities, each dataset was useful for delineating acid-generating bedrock. Areas of quartz–sericite–pyrite mapped by AVIRIS have the highest correlations with acidic surface water and elevated iron and aluminum concentrations. Alkalinity was only correlated with area of acid neutralizing, propylitically altered bedrock containing calcite and chlorite mapped by AVIRIS. Total watershed area of acid-generating bedrock is more significantly correlated with acidic and metal-rich surface water when compared with acid-generating bedrock intersected by GIS-buffered areas along streams. This methodology could be useful in assessing the possible effects that alteration type area has in either generating or neutralizing acidity in unmined watersheds and in areas where new mining is planned.

Infrared super-resolution imaging based on compressed sensing

NASA Astrophysics Data System (ADS)

Sui, Xiubao; Chen, Qian; Gu, Guohua; Shen, Xuewei

2014-03-01

The theoretical basis of traditional infrared super-resolution imaging method is Nyquist sampling theorem. The reconstruction premise is that the relative positions of the infrared objects in the low-resolution image sequences should keep fixed and the image restoration means is the inverse operation of ill-posed issues without fixed rules. The super-resolution reconstruction ability of the infrared image, algorithm's application area and stability of reconstruction algorithm are limited. To this end, we proposed super-resolution reconstruction method based on compressed sensing in this paper. In the method, we selected Toeplitz matrix as the measurement matrix and realized it by phase mask method. We researched complementary matching pursuit algorithm and selected it as the recovery algorithm. In order to adapt to the moving target and decrease imaging time, we take use of area infrared focal plane array to acquire multiple measurements at one time. Theoretically, the method breaks though Nyquist sampling theorem and can greatly improve the spatial resolution of the infrared image. The last image contrast and experiment data indicate that our method is effective in improving resolution of infrared images and is superior than some traditional super-resolution imaging method. The compressed sensing super-resolution method is expected to have a wide application prospect.

Porous glass makes effective substrate for ozone-sensing reagent

NASA Technical Reports Server (NTRS)

1965-01-01

Porous-glass substrate is used for absorption of a dye used in measuring the concentration of atmospheric ozone at high altitudes. This measurement is based on the chemiluminescence produced in the reaction between ozone and the dye, rhodamine B. The porous glass provides a large interstitial surface area which promotes this reaction.

ACCOUNTING FOR ERROR PROPAGATION IN THE DEVELOPMENT OF A LEAF AREA INDEX (LAI) REFERENCE MAP TO ASSESS THE MODIS LAI MODI5A LAI PRODUCT

EPA Science Inventory

The ability to effectively use remotely sensed data for environmental spatial analysis is dependent on understanding the underlying procedures and associated variances attributed to the data processing and image analysis technique. Equally important, also, is understanding the er...

Remote Sensing of Saltcedar Biological Control Effectiveness

Treesearch

Ray Carruthers; Gerald Anderson; Jack DeLoach; Jeff Knight; Shaokui Ge; Peng Gong

2006-01-01

Saltcedar (Tamarix spp.) is a major invasive weed found throughout the Western United States and Mexico. Introduced into North America in the 1800s, this shrub to small tree, now infests many riparian areas where it displaces native vegetation, increases fire hazards, uses extensive amounts of water, increases flooding during high water events and...

Insistence on Teaching about Photosynthesis of Plants by Their Green Colour

ERIC Educational Resources Information Center

Çeken, Ramazan

2014-01-01

"Green" has a common use among the public. Both natural and social environment have an important effect on this expression. People tend to explain the scientific concepts using well-known situations which they intensively see around the living area. In this sense, photosynthesis is one of the most important biological concepts including…

Land cover changes in central Sonora Mexico

Treesearch

Diego Valdez-Zamudio; Alejandro Castellanos-Villegas; Stuart Marsh

2000-01-01

Remote sensing techniques have been demonstrated to be very effective tools to help detect, analyze, and evaluate land cover changes in natural areas of the world. Changes in land cover can generally be attributed to either natural or anthropogenic forces. Multitemporal satellite imagery and airborne videography were used to detect, analyze, and evaluate land cover...

Making Sense of All Your Data

ERIC Educational Resources Information Center

Lachat, Mary Ann; Williams, Martha; Smith, Stephen C.

2006-01-01

Schools today are more data rich than ever, requiring staff members to develop their data literacy--that is, their knowledge of how to use assessment data with other types of data to identify areas of effectiveness and to target instructional improvement efforts. Administrators and teachers are expected to use combinations of data (diagnostic and…

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE PAGES

Meng, Ran; Wu, Jin; Zhao, Feng; ...

2018-06-01

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

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

Meng, Ran; Wu, Jin; Zhao, Feng

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

[Crop geometry identification based on inversion of semiempirical BRDF models].

PubMed

Zhao, Chun-jiang; Huang, Wen-jiang; Mu, Xu-han; Wang, Jin-diz; Wang, Ji-hua

2009-09-01

With the rapid development of remote sensing technology, the application of remote sensing has extended from single view angle to multi-view angles. It was studied for the qualitative and quantitative effect of average leaf angle (ALA) on crop canopy reflected spectrum. Effect of ALA on canopy reflected spectrum can not be ignored with inversion of leaf area index (LAI) and monitoring of crop growth condition by remote sensing technology. Investigations of the effect of erective and horizontal varieties were conducted by bidirectional canopy reflected spectrum and semiempirical bidirectional reflectance distribution function (BRDF) models. The sensitive analysis was done based on the weight for the volumetric kernel (fvol), the weight for the geometric kernel (fgeo), and the weight for constant corresponding to isotropic reflectance (fiso) at red band (680 nm) and near infrared band (800 nm). By combining the weights of the red and near-infrared bands, the semiempirical models can obtain structural information by retrieving biophysical parameters from the physical BRDF model and a number of bidirectional observations. So, it will allow an on-site and non-sampling mode of crop ALA identification, which is useful for using remote sensing for crop growth monitoring and for improving the LAI inversion accuracy, and it will help the farmers in guiding the fertilizer and irrigation management in the farmland without a priori knowledge.

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Damage identification method for continuous girder bridges based on spatially-distributed long-gauge strain sensing under moving loads

NASA Astrophysics Data System (ADS)

Wu, Bitao; Wu, Gang; Yang, Caiqian; He, Yi

2018-05-01

A novel damage identification method for concrete continuous girder bridges based on spatially-distributed long-gauge strain sensing is presented in this paper. First, the variation regularity of the long-gauge strain influence line of continuous girder bridges which changes with the location of vehicles on the bridge is studied. According to this variation regularity, a calculation method for the distribution regularity of the area of long-gauge strain history is investigated. Second, a numerical simulation of damage identification based on the distribution regularity of the area of long-gauge strain history is conducted, and the results indicate that this method is effective for identifying damage and is not affected by the speed, axle number and weight of vehicles. Finally, a real bridge test on a highway is conducted, and the experimental results also show that this method is very effective for identifying damage in continuous girder bridges, and the local element stiffness distribution regularity can be revealed at the same time. This identified information is useful for maintaining of continuous girder bridges on highways.

Skylab experiments. Volume 2: Remote sensing of earth resources

NASA Technical Reports Server (NTRS)

1973-01-01

This volume covers the broad area of earth resources in which Skylab experiments will be performed. A brief description of the Skylab program, its objectives, and vehicles is included. Section 1 introduces the concept and historical significance of remote sensing, and discusses the major scientific considerations involved in remotely sensing the earth's resources. Sections 2 through 6 provide a description of the individual earth resource sensors and experiments to be performed. Each description includes a discussion of the experiment background and scientific objectives, the equipment involved, and a discussion of significant experiment performance areas.

The potential for remote sensing and hydrologic modelling to assess the spatio-temporal dynamics of ponds in the Ferlo Region (Senegal)

NASA Astrophysics Data System (ADS)

Soti, V.; Puech, C.; Lo Seen, D.; Bertran, A.; Vignolles, C.; Mondet, B.; Dessay, N.; Tran, A.

2010-08-01

In the Ferlo Region in Senegal, livestock depend on temporary ponds for water but are exposed to the Rift Valley Fever (RVF), a disease transmitted to herds by mosquitoes which develop in these ponds. Mosquito abundance is related to the emptying and filling phases of the ponds, and in order to study the epidemiology of RVF, pond modelling is required. In the context of a data scarce region, a simple hydrologic model which makes use of remote sensing data was developed to simulate pond water dynamics from daily rainfall. Two sets of ponds were considered: those located in the main stream of the Ferlo Valley whose hydrological dynamics are essentially due to runoff, and the ponds located outside, which are smaller and whose filling mechanisms are mainly due to direct rainfall. Separate calibrations and validations were made for each set of ponds. Calibration was performed from daily field data (rainfall, water level) collected during the 2001 and 2002 rainy seasons and from three different sources of remote sensing data: 1) very high spatial resolution optical satellite images to access pond location and surface area at given dates, 2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) data to estimate pond catchment area and 3) Tropical Rainfall Measuring Mission (TRMM) data for rainfall estimates. The model was applied to all ponds of the study area, the results were validated and a sensitivity analysis was performed. Water height simulations using gauge rainfall as input were compared to water level measurements from four ponds and Nash coefficients >0.7 were obtained. Comparison with simulations using TRMM rainfall data gave mixed results, with poor water height simulations for the year 2001 and good estimations for the year 2002. A pond map derived from a Quickbird satellite image was used to assess model accuracy for simulating pond water areas for all the ponds of the study area. The validation showed that modelled water areas were mostly underestimated but significantly correlated, particularly for the larger ponds. The results of the sensitivity analysis showed that parameters relative to pond shape and catchment area estimation have less effects on model simulation than parameters relative to soil properties (rainfall threshold causing runoff in dry soils and the coefficient expressing soil moisture decrease with time) or the water loss coefficient. Overall, our results demonstrate the possibility of using a simple hydrologic model with remote sensing data to track pond water heights and water areas in a homogeneous arid area.

Anisotropic Scattering Shadow Compensation Method for Remote Sensing Image with Consideration of Terrain

NASA Astrophysics Data System (ADS)

Wang, Qiongjie; Yan, Li

2016-06-01

With the rapid development of sensor networks and earth observation technology, a large quantity of high resolution remote sensing data is available. However, the influence of shadow has become increasingly greater due to the higher resolution shows more complex and detailed land cover, especially under the shadow. Shadow areas usually have lower intensity and fuzzy boundary, which make the images hard to interpret automatically. In this paper, a simple and effective shadow (including soft shadow) detection and compensation method is proposed based on normal data, Digital Elevation Model (DEM) and sun position. First, we use high accuracy DEM and sun position to rebuild the geometric relationship between surface and sun at the time the image shoot and get the hard shadow boundary and sky view factor (SVF) of each pixel. Anisotropic scattering assumption is accepted to determine the soft shadow factor mainly affected by diffuse radiation. Finally, an easy radiation transmission model is used to compensate the shadow area. Compared with the spectral detection method, our detection method has strict theoretical basis, reliable compensation result and minor affected by the image quality. The compensation strategy can effectively improve the radiation intensity of shadow area, reduce the information loss brought by shadow and improve the robustness and efficiency of the classification algorithms.

Motion Trajectories for Wide-area Surveying with a Rover-based Distributed Spectrometer

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Anderson, Gary; Wilson, Edmond

2006-01-01

A mobile ground survey application that employs remote sensing as a primary means of area coverage is highlighted. It is distinguished from mobile robotic area coverage problems that employ contact or proximity-based sensing. The focus is on a specific concept for performing mobile surveys in search of biogenic gases on planetary surfaces using a distributed spectrometer -- a rover-based instrument designed for wide measurement coverage of promising search areas. Navigation algorithms for executing circular and spiral survey trajectories are presented for widearea distributed spectroscopy and evaluated based on area covered and distance traveled.

Use of remote sensing for land use policy formulation. [Allegan, Bay, Branch, Ionia, Livingston, and St. Clair Counties in Michigan and Lake Michigan shorelines

NASA Technical Reports Server (NTRS)

Boylan, M. (Principal Investigator)

1978-01-01

The author has identified the following significant results. By utilizing remote sensing techniques, it was possible to accurately inventory a relatively large area for sand mining impact on protection and management of shoreland dunes within a limited time period and at a relatively low cost. Analysis of two sample areas selected from the Grand Mere area after prohibition of off-road-vehicle use indicated an increase in vegetation regrowth of 8.52% for sample area 1 and of 4.44% for sample area 2.

Analysis of potential urban unstable areas and landslide-induced damages on Volterra historical site through a remote sensing approach

NASA Astrophysics Data System (ADS)

Del Soldato, Matteo; Bianchini, Silvia; Nolesini, Teresa; Frodella, William; Casagli, Nicola

2017-04-01

Multisystem remote sensing techniques were exploited to provide a comprehensive overview of Volterra (Italy) site stability with regards to its landscape, urban fabric and cultural heritage. Interferometric Synthetic Aperture Radar (InSAR) techniques allow precise measurements of Earth surface displacement, as well as the detection of building deformations on large urban areas. In the field of cultural heritage conservation Infrared thermography (IRT) provides surface temperature mapping and therefore detects various potential criticalities, such as moisture, seepage areas, cracks and structural anomalies. Between winter 2014 and spring 2015 the historical center and south-western sectors of Volterra (Tuscany region, central Italy) were affected by instability phenomena. The spatial distribution, typology and effect on the urban fabrics of the landslide phenomena were investigated by analyzing the geological and geomorphological settings, traditional geotechnical monitoring and advanced remote sensing data such as Persistent Scatterers Interferometry (PSI). The ground deformation rates and the maximum settlement values derived from SAR acquisitions of historical ENVISAT and recent COSMO-SkyMed sensors, in 2003-2009 and 2010-2015 respectively, were compared with background geological data, constructive features, in situ evidences and detailed field inspections in order to classify landslide-damaged buildings. In this way, the detected movements and their potential correspondences with recognized damages were investigated in order to perform an assessment of the built-up areas deformations and damages on Volterra. The IRT technique was applied in order to survey the surface temperature of the historical Volterra wall-enclosure, and allowed highlighting thermal anomalies on this cultural heritage element of the site. The obtained results permitted to better correlate the landslide effects of the recognized deformations in the urban fabric, in order to provide useful information for future risk mitigation strategies to be planned by the local authorities and the involved technicians and conservators.

Inverse analysis of non-uniform temperature distributions using multispectral pyrometry

NASA Astrophysics Data System (ADS)

Fu, Tairan; Duan, Minghao; Tian, Jibin; Shi, Congling

2016-05-01

Optical diagnostics can be used to obtain sub-pixel temperature information in remote sensing. A multispectral pyrometry method was developed using multiple spectral radiation intensities to deduce the temperature area distribution in the measurement region. The method transforms a spot multispectral pyrometer with a fixed field of view into a pyrometer with enhanced spatial resolution that can give sub-pixel temperature information from a "one pixel" measurement region. A temperature area fraction function was defined to represent the spatial temperature distribution in the measurement region. The method is illustrated by simulations of a multispectral pyrometer with a spectral range of 8.0-13.0 μm measuring a non-isothermal region with a temperature range of 500-800 K in the spot pyrometer field of view. The inverse algorithm for the sub-pixel temperature distribution (temperature area fractions) in the "one pixel" verifies this multispectral pyrometry method. The results show that an improved Levenberg-Marquardt algorithm is effective for this ill-posed inverse problem with relative errors in the temperature area fractions of (-3%, 3%) for most of the temperatures. The analysis provides a valuable reference for the use of spot multispectral pyrometers for sub-pixel temperature distributions in remote sensing measurements.

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

NASA Astrophysics Data System (ADS)

Kyriou, Aggeliki; Nikolakopoulos, Konstantinos

2015-10-01

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

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Wilbanks, Thomas J.; Kirshen, Paul; Romero-Lankao, Patricia; Rosenzweig, Cynthia; Ruth, Mattias; Solecki, William; Tarr, Joel

2008-01-01

This slide presentation reviews some of the effects that global change has on urban areas in the United States and how the growth of urban areas will affect the environment. It presents the elements of our Synthesis and Assessment Report (SAP) report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We will also present some recommendations about what should be done to further research on how climate change and variability will impact human settlements in the U.S., as well as how to engage government officials, policy and decision makers, and the general public in understanding the implications of climate change and variability on the local and regional levels. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

Effects of grazing on leaf area index, fractional cover and evapotranspiration by a desert phreatophyte community at a former uranium mill site on the Colorado Plateau

USGS Publications Warehouse

Bresloff, Cynthia J.; Nguyen, Uyen; Glenn, Edward P.; Waugh, Jody; Nagler, Pamela L.

2013-01-01

This study employed ground and remote sensing methods to monitor the effects of grazing on leaf area index (LAI), fractional cover (fc) and evapotranspiration (ET) of a desert phreatophyte community over an 11 year period at a former uranium mill site on the Colorado Plateau, U.S. Nitrate, ammonium and sulfate are migrating away from the mill site in a shallow alluvial aquifer. The phreatophyte community, consisting of Atriplex canescens (ATCA) and Sarcobatus vermiculatus (SAVE) shrubs, intercepts groundwater and could potentially slow the movement of the contaminant plume through evapotranspiration (ET). However, the site has been heavily grazed by livestock, reducing plant cover and LAI. We used livestock exclosures and revegetation plots to determine the effects of grazing on LAI, fc and ET, then projected the findings over the whole site using multi-platform remote sensing methods. We show that ET is approximately equal to annual precipitation at the site, but when ATCA and SAVE are protected from grazing they can develop high fc and LAI values, and ET can exceed annual precipitation, with the excess coming from groundwater discharge. Therefore, control of grazing could be an effective method to slow migration of contaminants at this and similar sites in the western U.S.

Research on the demodulation techniques of long-period fiber gratings strain sensing with low cost

NASA Astrophysics Data System (ADS)

Wang, Qingwei; Liu, Yueming; Tian, Weijian; Feng, Guilan

2012-10-01

The working principle of LPFG(Long-Period Fiber Grating) is based on coupling effect between propagating core-mode and co-propagating cladding-modes. The effective refractive index of cladding-modes could be obviously influenced by the environmental changes resulting in LPFG more sensitive than FBG (Fiber Bragg Grating) in sensing areas, such as temperature, strain, concentration, bending and etc. LPFG should have more potential in the field of sensors compared with FBG. One of the challenges in using LPFG for environmental sensing is how to interrogate the signal from the LPFG transmission spectrum, due to the large spectral range of the resonant dip. Nowadays the application of LPFG is normally limited in signal interrogation of FBG as optical edge filter. The signal interrogation of LPFG itself needs further research. Presently research on signal interrogation of fiber grating focuses on wavelength interrogation. The aim of wavelength interrogation is to get the wavelength shift caused by environmental change. To solve these problems, a kind of strain sensing interrogation technique for LPFG with low-cost based on tunable FBGs has been developed. Comparing with the method using Fabry-Perot cavity, tunable FBGs can lower the cost with the guarantee of sensing precision. The cost is further lowered without using expensive optical instruments such as optical switch. The problem of temperature cross-sensitivity was solved by using reference gratings. An experiment was performed to demonstrate the interrogation system. And in the experiment, the sensing signal of LPFG applied 0-1300μɛ was successfully interrogated. The results of the interrogation system and OSA are similar.

The effects of SENSE on PROPELLER imaging.

PubMed

Chang, Yuchou; Pipe, James G; Karis, John P; Gibbs, Wende N; Zwart, Nicholas R; Schär, Michael

2015-12-01

To study how sensitivity encoding (SENSE) impacts periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) image quality, including signal-to-noise ratio (SNR), robustness to motion, precision of motion estimation, and image quality. Five volunteers were imaged by three sets of scans. A rapid method for generating the g-factor map was proposed and validated via Monte Carlo simulations. Sensitivity maps were extrapolated to increase the area over which SENSE can be performed and therefore enhance the robustness to head motion. The precision of motion estimation of PROPELLER blades that are unfolded with these sensitivity maps was investigated. An interleaved R-factor PROPELLER sequence was used to acquire data with similar amounts of motion with and without SENSE acceleration. Two neuroradiologists independently and blindly compared 214 image pairs. The proposed method of g-factor calculation was similar to that provided by the Monte Carlo methods. Extrapolation and rotation of the sensitivity maps allowed for continued robustness of SENSE unfolding in the presence of motion. SENSE-widened blades improved the precision of rotation and translation estimation. PROPELLER images with a SENSE factor of 3 outperformed the traditional PROPELLER images when reconstructing the same number of blades. SENSE not only accelerates PROPELLER but can also improve robustness and precision of head motion correction, which improves overall image quality even when SNR is lost due to acceleration. The reduction of SNR, as a penalty of acceleration, is characterized by the proposed g-factor method. © 2014 Wiley Periodicals, Inc.

[Research on hyperspectral remote sensing in monitoring snow contamination concentration].

PubMed

Tang, Xu-guang; Liu, Dian-wei; Zhang, Bai; Du, Jia; Lei, Xiao-chun; Zeng, Li-hong; Wang, Yuan-dong; Song, Kai-shan

2011-05-01

Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well.

Comparison and evaluation of fusion methods used for GF-2 satellite image in coastal mangrove area

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Ju, Hongbo; Liu, Hua; Zhang, Huaiqing; Sun, Hua

2018-04-01

GF-2 satellite is the highest spatial resolution Remote Sensing Satellite of the development history of China's satellite. In this study, three traditional fusion methods including Brovey, Gram-Schmidt and Color Normalized (CN were used to compare with the other new fusion method NNDiffuse, which used the qualitative assessment and quantitative fusion quality index, including information entropy, variance, mean gradient, deviation index, spectral correlation coefficient. Analysis results show that NNDiffuse method presented the optimum in qualitative and quantitative analysis. It had more effective for the follow up of remote sensing information extraction and forest, wetland resources monitoring applications.

Key Issues in the Analysis of Remote Sensing Data: A report on the workshop

NASA Technical Reports Server (NTRS)

Swain, P. H. (Principal Investigator)

1981-01-01

The procedures of a workshop assessing the state of the art of machine analysis of remotely sensed data are summarized. Areas discussed were: data bases, image registration, image preprocessing operations, map oriented considerations, advanced digital systems, artificial intelligence methods, image classification, and improved classifier training. Recommendations of areas for further research are presented.

ON-ROAD REMOTE SENSING OF AUTOMOBILE EMISSIONS IN THE RESEARCH TRIANGLE PARK, NORTH CAROLINA AREA: 1997-2001

EPA Science Inventory

The report describes automobile exhaust remote sensing data collected by EPA at a number of sites in the Research Triangle Park, NC area during 1997. Data were also collected at one site in Raleigh, NC from 1998 through 2001 for the Coordinating Research Council (CRC) study of re...

Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

Treesearch

S. Panda; D.M. Amatya; G. Hoogenboom

2014-01-01

Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

Remote Sensing of Water Pollution

NASA Technical Reports Server (NTRS)

White, P. G.

1971-01-01

Remote sensing, as a tool to aid in the control of water pollution, offers a means of making rapid, economical surveys of areas that are relatively inaccessible on the ground. At the same time, it offers the only practical means of mapping pollution patterns that cover large areas. Detection of oil slicks, thermal pollution, sewage, and algae are discussed.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

Research for applications of remote sensing to state and local governments (ARSIG)

NASA Technical Reports Server (NTRS)

Foster, K. E.; Johnson, J. D.

1973-01-01

Remote sensing and its application to problems confronted by local and state planners are reported. The added dimension of remote sensing as a data gathering tool has been explored identifying pertinent land use factors associated with urban growth such as soil associations, soil capability, vegetation distribution, and flood prone areas. Remote sensing within rural agricultural setting has also been utilized to determine irrigation runoff volumes, cropping patterns, and land use. A variety of data sources including U-2 70 mm multispectral black and white photography, RB-57 9-inch color IR, HyAC panoramic color IR and ERTS-1 imagery have been used over selected areas of Arizona including Tucson, Arizona (NASA Test Site #30) and the Sulphur Springs Valley.

Advances in the development of remote sensing technology for agricultural applications

NASA Technical Reports Server (NTRS)

Powers, J. E.; Erb, R. B.; Hall, F. G.; Macdonald, R. B.

1979-01-01

The application of remote sensing technology to crop forecasting is discussed. The importance of crop forecasts to the world economy and agricultural management is explained, and the development of aerial and spaceborne remote sensing for global crop forecasting by the United States is outlined. The structure, goals and technical aspects of the Large Area Crop Inventory Experiment (LACIE) are presented, and main findings on the accuracy, efficiency, applicability and areas for further study of the LACIE procedure are reviewed. The current status of NASA crop forecasting activities in the United States and worldwide is discussed, and the objectives and organization of the newly created Agriculture and Resources Inventory Surveys through Aerospace Remote Sensing (AgRISTARS) program are presented.

Hyperspectral forest monitoring and imaging implications

NASA Astrophysics Data System (ADS)

Goodenough, David G.; Bannon, David

2014-05-01

The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm2. The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing

A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

NASA Astrophysics Data System (ADS)

Liu, Likun

2018-01-01

In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

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.

Spatial assessment of Geo-environmental data by the integration of Remote Sensing and GIS techniques for Sitakund Region, Eastern foldbelt, Bangladesh.

NASA Astrophysics Data System (ADS)

Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.

2016-12-01

Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.

Opportunities and problems in introducing or expanding the teaching of remote sensing in universities

NASA Technical Reports Server (NTRS)

Maxwell, E. L.

1980-01-01

The need for degree programs in remote sensing is considered. Any education program which claims to train remote sensing specialists must include expertise in the physical principles upon which remote sensing is based. These principles dictate the limits of engineering and design, computer analysis, photogrammetry, and photointerpretation. Faculty members must be hired to provide emphasis in those five areas.

Constructing river stage-discharge rating curves using remotely sensed river cross-sectional inundation areas and river bathymetry

NASA Astrophysics Data System (ADS)

Pan, Feifei; Wang, Cheng; Xi, Xiaohuan

2016-09-01

Remote sensing from satellites and airborne platforms provides valuable data for monitoring and gauging river discharge. One effective approach first estimates river stage from satellite-measured inundation area based on the inundation area-river stage relationship (IARSR), and then the estimated river stage is used to compute river discharge based on the stage-discharge rating (SDR) curve. However, this approach is difficult to implement because of a lack of data for constructing the SDR curves. This study proposes a new method to construct the SDR curves using remotely sensed river cross-sectional inundation areas and river bathymetry. The proposed method was tested over a river reach between two USGS gauging stations, i.e., Kingston Mines (KM) and Copperas Creek (CC) along the Illinois River. First a polygon over each of two cross sections was defined. A complete IARSR curve was constructed inside each polygon using digital elevation model (DEM) and river bathymetric data. The constructed IARSR curves were then used to estimate 47 river water surface elevations at each cross section based on 47 river inundation areas estimated from Landsat TM images collected during 1994-2002. The estimated water surface elevations were substituted into an objective function formed by the Bernoulli equation of gradually varied open channel flow. A nonlinear global optimization scheme was applied to solve the Manning's coefficient through minimizing the objective function value. Finally the SDR curve was constructed at the KM site using the solved Manning's coefficient, channel cross sectional geometry and the Manning's equation, and employed to estimate river discharges. The root mean square error (RMSE) in the estimated river discharges against the USGS measured river discharges is 112.4 m3/s. To consider the variation of the Manning's coefficient in the vertical direction, this study also suggested a power-law function to describe the vertical decline of the Manning's coefficient with the water level from the channel bed lowest elevation to the bank-full level. The constructed SDR curve with the vertical variation of the Manning's coefficient reduced the RMSE in the estimated river discharges to 83.9 m3/s. These results indicate that the method developed and tested in this study is effective and robust, and has the potential for improving our ability of remote sensing of river discharge and providing data for water resources management, global water cycle study, and flood forecasting and prevention.

Development and use of remote sensing tools to study the impact of water hyacinth (Eichhornia crassipes) invasion in an estuarine ecosystem

NASA Astrophysics Data System (ADS)

Khanna, Shruti

Invasive species are the second greatest threat to biological diversity after habitat loss and fragmentation. Remote sensing is being used to map and model invasive species spread with increasing frequency every year. This study illustrates how remote sensing techniques can be used to map invasive species, examine the effects of environmental factors and management on their distribution, and look at the community response to spread or reduction in invasive species cover. Water hyacinth, a floating aquatic macrophyte, boasts an intimidating reputation as an aggressive global invasive. Water hyacinth was mapped in the Delta by pooling together several remote sensing techniques such as spectral indices, linear spectral unmixing, spectral mixture analysis, continuum removal, and LiDAR derived canopy height in a decision tree format with an overall accuracy greater than 90%. Water indices such as NDWI (Normalized Difference Water Index), continuum removal of water absorptions and average reflectance in the SWIR (shortwave infrared) were found to be the most important inputs for differentiating water hyacinth from other co-occuring species due to the high water content in its leaves. Water hyacinth maps from five years of data (2004 to 2008) showed that water hyacinth area significantly decreased between June of 2004 and 2005 and between June of 2007 and 2008. The decrease was larger in trapped areas (with restricted movement of water) compared to free-flowing channels. Three continuous weeks of frost in January of 2007 might have critically reduced water hyacinth cover across the Delta. There was no lasting effect of chemical control from one year to the next since no significant difference was found in water hyacinth cover in treated vs. untreated sites. The main objective of controlling water hyacinth -- to keep water channels clear for recreational and navigation use -- was not being met. Change detection analysis on the classification maps with six classes revealed that SAP (Submerged Aquatic Plants) was the most likely class to be colonized by water hyacinth and the most likely to spread into areas cleared of water hyacinth. The spread of water hyacinth into an empty niche (open water) and the return of an area after a decline in water hyacinth to open water were less common and more site dependant than with SAP. Water hyacinth interaction with other floating species was relatively limited, site dependant and more variable. The majority of water hyacinth cleared area was colonized by non-native species rather than returning to open water.

Factors affecting the remotely sensed response of coniferous forest plantations

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

Danson, F.M.; Curran, P.J.

1993-01-01

Remote sensing of forest biophysical properties has concentrated upon forest sites with a wide range of green vegetation amount and thereby leaf area index and canopy cover. However, coniferous forest plantations, an important forest type in Europe, are managed to maintain a large amount of green vegetation with little spatial variation. Therefore, the strength of the remotely sensed signal will, it is hypothesized, be determined more by the structure of this forest than by its cover. Airborne Thematic Mapper (ATM) and SPOT-1 HRV data were used to determine the effects of this structural variation on the remotely sensed response ofmore » a coniferous forest plantation in the United Kingdom. Red and near infrared radiance were strongly and negatively correlated with a range of structural properties and with the age of the stands but weakly correlated with canopy cover. A composite variable, related to the volume of the canopy, accounted for over 75% of the variation in near infrared radiance. A simple model that related forest structural variables to the remotely sensed response was used to understand and explain this response from a coniferous forest plantation.« less

Pervasive sensing

NASA Astrophysics Data System (ADS)

Nagel, David J.

2000-11-01

The coordinated exploitation of modern communication, micro- sensor and computer technologies makes it possible to give global reach to our senses. Web-cameras for vision, web- microphones for hearing and web-'noses' for smelling, plus the abilities to sense many factors we cannot ordinarily perceive, are either available or will be soon. Applications include (1) determination of weather and environmental conditions on dense grids or over large areas, (2) monitoring of energy usage in buildings, (3) sensing the condition of hardware in electrical power distribution and information systems, (4) improving process control and other manufacturing, (5) development of intelligent terrestrial, marine, aeronautical and space transportation systems, (6) managing the continuum of routine security monitoring, diverse crises and military actions, and (7) medicine, notably the monitoring of the physiology and living conditions of individuals. Some of the emerging capabilities, such as the ability to measure remotely the conditions inside of people in real time, raise interesting social concerns centered on privacy issues. Methods for sensor data fusion and designs for human-computer interfaces are both crucial for the full realization of the potential of pervasive sensing. Computer-generated virtual reality, augmented with real-time sensor data, should be an effective means for presenting information from distributed sensors.

Porous NiCo2O4 nanoarray-integrated binder-free 3D open electrode offers a highly efficient sensing platform for enzyme-free glucose detection.

PubMed

Luo, X; Huang, M; He, D; Wang, M; Zhang, Y; Jiang, P

2018-05-29

High electrical conductivity and the exposure to more active sites are crucial to boost the performance of a glucose sensor. A porous binary metal oxide nanoarray integrated on a binder-free 3D electrode is expected to offer a highly sensitive sensing platform. As a model, porous NiCo2O4 nanowire arrays supported on carbon cloth (NiCo2O4 NWA/CC) have been prepared and used for enzyme-free glucose sensing. NiCo2O4 NWA/CC shows larger effective surface area, superior electronic conductivity, and higher catalytic activity towards enzyme-free glucose sensing, with a linear range from 1 μM to 0.63 mM, a sensitivity of 4.12 mA mM-1 cm-2, and low detection limit of 0.5 μM. Moreover, NiCo2O4 NWA/CC also displays good selectivity and stability and thus, it can be reliable for glucose detection in human serum samples. These findings inspire the fabrication of a high-performance electrochemical sensing platform by preparing porous binary metal oxide nanoarrays supported on a 3D conductive substrate.

Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost

PubMed Central

Zhou, Zhen; Huang, Jingfeng; Wang, Jing; Zhang, Kangyu; Kuang, Zhaomin; Zhong, Shiquan; Song, Xiaodong

2015-01-01

Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited. PMID:26528811

Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost.

PubMed

Zhou, Zhen; Huang, Jingfeng; Wang, Jing; Zhang, Kangyu; Kuang, Zhaomin; Zhong, Shiquan; Song, Xiaodong

2015-01-01

Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited.

COSMO-SkyMed and GIS applications

NASA Astrophysics Data System (ADS)

Milillo, Pietro; Sole, Aurelia; Serio, Carmine

2013-04-01

Geographic Information Systems (GIS) and Remote Sensing have become key technology tools for the collection, storage and analysis of spatially referenced data. Industries that utilise these spatial technologies include agriculture, forestry, mining, market research as well as the environmental analysis . Synthetic Aperture Radar (SAR) is a coherent active sensor operating in the microwave band which exploits relative motion between antenna and target in order to obtain a finer spatial resolution in the flight direction exploiting the Doppler effect. SAR have wide applications in Remote Sensing such as cartography, surface deformation detection, forest cover mapping, urban planning, disasters monitoring , surveillance etc… The utilization of satellite remote sensing and GIS technology for this applications has proven to be a powerful and effective tool for environmental monitoring. Remote sensing techniques are often less costly and time-consuming for large geographic areas compared to conventional methods, moreover GIS technology provides a flexible environment for, analyzing and displaying digital data from various sources necessary for classification, change detection and database development. The aim of this work si to illustrate the potential of COSMO-SkyMed data and SAR applications in a GIS environment, in particular a demostration of the operational use of COSMO-SkyMed SAR data and GIS in real cases will be provided for what concern DEM validation, river basin estimation, flood mapping and landslide monitoring.

Development of Ion Chemosensors Based on Porphyrin Analogues.

PubMed

Ding, Yubin; Zhu, Wei-Hong; Xie, Yongshu

2017-02-22

Sensing of metal ions and anions is of great importance because of their widespread distribution in environmental systems and biological processes. Colorimetric and fluorescent chemosensors based on organic molecular species have been demonstrated to be effective for the detection of various ions and possess the significant advantages of low cost, high sensitivity, and convenient implementation. Of the available classes of organic molecules, porphyrin analogues possess inherently many advantageous features, making them suitable for the design of ion chemosensors, with the targeted sensing behavior achieved and easily modulated based on their following characteristics: (1) NH moieties properly disposed for binding of anions through cooperative hydrogen-bonding interactions; (2) multiple pyrrolic N atoms or other heteroatoms for selectively chelating metal ions; (3) variability of macrocycle size and peripheral substitution for modulation of ion selectivity and sensitivity; and (4) tunable near-infrared emission and good biocompatibility. In this Review, design strategies, sensing mechanisms, and sensing performance of ion chemosensors based on porphyrin analogues are described by use of extensive examples. Ion chemosensors based on normal porphyrins and linear oligopyrroles are also briefly described. This Review provides valuable information for researchers of related areas and thus may inspire the development of more practical and effective approaches for designing high-performance ion chemosensors based on porphyrin analogues and other relevant compounds.

Ecological Sensitivity Evaluation of Tourist Region Based on Remote Sensing Image - Taking Chaohu Lake Area as a Case Study

NASA Astrophysics Data System (ADS)

Lin, Y.; Li, W. J.; Yu, J.; Wu, C. Z.

2018-04-01

Remote sensing technology is of significant advantages for monitoring and analysing ecological environment. By using of automatic extraction algorithm, various environmental resources information of tourist region can be obtained from remote sensing imagery. Combining with GIS spatial analysis and landscape pattern analysis, relevant environmental information can be quantitatively analysed and interpreted. In this study, taking the Chaohu Lake Basin as an example, Landsat-8 multi-spectral satellite image of October 2015 was applied. Integrated the automatic ELM (Extreme Learning Machine) classification results with the data of digital elevation model and slope information, human disturbance degree, land use degree, primary productivity, landscape evenness , vegetation coverage, DEM, slope and normalized water body index were used as the evaluation factors to construct the eco-sensitivity evaluation index based on AHP and overlay analysis. According to the value of eco-sensitivity evaluation index, by using of GIS technique of equal interval reclassification, the Chaohu Lake area was divided into four grades: very sensitive area, sensitive area, sub-sensitive areas and insensitive areas. The results of the eco-sensitivity analysis shows: the area of the very sensitive area was 4577.4378 km2, accounting for about 37.12 %, the sensitive area was 5130.0522 km2, accounting for about 37.12 %; the area of sub-sensitive area was 3729.9312 km2, accounting for 26.99 %; the area of insensitive area was 382.4399 km2, accounting for about 2.77 %. At the same time, it has been found that there were spatial differences in ecological sensitivity of the Chaohu Lake basin. The most sensitive areas were mainly located in the areas with high elevation and large terrain gradient. Insensitive areas were mainly distributed in slope of the slow platform area; the sensitive areas and the sub-sensitive areas were mainly agricultural land and woodland. Through the eco-sensitivity analysis of the study area, the automatic recognition and analysis techniques for remote sensing imagery are integrated into the ecological analysis and ecological regional planning, which can provide a reliable scientific basis for rational planning and regional sustainable development of the Chaohu Lake tourist area.

Radiation area monitor device and method

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

Vencelj, Matjaz; Stowe, Ashley C.; Petrovic, Toni

A radiation area monitor device/method, utilizing: a radiation sensor having a directional radiation sensing capability; a rotation mechanism operable for selectively rotating the radiation sensor such that the directional radiation sensing capability selectively sweeps an area of interest; and a processor operable for analyzing and storing a radiation fingerprint acquired by the radiation sensor as the directional radiation sensing capability selectively sweeps the area of interest. Optionally, the radiation sensor includes a gamma and/or neutron radiation sensor. The device/method selectively operates in: a first supervised mode during which a baseline radiation fingerprint is acquired by the radiation sensor; and amore » second unsupervised mode during which a subsequent radiation fingerprint is acquired by the radiation sensor, wherein the subsequent radiation fingerprint is compared to the baseline radiation fingerprint and, if a predetermined difference threshold is exceeded, an alert is issued.« less

Frontiers of Remote Sensing of the Oceans and Troposphere from Air and Space Platforms

NASA Technical Reports Server (NTRS)

1984-01-01

Several areas of remote sensing are addressed including: future satellite systems; air-sea interaction/wind; ocean waves and spectra/S.A.R.; atmospheric measurements (particulates and water vapor); synoptic and weather forecasting; topography; bathymetry; sea ice; and impact of remote sensing on synoptic analysis/forecasting.

Remote Sensing in Latin America: Technology and Markets for the 1980s

DTIC Science & Technology

1981-08-01

A review is made on the impact of satellite derived remote sensing data in Latin America. Data availability has generated a phenomenal growth in the...The international institutionalization of remote sensing interests in the area is an indicator submitted as a viable force in the continued, future

A data fusion framework for floodplain analysis using GIS and remotely sensed data

NASA Astrophysics Data System (ADS)

Necsoiu, Dorel Marius

Throughout history floods have been part of the human experience. They are recurring phenomena that form a necessary and enduring feature of all river basin and lowland coastal systems. In an average year, they benefit millions of people who depend on them. In the more developed countries, major floods can be the largest cause of economic losses from natural disasters, and are also a major cause of disaster-related deaths in the less developed countries. Flood disaster mitigation research was conducted to determine how remotely sensed data can effectively be used to produce accurate flood plain maps (FPMs), and to identify/quantify the sources of error associated with such data. Differences were analyzed between flood maps produced by an automated remote sensing analysis tailored to the available satellite remote sensing datasets (rFPM), the 100-year flooded areas "predicted" by the Flood Insurance Rate Maps, and FPMs based on DEM and hydrological data (aFPM). Landuse/landcover was also examined to determine its influence on rFPM errors. These errors were identified and the results were integrated in a GIS to minimize landuse/landcover effects. Two substantial flood events were analyzed. These events were selected because of their similar characteristics (i.e., the existence of FIRM or Q3 data; flood data which included flood peaks, rating curves, and flood profiles; and DEM and remote sensing imagery). Automatic feature extraction was determined to be an important component for successful flood analysis. A process network, in conjunction with domain specific information, was used to map raw remotely sensed data onto a representation that is more compatible with a GIS data model. From a practical point of view, rFPM provides a way to automatically match existing data models to the type of remote sensing data available for each event under investigation. Overall, results showed how remote sensing could contribute to the complex problem of flood management by providing an efficient way to revise the National Flood Insurance Program maps.

Depletion type floating gate p-channel MOS transistor for recording action potentials generated by cultured neurons.

PubMed

Cohen, Ariel; Spira, Micha E; Yitshaik, Shlomo; Borghs, Gustaaf; Shwartzglass, Ofer; Shappir, Joseph

2004-07-15

We report the realization of electrical coupling between neurons and depletion type floating gate (FG) p-channel MOS transistors. The devices were realized in a shortened 0.5 microm CMOS technology. Increased boron implant dose was used to form the depletion type devices. Post-CMOS processing steps were added to expose the devices sensing area. The neurons are coupled to the polycrystalline silicon (PS) FG through 420A thermal oxide in an area which is located over the thick field oxide away from the transistor. The combination of coupling area pad having a diameter of 10 or 15 microm and sensing transistor with W/L of 50/0.5 microm results in capacitive coupling ratio of the neuron signal of about 0.5 together with relatively large transistor transconductance. The combination of the FG structure with a depletion type device, leads to the following advantages. (a) No need for dc bias between the solution in which the neurons are cultured and the transistor with expected consequences to the neuron as well as the silicon die durability. (b) The sensing area of the neuron activity is separated from the active area of the transistor. Thus, it is possible to design the sensing area and the channel area separately. (c) The channel area, which is the most sensitive part of the transistor, can be insulated and shielded from the ionic solution in which the neurons are cultured. (d) There is an option to add a switching transistor to the FG and use the FG also for the neuron stimulation.

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.

Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007

NASA Astrophysics Data System (ADS)

Mason, D. C.; Scott, T. R.; Dance, S. L.

2010-04-01

Tidal Flats are important examples of extensive areas of natural environment that remain relatively unaffected by man. Monitoring of tidal flats is required for a variety of purposes. Remote sensing has become an established technique for the measurement of topography over tidal flats. A further requirement is to measure topographic changes in order to measure sediment budgets. To date there have been few attempts to make quantitative estimates of morphological change over tidal flat areas. This paper illustrates the use of remote sensing to measure quantitative and qualitative changes in the tidal flats of Morecambe Bay during the relatively long period 1991-2007. An understanding of the patterns of sediment transport within the Bay is of considerable interest for coastal management and defence purposes. Tidal asymmetry is considered to be the dominant cause of morphological change in the Bay, with the higher currents associated with the flood tide being the main agency moulding the channel system. Quantitative changes were measured by comparing a Digital Elevation Model (DEM) of the intertidal zone formed using the waterline technique applied to satellite Synthetic Aperture Radar (SAR) images from 1991-1994, to a second DEM constructed from airborne laser altimetry data acquired in 2005. Qualitative changes were studied using additional SAR images acquired since 2003. A significant movement of sediment from below Mean Sea Level (MSL) to above MSL was detected by comparing the two Digital Elevation Models, though the proportion of this change that could be ascribed to seasonal effects was not clear. Between 1991 and 2004 there was a migration of the Ulverston channel of the river Leven north-east by about 5 km, followed by the development of a straighter channel to the west, leaving the previous channel decoupled from the river. This is thought to be due to independent tidal and fluvial forcing mechanisms acting on the channel. The results demonstrate the effectiveness of remote sensing for measurement of long-term morphological change in tidal flat areas. An alternative use of waterlines as partial bathymetry for assimilation into a morphodynamic model of the coastal zone is also discussed.

Preliminary work of mangrove ecosystem carbon stock mapping in small island using remote sensing: above and below ground carbon stock mapping on medium resolution satellite image

NASA Astrophysics Data System (ADS)

Wicaksono, Pramaditya; Danoedoro, Projo; Hartono, Hartono; Nehren, Udo; Ribbe, Lars

2011-11-01

Mangrove forest is an important ecosystem located in coastal area that provides various important ecological and economical services. One of the services provided by mangrove forest is the ability to act as carbon sink by sequestering CO2 from atmosphere through photosynthesis and carbon burial on the sediment. The carbon buried on mangrove sediment may persist for millennia before return to the atmosphere, and thus act as an effective long-term carbon sink. Therefore, it is important to understand the distribution of carbon stored within mangrove forest in a spatial and temporal context. In this paper, an effort to map carbon stocks in mangrove forest is presented using remote sensing technology to overcome the handicap encountered by field survey. In mangrove carbon stock mapping, the use of medium spatial resolution Landsat 7 ETM+ is emphasized. Landsat 7 ETM+ images are relatively cheap, widely available and have large area coverage, and thus provide a cost and time effective way of mapping mangrove carbon stocks. Using field data, two image processing techniques namely Vegetation Index and Linear Spectral Unmixing (LSU) were evaluated to find the best method to explain the variation in mangrove carbon stocks using remote sensing data. In addition, we also tried to estimate mangrove carbon sequestration rate via multitemporal analysis. Finally, the technique which produces significantly better result was used to produce a map of mangrove forest carbon stocks, which is spatially extensive and temporally repetitive.

Analysis of Human Activities in Nature Reserves Based on Nighttime Light Remote Sensing and Microblogging Data - by the Case of National Nature Reserves in Jiangxi Province

NASA Astrophysics Data System (ADS)

Shi, F.; Li, X.; Xu, H.

2017-09-01

The study used the mainstream social media in china - Sina microblogging data combined with nighttime light remote sensing and various geographical data to reveal the pattern of human activities and light pollution of the Jiangxi Provincial National Nature Reserves. Firstly, we performed statistical analysis based on both functional areas and km-grid from the perspective of space and time, and selected the key areas for in-depth study. Secondly, the relationship between microblogging data and nighttime light remote sensing, population, GDP, road coverage, road distance and road type in nature reserves was analyzed by Spearman correlation coefficient method, so the distribution pattern and influencing factors of the microblogging data were explored. Thirdly, a region where the luminance value was greater than 0.2 was defined as a light region. We evaluated the management status by analyzing the distribution of microblogging data in both light area and non-light area. Final results showed that in all nature reserves, the top three were the Lushan Nature Reserve, the Jinggangshan Nature Reserve, the Taohongling National Nature Reserve of Sikas both on the total number and density of microblogging ; microblogging had a significant correlation with nighttime light remote sensing , the GDP, population, road and other factors; the distribution of microblogging near roads in protected area followed power laws; luminous radiance of Lushan Nature Reserve was the highest, with 43 percent of region was light at night; analysis combining nighttime light remote sensing with microblogging data reflected the status of management of nature reserves.

Rapid Change Detection Algorithm for Disaster Management

NASA Astrophysics Data System (ADS)

Michel, U.; Thunig, H.; Ehlers, M.; Reinartz, P.

2012-07-01

This paper focuses on change detection applications in areas where catastrophic events took place which resulted in rapid destruction especially of manmade objects. Standard methods for automated change detection prove not to be sufficient; therefore a new method was developed and tested. The presented method allows a fast detection and visualization of change in areas of crisis or catastrophes. While often new methods of remote sensing are developed without user oriented aspects, organizations and authorities are not able to use these methods because of absence of remote sensing know how. Therefore a semi-automated procedure was developed. Within a transferable framework, the developed algorithm can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated Temporal Change Index (TCI) only panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas where rebuilding has already started.

Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience

PubMed Central

Bellavista, Paolo; Corradi, Antonio; Foschini, Luca; Ianniello, Raffaele

2015-01-01

Nowadays, sensor-rich smartphones potentially enable the harvesting of huge amounts of valuable sensing data in urban environments, by opportunistically involving citizens to play the role of mobile virtual sensors to cover Smart City areas of interest. This paper proposes an in-depth study of the challenging technical issues related to the efficient assignment of Mobile Crowd Sensing (MCS) data collection tasks to volunteers in a crowdsensing campaign. In particular, the paper originally describes how to increase the effectiveness of the proposed sensing campaigns through the inclusion of several new facilities, including accurate participant selection algorithms able to profile and predict user mobility patterns, gaming techniques, and timely geo-notification. The reported results show the feasibility of exploiting profiling trends/prediction techniques from volunteers’ behavior; moreover, they quantitatively compare different MCS task assignment strategies based on large-scale and real MCS data campaigns run in the ParticipAct living lab, an ongoing MCS real-world experiment that involved more than 170 students of the University of Bologna for more than one year. PMID:26263985

Rational design of 3D inverse opal heterogeneous composite microspheres as excellent visible-light-induced NO2 sensors at room temperature.

PubMed

Wang, Tianshuang; Yu, Qi; Zhang, Sufang; Kou, Xueying; Sun, Peng; Lu, Geyu

2018-03-08

The lower gas sensitivity, humidity dependence of the gas sensing properties, and long recovery times of room-temperature gas sensors severely limit their applications. Herein, to address these issues, a series of 3D inverse opal (IO) In 2 O 3 -ZnO heterogeneous composite microspheres (HCMs) are fabricated by ultrasonic spray pyrolysis (USP) employing self-assembled sulfonated polystyrene (S-PS) spheres as a sacrificial template. The 3D IO In 2 O 3 -ZnO HCMs possess highly ordered 3D inverse opal structures and bimodal (meso-scale and macro-scale) pores, which can provide large accessible surface areas and rapid mass transfer, resulting in enhanced gas sensing characteristics. Furthermore, the 3D IO architecture and n-n heterojunctions can extend the photoabsorption range to the visible light area, effectively prolonging the lifetimes of photo-generated charge carriers, and can increase separation of visible light-generated charges. As a result, the as-prepared 3D IO In 2 O 3 -ZnO HCMs deliver excellent NO 2 sensing performance under visible light irradiation at room temperature, such as high sensitivity (R gas /R air = 54.3 to 5 ppm NO 2 ), low detection limit (250 ppb), fast recovery time (188 s), excellent selectivity and humidity independence. These enhanced photo-electronic gas sensing properties are attributed to the combination of highly ordered 3D IO microspheres and In 2 O 3 -ZnO heterogeneous composites.

A Remote Sensing Class Exercise To Study the Effects of "El Nino" in South America.

ERIC Educational Resources Information Center

Moxey, Lucas Eduardo

2002-01-01

Describes an undergraduate physical science laboratory course exercising the utilization of satellite imagery for studying the floods that resulted in the Parana River region in South America during El Nino (1997-1998), and examines vegetation cover and spectral profiles from the study area in order to further understand and assess the changes…

Using NASA Using Remote Sensing in Public Health Applications

NASA Technical Reports Server (NTRS)

Estes, Sue; Haynes, John

2011-01-01

The Public Health application area focuses on Earth science applications to public health and safety, particularly regarding infectious disease, emergency preparedness and response, and environmental health issues. The application explores issues of toxic and pathogenic exposure, as well as natural and man-made hazards and their effects, for risk characterization/mitigation and improvements to health and safety.

Lessons from Katrina: Crisis Communication and Rhetorical Protocol

ERIC Educational Resources Information Center

Smith, Donald C.

2007-01-01

Widely misunderstood and often maligned, rhetoric in the simplest sense is the effective use of language in speech or writing. Much as law and medicine have well considered standards of conduct, so too does the field of communication. Experts in this area look at--patterns--of discourse in relation to specific kinds of events--tornadoes,…

Integrating remote sensing and forest inventory data for assessing forest blowdown in the boundary waters canoe area wilderness

Treesearch

Mark D. Nelson; W. Keith Moser

2007-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) program conducts strategic inventories of our Nation's forest resources. There is increasing need to assess effects of forest disturbance from catastrophic events, often within geographic extents not typically addressed by strategic forest inventories. One such event occurred within the Boundary...

On the use of a snow aridity index to predict remotely sensed forest productivity in the presence of bark beetle disturbance

NASA Astrophysics Data System (ADS)

Knowles, John F.; Lestak, Leanne R.; Molotch, Noah P.

2017-06-01

We used multiple sources of remotely sensed and ground based information to evaluate the spatiotemporal variability of snowpack accumulation, potential evapotranspiration (PET), and Normalized Difference Vegetation Index (NDVI) throughout the Southern Rocky Mountain ecoregion, USA. Relationships between these variables were used to establish baseline values of expected forest productivity given water and energy inputs. Although both the snow water equivalent (SWE) and a snow aridity index (SAI), which used SWE to normalize PET, were significant predictors of the long-term (1989-2012) NDVI, SAI explained 11% more NDVI variability than SWE. Deviations from these relationships were subsequently explored in the context of widespread forest mortality due to bark beetles. Over the entire study area, NDVI was lower per unit SAI in beetle-disturbed compared to undisturbed areas during snow-related drought; however, both SAI and NDVI were spatially heterogeneous within this domain. As a result, we selected three focus areas inside the larger study area within which to isolate the relative impacts of SAI and disturbance on NDVI using multivariate linear regression. These models explained 66%-85% of the NDVI and further suggested that both SAI and disturbance effects were significant, although the disturbance effect was generally greater. These results establish the utility of SAI as a measure of moisture limitation in snow-dominated systems and demonstrate a reduction in forest productivity due to bark beetle disturbance that is particularly evident during drought conditions resultant from low snow accumulation during the winter.

Mesoporous Silicate Materials in Sensing

PubMed Central

Melde, Brian J.; Johnson, Brandy J.; Charles, Paul T.

2008-01-01

Mesoporous silicas, especially those exhibiting ordered pore systems and uniform pore diameters, have shown great potential for sensing applications in recent years. Morphological control grants them versatility in the method of deployment whether as bulk powders, monoliths, thin films, or embedded in coatings. High surface areas and pore sizes greater than 2 nm make them effective as adsorbent coatings for humidity sensors. The pore networks also provide the potential for immobilization of enzymes within the materials. Functionalization of materials by silane grafting or through co-condensation of silicate precursors can be used to provide mesoporous materials with a variety of fluorescent probes as well as surface properties that aid in selective detection of specific analytes. This review will illustrate how mesoporous silicas have been applied to sensing changes in relative humidity, changes in pH, metal cations, toxic industrial compounds, volatile organic compounds, small molecules and ions, nitroenergetic compounds, and biologically relevant molecules. PMID:27873810

Platinum decorated carbon nanotubes for highly sensitive amperometric glucose sensing

NASA Astrophysics Data System (ADS)

Xie, Jining; Wang, Shouyan; Aryasomayajula, L.; Varadan, V. K.

2007-02-01

Fine platinum nanoparticles (1-5 nm in diameter) were deposited on functionalized multi-walled carbon nanotubes (MWNTs) through a decoration technique. A novel type of enzymatic Pt/MWNTs paste-based mediated glucose sensor was fabricated. Electrochemical measurements revealed a significantly improved sensitivity (around 52.7 µA mM-1 cm-2) for glucose sensing without using any picoampere booster or Faraday cage. In addition, the calibration curve exhibited a good linearity in the range of 1-28 mM of glucose concentration. Transmission electron microscopy (TEM) and x-ray photoelectron spectroscopy (XPS) were performed to investigate the nanoscale structure and the chemical bonding information of the Pt/MWNTs paste-based sensing material, respectively. The improved sensitivity of this novel glucose sensor could be ascribed to its higher electroactive surface area, enhanced electron transfer, efficient enzyme immobilization, unique interaction in nanoscale and a synergistic effect on the current signal from possible multi-redox reactions.

Remote sensing techniques applied to multispectral recognition of the Aranjuez pilot zone

NASA Technical Reports Server (NTRS)

Lemos, G. L.; Salinas, J.; Rebollo, M.

1977-01-01

A rectangular (7 x 14 km) area 40 km S of Madrid was remote-sensed with a three-stage recognition process. Ground truth was established in the first phase, airborne sensing with a multispectral scanner and photographic cameras were used in the second phase, and Landsat satellite data were obtained in the third phase. Agronomic and hydrological photointerpretation problems are discussed. Color, black/white, and labeled areas are displayed for crop recognition in the land-use survey; turbidity, concentrations of pollutants and natural chemicals, and densitometry of the water are considered in the evaluation of water resources.

Estimating urban forest carbon sequestration potential in the southern United States using current remote sensing imagery sources

Treesearch

Krista Merry; Pete Bettinger; Jacek Siry; J. Michael Bowker

2015-01-01

With an increased interest in reducing carbon dioxide in the atmosphere, tree planting and maintenance in urban areas has become a viable option for increasing carbon sequestration. Methods for assessing the potential for planting trees within an urban area should allow for quick, inexpensive, and accurate estimations of available land using current remote sensing...

Colorado SIP: 5 CCR 1001-13, Reg 11, Motor Vehicle Emissions Inspection Program—Part A, General Provisions, Area of Applicability, Schedules for Obtaining Certification of Emissions Control, Definitions, Exemptions, and Clean Screening/Remote Sensing

EPA Pesticide Factsheets

Colorado SIP: 5 CCR 1001-13, Reg 11, Motor Vehicle Emissions Inspection Program—Part A, General Provisions, Area of Applicability, Schedules for Obtaining Certification of Emissions Control, Definitions, Exemptions, and Clean Screening/Remote Sensing

A study to identify research issues in the area of electromagnetic measurements and signal handling of remotely sensed data

NASA Technical Reports Server (NTRS)

1982-01-01

Research issues in the area of electromagnetic measurements and signal handling of remotely sensed data are identified. The following seven issues are discussed; platform/sensor system position and velocity, platform/sensor attitudes and attitude rates, optics and antennas, detectors and associated electronics, sensor calibration, signal handling, and system design.

How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment

USDA-ARS?s Scientific Manuscript database

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spannin...

SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

DTIC Science & Technology

The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was

REMOTE SENSING IN OCEANOGRAPHY.

DTIC Science & Technology

remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and

[Monitoring of soil salinization in Northern Tarim Basin, Xinjiang of China in dry and wet seasons based on remote sensing].

PubMed

Yao, Yuan; Ding, Jian-Li; Zhang, Fang; Wang, Gang; Jiang, Hong-Nan

2013-11-01

Soil salinization is one of the most important eco-environment problems in arid area, which can not only induce land degradation, inhibit vegetation growth, but also impede regional agricultural production. To accurately and quickly obtain the information of regional saline soils by using remote sensing data is critical to monitor soil salinization and prevent its further development. Taking the Weigan-Kuqa River Delta Oasis in the northern Tarim River Basin of Xinjiang as test object, and based on the remote sensing data from Landsat-TM images of April 15, 2011 and September 22, 2011, in combining with the measured data from field survey, this paper extracted the characteristic variables modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), and the third principal component from K-L transformation (K-L-3). The decision tree method was adopted to establish the extraction models of soil salinization in the two key seasons (dry and wet seasons) of the study area, and the classification maps of soil salinization in the two seasons were drawn. The results showed that the decision tree method had a higher discrimination precision, being 87.2% in dry season and 85.3% in wet season, which was able to be used for effectively monitoring the dynamics of soil salinization and its spatial distribution, and to provide scientific basis for the comprehensive management of saline soils in arid area and the rational utilization of oasis land resources.

[High Resolution Remote Sensing Monitoring and Assessment of Secondary Geological Disasters Triggered by the Lushan Earthquake].

PubMed

Wang, Fu-tao; Wang, Shi-xin; Zhou, Yi; Wang, Li-tao; Yan, Fu-li; Li, Wen-jun; Liu, Xiong-fei

2016-01-01

The secondary geological disasters triggered by the Lushan earthquake on April 20, 2013, such as landslides, collapses, debris flows, etc., had caused great casualties and losses. We monitored the number and spatial distribution of the secondary geological disasters in the earthquake-hit area from airborne remote sensing images, which covered areas about 3 100 km2. The results showed that Lushan County, Baoxing County and Tianquan County were most severely affected; there were 164, 126 and 71 secondary geological disasters in these regions. Moreover, we analyzed the relationship between the distribution of the secondary geological disasters, geological structure and intensity. The results indicate that there were 4 high-hazard zones in the monitored area, one focused within six kilometers from the epicenter, and others are distributed along the two main fault zones of the Longmen Mountain. More than 97% secondary geological disasters occurred in zones with a seismic intensity of VII to IX degrees, a slope between 25 A degrees and 50 A degrees, and an altitude of between 800 and 2 000 m. At last, preliminary suggestions were proposed for the rehabilitation and reconstruction planning of Lushan earthquake. According to the analysis result, airborne and space borne remote sensing can be used accurately and effectively in almost real-time to monitor and assess secondary geological disasters, providing a scientific basis and decision making support for government emergency command and post-disaster reconstruction.

Natural Resource Information System, remote sensing studies

NASA Technical Reports Server (NTRS)

Leachtenauer, J.; Hirsch, R.; Williams, V.; Tucker, R.

1972-01-01

Potential applications of remote sensing data were reviewed, and available imagery was interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and qualities of imagery required to satisfy identified data needs. Ektachrome imagery available over the demonstration areas was reviewed to establish the feasibility of interpreting cultural features, range condition, and timber type. Using the same imagery, a land use map was prepared for the demonstration area. The feasibility of identifying commercial timber areas using a density slicing technique was tested on multispectral imagery available for a portion of the demonstration area.

Estimation of small reservoir storage capacities in the São Francisco, Limpopo, Bandama and Volta river basins using remotely sensed surface areas

NASA Astrophysics Data System (ADS)

Rodrigues, Lineu; Senzanje, Aidan; Cecchi, Philippe; Liebe, Jens

2010-05-01

People living in areas with highly variable rainfall, experience droughts and floods and often have insecure livelihoods. Small multi-purpose reservoirs (SR) are a widely used form of infrastructures to provide people in such areas with water during the dry season, e.g. in the basins of São Francisco, Brazil, Limpopo, Zimbabwe, Bandama, Ivory Coast and Volta, Ghana. In these areas, the available natural flow in the streams is sometimes less than the flow required for water supply or irrigation, however water can be stored in times of surplus, for example, from a wet season to a dry season. Efficient water management and sound reservoir planning are hindered by the lack of information about the functioning of these reservoirs. Reservoirs in these regions were constructed in a series of projects funded by different agencies, at different times, with little or no coordination among the implementing partners. Poor record keeping and the lack of appropriate institutional support result in deficiencies of information on the capacity, operation, and maintenance of these structures. Estimating the storage capacity of dams is essential to the responsible management of water diversion. Most of SR in these basins have never been evaluated, possibly because the tools currently used for such measurement are labor-intensive, costly and time-consuming. The objective of this research was to develop methodology to estimate small reservoir capacities as a function of their remotely sensed surface areas in the São Francisco, Limpopo, Bandama and Volta basins, as a way to contribute to improve the water resource management in those catchments. Remote sensing was used to identify, localize and characterize small reservoirs. The surface area of each was calculated from satellite images. A sub-set of reservoirs was selected. For each reservoir in the sub-set, the surface area was estimated from field surveys, and storage capacity was estimated using information on reservoir surface area, depth and shape. Depth was measured using a stadia rod or a manual echosounder. For reservoirs in the sub-set, estimated surface area was used as an input into the triangulated irregular network model. With the surface area and depth, measured volume was calculated. Comparisons were made between estimates of surface area from field surveys and estimates of surface area from remote sensing. A linear regression analysis was carried out to establish the relationship between surface area and storage capacities. Within geomorphologically homogenous regions, one may expect a good correlation between the surface area, which may be determined through satellite observations, and the stored volume. Such a relation depends on the general shape of the slopes (convex, through straight, to concave). The power relationships between remotely sensed surface areas (m^2) and storage capacities of reservoirs (m^3) obtained were - Limpopo basin (Lower Mzingwane sub-catchment): Volume = 0.023083 x Area^1.3272 (R2 = 95%); Bandama basin (North of the basin in Ivory Coast): Volume = 0.00405 x Area^1.4953 (R2 = 88.9%); Volta basin (Upper East region of the Volta Basin in Ghana): Volume = 0.00857 × Area^1.43 (R2 = 97.5%); São Francisco basin (Preto river sub-catchment): Volume = 0.2643 x Area^1.1632 (R2 = 92.1%). Remote sensing was found to be a suitable means to detect small reservoirs and accurately measure their surface areas. The general relationship between measured reservoir volumes and their remotely sensed surface areas showed good accuracy for all four basins. Combining such relationships with periodical satellite-based reservoir area measurements may allow hydrologists and planners to have clear picture of water resource system in the Basins, especially in ungauged sub-basins.

Developing particle emission inventories using remote sensing (PEIRS).

PubMed

Tang, Chia-Hsi; Coull, Brent A; Schwartz, Joel; Lyapustin, Alexei I; Di, Qian; Koutrakis, Petros

2017-01-01

Information regarding the magnitude and distribution of PM 2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM 2.5 . This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R 2 = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM 2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.

Remote Sensing: The View from Above. Know Your Environment.

ERIC Educational Resources Information Center

Academy of Natural Sciences, Philadelphia, PA.

This publication identifies some of the general concepts of remote sensing and explains the image collection process and computer-generated reconstruction of the data. Monitoring the ecological collapse in coral reefs, weather phenomena like El Nino/La Nina, and U.S. Space Shuttle-based sensing projects are some of the areas for which remote…

Project THEMIS: A Center for Remote Sensing.

DTIC Science & Technology

This report summarizes the technical work accomplished under Project THEMIS, A Center for Remote Sensing at the University of Kansas during the...period 16 September 1967 through 15 September 1973. The highlights of the four major areas forming the remote sensing system are presented. A detailed description of the latest radar spectrometer results is presented.

Calibration of remotely sensed proportion or area estimates for misclassification error

Treesearch

Raymond L. Czaplewski; Glenn P. Catts

1992-01-01

Classifications of remotely sensed data contain misclassification errors that bias areal estimates. Monte Carlo techniques were used to compare two statistical methods that correct or calibrate remotely sensed areal estimates for misclassification bias using reference data from an error matrix. The inverse calibration estimator was consistently superior to the...

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors

PubMed Central

Zheng, Guang; Moskal, L. Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels. PMID:22574042

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.

PubMed

Zheng, Guang; Moskal, L Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.

Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research.

PubMed

Siena, Francesco Luke; Byrom, Bill; Watts, Paul; Breedon, Philip

2018-02-05

Applications utilising 3D Camera technologies for the measurement of health outcomes in the health and wellness sector continues to expand. The Intel® RealSense™ is one of the leading 3D depth sensing cameras currently available on the market and aligns itself for use in many applications, including robotics, automation, and medical systems. One of the most prominent areas is the production of interactive solutions for rehabilitation which includes gait analysis and facial tracking. Advancements in depth camera technology has resulted in a noticeable increase in the integration of these technologies into portable platforms, suggesting significant future potential for pervasive in-clinic and field based health assessment solutions. This paper reviews the Intel RealSense technology's technical capabilities and discusses its application to clinical research and includes examples where the Intel RealSense camera range has been used for the measurement of health outcomes. This review supports the use of the technology to develop robust, objective movement and mobility-based endpoints to enable accurate tracking of the effects of treatment interventions in clinical trials.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

PubMed

Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

Comparision of Bathymetry and Bottom Characteristics From Hyperspectral Remote Sensing Data and Shipborne Acoustic Measurements

NASA Astrophysics Data System (ADS)

McIntyre, M. L.; Naar, D. F.; Carder, K. L.; Howd, P. A.; Lewis, J. M.; Donahue, B. T.; Chen, F. R.

2002-12-01

There is growing interest in applying optical remote sensing techniques to shallow-water geological applications such as bathymetry and bottom characterization. Model inversions of hyperspectral remote-sensing reflectance imagery can provide estimates of bottom albedo and depth. This research was conducted in support of the HyCODE (Hyperspectral Coupled Ocean Dynamics Experiment) project in order to test optical sensor performance and the use of a hyperspectral remote-sensing reflectance algorithm for shallow waters in estimating bottom depths and reflectance. The objective of this project was to compare optically derived products of bottom depths and reflectance to shipborne acoustic measurements of bathymetry and backscatter. A set of three high-resolution, multibeam surveys within an 18 km by 1.5 km shore-perpendicular transect 5 km offshore of Sarasota, Florida were collected at water depths ranging from 8 m to 16 m. These products are compared to bottom depths derived from aircraft remote-sensing data collected with the AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) instrument data by means of a semi-analytical remote sensing reflectance model. The pixel size of the multibeam bathymetry and AVIRIS data are 0.25 m and 10 m, respectively. When viewed at full resolution, the multibeam bathymetry data show small-scale sedimentary bedforms (wavelength ~10m, amplitude ~1m) that are not observed in the lower resolution hyperspectral bathymetry. However, model-derived bottom depths agree well with a smoothed version of the multibeam bathymetry. Depths derived from shipborne hyperspectral measurements were accurate within 13%. In areas where diver observations confirmed biological growth and bioturbation, derived bottom depths were less accurate. Acoustic backscatter corresponds well with the aircraft hyperspectral imagery and in situ measurements of bottom reflectance. Acoustic backscatter was used to define the distribution of different bottom types. Acoustic backscatter imagery corresponds well with the AVIRIS data in the middle to outer study area, implying a close correspondence between seafloor character and optical reflectance. AVIRIS data in the inner study area show poorer correspondence with the acoustic facies, indicating greater water column effects (turbidity). Acoustic backscatter as a proxy for bottom albedo, in conjunction with multibeam bathymetry data, will allow for more precise modeling of the optical signal in coastal environments.

Tailoring the structure of metal oxide nanostructures towards enhanced sensing properties for environmental applications.

PubMed

Yang, Mingqing; He, Junhui

2012-02-15

The present article reviews recent works in our laboratory about the sensing properties to toxic gases using nanostructured WO(3), TiO(2), FTiO(2), and CuO functionalized quartz crystal microbalance (QCM) sensors. WO(3) and TiO(2) functionalized QCM sensors have much shorter response time than those functionalized by conventional hydrogen-bond acidic branched copolymers for detection of dimethyl methylphosphonate (DMMP). FTiO(2) functionalized QCM sensors can improve the gas sensing characteristics by shortening the response time but at the price of partial irreversibility. The sensing mechanism was examined by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Varied CuO nanostructures were synthesized by simple modulation of reaction conditions. All the as-prepared CuO was applied on QCM resonators and explored for HCN sensing. Surprisingly, responses of all the sensors to HCN were found to be in an opposite direction as compared with other common volatile substances, offering excellent selectivity for HCN detection. The sensitivity was very high, and the response and recovery were very fast. Comparison of the specific surface areas of CuO nanostructures showed that CuO of higher surface area is more sensitive than that of lower surface area, indicating that the specific surface area of these CuO nanostructures plays an important role in the sensitivity of related sensors. Based on experimental results, a sensing mechanism was proposed in which a surface redox reaction occurs between CuO and Cu(2)O on the CuO nanostructures reversibly upon contact with HCN and air, respectively. The CuO functionalized QCM sensors are considered to be a promising candidate for trace HCN gas detection in practical applications. Copyright © 2011 Elsevier Inc. All rights reserved.

Polarization-independent transparent effect in windmill-like metasurface

NASA Astrophysics Data System (ADS)

Zhu, Lei; Dong, Liang; Guo, Jing; Meng, Fan Yi; He, Xun Jun; Hao Wu, Tian

2018-07-01

A windmill-like metasurface featuring a polarization-independent electromagnetically induced transparency (EIT) at microwave frequencies is numerically and experimentally demonstrated. The unit cell of the metasurface consists of four rotated identical metal wires, with a 45° angle between the adjacent wires. Destructive coupling between the resonance modes of the metal wires results in the emergence of a transparent window. By combining the metal wires with different degrees of symmetry, EIT effects in the metasurface show polarization-independent properties to incident linear and circular polarization waves. In addition, it is numerically demonstrated that the metasurface possesses a low-loss slow wave property with a group index of 125 and sensing capability based on the refractive index with a figure of merit of 8.73. Such a scheme may lead to many potential applications in areas of slow light and sensing.

Enhanced pH sensitivity of AlGaN/GaN ion-sensitive field effect transistor with Al2O3 synthesized by atomic layer deposition

NASA Astrophysics Data System (ADS)

Wang, Lei; Li, Liuan; Zhang, Tong; Liu, Xinke; Ao, Jin-Ping

2018-01-01

In this study, we evaluated the pH sensitivity enhancement of AlGaN/GaN ion-sensitive field-effect transistor (ISFET) coated by Al2O3 film on the sensing area utilizing atomic layer deposition (ALD). The presence of the Al2O3 film leads to an obvious reduction of surface state density as well as leakage current in the solution, which is beneficial for improving the stability of the ISFET. Furthermore, the sensitivity of the ISFET was improved to 57.8 mV/pH, which is very close to the Nernstian limit at room temperature. The pH sensitivity enhancement can be explained by the higher density of sensing site as well as better surface hydrophilicity.

Remote sensing of effects of land-use practices on water quality. [environmental surveys using Landsat satellites

NASA Technical Reports Server (NTRS)

Graves, D. H.

1975-01-01

Research efforts are presented for the use of remote sensing in environmental surveys in Kentucky. Ground truth parameters were established that represent the vegetative cover of disturbed and undisturbed watersheds in the Cumberland Plateau of eastern Kentucky. Several water quality parameters were monitored of the watersheds utilized in the establishment of ground truth data. The capabilities of multistage-multispectral aerial photography and satellite imagery were evaluated in detecting various land use practices. The use of photographic signatures of known land use areas utilizing manually-operated spot densitometers was studied. The correlation of imagery signature data to water quality data was examined. Potential water quality predictions were developed from forested and nonforested watersheds based upon the above correlations. The cost effectiveness of predicting water quality values was evaluated using multistage and satellite imagery sampling techniques.

A flexible dual-mode proximity sensor based on cooperative sensing for robot skin applications

NASA Astrophysics Data System (ADS)

Huang, Ying; Cai, Xia; Kan, Wenqing; Qiu, Shihua; Guo, Xiaohui; Liu, Caixia; Liu, Ping

2017-08-01

A flexible dual-mode proximity sensor has been designed and implemented, which is capable of combining capacitive-resistive detection in this paper. The capacitive type proximity sensor detecting is defined as mode-C, and the resistive type proximity sensor detecting is defined as mode-R. The characteristics of the proximity sensor are as follows: (1) the theoretical mode is developed which indicates that this proximity sensor can reflect proximity information accurately; (2) both sensing modes are vertically integrated into a sandwich-like chip with an 8 mm × 12 mm unit area. The thickness of a mode-R sensing material (graphene nanoplatelets) and mode-C dielectric (the mixture of carbon black and silicone rubber) is 1 mm and 2.5 mm, respectively; (3) for mode-R, the linearity of temperature-resistance curve can achieve 0.998 in the temperature range from 25°C to 65°C. And for mode-C, various materials can be successfully detected with fast response and high reversibility. Meanwhile, the study compensated the influence of object temperature to ensure mode-C properly works. A cooperative sensing test shows that R-C dual modes sense effectively which can enlarge the sensing distance compared with the single mode proximity sensor. The fabrication of this sensor is convenient, and the integrity of a flexible sandwich-like structure based on dual modes is beneficial to form arrays, which is suitable to be used in skin-like sensing applications.

Metal Oxide Nanostructures and Their Gas Sensing Properties: A Review

PubMed Central

Sun, Yu-Feng; Liu, Shao-Bo; Meng, Fan-Li; Liu, Jin-Yun; Jin, Zhen; Kong, Ling-Tao; Liu, Jin-Huai

2012-01-01

Metal oxide gas sensors are predominant solid-state gas detecting devices for domestic, commercial and industrial applications, which have many advantages such as low cost, easy production, and compact size. However, the performance of such sensors is significantly influenced by the morphology and structure of sensing materials, resulting in a great obstacle for gas sensors based on bulk materials or dense films to achieve highly-sensitive properties. Lots of metal oxide nanostructures have been developed to improve the gas sensing properties such as sensitivity, selectivity, response speed, and so on. Here, we provide a brief overview of metal oxide nanostructures and their gas sensing properties from the aspects of particle size, morphology and doping. When the particle size of metal oxide is close to or less than double thickness of the space-charge layer, the sensitivity of the sensor will increase remarkably, which would be called “small size effect”, yet small size of metal oxide nanoparticles will be compactly sintered together during the film coating process which is disadvantage for gas diffusion in them. In view of those reasons, nanostructures with many kinds of shapes such as porous nanotubes, porous nanospheres and so on have been investigated, that not only possessed large surface area and relatively mass reactive sites, but also formed relatively loose film structures which is an advantage for gas diffusion. Besides, doping is also an effective method to decrease particle size and improve gas sensing properties. Therefore, the gas sensing properties of metal oxide nanostructures assembled by nanoparticles are reviewed in this article. The effect of doping is also summarized and finally the perspectives of metal oxide gas sensor are given. PMID:22736968

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

Long-term remote monitoring of salt marsh biomass

NASA Astrophysics Data System (ADS)

Gross, M. F.; Klemas, V.; Hardisky, M. A.

1990-12-01

An objective of NASA's Biospheric Research Program is to understand biogeochemical cycling on a global scale. Being both very biologically productive and anoxic, wetlands are major sites of carbon dioxide, mean, and sulfur gas flux on a per area basis. Biogeochemical cycling in wetlands is intricately linked to vegetation biomass production. We have been monitoring biomass dynamics of the dominant salt marsh grass Spartina alterniflora for over ten years using remote sensing. Live above ground biomass is highly correlated (r = .79) with Laridsat Thematic Mapper ('IN) and SPOT spectral data transformed into normalized difference vegetation indices. Live belowg round biomass is, in turn, highly correlated (r = .86) with live above ground biomass. Therefore, below ground biomass, a source of carbon substrates for microbial gas production, can be measured using remote sensing indirectly. These relationships have been tested over a wide latitudinal range (from Georgia to Nova Scotia). Analysis of TM and SPOT satellite images from several years has revealed substantial interannual variability in mean live aerial biomass of this species in a 580ha Delaware marsh. Additionally, interannual spatial variability in biomass distribution within the marsh is evident and seems to be linked to precipitation. The aerial biomass of high salinity areas least influenced by upland runoff is the most sensitive to precipitation, whereas marsh areas adjacent to large upland areas or freshwater creeks are the least sensitive. In summary, remote sensing is an effective tool for studying aboveground and belowground biomass in salt marshes. Once the relationship between gas flux data and vegetation biomass is better understood, satellite data could be used to estimate biomass arid gas flux over large regions of the world.

ZIF-8 derived hexagonal-like α-Fe2O3/ZnO/Au nanoplates with tunable surface heterostructures for superior ethanol gas-sensing performance

NASA Astrophysics Data System (ADS)

Chen, Ying; Li, Hui; Ma, Qian; Che, Quande; Wang, Junpeng; Wang, Gang; Yang, Ping

2018-05-01

A series of hexagonal-like α-Fe2O3/ZnO/Au nanoplate heterostructures with tunable morphologies and superior ethanol gas-sensing performance were successfully synthesized via the facile multi-step reaction processes. Hexagonal-like α-Fe2O3 nanoplates with uniform size around 150 nm are employed as new sensor substrates for loading the well-distributed ZnO and Au nanoparticles with adjustable size distribution on the different surfaces. Brunauer-EmmeQ-Teller (BET) surface areas of α-Fe2O3 and α-Fe2O3/ZnO samples are evaluated to be 37.94 and 61.27 m2/g, respectively, while α-Fe2O3/ZnO/Au composites present the highest value of 79.08 m2/g. These α-Fe2O3-based functional materials can exhibit outstanding sensing properties to ethanol. When the ethanol concentration is 100 ppm, the response value of α-Fe2O3/ZnO/Au composites can reach up to 170, which is 14.6 and 80.3 times higher than that of α-Fe2O3/ZnO and pure α-Fe2O3, respectively. The recycling stability and long-time effectiveness can be availably maintained within 30 days, as well as the response and recovery times are shortened to 4 and 5 s, respectively. Significantly, the response value of α-Fe2O3/ZnO/Au composite is still up to 63 at an operating temperature of 280 °C even though the ethanol concentration decreases to 10 ppm. The enhanced gas sensing mechanism would be focused on the synergistic effects of phase compositions, surface heterogeneous structures, large specific surface area, and the selective depositions of Au nanoparticles in α-Fe2O3/ZnO/Au sensors. The synergistic effect of different surface heterostructures referring to α-Fe2O3/Au and α-Fe2O3/ZnO/Au and their novel electron transport processes on the surfaces are first investigated and discussed in details. It is expected that hexagonal-like α-Fe2O3/ZnO/Au nanoplate heterostructures with excellent sensing performance can be the promising highly-sensitive materials in the actual application for monitoring and detecting ethanol.

Difficulties of biomass estimation over natural grassland

NASA Astrophysics Data System (ADS)

Kertész, Péter; Gecse, Bernadett; Pintér, Krisztina; Fóti, Szilvia; Nagy, Zoltán

2017-04-01

Estimation of biomass amount in grasslands using remote sensing is a challenge due to the high diversity and different phenologies of the constituting plant species. The aim of this study was to estimate the biomass amount (dry weight per area) during the vegetation period of a diverse semi-natural grassland with remote sensing. A multispectral camera (Tetracam Mini-MCA 6) was used with 3 cm ground resolution. The pre-processing method includes noise reduction, the correction for the vignetting effect and the calculation of the reflectance using an Incident Light Sensor (ILS). Calibration was made with ASD spectrophotometer as reference. To estimate biomass Partial Least Squares Regression (PLSR) statistical method was used with 5 bands and NDVI as input variables. Above ground biomass was cut in 15 quadrats (50×50 cm) as reference. The best prediction was attained in spring (r2=0.94, RMSE: 26.37 g m-2). The average biomass amount was 167 g m-2. The variability of the biomass is mainly determined by the relief, which causes the high and low biomass patches to be stable. The reliability of biomass estimation was negatively affected by the appearance of flowers and by the senescent plant parts during the summer. To determine the effects of flower's presence on the biomass estimation, 20 dominant species with visually dominant flowers in the area were selected and cover of flowers (%) were estimated in permanent plots during measurement campaigns. If the cover of flowers was low (<25%), the biomass amount estimation was successful (r2 >0,9), while at higher cover of flowers (>30%), the estimation failed (r2 <0,2). This effect restricts the usage of the remote sensing method to the spring - early summer period in diverse grasslands.

The Use of ATLAS Data to Quantify Surface Radiative Budgets in Four US Cities

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey; Gonzalez, Jorge; Rickman, Douglas; Quattrochi, Dale; Schiller, Steve; Comarazamy, Daniel; Estes, Maury

2011-01-01

The additional heating of the air over the city is the result of the replacement of naturally vegetated surfaces with those composed of asphalt, concrete, rooftops and other manmade materials. The temperatures of these artificial surfaces can be 20 to 40 C higher than vegetated surfaces. This produces a dome of elevated air temperatures 5 to 8 C greater over the city, compared to the air temperatures over adjacent rural areas. This effect is called the "urban heat island". Urban landscapes are a complex mixture of vegetated and non-vegetated surfaces. It is difficult to take enough temperature measurements over a large city area to. The use of remotely sensed data from airborne scanners is ideal to characterize the complexity of urban albedo and radiant surface temperatures. The National Aeronautics and Space Administration (NASA) Airborne Thermal and Land Applications Sensor (ATLAS) operates in the visual and IR bands was used to collect data from Salt Lake City, UT, Sacramento, CA, Baton Rouge, LA. And San Juan, Puerto Rico with the main objective of investigating the Urban Heat Island (UHI). In this presentation we will examine the techniques of analyzing remotely sensed data for measuring the effect of various urban surfaces on their contribution to the urban heat island effect.

Use of satellite imagery as environmental impact assessment tool: a case study from the NW Egyptian Red Sea coastal zone.

PubMed

Moufaddal, Wahid M

2005-08-01

Knowledge and detecting impacts of human activities on the coastal ecosystem is an essential management requirement and also very important for future and proper planning of coastal areas. Moreover, documentation of these impacts can help in increasing public awareness about side effects of unsustainable practices. Analysis of multidate remote sensing data can be used as an effective tool in environmental impact assessment (EIA). Being synoptic and frequent in coverage, multidate data from Landsat and other satellites provide a reference record and bird's eye viewing to the environmental situation of the coastal ecosystem and the associated habitats. Furthermore, integration of satellite data with field observations and background information can help in decision if a certain activity has caused deterioration to a specific habitat or not. The present paper is an attempt to utilize remote sensing data for assessment impacts of some human activities on the major sensitive habitats of the NW Egyptian Red Sea coastal zone, definitely between Ras Gemsha and Safaga. Through multidate change analysis of Landsat data (TM & ETM+ sensors), it was possible to depict some of the human infringements in the area and to provide, in some cases, exclusive evidences for the damaging effect of some developmental activities.

Linear Fresnel Spectrometer Chip with Gradient Line Grating

NASA Technical Reports Server (NTRS)

Choi, Sang Hyouk (Inventor); Park, Yeonjoon (Inventor)

2015-01-01

A spectrometer that includes a grating that disperses light via Fresnel diffraction according to wavelength onto a sensing area that coincides with an optical axis plane of the grating. The sensing area detects the dispersed light and measures the light intensity associated with each wavelength of the light. Because the spectrometer utilizes Fresnel diffraction, it can be miniaturized and packaged as an integrated circuit.

Accuracy of Remotely Sensed Classifications For Stratification of Forest and Nonforest Lands

Treesearch

Raymond L. Czaplewski; Paul L. Patterson

2001-01-01

We specify accuracy standards for remotely sensed classifications used by FIA to stratify landscapes into two categories: forest and nonforest. Accuracy must be highest when forest area approaches 100 percent of the landscape. If forest area is rare in a landscape, then accuracy in the nonforest stratum must be very high, even at the expense of accuracy in the forest...

Whose Sense of Place? Re-thinking Place Concept and Urban Heritage Conservation in Social Media Era

NASA Astrophysics Data System (ADS)

Dameria, Christin; Akbar, Roos; Natalivan Indradjati, Petrus

2018-05-01

A change in a conservation approach that is now more focused on the conservation of a place than on a single object has placed an understanding of a place as an important concept that must be understood in urban heritage planning. However, the urban place perspective has been shifted, as a result of the change of attitude of people living in the urban area due to the rising of social media. This paper argues the concept of place in the heritage conservation planning, especially in the area designed to be tourism objects, which needs to be revisited. The very dynamic urban people as a result of technology and information must be considered. In order to understand the man-place relationship, the sense of place concept is the most common concept used and in the current context of heritage conservation, the review of place concept could be traced by understanding who is the owner of a sense of place in the social media era. In the current academic literature, the common discourse says the local community as the owner of the sense of place because visitors have limited chance to own the sense of place. This paper also argues that the shift of place perspective due to social media could be the catalyst in creating a strong sense of place for visitors. To support the argument, this paper uses the study of Concept of Mediatization and Concept of Parochial that have successfully explained how social media provides indirect experience based on people-place interaction and a sense of familiarity of an unknown or strange place. Therefore, this paper states that in the sense of place context: (1) the experience factor, as one of the factors in the creation of a sense of place, does not need to be physically experienced but it can be built based on other person’s personal reflection. It also gives an opportunity to make a self-interpretation about the value of the heritage place; (2) sense of familiarity, which is believed to be owned by the locals only due to the period of staying in the area, can be owned by persons who have never visited the place. That is why when the tourists come to visit the heritage place with their own interpretation of experience built previously they are very potential to have a strong sense of place when doing activities in such short time of visit. In the context of heritage planning, this change will certainly have an impact on (1) the change of the stakeholder mapping of urban heritage area conservation, and (2) the change of place-making concept in an effort to conserve the public space of heritage areas, where heritage planning needs to make room for digital dimension contribution as one form of advancement in information technology that has become the urban lifestyle of today.

Exploring the Influence of Topographic Correction and SWIR Spectral Information Inclusion on Burnt Scars Detection From High Resolution EO Imagery: A Case Study Using ASTER imagery

NASA Astrophysics Data System (ADS)

Said, Yahia A.; Petropoulos, George; Srivastava, Prashant K.

2014-05-01

Information on burned area estimates is of key importance in environmental and ecological studies as well as in fire management including damage assessment and planning of post-fire recovery of affected areas. Earth Observation (EO) provides today the most efficient way in obtaining such information in a rapid, consistent and cost-effective manner. The present study aimed at exploring the effect of topographic correction to the burnt area delineation in conditions characteristic of a Mediterranean environment using ASTER high resolution multispectral remotely sensed imagery. A further objective was to investigate the potential added-value of the inclusion of the shortwave infrared (SWIR) bands in improving the retrievals of burned area cartography from the ASTER data. In particular the capability of the Maximum Likelihood (ML), the Support Vector Machines (SVMs) and Object-based Image Analysis (OBIA) classification techniques has been examined herein for the purposes of our study. As a case study is used a typical Mediterranean site on which a fire event occurred in Greece during the summer of 2007, for which post-fire ASTER imagery has been acquired. Our results indicated that the combination of topographic correction (ortho-rectification) with the inclusion of the SWIR bands returned the most accurate results in terms of burnt area mapping. In terms of image processing methods, OBIA showed the best results and found as the most promising approach for burned area mapping with least absolute difference from the validation polygon followed by SVM and ML. All in all, our study provides an important contribution to the understanding of the capability of high resolution imagery such as that from ASTER sensor and corroborates the usefulness particularly of the topographic correction as an image processing step when in delineating the burnt areas from such data. It also provides further evidence that use of EO technology can offer an effective practical tool for the extent of ecosystem destruction from wildfires, providing extremely useful information in co-ordinating efforts for the recovery of fire-affected ecosystems after wildfire. Keywords: Remote Sensing, ASTER, Burned area mapping, Maximum Likelihood, Support Vector Machines, Object-based image analysis, Greece

The effect of urban heat island on Izmir's city ecosystem and climate.

PubMed

Corumluoglu, Ozsen; Asri, Ibrahim

2015-03-01

Depending on the researches done on urban landscapes, it is found that the heat island intensity caused by the activities in any city has some impact on the ecosystem of the region and on the regional climate. Urban areas located in arid and semiarid lands somehow represent heat increase when it is compared with the heat in the surrounding rural areas. Thus, cities located amid forested and temperate climate regions show moderate temperatures. The impervious surfaces let the rainfall leave the city lands faster than undeveloped areas. This effect reduces water's cooling effects on these lands. More significantly, if trees and other vegetations are rare in any region, it means less evapotranspiration-the process by which trees "exhale" water. Trees also contribute to the cooling of urban lands by their shade. Land cover and land use maps can easily be produced by processing of remote sensing satellites' images, like processing of Landsat's images. As a result of this process, urban regions can be distinguished from vegetation. Analyzed GIS data produced and supported by these images can be utilized to determine the impact of urban land on energy, water, and carbon balances at the Earth's surface. Here in this study, it is found that remote sensing technique with thermal images is a liable technique to asses where urban heat islands and hot spots are located in cities. As an application area, in Izmir, it was found that the whole city was in high level of surface temperature as it was over 28 °C during the summer times. Beside this, the highest temperature values which go up to 47 °C are obtained at industrial regions especially where the iron-steel factories and the related industrial activities are.

Association Between Bereaved Families' Sense of Security and Their Experience of Death in Cancer Patients: Cross-Sectional Population-Based Study.

PubMed

Igarashi, Ayumi; Miyashita, Mitsunori; Morita, Tatsuya; Akizuki, Nobuya; Akiyama, Miki; Shirahige, Yutaka; Sato, Kazuki; Yamamoto-Mitani, Noriko; Eguchi, Kenji

2016-05-01

The sense of security scale was developed to indicate care quality within the community. Bereaved families have perspective to evaluate the quality of the care system. The aim was to examine associations between end-of-life care and sense of security regarding regional cancer care among bereaved families. A cross-sectional population-based survey was conducted with families of cancer patients who died in regional areas of Japan. A total of 1046 family caregivers of patients responded to surveys (effective response rate of 65%). In multiple regression analyses, the families' higher age (P < 0.001), home death (P = 0.039), better health status of the family at patients' end of life (P = 0.016), lower caregiving burden (P < 0.001), and elements of perceived good patient death, including being free from physical distress (P < 0.001), trusting the physician (P < 0.001), living in calm circumstances (P = 0.042), and feeling that one's life was fulfilling (P = 0.035), were associated with a higher sense of security. Quality of death and lower burden on family caregivers were associated with families' sense of security. This suggests strategies for improving care quality for each patient to improve the sense of security. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS).

PubMed

Zhang, Yuanzhi; Chen, Zhengyi; Zhu, Boqin; Luo, Xiuyue; Guan, Yanning; Guo, Shan; Nie, Yueping

2008-12-01

The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.

Water supply studies. [management and planning of water supplies in California

NASA Technical Reports Server (NTRS)

Burgy, R. H.; Algazi, V. R.; Draeger, W. C.; Churchman, C. W.; Thomas, R. W.; Lauer, D. T.; Hoos, I.; Krumpe, P. F.; Nichols, J. D.; Gialdini, M. J.

1973-01-01

The primary test site for water supply investigations continues to be the Feather River watershed in northeastern California. This test site includes all of the area draining into and including the Oroville Reservoir. The principal effort is to determine the extent to which remote sensing techniques, when properly employed, can provide information useful to those persons concerned with the management and planning of lands and facilities for the production of water, using the Oroville Reservoir and the California Water Project as the focus for the study. In particular, emphasis is being placed on determining the cost effectiveness of information derived through remote sensing as compared with that currently being derived through more conventional means.

Survey of remote sensing applications

USGS Publications Warehouse

Deutsch, Morris

1974-01-01

Data from the first earth resources technology satellite (ERTS) as well as from NASA and other aircraft, contain much of the information indicative of the distribution of groundwater and the extent of its utilization. Thermal infrared imagery from aircraft is particularly valuable in studying groundwater discharge to the sea and other surface water bodies. Color infrared photography from aircraft and space is also used to locate areas of potential groundwater development. Anomalies in vegetation, soils, moisture, and their pattern of distribution may be indicative of underlying groundwater conditions. Remote sensing may be used directly or indirectly to identify stream reaches for test holes or production wells. Similarly, location of submarine springs increase effectiveness of groundwater exploration in the coastal zone.

Electrical stimulation of mechanoreceptors

NASA Astrophysics Data System (ADS)

Echenique, A. M.; Graffigna, J. P.

2011-12-01

Within the field of Rehabilitation Engineering, this work is aimed at identifying the optimal parameters of electric current stimulus which activate the nervous axons of mecanoreceptors found in the fingertip, allowing, this way, to resemble tactile senses. These sensorial feelings can be used by aiding technological means, namely, the sensorial substitution technology, in an attempt to render information to blind people through the tactile sense. The physical pressure on sensorial areas (fingertips) used for reading activities through the Braille System is the main effect that is imitated and studied in this research work. An experimental aiding prototype for Braille reading research has been developed and tested with blinds and reduced vision people, with highly satisfactory results.

Effect of surfactant concentration on the ultraviolet sensing properties of ZnO-cellulose nanocomposites

NASA Astrophysics Data System (ADS)

Sahoo, Karunakar; Nayak, J.

2018-05-01

ZnO nanoparticles were grown, on cellulose fiber surfaces, at three different concentrations of hexamethylenetetramine by an aqueous chemical method. A typical ZnO-cellulose nanocomposite showed an enhanced UV sensing activity due to its large surface area. Due to illumination with ultraviolet light, the surface photocurrent of ZnO-cellulose nanocomposite pellet increased from 8.90 × 10‒7 A to 3.18 × 10‒5 A in 15 s. The UV ON to OFF (IUV/IDark) ratio for this sample was 35.73. Hence, an enhancement in the conductivity due to UV illumination shows that our ZnO-cellulose can be used for the fabrication of UV sensors.

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.

Environmental Public Health Survelliance for Exposure to Respiratory Health Hazards: A Joint NASA/CDC Project to Use Remote Sensing Data for Estimating Airborne Particulate Matter Over the Atlanta, Georgia Metropolitan Area

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Rickman, Douglas; Mohammad, Al-Hamdan; Crosson, William; Estes, Maurice, Jr.; Limaye, Ashutosh; Qualters, Judith

2008-01-01

Describes the public health surveillance efforts of NASA, in a joint effort with the Center for Disease Control (CDC). NASA/MSFC and the CDC are partners in linking nvironmental and health data to enhance public health surveillance. The use of NASA technology creates value - added geospatial products from existing environmental data sources to facilitate public health linkages. The venture sought to provide remote sensing data for the 5-country Metro-Atlanta area and to integrate this environmental data with public health data into a local network, in an effort to prevent and control environmentally related health effects. Remote sensing data used environmental data (Environmental Protection Agency [EPA] Air Quality System [AQS] ground measurements and MODIS Aerosol Optical Depth [AOD]) to estimate airborne particulate matter over Atlanta, and linked this data with health data related to asthma. The study proved the feasibility of linking environmental data (MODIS particular matter estimates and AQS) with health data (asthma). Algorithms were developed for QC, bias removal, merging MODIS and AQS particulate matter data, as well as for other applications. Additionally, a Business Associate Agreement was negotiated for a health care provider to enable sharing of Protected Health Information.

Building change detection via a combination of CNNs using only RGB aerial imageries

NASA Astrophysics Data System (ADS)

Nemoto, Keisuke; Hamaguchi, Ryuhei; Sato, Masakazu; Fujita, Aito; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes from remote sensing imageries. Recent studies have addressed this goal by exploiting 3-D information as a proxy for building height. In contrast, because in practice it is expensive or impossible to prepare 3-D information, we do not rely on 3-D data but focus on using only RGB aerial imageries. Instead, we employ deep convolutional neural networks (CNNs) to extract effective features, and improve change detection accuracy in RGB remote sensing imageries. We consider two aspects of building change detection, building detection and subsequent change detection. Our proposed methodology was tested on several areas, which has some differences such as dominant building characteristics and varying brightness values. On all over the tested areas, the proposed method provides good results for changed objects, with recall values over 75 % with a strict overlap requirement of over 50% in intersection-over-union (IoU). When the IoU threshold was relaxed to over 10%, resulting recall values were over 81%. We conclude that use of CNNs enables accurate detection of building changes without employing 3-D information.

Remote sensing of effects of land use practices on water quality

NASA Technical Reports Server (NTRS)

Graves, D. H.; Colthrap, G. B.

1977-01-01

An intensive study was conducted to determine the utility of manual densitometry and color additive viewing of aircraft and LANDSAT transparencies for monitoring land use and land use change. The relationship between land use and selected water quality parameters was also evaluated. Six watersheds located in the Cumberland Plateau region of eastern Kentucky comprised the study area for the project. Land uses present within the study area were reclaimed surface mining and forestry. Fertilization of one of the forested watersheds also occurred during the study period.

U.S. national report to the International Union of Geodesy and Geophysics

NASA Technical Reports Server (NTRS)

Gorney, D. J.

1987-01-01

This paper highlights progress by U.S. authors during 1983-1986 in the broad area of auroral research. Atmospheric emissions and their use as a tool for remote-sensing the dynamics, energetics, and effects of auroral activity is a subject which is emphasized here because of the vast progress made in this area on both observational and theoretical fronts. The evolution of primary auroral electrons, the acceleration of auroral ions, small-scale electric fields, auroral kilometric radiation, auroral empirical models and activity indices are also reviewed. An extensive bibliography is supplied.

Ubiquitous Wireless Smart Sensing and Control

NASA Technical Reports Server (NTRS)

Wagner, Raymond

2013-01-01

Need new technologies to reliably and safely have humans interact within sensored environments (integrated user interfaces, physical and cognitive augmentation, training, and human-systems integration tools). Areas of focus include: radio frequency identification (RFID), motion tracking, wireless communication, wearable computing, adaptive training and decision support systems, and tele-operations. The challenge is developing effective, low cost/mass/volume/power integrated monitoring systems to assess and control system, environmental, and operator health; and accurately determining and controlling the physical, chemical, and biological environments of the areas and associated environmental control systems.

Ubiquitous Wireless Smart Sensing and Control. Pumps and Pipes JSC: Uniquely Houston

NASA Technical Reports Server (NTRS)

Wagner, Raymond

2013-01-01

Need new technologies to reliably and safely have humans interact within sensored environments (integrated user interfaces, physical and cognitive augmentation, training, and human-systems integration tools).Areas of focus include: radio frequency identification (RFID), motion tracking, wireless communication, wearable computing, adaptive training and decision support systems, and tele-operations. The challenge is developing effective, low cost/mass/volume/power integrated monitoring systems to assess and control system, environmental, and operator health; and accurately determining and controlling the physical, chemical, and biological environments of the areas and associated environmental control systems.

Cornell University remote sensing program. [New York

NASA Technical Reports Server (NTRS)

Liang, T.; Mcnair, A. J.; Philipson, W. R. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Available aerial photographs were used to characterize mosquito breeding sites in Oswego County, New York. Numerous wetlands are contained within this county; this area is the only inland area in North America to have confirmed outbreaks of eastern equine encephalitis. This photocharacterization of primary mosquito breeding sites will be used to develop effective spraying. Large scale color and color infrared aerial photographs were used to assess changes in aquatic vegetation that accompanied phosphorus reduction in an eutrophic lake in New York.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

US national report to the International Union of Geodesy and Geophysics

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

Gorney, D.J.

1987-04-01

This paper highlights progress by U.S. authors during 1983-1986 in the broad area of auroral research. Atmospheric emissions and their use as a tool for remote-sensing the dynamics, energetics, and effects of auroral activity is a subject which is emphasized here because of the vast progress made in this area on both observational and theoretical fronts. The evolution of primary auroral electrons, the acceleration of auroral ions, small-scale electric fields, auroral kilometric radiation, auroral empirical models and activity indices are also reviewed. An extensive bibliography is supplied.

Monitoring the lake area changes of the Qinghai-Tibet Plateau using coarse-resolution time series remote sensing data

NASA Astrophysics Data System (ADS)

Ma, M.

2015-12-01

The Qinghai-Tibet Plateau (QTP) is the world's highest and largest plateau and is occasionally referred to as "the roof of the world". As the important "water tower", there are 1,091 lakes of more than 1.0 km2 in the QTP areas, which account for 49.4% of the total area of lakes in China. Some studies focus on the lake area changes of the QTP areas, which mainly use the middle-resolution remote sensing data (e.g. Landsat TM). In this study, the coarse-resolution time series remote sensing data, MODIS data at a spatial resolution of 250m, was used to monitor the lake area changes of the QTP areas during the last 15 years. The dataset is the MOD13Q1 and the Normal Difference Vegetation Index (NDVI) is used to identify the lake area when the NDVI is less than 0. The results show the obvious inner-annual changes of most of the lakes. Therefore the annually average and maximum lake areas are calculated based on the time series remote data, which can better quantify the change characteristics than the single scene of image data from the middle-resolution data. The results indicate that there are big spatial variances of the lake area changes in the QTB. The natural driving factors are analyzed for revealing the causes of changes.

Remote sensing application to regional activities

NASA Technical Reports Server (NTRS)

Shahrokhi, F.; Jones, N. L.; Sharber, L. A.

1976-01-01

Two agencies within the State of Tennessee were identified whereby the transfer of aerospace technology, namely remote sensing, could be applied to their stated problem areas. Their stated problem areas are wetland and land classification and strip mining studies. In both studies, LANDSAT data was analyzed with the UTSI video-input analog/digital automatic analysis and classification facility. In the West Tennessee area three land-use classifications could be distinguished; cropland, wetland, and forest. In the East Tennessee study area, measurements were submitted to statistical tests which verified the significant differences due to natural terrain, stripped areas, various stages of reclamation, water, etc. Classifications for both studies were output in the form of maps of symbols and varying shades of gray.

Remote sensing: An inventory of earth's resources

NASA Technical Reports Server (NTRS)

Gramenopoulos, N.

1974-01-01

The remote sensing capabilities of Landsat are reviewed along with the broad areas of application of the Landsat imagery. The importance of Landsat imagery in urban planning and resources management is stressed.

Applications of Sentinel-2 data for agriculture and forest monitoring using the absolute difference (ZABUD) index derived from the AgroEye software (ESA)

NASA Astrophysics Data System (ADS)

de Kok, R.; WeŻyk, P.; PapieŻ, M.; Migo, L.

2017-10-01

To convince new users of the advantages of the Sentinel_2 sensor, a simplification of classic remote sensing tools allows to create a platform of communication among domain specialists of agricultural analysis, visual image interpreters and remote sensing programmers. An index value, known in the remote sensing user domain as "Zabud" was selected to represent, in color, the essentials of a time series analysis. The color index used in a color atlas offers a working platform for an agricultural field control. This creates a database of test and training areas that enables rapid anomaly detection in the agricultural domain. The use cases and simplifications now function as an introduction to Sentinel_2 based remote sensing, in an area that before relies on VHR imagery and aerial data, to serve mainly the visual interpretation. The database extension with detected anomalies allows developers of open source software to design solutions for further agricultural control with remote sensing.

Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

NASA Astrophysics Data System (ADS)

Hochschild, V.

2012-12-01

This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

NASA Astrophysics Data System (ADS)

Sun, Cheng; Wu, Zhi-feng; Lv, Zhi-qiang; Yao, Na; Wei, Jian-bing

2013-04-01

There is a widespread concern about urban sprawl. It has negative impacts on natural resources, economic health, and community character. Without a universal definition of urban sprawl, its quantification and modeling is difficult. Traditionally, urban sprawl was described using qualitative terms, and landscape patterns. Quantitative methods are required to help local, regional and state land use planners to better identify, understand and address it. In this study, an integrated approach of remote sensing and GIS was used to identify three urban growth types of infilling growth, outlying growth and edge-expansion growth at the city of Guangzhou, China. Spatial metrics were used to characterize long-term trends and patterns of urban growth. Result shows that the proposed method can identify and visualize different urban growth types. Infilling growth is the dominant expansion type. Edge-expansion is concentrated at suburban areas. Outlying growth mainly occurs relatively far from the urban core. The analysis shows that initially the urban area expands mainly as outlying growth, causing increased fragmentation and dispersion of urban areas. Next, growth filled in vacant non-urban area inwards, resulting into a more compact and aggregated urban pattern. The study shows an improved understanding of urban growth, and helps to provide an effective way for urban planning.

High Surface Area MoS 2/Graphene Hybrid Aerogel for Ultrasensitive NO 2 Detection

DOE PAGES

Long, Hu; Harley-Trochimczyk, Anna; Pham, Thang; ...

2016-05-23

A MoS 2/graphene hybrid aerogel synthesized with two-dimensional MoS 2 sheets coating a high surface area graphene aerogel scaffold is characterized and used for ultrasensitive NO 2 detection. The combination of graphene and MoS 2 leads to improved sensing properties with the graphene scaffold providing high specific surface area and high electrical and thermal conductivity and the single to few-layer MoS2 sheets providing high sensitivity and selectivity to NO 2. The hybrid aerogel is integrated onto a low-power microheater platform to probe the gas sensing performance. At room temperature, the sensor exhibits an ultralow detection limit of 50 ppb NOmore » 2. By heating the material to 200 °C, the response and recovery times to reach 90% of the final signal decrease to <1 min, while retaining the low detection limit. The MoS 2/graphene hybrid also shows good selectivity for NO 2 against H 2 and CO, especially when compared to bare graphene aerogel. The unique structure of the hybrid aerogel is responsible for the ultrasensitive, selective, and fast NO 2 sensing. The improved sensing performance of this hybrid aerogel also suggests the possibility of other 2D material combinations for further sensing applications.« less

Effects of grazing on leaf area index, fractional cover and evapotranspiration by a desert phreatophyte community at a former uranium mill site on the Colorado Plateau.

PubMed

Bresloff, Cynthia J; Nguyen, Uyen; Glenn, Edward P; Waugh, Jody; Nagler, Pamela L

2013-01-15

This study employed ground and remote sensing methods to monitor the effects of grazing on leaf area index (LAI), fractional cover (f(c)) and evapotranspiration (ET) of a desert phreatophyte community over an 11 year period at a former uranium mill site on the Colorado Plateau, U.S. Nitrate, ammonium and sulfate are migrating away from the mill site in a shallow alluvial aquifer. The phreatophyte community, consisting of Atriplex canescens (ATCA) and Sarcobatus vermiculatus (SAVE) shrubs, intercepts groundwater and could potentially slow the movement of the contaminant plume through evapotranspiration (ET). However, the site has been heavily grazed by livestock, reducing plant cover and LAI. We used livestock exclosures and revegetation plots to determine the effects of grazing on LAI, f(c) and ET, then projected the findings over the whole site using multi-platform remote sensing methods. We show that ET is approximately equal to annual precipitation at the site, but when ATCA and SAVE are protected from grazing they can develop high f(c) and LAI values, and ET can exceed annual precipitation, with the excess coming from groundwater discharge. Therefore, control of grazing could be an effective method to slow migration of contaminants at this and similar sites in the western U.S. Copyright © 2012 Elsevier Ltd. All rights reserved.

Investigation of forestry resources and other remote sensing data. 1: LANDSAT. 2: Remote sensing of volcanic emissions

NASA Technical Reports Server (NTRS)

Birnie, R. W.; Stoiber, R. E. (Principal Investigator)

1983-01-01

Computer classification of LANDSAT data was used for forest type mapping in New England. The ability to classify areas of hardwood, softwood, and mixed tree types was assessed along with determining clearcut regions and gypsy moth defoliation. Applications of the information to forest management and locating potential deer yards were investigated. The principal activities concerned with remote sensing of volcanic emissions centered around the development of remote sensors for SO2 and HCl gas, and their use at appropriate volcanic sites. Two major areas were investigated (Masaya, Nicaragua, and St. Helens, Washington) along with several minor ones.

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

NASA Astrophysics Data System (ADS)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

μ-'Diving suit' for liquid-phase high-Q resonant detection.

PubMed

Yu, Haitao; Chen, Ying; Xu, Pengcheng; Xu, Tiegang; Bao, Yuyang; Li, Xinxin

2016-03-07

A resonant cantilever sensor is, for the first time, dressed in a water-proof 'diving suit' for real-time bio/chemical detection in liquid. The μ-'diving suit' technology can effectively avoid not only unsustainable resonance due to heavy liquid-damping, but also inevitable nonspecific adsorption on the cantilever body. Such a novel technology ensures long-time high-Q resonance of the cantilever in solution environment for real-time trace-concentration bio/chemical detection and analysis. After the formation of the integrated resonant micro-cantilever, a patterned photoresist and hydrophobic parylene thin-film are sequentially formed on top of the cantilever as sacrificial layer and water-proof coat, respectively. After sacrificial-layer release, an air gap is formed between the parylene coat and the cantilever to protect the resonant cantilever from heavy liquid damping effect. Only a small sensing-pool area, located at the cantilever free-end and locally coated with specific sensing-material, is exposed to the liquid analyte for gravimetric detection. The specifically adsorbed analyte mass can be real-time detected by recording the frequency-shift signal. In order to secure vibration movement of the cantilever and, simultaneously, reject liquid leakage from the sensing-pool region, a hydrophobic parylene made narrow slit structure is designed surrounding the sensing-pool. The anti-leakage effect of the narrow slit and damping limited resonance Q-factor are modelled and optimally designed. Integrated with electro-thermal resonance excitation and piezoresistive frequency readout, the cantilever is embedded in a micro-fluidic chip to form a lab-chip micro-system for liquid-phase bio/chemical detection. Experimental results show the Q-factor of 23 in water and longer than 20 hours liquid-phase continuous working time. Loaded with two kinds of sensing-materials at the sensing-pools, two types of sensing chips successfully show real-time liquid-phase detection to ppb-level organophosphorous pesticide of acephate and E.coli DH5α in PBS, respectively. The proposed method fundamentally solves the long-standing problem of being unable to operate a resonant micro-sensor in liquid well.

Experiencing limits of acceptable change: some thoughts after a decade of implementation

Treesearch

Stephen F. McCool; David N. Cole

1997-01-01

Wilderness managers and researchers have experienced implementation of the Limits of Acceptable Change planning system for over a decade. In a sense, implementation of LAC has been a broad scale experiment in planning, with the hypothesis being that LAC processes are more effective approaches to deal with questions of recreation management in protected areas than the...

Island Biogeography Theory: Emerging Patterns and Human Effects

Treesearch

Qinfeng Guo

2015-01-01

Islands are conventionally (and narrowly) referred to as isolated lands in surrounding waters. However, in broad senses and when loosely defined, ‘islands’ also include insular areas or entities such as mountain tops, lakes (e.g., potholes in northern Great Plains in North America), oasis (in deserts), and springs (especially in deserts) that support unique species...

Quantitative Assessment of a Field-Based Course on Integrative Geology, Ecology and Cultural History

ERIC Educational Resources Information Center

Sheppard, Paul R.; Donaldson, Brad A.; Huckleberry, Gary

2010-01-01

A field-based course at the University of Arizona called Sense of Place (SOP) covers the geology, ecology and cultural history of the Tucson area. SOP was quantitatively assessed for pedagogical effectiveness. Students of the Spring 2008 course were given pre- and post-course word association surveys in order to assess awareness and comprehension…

Visual Display Study: National 4-H Center. A 4-H Intern Report.

ERIC Educational Resources Information Center

Farwell, Sanford W.

An internship report cites ways in which the National 4-H Center could be more effective in a visual sense. The author suggests collecting the memorabilia already at the Center to form an historical museum and coordinating the historical items with present items. Impact areas, those with a lot of traffic, are discussed individually in terms of…

1. Photocopy of photograph (original photograph/negative located at the Remote ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. Photocopy of photograph (original photograph/negative located at the Remote Sensing Laboratory, Nellis Air Force Base, Las Vegas, Nevada). R.B., Photograph for Civil Effects Test Organization, May 9, 1962. Historic view of Japanese village, facing west - Nevada Test Site, Japanese Village, Area 4, Yucca Flat, 4-04 Road near Rainier Mesa Road, Mercury, Nye County, NV

Sensitivity of Landsat image-derived burn severity indices to immediate post-fire effects

Treesearch

A. T. Hudak; S. Lewis; P. Robichaud; P. Morgan; M. Bobbitt; L. Lentile; A. Smith; Z. Holden; J. Clark; R. McKinley

2006-01-01

The USFS Remote Sensing Applications Center (RSAC) and the USGS Center for Earth Resources Observation and Science (EROS) produce Burned Area Reflectance Classification (BARC) maps as a rapid, preliminary indication of burn severity on large wildfire events. Currently the preferred burn severity index is the delta Normalized Burn Ratio (dNBR), which requires NBR values...

Nanoporous Pirani sensor based on anodic aluminum oxide

NASA Astrophysics Data System (ADS)

Jeon, Gwang-Jae; Kim, Woo Young; Shim, Hyun Bin; Lee, Hee Chul

2016-09-01

A nanoporous Pirani sensor based on anodic aluminum oxide (AAO) is proposed, and the quantitative relationship between the performance of the sensor and the porosity of the AAO membrane is characterized with a theoretical model. The proposed Pirani sensor is composed of a metallic resistor on a suspended nanoporous membrane, which simultaneously serves as the sensing area and the supporting structure. The AAO membrane has numerous vertically-tufted nanopores, resulting in a lower measurable pressure limit due to both the increased effective sensing area and the decreased effective thermal loss through the supporting structure. Additionally, the suspended AAO membrane structure, with its outer periphery anchored to the substrate, known as a closed-type design, is demonstrated using nanopores of AAO as an etch hole without a bulk micromachining process used on the substrate. In a CMOS-compatible process, a 200 μm × 200 μm nanoporous Pirani sensor with porosity of 25% was capable of measuring the pressure from 0.1 mTorr to 760 Torr. With adjustment of the porosity of the AAO, the measurable range could be extended toward lower pressures of more than one decade compared to a non-porous membrane with an identical footprint.

Remote sensing study of the impact of vegetation on thermal environment in different contexts

NASA Astrophysics Data System (ADS)

Xie, Qijiao; Wu, Yingjiao; Zhou, Zhixiang; Wang, Zhengxiang

2018-02-01

Satellite remote sensing technology provides informative data for detecting the land surface temperature (LST) distribution and urban heat island (UHI) effect remotely and regionally. In this study, two Landsat Thematic Mapper (TM) images acquired on September 26, 1987 and September 17, 2013 were used to derive LST and the normalized difference vegetation index (NDVI) values in Wuhan, China. The relationships between NDVI and LST were examined in different contexts, namely built-up area, farmland, grassland and forest. Results showed that negative correlations between the mean NDVI and LST were detected in all observed land covers, which meant that vegetation was efficient in decreasing surface temperatures and mitigating UHI effect. The cooling efficiency of vegetation on thermal environment varied with different contexts. As mean NDVI increased at each 0.1, the decreased LST values in built-up area, farmland, grassland and forest were 1.4 °C, 1.4 °C, 1.1 °C, 1.9 °C in 1987 and 1.4 °C, 1.7 °C, 1.3 °C, 1.8 °C in 2013, respectively. This finding encourages urban planners and greening designers to devote more efforts in protecting urban forests.

Acoustic Wave Propagation in Pressure Sense Lines

NASA Technical Reports Server (NTRS)

Vitarius, Patrick; Gregory, Don A.; Wiley, John; Korman, Valentin

2003-01-01

Sense lines are used in pressure measurements to passively transmit information from hostile environments to areas where transducers can be used. The transfer function of a sense line can be used to obtain information about the measured environment from the protected sensor. Several properties of this transfer function are examined, including frequency dependence, Helmholtz resonance, and time of flight delay.

Optical Microfiber Technology for Current, Temperature, Acceleration, Acoustic, Humidity and Ultraviolet Light Sensing

PubMed Central

Lancaster, David G.; Monro, Tanya M.

2017-01-01

Optical microfibers possess excellent optical and mechanical properties that have been exploited for sensing. We highlight the authors’ recent work in the areas of current, temperature, acceleration, acoustic, humidity and ultraviolet-light sensing based on this exquisite technology, and the advantages and challenges of using optical microfibers are discussed. PMID:29283414

Using a remote sensing-based, percent tree cover map to enhance forest inventory estimation

Treesearch

Ronald E. McRoberts; Greg C. Liknes; Grant M. Domke

2014-01-01

For most national forest inventories, the variables of primary interest to users are forest area and growing stock volume. The precision of estimates of parameters related to these variables can be increased using remotely sensed auxiliary variables, often in combination with stratified estimators. However, acquisition and processing of large amounts of remotely sensed...

Mapping of risk prone areas of kala-azar (Visceral leishmaniasis) in parts of Bihar State, India: an RS and GIS approach.

PubMed

Sudhakar, S; Srinivas, T; Palit, A; Kar, S K; Battacharya, S K

2006-09-01

The kala-azar fever (Visceral leishmaniasis) is continuing unabated in India for over a century, now being largely confined to the eastern part of India mainly in Bihar state and to some extent in its bordering states like West Bengal and Uttar Pradesh. Two study sites namely Patepur block in Vaishali district with high endemicity in northern part and Lohardagga block in Lohardagga district with absolute non-endemicity in southern part of Bihar were selected for the study with the following objectives : (i) to study the macro-ecosystem in relation to distribution of vector -Phlebotomus argentipes; (ii) to identify/map the risk prone areas or villages in a block for quick remedial measures; and (iii) to make use of satellite remote sensing and GIS to demonstrate the utility for rapid assessment of landuse/landcover and their relation with the incidence of kalaazar leading to the mapping of risk prone areas. Indian Remote Sensing (IRS)-1D LISS III satellite data for the periods of March and November 2000 were analysed in Silicon graphic image processing system using ERDAS software. False color composites (FCC) were generated and landuse/landcover was assessed using Maximum likelihood supervised classification techniques based on ground truth training sets. During the study the GIS functions are used to quantify the remotely sensed landscape proportions of 5 km2 buffer surrounding each known group of villages of high occurrence of sandflies in endemic and nonendemic study sites. Instead of traditional ground based survey methods to vector surveillance, the present study used a combination of remote sensing (RS) and geographical information system (GIS) approach to develop landscape predictors of sandfly abundance-an indicator of human vector contact and as a measure of risk prone areas. Statistical analysis using the remotely sensed landscape variables showed that rural villages surrounded by higher proportion of transitional swamps with soft stemmed edible plants and banana, sugarcane plantations had higher sandfly abundance and would, therefore, be at higher risk prone areas for man-vector contact. The present study clearly brought out the usefulness of satellite remote sensing technology in generating the crucial information on spatial distribution of landuse/landcover classes with special emphasis on indicator landcover classes thereby helping in prioritising the area to identify risk prone areas of kala-azar through GIS application tools.

Detection of heavy metal ions in drinking water using a high-resolution differential surface plasmon resonance sensor.

PubMed

Forzani, Erica S; Zhang, Haiqian; Chen, Wilfred; Tao, Nongjian

2005-03-01

We have built a high-resolution differential surface plasmon resonance (SPR) sensor for heavy metal ion detection. The sensor surface is divided into a reference and sensing areas, and the difference in the SPR angles from the two areas is detected with a quadrant cell photodetector as a differential signal. In the presence of metal ions, the differential signal changes due to specific binding of the metal ions onto the sensing area coated with properly selected peptides, which provides an accurate real-time measurement and quantification of the metal ions. Selective detection of Cu2+ and Ni2+ in the ppt-ppb range was achieved by coating the sensing surface with peptides NH2-Gly-Gly-His-COOH and NH2-(His)6-COOH. Cu2+ in drinking water was tested using this sensor.

The rationale for attempting to define salt marsh mosquito-breeding areas in Galveston County by remote sensing the associated vegetation

NASA Technical Reports Server (NTRS)

Arp, G. K.

1975-01-01

The rationale for attempting to define salt marsh mosquito breeding areas in Galveston County was discussed, including a botanical survey of the marsh plant communities, their relationship to flooding, and their exposure to salt water. Particular emphasis is given to Distichlis spicata, a widespread marsh grass. Evidence suggests that breeding areas of Aedes sollicitans are associated with Distichlis and that both species respond to similar ecological conditions in the salt marsh. Aspects of the remote sensing of the Distichlis are considered.

Scintillometer networks for calibration and validation of energy balance and soil moisture remote sensing algorithms

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Kleissl, Jan; Gómez Vélez, Jesús D.; Hong, Sung-ho; Fábrega Duque, José R.; Vega, David; Moreno Ramírez, Hernán A.; Ogden, Fred L.

2007-04-01

Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.

Report of the Workshop on Geologic Applications of Remote Sensing to the Study of Sedimentary Basins

NASA Technical Reports Server (NTRS)

Lang, H. R. (Editor)

1985-01-01

The Workshop on Geologic Applications of Remote Sensing to the Study of Sedimentary Basins, held January 10 to 11, 1985 in Lakewood, Colorado, involved 43 geologists from industry, government, and academia. Disciplines represented ranged from vertebrate paleontology to geophysical modeling of continents. Deliberations focused on geologic problems related to the formation, stratigraphy, structure, and evolution of foreland basins in general, and to the Wind River/Bighorn Basin area of Wyoming in particular. Geological problems in the Wind River/Bighorn basin area that should be studied using state-of-the-art remote sensing methods were identified. These include: (1) establishing the stratigraphic sequence and mapping, correlating, and analyzing lithofacies of basin-filling strata in order to refine the chronology of basin sedimentation, and (2) mapping volcanic units, fracture patterns in basement rocks, and Tertiary-Holocene landforms in searches for surface manifestations of concealed structures in order to refine models of basin tectonics. Conventional geologic, topographic, geophysical, and borehole data should be utilized in these studies. Remote sensing methods developed in the Wind River/Bighorn Basin area should be applied in other basins.

On-Chip Neural Data Compression Based On Compressed Sensing With Sparse Sensing Matrices.

PubMed

Zhao, Wenfeng; Sun, Biao; Wu, Tong; Yang, Zhi

2018-02-01

On-chip neural data compression is an enabling technique for wireless neural interfaces that suffer from insufficient bandwidth and power budgets to transmit the raw data. The data compression algorithm and its implementation should be power and area efficient and functionally reliable over different datasets. Compressed sensing is an emerging technique that has been applied to compress various neurophysiological data. However, the state-of-the-art compressed sensing (CS) encoders leverage random but dense binary measurement matrices, which incur substantial implementation costs on both power and area that could offset the benefits from the reduced wireless data rate. In this paper, we propose two CS encoder designs based on sparse measurement matrices that could lead to efficient hardware implementation. Specifically, two different approaches for the construction of sparse measurement matrices, i.e., the deterministic quasi-cyclic array code (QCAC) matrix and -sparse random binary matrix [-SRBM] are exploited. We demonstrate that the proposed CS encoders lead to comparable recovery performance. And efficient VLSI architecture designs are proposed for QCAC-CS and -SRBM encoders with reduced area and total power consumption.

Growth and reflectance characteristics of winter wheat canopies

NASA Technical Reports Server (NTRS)

Hinzman, L. D.; Bauer, M. E.; Daughtry, C. S. T.

1984-01-01

A valuable input to crop growth and yield models would be estimates of current crop condition. If multispectral reflectance indicates crop condition, then remote sensing may provide an additional tool for crop assessment. The effects of nitrogen fertilization on the spectral reflectance and agronomic characteristics of winter wheat (Triticum aestivum L.) were determined through field experiments. Spectral reflectance was measured during the 1979 and 1980 growing seasons with a spectroradiometer. Agronomic data included total leaf N concentration, leaf chlorophyll concentration, stage of development, leaf area index (LAI), plant moisture, and fresh and dry phytomass. Nitrogen deficiency caused increased visible, reduced near infrared, and increased middle infrared reflectance. These changes were related to lower levels of chlorophyll and reduced leaf area in the N-deficient plots. Green LAI, an important descriptor of wheat canopies, could be reliably estimated with multispectral data. The potential of remote sensing in distinguishing stressed from healthy crops is demonstrated. Evidence suggests multispectral imagery may be useful for monitoring crop condition.

Research on Dynamic Monitoring (1990-2010)of Schistosomiasis Vector- Snail at Xinmin Beach, Gaoyou Lake, Jiangsu Province, China

NASA Astrophysics Data System (ADS)

Liu, Zhaoyan; Li, Chuanrong; Tang, Lingli; Zhou, Xiaonong; Ma, Lingling

2014-11-01

Schistosomiasis is a parasitic disease that menaces human health. In terms of impact, this disease is second only to malaria as the most devastating parasitic disease. Oncomelania hupensis (snail) is the unique intermediate host of schistosoma, so monitoring and controlling of the number of snail is key to reduce the risk of schistosomiasis transmission. Remote sensing technology can real-timely access the large-scale environmental factors related to snail breeding and reproduction, and can also provide the efficient information to determine the location, area, and spread tendency of snail. Based on the T-S (Takagi-Sugeno) fuzzy information theory, a quantitative remote sensing monitoring model of snail has been developed in previous wok. In a case study, this paper will take Xinmin beach, Gaoyou Lake as new research area, carry out 20 years (1990 - 2010) dynamic monitoring, to further validate the effectiveness of the T-S Fuzzy RS snail monitoring model.

Research on Dynamic Monitoring (1990-2010) of Schistosomiasis Vector-Snail at Xinmin Beach, Gaoyou Lake, Jiangsu Province, China

NASA Astrophysics Data System (ADS)

Liu, Zhaoyan; Li, Chuanrong; Tang, Lingli; Zhou, Xiaonong; Ma, Lingling

2014-11-01

Schistosomiasis is a parasitic disease that menaces human health. In terms of impact, this disease is second only to malaria as the most devastating parasitic disease. Oncomelania hupensis (snail) is the unique intermediate host of schistosoma, so monitoring and controlling of the number of snail is key to reduce the risk of schistosomiasis transmission. Remote sensing technology can real-timely access the large-scale environmental factors related to snail breeding and reproduction, and can also provide the efficient information to determine the location, area, and spread tendency of snail. Based on the T-S (Takagi-Sugeno) fuzzy information theory, a quantitative remote sensing monitoring model of snail has been developed in previous wok. In a case study, this paper will take Xinmin beach, Gaoyou Lake as new research area, carry out 20 years (1990 - 2010) dynamic monitoring, to further validate the effectiveness of the T-S Fuzzy RS snail monitoring model.

Sensing and Virtual Worlds - A Survey of Research Opportunities

NASA Technical Reports Server (NTRS)

Moore, Dana

2012-01-01

Virtual Worlds (VWs) have been used effectively in live and constructive military training. An area that remains fertile ground for exploration and a new vision involves integrating various traditional and now non-traditional sensors into virtual worlds. In this paper, we will assert that the benefits of this integration are several. First, we maintain that virtual worlds offer improved sensor deployment planning through improved visualization and stimulation of the model, using geo-specific terrain and structure. Secondly, we assert that VWs enhance the mission rehearsal process, and that using a mix of live avatars, non-player characters, and live sensor feeds (e.g. real time meteorology) can help visualization of the area of operations. Finally, tactical operations are improved via better collaboration and integration of real world sensing capabilities, and in most situations, 30 VWs improve the state of the art over current "dots on a map" 20 geospatial visualization. However, several capability gaps preclude a fuller realization of this vision. In this paper, we identify many of these gaps and suggest research directions

Near infrared spectroscopy for fibre based gas detection

NASA Astrophysics Data System (ADS)

Stewart, George; Johnstone, Walter; Thursby, Graham; Culshaw, Brian

2010-04-01

Gas sensing systems based on fibre optic linked near infra red absorption cells are potentially a flexible and effective tool for monitoring accumulations of hazardous and noxious gases in enclosed areas such as tunnels and mines. Additionally the same baseline technology is readily modified to measure concentrations of hydrocarbon fuels - notably but not exclusively methane, and monitoring emissions of greenhouse gases. Furthermore the system can be readily implemented to provide intrinsically safe monitoring over extensive areas at up to ~250 points from a single interrogation unit. In this paper we review our work on fibre coupled gas sensing systems. We outline the basic principles through which repeatable and accurate self calibrating gas measurements may be realised, including the recover of detailed line shapes for non contact temperature and / or pressure measurements in addition to concentration assessments in harsh environments. We also outline our experience in using these systems in extensive networks operating under inhospitable conditions over extended periods extending to several years.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote sensing could yet be regarded as an optimal plan. Therefore, in the case of more and more available remote sensing information sources, agricultural UAV remote sensing could become an important information resource for guiding field-scale crop management and provide more scientific and accurate information for precision agriculture research.

Remote Sensing Application to Land Use Classification in a Rapidly Changing Agricultural/Urban Area: City of Virginia Beach, Virginia. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Odenyo, V. A. O.

1975-01-01

Remote sensing data on computer-compatible tapes of LANDSAT 1 multispectral scanner imager were analyzed to generate a land use map of the City of Virginia Beach. All four bands were used in both the supervised and unsupervised approaches with the LAYSYS software system. Color IR imagery of a U-2 flight of the same area was also digitized and two sample areas were analyzed via the unsupervised approach. The relationships between the mapped land use and the soils of the area were investigated. A land use land cover map at a scale of 1:24,000 was obtained from the supervised analysis of LANDSAT 1 data. It was concluded that machine analysis of remote sensing data to produce land use maps was feasible; that the LAYSYS software system was usable for this purpose; and that the machine analysis was capable of extracting detailed information from the relatively small scale LANDSAT data in a much shorter time without compromising accuracy.

Appraisement of environment remote sensing method in mining area

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Zhen, Han; Jiang, Tao; Lei, Liqing; Gong, Cailan

1998-08-01

Coal mining is attached great importance by society as a key profession of environmental pollution. The monitor and protection of coal-mine environment is a developing profession in China. The sulfur dioxide, carbon dioxide, carbon monoxide and other waste gases, which are put out by the spontaneous combustion or weathering of gangue are an important pollution resource of atmosphere. The stack of gangue held down many farmlands. Smoke, coal dust and powder coal ash pollute the environment of mining area and surroundings though the affection of monsoon. The pH value of water which coal mine drained off is low, and the drinking, farming and animal husbandry water where it flowed are affected. The surface subsidence which mining caused is a typical destruction of ground environment. The people pay attention to remote sensing as a method of rapidly, cheaply regional environment investigation. The paper tires making an appraisement of mining area environment monitor by many kind methods of remote sensing from the characteristic of mining area environment.

Effect of Forest Canopy on Remote Sensing Soil Moisture at L-band

NASA Technical Reports Server (NTRS)

LeVine, D. M.; Lang, R. H.; Jackson, T. J.; Haken, M.

2005-01-01

Global maps of soil moisture are needed to improve understanding and prediction of the global water and energy cycles. Accuracy requirements imply the use of lower frequencies (L-band) to achieve adequate penetration into the soil and to minimize attenuation by the vegetation canopy and effects of surface roughness. Success has been demonstrated over agricultural areas, but canopies with high biomass (e.g. forests) still present a challenge. Examples from recent measurements over forests with the L-band radiometer, 2D-STAR, and its predecessor, ESTAR, will be presented to illustrate the problem. ESTAR and 2D-STAR are aircraft-based synthetic aperture radiometers developed to help resolve both the engineering and algorithm issues associated with future remote sensing of soil moisture. ESTAR, which does imaging across track, was developed to demonstrate the viability of aperture synthesis for remote sensing. The instrument has participated several soil moisture experiments (e.g. at the Little Washita Watershed in 1992 and the Southern Great Plains experiments in 1997 and 1999). In addition, measurements have been made at a forest site near Waverly, VA which contains conifer forests with a variety of biomass. These data have demonstrated the success of retrieving soil moisture at L-band over agricultural areas and the response of passive observations at L-band to biomass over forests. 2D-STAR is a second generation instrument that does aperture synthesis in two dimensions (along track and cross track) and is dual polarized. This instrument has the potential to provide measurements at L-band that simulate the measurements that will be made by the two L-band sensors currently being developed for future remote sensing of soil moisture from space: Hydros (conical scan and real aperture) and SMOS (multiple incidence angle and synthetic aperture). 2D-STAR participated in the SMEX-03 soil moisture experiment, providing images from the NASA P-3 aircraft. Preliminary results include images of the experiment site area near Huntsville, AL that included a mixture of forest and agriculture. Changes during a rain event further illustrate the issues presented by forests. Work is continuing to reduce the 2D-STAR data and to support the two future remote sensing missions. Among the goals is to process the 2D-STAR data to create multiple looks (at the same pixel) with different incidence angles. Data in this format can be used to test algorithms for retrieving soil moisture and biomass such as are planned for SMOS. Also, the data are being processed to provide images at constant incidence angles such as will be obtained by Hydros. Although Hydros will have only one incidence angle, it will also carry an L-band radar, The goal is to use the radar to improve spatial resolution, an issue for remote sensing from space at the long wavelengths. Simultaneous observations with active and passive sensors also offers interesting prospects for treating areas of high biomass (forests) and irregular terrain and may be the challenge for the future.

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.

Distributed measurement of acoustic vibration location with frequency multiplexed phase-OTDR

NASA Astrophysics Data System (ADS)

Iida, Daisuke; Toge, Kunihiro; Manabe, Tetsuya

2017-07-01

All-fiber distributed vibration sensing is attracting attention in relation to structural health monitoring because it is cost effective, offers high coverage of the monitored area and can detect various structural problems. And in particular the demand for high-speed vibration sensing operating at more than 10 kHz has increased because high frequency vibration indicates high energy and severe trouble in the monitored object. Optical fiber vibration sensing with phase-sensitive optical time domain reflectometry (phase-OTDR) has long been studied because it can be used for distributed vibration sensing in optical fiber. However, pulse reflectometry such as OTDR cannot measure high-frequency vibration whose cycle is shorter than the repetition time of the OTDR. That is, the maximum detectable frequency depends on fiber length. In this paper, we describe a vibration sensing technique with frequency-multiplexed OTDR that can detect the entire distribution of a high-frequency vibration thus allowing us to locate a high-speed vibration point. We can measure the position, frequency and dynamic change of a high-frequency vibration whose cycle is shorter than the repetition time. Both frequency and position are visualized simultaneously for a 5-km fiber with an 80-kHz frequency response and a 20-m spatial resolution.

Technology development: A partnership that makes sense

NASA Technical Reports Server (NTRS)

Rone, Kyle Y.; Macdonald, Robert B.; Houston, A. Glen

1991-01-01

Discussed here is an approach to how academic institutions, government entities, and industrial organizations can work effectively to utilize their relative strengths to more effectively meet common goals. The discussion relates to the University of Houston-Clear Lake (UHCL) Research Institute for Computing and Information Systems (RICIS) Program to bring about this type of triad in the Clear Lake area. It is concluded that the interfaces among these groups must remain independent to maintain a healthy counterbalance to their respective entities. However, each entity can and must understand the entire mechanism to exploit each interface to the fullest. Only through such cooperation can the continued technical success of the NASA/Clear Lake area be assured.

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

Ganges-Brahmaputra-Meghna Delta Connectivity Analysis Using New Tools for the Automatic Extraction of Channel Networks from Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Jarriel, T. M.; Isikdogan, F.; Passalacqua, P.; Bovik, A.

2017-12-01

River deltas are one of the environmental ecosystems most threatened by climate change and anthropogenic activity. While their low elevation gradients and fertile soil have made them optimal for human inhabitation and diverse ecologic growth, it also makes them susceptible to adverse effects of sea level rise, flooding, subsidence, and manmade structures such as dams, levees, and dikes. One particularly large and threatened delta that is the focus area of this study, is the Ganges-Brahmaputra-Meghna Delta (GBMD) on the southern coast of Bangladesh/West Bengal India. In this study we analyze the GBMD channel network, identify areas of maximum change of the network, and use this information to predict how the network will respond under future scenarios. Landsat images of the delta from 1973 to 2017 are analyzed using new tools for the automatic extraction of channel networks from remotely sensed imagery [Isikdogan et al., 2017a, Isikdogan et al., 2017b]. The tools return channel width and channel centerline location at the resolution of the input imagery (30 m). Channel location variance over time is computed using the combined data from 1973 to 2017 and, based on this information, zones of highest change in the system are identified (Figure 1). Network metrics measuring characteristics of the delta's channels and islands are calculated for each year of the study and compared to the variance results in order to identify what metrics capture this change. These results provide both a method to identify zones of the GBMD that are currently experiencing the most change, as well as a means to predict what areas of the delta will experience network changes in the future. This information will be useful for informing coastal sustainability decisions about what areas of such a large and complex network should be the focus of remediation and mitigation efforts. Isikdogan, F., A. Bovik, P. Passalacqua (2017a), RivaMap: An Automated River Analysis and Mapping Engine, Remote Sensing of Environment, in press. Isikdogan, F., A. Bovik, P. Passalacqua (2017b), River Network Extraction by Deep Convolutional Neural Networks, IEEE Geoscience and Remote Sensing Letters, under review.

Spatio-temporal modeling with GIS and remote sensing for schistosomiasis control in Sichuan, China

NASA Astrophysics Data System (ADS)

Xu, Bing

Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.

Metal-Organic Frameworks-Derived Hierarchical Co3O4 Structures as Efficient Sensing Materials for Acetone Detection.

PubMed

Zhang, Rui; Zhou, Tingting; Wang, Lili; Zhang, Tong

2018-03-21

Highly sensitive and stable gas sensors have attracted much attention because they are the key to innovations in the fields of environment, health, energy savings and security, etc. Sensing materials, which influence the practical sensing performance, are the crucial parts for gas sensors. Metal-organic frameworks (MOFs) are considered as alluring sensing materials for gas sensors because of the possession of high specific surface area, unique morphology, abundant metal sites, and functional linkers. Herein, four kinds of porous hierarchical Co 3 O 4 structures have been selectively controlled by optimizing the thermal decomposition (temperature, rate, and atmosphere) using ZIF-67 as precursor that was obtained from coprecipitation method with the co-assistance of cobalt salt and 2-methylimidazole in the solution of methanol. These hierarchical Co 3 O 4 structures, with controllable cross-linked channels, meso-/micropores, and adjustable surface area, are efficient catalytic materials for gas sensing. Benefits from structural advantages, core-shell, and porous core-shell Co 3 O 4 exhibit enhanced sensing performance compared to those of porous popcorn and nanoparticle Co 3 O 4 to acetone gas. These novel MOF-templated Co 3 O 4 hierarchical structures are so fantastic that they can be expected to be efficient sensing materials for development of low-temperature operating gas sensors.

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

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), 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. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed 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 will be 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.

Preliminary determination of geothermal working area based on Thermal Infrared and Synthetic Aperture Radar (SAR) remote sensing

NASA Astrophysics Data System (ADS)

Agoes Nugroho, Indra; Kurniawahidayati, Beta; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Remote sensing is one of the methods for geothermal exploration. This method can be used to map the geological structures, manifestations, and predict the geothermal potential area. The results from remote sensing were used as guidance for the next step exploration. Analysis of target in remote sensing is an efficient method to delineate geothermal surface manifestation without direct contact to the object. The study took a place in District Merangin, Jambi Province, Indonesia. The area was selected due to existing of Merangin volcanic complex composed by Mounts Sumbing and Hulunilo with surface geothermal manifestations presented by hot springs and hot pools. The location of surface manifestations could be related with local and regional structures of Great Sumatra Fault. The methods used in this study were included identification of volcanic products, lineament extraction, and lineament density quantification. The objective of this study is to delineate the potential zones for sitting the geothermal working site based on Thermal Infrared and Synthetic Aperture Radar (SAR) sensors. The lineament-related to geological structures, was aimed for high lineament density, is using ALOS - PALSAR (Advanced Land Observing Satellite - The Phased Array type L-band Synthetic Aperture Radar) level 1.1. The Normalized Difference Vegetation Index (NDVI) analysis was used to predict the vegetation condition using Landsat 8 OLI-TIRS (The Operational Land Imager - Thermal Infrared Sensor). The brightness temperature was extracted from TIR band to estimate the surface temperature. Geothermal working area identified based on index overlay method from extracted parameter of remote sensing data was located at the western part of study area (Graho Nyabu area). This location was identified because of the existence of high surface temperature about 30°C, high lineament density about 4 - 4.5 km/km2 and low NDVI values less than 0.3.

A remote sensing method for estimating regional reservoir area and evaporative loss

DOE PAGES

Zhang, Hua; Gorelick, Steven M.; Zimba, Paul V.; ...

2017-10-07

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. In this paper, we propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporationmore » volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. Finally, this study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.« less

A remote sensing method for estimating regional reservoir area and evaporative loss

NASA Astrophysics Data System (ADS)

Zhang, Hua; Gorelick, Steven M.; Zimba, Paul V.; Zhang, Xiaodong

2017-12-01

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. We propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporation volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. This study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.

A remote sensing method for estimating regional reservoir area and evaporative loss

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

Zhang, Hua; Gorelick, Steven M.; Zimba, Paul V.

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. In this paper, we propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporationmore » volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. Finally, this study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.« less

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

NASA Astrophysics Data System (ADS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

2010-05-01

Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection was suggested. On the basis of analyzing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from remote sensing data was discussed. Spectral signatures of different terrain features have been used to extract structural patterns aiming to separate surface units and to classify the general categories. The synergetic analysis and interpretation of the different satellite images (LANDSAT: TM, ETM; MODIS, IKONOS) acquired over a period of more than 20 years reveals significant aspects regarding impacts of climate and anthropogenic changes on urban/periurban environment. It was delimited residential zones of industrial zones which are very often a source of pollution. An important role has urban green cover assessment. Have been emphasized the particularities of the functional zones from different points of view: architectural, streets and urban surface traffic, some components of urban infrastructure as well as habitat quality. The growth of Bucharest urban area in Romania has been a result of a rapid process of industrialization, and also of the increase of urban population. Information on the spatial pattern and temporal dynamics of land cover and land use of urban areas is critical to address a wide range of practical problems relating to urban regeneration, urban sustainability and rational planning policy.

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.

Integration of geological remote-sensing techniques in subsurface analysis

USGS Publications Warehouse

Taranik, James V.; Trautwein, Charles M.

1976-01-01

Geological remote sensing is defined as the study of the Earth utilizing electromagnetic radiation which is either reflected or emitted from its surface in wavelengths ranging from 0.3 micrometre to 3 metres. The natural surface of the Earth is composed of a diversified combination of surface cover types, and geologists must understand the characteristics of surface cover types to successfully evaluate remotely-sensed data. In some areas landscape surface cover changes throughout the year, and analysis of imagery acquired at different times of year can yield additional geological information. Integration of different scales of analysis allows landscape features to be effectively interpreted. Interpretation of the static elements displayed on imagery is referred to as an image interpretation. Image interpretation is dependent upon: (1) the geologist's understanding of the fundamental aspects of image formation, and (2.) his ability to detect, delineate, and classify image radiometric data; recognize radiometric patterns; and identify landscape surface characteristics as expressed on imagery. A geologic interpretation integrates surface characteristics of the landscape with subsurface geologic relationships. Development of a geologic interpretation from imagery is dependent upon: (1) the geologist's ability to interpret geomorphic processes from their static surface expression as landscape characteristics on imagery, (2) his ability to conceptualize the dynamic processes responsible for the evolution 6f interpreted geologic relationships (his ability to develop geologic models). The integration of geologic remote-sensing techniques in subsurface analysis is illustrated by development of an exploration model for ground water in the Tucson area of Arizona, and by the development of an exploration model for mineralization in southwest Idaho.

A Remote Sensing Approach for Urban Environmental Decision-Making: An Atlanta, Georgia Case Study

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Rickman, Douglas L.; Laymon, Charles A.; Estes, Maurice G., Jr.; Howell, Burgess F.; Arnold, James E. (Technical Monitor)

2002-01-01

Unquestionably, urbanization causes tremendous changes in land cover and land use, as well as impacting a host of environmental characteristics. For example, unlike natural surfaces, urban surfaces have very different thermal energy properties whereby they store solar energy throughout the day and continue to release it as heat well after sunset. This effect, known as the 'Urban Heat Island', serves as a catalyst for chemical reactions from vehicular exhaust and industrial activities leading to the deterioration in air quality, especially exacerbating the production of ground level ozone. 'Cool Community' strategies that utilize remote sensing data, are now being implemented as a way to reduce the impacts of the urban heat island and its subsequent environmental impacts. This presentation focuses on how remote sensing data have been used to provide descriptive and quantitative data for characterizing the Atlanta, Georgia metropolitan area - particularly for measuring surface energy fluxes, such as the thermal or "heat" energy that emanates from different land cover types across the Atlanta urban landscape. In turn, this information is useful for developing a better understanding of how the thermal characteristics of the city surface affect the urban heat island phenomena and, ultimately, air quality and other environmental parameters over the Atlanta metropolitan region. Additionally, this paper also provides insight on how remote sensing, with its synoptic approach, can be used to provide urban planners, local, state, and federal government officials, and other decision-makers, as well as the general public, with information to better manage urban areas as sustainable environments.

Yellow River Icicle Hazard Dynamic Monitoring Using UAV Aerial Remote Sensing Technology

NASA Astrophysics Data System (ADS)

Wang, H. B.; Wang, G. H.; Tang, X. M.; Li, C. H.

2014-02-01

Monitoring the response of Yellow River icicle hazard change requires accurate and repeatable topographic surveys. A new method based on unmanned aerial vehicle (UAV) aerial remote sensing technology is proposed for real-time data processing in Yellow River icicle hazard dynamic monitoring. The monitoring area is located in the Yellow River ice intensive care area in southern BaoTou of Inner Mongolia autonomous region. Monitoring time is from the 20th February to 30th March in 2013. Using the proposed video data processing method, automatic extraction covering area of 7.8 km2 of video key frame image 1832 frames took 34.786 seconds. The stitching and correcting time was 122.34 seconds and the accuracy was better than 0.5 m. Through the comparison of precise processing of sequence video stitching image, the method determines the change of the Yellow River ice and locates accurate positioning of ice bar, improving the traditional visual method by more than 100 times. The results provide accurate aid decision information for the Yellow River ice prevention headquarters. Finally, the effect of dam break is repeatedly monitored and ice break five meter accuracy is calculated through accurate monitoring and evaluation analysis.

Analyzing the Effects of Climate Change on Sea Surface Temperature in Monitoring Coral Reef Health in the Florida Keys Using Sea Surface Temperature Data

NASA Technical Reports Server (NTRS)

Jones, Jason; Burbank, Renane; Billiot, Amanda; Schultz, Logan

2011-01-01

This presentation discusses use of 4 kilometer satellite-based sea surface temperature (SST) data to monitor and assess coral reef areas of the Florida Keys. There are growing concerns about the impacts of climate change on coral reef systems throughout the world. Satellite remote sensing technology is being used for monitoring coral reef areas with the goal of understanding the climatic and oceanic changes that can lead to coral bleaching events. Elevated SST is a well-documented cause of coral bleaching events. Some coral monitoring studies have used 50 km data from the Advanced Very High Resolution Radiometer (AVHRR) to study the relationships of sea surface temperature anomalies to bleaching events. In partnership with NOAA's Office of National Marine Sanctuaries and the University of South Florida's Institute for Marine Remote Sensing, this project utilized higher resolution SST data from the Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR. SST data for 2000-2010 was employed to compute sea surface temperature anomalies within the study area. The 4 km SST anomaly products enabled visualization of SST levels for known coral bleaching events from 2000-2010.

Intelligent image processing for vegetation classification using multispectral LANDSAT data

NASA Astrophysics Data System (ADS)

Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.

2015-09-01

We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.

Improving GLOBALlAND30 Artificial Type Extraction Accuracy in Low-Density Residents

NASA Astrophysics Data System (ADS)

Hou, Lili; Zhu, Ling; Peng, Shu; Xie, Zhenlei; Chen, Xu

2016-06-01

GlobalLand 30 is the first 30m resolution land cover product in the world. It covers the area within 80°N and 80°S. There are ten classes including artificial cover, water bodies, woodland, lawn, bare land, cultivated land, wetland, sea area, shrub and snow,. The TM imagery from Landsat is the main data source of GlobalLand 30. In the artificial surface type, one of the omission error happened on low-density residents' part. In TM images, hash distribution is one of the typical characteristics of the low-density residents, and another one is there are a lot of cultivated lands surrounded the low-density residents. Thus made the low-density residents part being blurred with cultivated land. In order to solve this problem, nighttime light remote sensing image is used as a referenced data, and on the basis of NDBI, we add TM6 to calculate the amount of surface thermal radiation index TR-NDBI (Thermal Radiation Normalized Difference Building Index) to achieve the purpose of extracting low-density residents. The result shows that using TR-NDBI and the nighttime light remote sensing image are a feasible and effective method for extracting low-density residents' areas.

Use of Space Technology in Flood Mitigation (Western Province, Zambia)

NASA Astrophysics Data System (ADS)

Mulando, A.

2001-05-01

Disasters, by definition are events that appear suddenly and with little warning. They are usually short lived, with extreme events bringing death, injury and destruction of buildings and communications. Their aftermath can be as damaging as their physical effects through destruction of sanitation and water supplies, destruction of housing and breakdown of transport for food, temporary shelter and emergency services. Since floods are one of the natural disasters which endanger both life and property, it becomes vital to know its extents and where the hazards exists. Flood disasters manifest natural processes on a larger scale and information provided by Remote Sensing is a most appropriate input to analysis of actual events and investigations of potential risks. An analytical and qualitative image processing and interpretation of Remotely Sensed data as well as other data such as rainfall, population, settlements not to mention but a few should be used to derive good mitigation strategies. Since mitigation is the cornerstone of emergency management, it therefore becomes a sustained action that will reduce or eliminate long term risks to people and property from natural hazards such as floods and their effects. This will definitely involve keeping of homes and other sensitive structures away from flood plains. Promotion of sound land use planning based on this known hazard, "FLOODS" is one such form of mitigation that can be applied in flood affected areas within flood plain. Therefore future mitigation technologies and procedures should increasingly be based on the use of flood extent information provided by Remote Sensing Satellites like the NOAA AVHRR as well as information on the designated flood hazard and risk areas.

The effect of Co-doping on the humidity sensing properties of ordered mesoporous TiO2

NASA Astrophysics Data System (ADS)

Li, Zhong; Haidry, Azhar Ali; Gao, Bin; Wang, Tao; Yao, ZhengJun

2017-08-01

Monitoring of humidity is of utmost importance as it is essential part of almost every process in our life. Many commercial humidity sensors based on metal oxide semiconductors are available in the market, but there is still need to synthesize low-cost, fast and highly sensitive humidity sensors with no interference from background environment. The aim of this work was to fabricate the ordered mesoporous un-doped and Co-doped TiO2 (0.1-5 mol% Co) and to analyze its humidity sensing properties at room temperatures. The ordered mesoporous powders with high specific surface area (SSA) were prepared by multicomponent self-assembly procedure and then spray-coated onto the sensor substrates with interdigitated gold electrodes. The sensors exhibited excellent stability and reproducible resistance change under various relative humidity percentages (9-90% RH) with negligible effect of background environment. For instance, the response to 90% RH at room temperature was about five orders of magnitude (∼1.39 × 105) and the response time (Tres) was ∼24 s. The reaction/recovery times of the sensors were compared with commercial humidity sensor to show that the reaction times in this work are not given by the surface reaction of water vapor on the sensor surfaces, rather these are mainly influenced by the experimental setup. The sensor response increased up to 3 mol% Co-contents and then decreased for 5 mol% Co-contents. Based on the experimental results, the surface reaction of humidity is discussed related to specific surface area, average grain size and cobalt contents to understand the humidity sensing mechanism.

Enhancing Remotely Sensed TIR Data for Public Health Applications: Is West Nile Virus Heat-Related?

NASA Astrophysics Data System (ADS)

Weng, Q.; Liu, H.; Jiang, Y.

2014-12-01

Public health studies often require thermal infrared (TIR) images at both high temporal and spatial resolution to retrieve LST. However, currently, no single satellite sensors can deliver TIR data at both high temporal and spatial resolution. This technological limitation prevents the wide usage of remote sensing data in epidemiological studies. To solve this issue, we have developed a few image fusion techniques to generate high temporally-resolved image data. We downscaled GOES LST data to 15-minute 1-km resolution to assess community-based heat-related risk in Los Angeles County, California and simulated ASTER datasets by fusing ASTER and MODIS data to derive biophysical variables, including LST, NDVI, and normalized difference water index, to examine the effects of those environmental characteristics on WNV outbreak and dissemination. A spatio-temporal analysis of WNV outbreak and dissemination was conducted by synthesizing the remote sensing variables and mosquito surveillance data, and by focusing on WNV risk areas in July through September due to data sufficiency of mosquito pools. Moderate- and high-risk areas of WNV infections in mosquitoes were identified for five epidemiological weeks. These identified WNV-risk areas were then collocated in GIS with heat hazard, exposure, and vulnerability maps to answer the question of whether WNV is a heat related virus. The results show that elevation and built-up conditions were negatively associated with the WNV propagation, while LST positively correlated with the viral transmission. NDVI was not significantly associated with WNV transmission. San Fernando Valley was found to be the most vulnerable to mosquito infections of WNV. This research provides important insights into how high temporal resolution remote sensing imagery may be used to study time-dependant events in public health, especially in the operational surveillance and control of vector-borne, water-borne, or other epidemic diseases.

America's Urban Forests: Keeping Our Cities Cool

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Quattrochi, Dale A.

1997-01-01

The additional heating of the air over the city is the result of the replacement of naturally vegetated surfaces with those composed of asphalt, concrete, rooftops and other man-made materials. The temperatures of these artificial surfaces can be 20 to 40 C higher than vegetated surfaces. Materials such as asphalt store much of the sun's energy and remains hot long after sunset. This produces a dome of elevated air temperatures 5 to 8 C greater over the city, compared to the air temperatures over adjacent rural areas. This effect is called the "urban heat island". Tree canopies can reduce the urban heat island effect by dissipating the solar energy received by transpiring water from leaf surfaces which cools the air by taking "heat" from the air to evaporate the water and by shading surfaces like asphalt, roofs, and concrete parking lots which prevents initial heating and storage of heat. It is difficult to take enough temperature measurements over a large city area to characterize the surface temperature variability and quantify the temperature reduction effects of tree canopies. However, the use of remotely sensed thermal data from airborne scanners are ideal for the task. In a study funded by NASA, a series of flights over Huntsville AL were performed in September 1994 and over Atlanta in May 1997. In this article we will examine the techniques of analyzing remotely sensed data for measuring the effect of tree canopies in reducing the urban heat island effect.

Making Sense of Math: How to Help Every Student become a Mathematical Thinker and Problem Solver (ASCD Arias)

ERIC Educational Resources Information Center

Seeley, Cathy L.

2016-01-01

In "Making Sense of Math," Cathy L. Seeley, former president of the National Council of Teachers of Mathematics, shares her insight into how to turn your students into flexible mathematical thinkers and problem solvers. This practical volume concentrates on the following areas: (1) Making sense of math by fostering habits of mind that…

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...

Assessing Number Sense Performance of Indonesian Elementary School Students

ERIC Educational Resources Information Center

Purnomo, Yoppy Wahyu; Kowiyah; Alyani, Fitri; Assiti, Saliza S.

2014-01-01

The intention of the present study is to know how students' performance on number sense based on the components of number sense and also the sub-components in it. The participants of the study are 80 six graders (12-13 year-old) from three different schools that represent the city, rural, and small town areas. The data were collected using the…

Sense of place along a scenic byway in Maine

Treesearch

Marilynne Mann; Jessica Leahy

2008-01-01

Sense of place defines the value and meaning of location. The Rangeley Lakes area of Maine, an unusual natural environment with cultural and historic significance, was nationally recognized in 2000 by the designation of the Rangeley Lakes National Scenic Byway. A survey during the summer of 2006 sought to identify sense of place in the midst of tourism-related growth...

Urban Growth in a Fragmented Landscape: Estimating the Relationship between Landscape Pattern and Urban Land Use Change in Germany, 2000-2006

NASA Astrophysics Data System (ADS)

Keller, R.

2013-12-01

One of the highest priorities in the conservation and management of biodiversity, natural resources and other vital ecosystem services is the assessment of the mechanisms that drive urban land use change. Using key landscape indicators, this study addresses why urban land increased 6 percent overall in Germany from 2000-2006. Building on regional science and economic geography research, I develop a model of landscape change that integrates remotely sensed and other geospatial data, and socioeconomic data in a spatial autoregressive model to explain the variance in urban land use change observed in German kreise (counties) over the past decade. The results reveal three key landscape mechanisms that drive urban land use change across Germany, aligning with those observed in US studies: (1) the level of fragmentation, (2) the share of designated protected areas, and (3) the share of prime soil. First, as fragmentation of once continuous habitats in the landscape increases, extensive urban growth follows. Second, designated protected areas have the perverse effect of hastening urbanization in surrounding areas. Third, greater shares of prime, productive soil experienced less urban land take over the 6 year period, an effect that is stronger in the former East Germany, where the agricultural sector remains large. The results suggest that policy makers concentrate their conservation efforts on preexisting fragmented land with high shares of protected areas in Germany to effectively stem urban land take. Given that comparative studies of land use change are vital for the scientific community to grasp the wider global process of urbanization and coincident ecological impacts, the methodology employed here is easily exportable to land cover and land use research programs in other fields and geographic areas. Key words: Urban land use change, Ecosystem services, Landscape fragmentation, Remote sensing, Spatial regression models, GermanyOLS and Spatial Autoregressive Model Results N = 439; Standard error in ( ) . *p < .1, **p < .01, ***p < .001

Applications of remote sensing to watershed management

NASA Technical Reports Server (NTRS)

Rango, A.

1975-01-01

Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.

Apparatus and method for detecting flaws in conductive material

DOEpatents

Hockey, Ronald L.; Riechers, Douglas M.

1999-01-01

The present invention is an improved sensing unit for detecting flaws in conductive material wherein the sensing coil is positioned away from a datum of either the datum point, the datum orientation, or a combination thereof. Position of the sensing coil away from a datum increases sensitivity for detecting flaws having a characteristic volume less than about 1 mm.sup.3, and further permits detection of subsurface flaws. Use of multiple sensing coils permits quantification of flaw area or volume.

Remote Sensing For Water Resources And Hydrology. Recommended research emphasis for the 1980's

NASA Technical Reports Server (NTRS)

1980-01-01

The problems and the areas of activity that the Panel believes should be emphasized in work on remote sensing for water resources and hydrology in the 1980's are set forth. The Panel deals only with those activities and problems in water resources and hydrology that the Panel considers important, and where, in the Panel's opinion, application of current remote sensing capability or advancements in remote sensing capability can help meet urgent problems and provide large returns in practical benefits.

Graphene Hybrid Materials in Gas Sensing Applications †

PubMed Central

Latif, Usman; Dickert, Franz L.

2015-01-01

Graphene, a two dimensional structure of carbon atoms, has been widely used as a material for gas sensing applications because of its large surface area, excellent conductivity, and ease of functionalization. This article reviews the most recent advances in graphene hybrid materials developed for gas sensing applications. In this review, synthetic approaches to fabricate graphene sensors, the nano structures of hybrid materials, and their sensing mechanism are presented. Future perspectives of this rapidly growing field are also discussed. PMID:26690156

Research on Method of Interactive Segmentation Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yang, Y.; Li, H.; Han, Y.; Yu, F.

2017-09-01

In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.

Potential reciprocal effect between land use / land cover change and climate change

NASA Astrophysics Data System (ADS)

Daham, Afrah; Han, Dawei; Rico-Ramirez, Miguel

2016-04-01

Land use/land cover (LULC) activity influences climate change and one way to explore climate change is to analyse the change in LULC patterns. Modelling the Spatio-temporal pattern of LULC change requires the use of satellite remote sensing data and aerial photographs with different pre-processing steps. The aim of this research is to analyse the reciprocal effects of LUCC (Land Use and Cover Change) and the climate change on each other in the study area which covers part of Bristol, South Gloucestershire, Bath and Somerset in England for the period (1975-2015). LUCC is assessed using remote sensing data. Three sets of remotely sensed data, LanSAT-1 Multispectral Scanner (MSS) data obtained in (1975 and 1976), LanSAT-5 Thematic Mapper (TM) data obtained in (1984 and 1997), and LandSAT-7 Enhanced Thematic Mapper Plus (ETM+) acquired in (2003 and 2015), with a time span of forty years were used in the study. One of the most common problems in the satellite images is the presence of cloud covers. In this study, the cloud cover problem is handled using a novel algorithm, which is capable of reducing the cloud coverage in the classified images significantly. This study also examines a suite of possible photogrammetry techniques applicable to detect the change in LULC. At the moment photogrammertic techniques are used to derive the ground truth for supervised classification from the high resolution aerial photos which were provided by Ordnance Survey (contract number: 240215) and global mapper for the years in (2001 and 2014). After obtaining the classified images almost free of clouds, accuracy assessment is implemented with the derived classified images using confusion matrix at some ground truth points. Eight classes (Improved grassland, Built up areas and gardens, Arable and horticulture, Broad-leaved / mixed woodland, Coniferous woodland, Oceanic seas, Standing open water and reservoir, and Mountain; heath; bog) have been classified in the chosen study area. Also, CORINE Land Cover (CLC) maps are used to study the environmental changes and to validate the obtained maps from remote sensing and photogrammetry data. On climate change, different sources of climate data were used in this research. Three rainfall datasets from the Global Precipitation Climatology Centre (GPCC), the Climate Research Unit (CRU) and Gridded Estimates of daily Areal Rainfall (CEH-GEAR) in the study area were compared at a resolution of 0.5 degrees. The dataset were available for the operational period 1975-2015. The historically observed rainfall datasets for the study area were obtained from the Met Office Integrated Data Archive System (MIDAS) Land and Marine downloaded through the British Atmospheric Data Centre (BADC) website, which includes the rainfall and the temperature, are collected from all the weather stations in the UK in the last 40 years. Only four gauging stations were available to represent the spatial variability of rainfall within and around the study area. The monthly rainfall time series were evaluated against a dataset based on four rain gauges. These data are processed and analysed statistically to find the changes in climate of the study area in the last 40 years. The potential reciprocal effect between the LULC change and the climate change is done by finding the correlation between LUCC and the variables Rainfall and Temperature. In addition, The Soil and Water Assessment Tool (SWAT) model is used to study the impact of LULC change on the water system and climate.

Estimating irrigated areas from satellite and model soil moisture data over the contiguous US

NASA Astrophysics Data System (ADS)

Zaussinger, Felix; Dorigo, Wouter; Gruber, Alexander

2017-04-01

Information about irrigation is crucial for a number of applications such as drought- and yield management and contributes to a better understanding of the water-cycle, land-atmosphere interactions as well as climate projections. Currently, irrigation is mainly quantified by national agricultural statistics, which do not include spatial information. The digital Global Map of Irrigated Areas (GMIA) has been the first effort to quantify irrigation at the global scale by merging these statistics with remote sensing data. Also, the MODIS-Irrigated Agriculture Dataset (MirAD-US) was created by merging annual peak MODIS-NDVI with US county level irrigation statistics. In this study we aim to map irrigated areas by confronting time series of various satellite soil moisture products with soil moisture from the ERA-Interim/Land reanalysis product. We follow the assumption that irrigation signals are not modelled in the reanalysis product, nor contributing to its forcing data, but affecting the spatially continuous remote sensing observations. Based on this assumption, spatial patterns of irrigation are derived from differences between the temporal slopes of the modelled and remotely sensed time series during the irrigation season. Results show that a combination of ASCAT and ERA-Interim/Land show spatial patterns which are in good agreement with the MIrAD-US, particularly within the Mississippi Delta, Texas and eastern Nebraska. In contrast, AMSRE shows weak agreements, plausibly due to a higher vegetation dependency of the soil moisture signal. There is no significant agreement to the MIrAD-US in California, which is possibly related to higher crop-diversity and lower field sizes. Also, a strong signal in the region of the Great Corn Belt is observed, which is generally not outlined as an irrigated area. It is not yet clear to what extent the signal obtained in the Mississippi Delta is related to re-reflection effects caused by standing water due to flood or furrow irrigation practices. Consequently, future research should focus on the specific effects of different irrigation practices and crop types. This study is supported by the European Union's FP7 EartH2Observe "Global Earth Observation for Integrated Water Resource Assessment" project (grant agreement number 331 603608).

Fe 2O 3-Au hybrid nanoparticles for sensing applications via sers analysis

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

Murph, Simona Hunyadi; Searles, Emily

2017-06-25

Nanoparticles with large amounts of surface area and unique characteristics that are distinct from their bulk material provide an interesting application in the enhancement of inelastic scattering signal. Surface Enhanced Raman Spectroscopy (SERS) strives to increase the Raman scattering effect when chemical species of interest are in the close proximity of metallic nnaostructures. Gold nanoparticles of various shapes have been used for sensing applications via SERS as they demonstrate the greatest effect of plasmonic behavior in the visible-near IR region of the spectrum. When coupled with other nanoparticles, namely iron oxide nanoparticles, hybrid structures with increased functionality were produced. Multifunctionalmore » iron oxide-gold hybrid nanostructures have been created via solution chemistries and investigated for analyte detection of a model analyte. By exploiting their magnetic properties, nanogaps or “hot spots” were rationally created and evaluated for SERS enhancement studies.« less

Applications of thermal remote sensing to detailed ground water studies

NASA Technical Reports Server (NTRS)

Souto-Maior, J.

1973-01-01

Three possible applications of thermal (8-14 microns) remote sensing to detailed hydrogeologic studies are discussed in this paper: (1) the direct detection of seeps and springs, (2) the indirect evaluation of shallow ground water flow through its thermal effects on the land surface, and (3) the indirect location of small volumes of ground water inflow into surface water bodies. An investigation carried out with this purpose in an area containing a complex shallow ground water flow system indicates that the interpretation of the thermal imageries is complicated by many factors, among which the most important are: (1) altitude, angle of view, and thermal-spatial resolution of the sensor; (2) vegetation type, density, and vigor; (3) topography; (4) climatological and micrometeorological effects; (5) variation in soil type and soil moisture; (6) variation in volume and temperature of ground water inflow; (7) the hydraulic characteristics of the receiving water body, and (8) the presence of decaying organic material.

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.

Integrating modelling and remote sensing to identify ecosystem performance anomalies in the boreal forest, Yukon River Basin, Alaska

USGS Publications Warehouse

Wylie, B.K.; Zhang, L.; Bliss, Norman B.; Ji, Lei; Tieszen, Larry L.; Jolly, W. M.

2008-01-01

High-latitude ecosystems are exposed to more pronounced warming effects than other parts of the globe. We develop a technique to monitor ecological changes in a way that distinguishes climate influences from disturbances. In this study, we account for climatic influences on Alaskan boreal forest performance with a data-driven model. We defined ecosystem performance anomalies (EPA) using the residuals of the model and made annual maps of EPA. Most areas (88%) did not have anomalous ecosystem performance for at least 6 of 8 years between 1996 and 2004. Areas with underperforming EPA (10%) often indicate areas associated with recent fires and areas of possible insect infestation or drying soil related to permafrost degradation. Overperforming areas (2%) occurred in older fire recovery areas where increased deciduous vegetation components are expected. The EPA measure was validated with composite burn index data and Landsat vegetation indices near and within burned areas.

Using data of remote sensing to retrieve surface's evapotranspiration in northwest of China

NASA Astrophysics Data System (ADS)

Yu, Xinwen; Zheng, Youfei; Guo, Jianmao; He, Jinhai

2005-08-01

Northwestern China is a semi-arid or arid area in China. Ningnan (or South Ningxia) district is located south of Ningxia Province belong to Northwestern part of China. Climate in this region is more dry and lack of precipitation. Because global climate have been changing, temperature has been increasing and rainfall has been decreasing in South Ningxia. The ecology has been deteriorating, such as vegetation cover destroying, water losing and soil erosion. Therefore, the people who live in South Ningxia have been poor. Recently, Chinese government put into effect on strategy of "great development of Chinese northwest", aiming to improve environmental and ecological conditions and rise people's living standard. South Ningxia district was defined as area of emigration where the measurements of returning land for farming to forestry were taken into account . How to evaluate the plans and measurements is very important to continue to improving local environmental and ecological conditions further. The basic index of evaluation is soil water profit and loss statement while evapotranspiration (ET) is an important component in statement income and outcome of soil water. It is a very complicated problem to estimate evapotranspiration (ET) over large area of natural surface. In this paper, the natural surface was classified as 5 categories based on information from remote sensing, each categories being dealt with special way. Using data of remote sensing and weather stations, the result of regional evapotranspiration over Ningnan(South Ningxia) was given out, and verified and discussing are also made out. The work helps to assess whether or not improve environmental and ecological conditions.

Geomorphometry of Drainage Basin for Natural Resources Management Using High Resolution Satellite Data an Indian Example

NASA Astrophysics Data System (ADS)

Venkateswarlu, P.; Reddy, M. A.; Prasad, A. T.

2003-12-01

Application of Remote Sensing and Geographic Information System for the development of land and water resources action plan at micro level for appropriate management of land/water resources of a watershed in rain fed region of Prakasam District in Andhra Pradesh, India forms the focal theme of this paper. The quantitative description of drainage basin geometry can be effectively determined using Remote Sensing and GIS techniques. Each of the sixty-two sub-watersheds of the study area have been studied in terms of the Morphometric parameters - Stream length, Bifurcation ratio, Length ratio, Drainage density, Stream frequency, Texture ratio, Form factor, Area Perimeters, Circularity ratio and Elongation ratio and prioritized all the sub-watersheds under study. The prioritization of sub sheds based on morphometry is compared with sediment yield prioritization and found nearly same for the study area. The information obtained from the thematic maps are integrated and action plans are suggested for land and water resources development on a sustainable basis. Landuse/Landcover, Hydrogeomorphology and Soil thematic maps were generated. In addition slope and Drainage maps were prepared from Survey of India toposheets. Based on the computerized database created using ARC/INFO software, information derived in terms of natural resources and their spatial distribution was then integrated with the socio economic data to formulate an action plan, which includes suggestion of alternative Landuse/Landcover practices. Such a plan is useful for natural resources management and for improving the socio-economic status of rural population on a sustainable basis. Keywords: Natural Resources, Remote Sensing, Morphometry sustainable development.

Evaluation of Impacts of Landuse Changes on Air Quality in Hyderabad Metropolis Using Remote Sensing and GIS - A Case Study from Indian Sub-Continent

NASA Astrophysics Data System (ADS)

Vuppala, P.; S. S, A.; Mareddy, A.

2004-12-01

Around the world cities in developing countries are rapidly growing as more and more people become urban dwellers resulting in increased level of air pollution caused by changes in transportation, energy production and industrial activities. Air quality is an issue of critical importance in view of the accumulating evidence showing the adverse effects of pollution on human health, agricultural crops, manmade environments and ecosystems. An integrated study for identification of appropriate sites for representative evaluation of air pollution, novel means of monitoring air quality, identifying the predominant sources of pollution, effective assessment of air quality and evaluation of different management strategies essential for the development of a healthy and livable region is carried out for Hyderabad metropolis in India using Remote sensing and Geographical Information System (GIS) based assessment tools. Correlation studies between the concentration level of pollutants in urban air and urban land use are also dealt with. Municipal Corporation of Hyderabad (MCH) is divided into eleven planning zones out of which the present study area i.e. Zone I & IIA comprises of industrial, highly commercial and densely populated areas, apart from medium and sparse residential areas making it environmentally sensitive. Sampling locations were identified based on the land use/ land cover of the region and air samples were collected from areas having varying land use patterns using a high volume air sampler. The samples were then analyzed for the presence of Sulphur oxides(SO--x), Oxides of Nitrogen(NO--x), Total Suspended Particulate Matter(TSPM) and Respirable Suspended Particulate Matter(RSPM) using standard protocols and maps showing spatial distribution of SOx, NO--x, TSPM & RSPM were prepared using curve fitting technique of Arc/Info & ArcView GIS software. Air Quality Index (AQI), indicating the overall quality of air and extent of pollution is also calculated, based on which the entire study area is classified into severely, highly, moderately and lightly polluted areas. Concentration of SOx and NOx were observed to be within limits, while particulate pollutants exceeded the standards prescribed by Central Pollution Control Board (CPCB). The major cause of pollution in the study area is attributed to the increasing vehicular movements and presence of commercial and public related activities such as shopping malls. It is observed for the category of severe air pollution that 42% of pollution is from dense residential areas, 19% from medium residential and 1% load of pollution from other public related activities. Based on the results obtained suitable remedial measures to combat the increasing urban air pollution are suggested in the study area. Key words: Air pollution, Remote sensing, Geographical Information System, Spatial distribution, Air quality index.

System and method for cancelling the effects of stray magnetic fields from the output of a variable reluctance sensor

DOEpatents

Chen, Chingchi; Degner, Michael W.

2002-11-19

A sensor system for sensing a rotation of a sensing wheel is disclosed. The sensor system has a sensing coil in juxtaposition with the sensing wheel. Moreover, the sensing coil has a sensing coil output signal indicative of the rotational speed of the sensing wheel. Further, a cancellation coil is located remotely from the sensing coil and connected in series therewith. Additionally, the cancellation coil has a cancellation coil output signal indicative of an environmental disturbance which is effecting the sensing coil output signal. The cancellation coil output signal operates to cancel the effects of the environmental disturbance on the sensing coil output signal.

Applying remote sensing and GIS for chimpanzee habitat change detection, behaviour and conservation

NASA Astrophysics Data System (ADS)

Pintea, Lilian

Chimpanzees (Pan troglodytes), our closest living relatives, are declining alarmingly in abundance and distribution all across Africa. Clearing of forests and woodlands has one of the most rapid and devastating impacts, leaving chimpanzees in isolated, small populations that face edge effects and elevated risk of extinction. Satellite imagery could be a powerful tool to map chimpanzee habitats and threats at the landscape scale even in the most remote, difficult to access areas. However, few applications exist to demonstrate how remote sensing methods can be used in Africa for chimpanzee research and conservation in practice. In chapter one, I investigate the use of Landsat MSS and ETM+ satellite imagery to monitor dry tropical forests and miombo woodlands change between 1972-1999 inside and outside Gombe National Park, Tanzania. I show that canopy cover increased in the northern and middle parts of the park but with severe canopy loss outside protected area. Deforestation has had unequal effects on the three chimpanzee communities inside the park. The Kasekela chimpanzees have been least affected by canopy loss outside the park. In contrast, the Mitumba and Kalande communities have likely lost key range areas. In chapter two, I use 25 years of data on Gombe chimpanzees to investigate to what extent vegetation variables detected from multi-temporal satellite images can be applied to understand changes in chimpanzee feeding and party size. NDVI positively correlated with the time chimpanzees spent feeding but had no affect on the average number of adult males in the party. Instead the number of males in the party increased with proximity to hostile neighboring communities. In chapter three, I use Landsat and SPOT satellite imagery as the basis for Threat Reduction Assessment to evaluate conservation outcomes of a ten year community based conservation project in Tanzania. The findings suggest that the remote sensing methods applied in this study could provide new exciting prospects for monitoring chimpanzee habitats, socioecological research and a baseline to measure our conservation success.

Remote Sensing Application in Oil and Gas Industry

NASA Astrophysics Data System (ADS)

Sizov, Oleg; Aloltsov, Alexander; Rubtsova, Natalia

2014-05-01

The main environmental problems of the Khanty-Mansi Autonomous Okrug (a federal subject of Russia) related to the activities of oil and gas industry (82 active companies which hold 77,000 oil wells). As on the 1st of January 2013 the subject produces more than 50% of all oil in Russia. The principle of environmental responsibility makes it necessary to minimize human impact and ecological impact. One of the most effective tools for environmental monitoring is remote sensing. The main advantages of such approach are: wide coverage of areas of interest, high temporal resolution, precise location, automatic processing, large set of extracted parameters, etc. Authorities of KhMAO are interested in regular detection of the impact on the environment by processing satellite data and plan to increase the coverage from 434.9 to 659.9 square kilometers with resolution not less than 10 m/pixel. Years of experience of our company shows the significant potential to expand the use of such remote sensing data in the solution of environmental problems. The main directions are: monitoring of rational use of associated petroleum gas (detection of all gas flares and volumes of burned gas), monitoring of soil pollution (detection of areas of oil pollution, assess of the extent of pollution, planning of reclamation activities and assessment of their efficiency, detection of potential areas of pipelines corrosion), monitoring of status of sludge pits (inventory of all sludge pits, assessment of their liquidation), monitoring of technogenic impact (detection of changes), upgrading of a geospatial database (topographic map of not less than 1:50000 scale). Implementation of modeling, extrapolation and remote analysis techniques based on satellite images will help to reduce unnecessary costs for instrumental methods. Thus, the introduction of effective remote monitoring technology to the activity of oil and gas companies promotes environmental responsibility of these companies.

Geosphere-biosphere interactions in European Protected Areas: a view from the H2020 ECOPOTENTIAL Project

NASA Astrophysics Data System (ADS)

Provenzale, Antonello; Beierkuhnlein, Carl; Karnieli, Arnon; Marangi, Carmela; Giamberini, Mariasilvia; Imperio, Simona

2017-04-01

The large H2020 project ECOPOTENTIAL (2015-2019, 47 partners, contributing to GEO and GEOSS - http://www.ecopotential-project.eu/) is devoted to making best use of remote sensing and in situ data to improve future ecosystem benefits, adopting the view of ecosystems as one physical system with their environment, focusing on geosphere-biosphere interactions, Earth Critical Zone dynamics, Macrosystem Ecology and cross-scale interactions, the effect of extreme events and using Essential (Climate, Biodiversity and Ocean) Variables as descriptors of change. In ECOPOTENTIAL, remote sensing and in situ data are collected, processed and used for a better understanding of the ecosystem dynamics, analysing and modelling the effects of global changes on ecosystem functions and services, over an array of different ecosystem types, including mountain, marine, coastal, arid and semi-arid ecosystems. The project focuses on a network of Protected Areas of international relevance, that is representative of the range of environmental and biogeographical conditions characterizing Europe. Some of the activities of the project are devoted to detect and quantify the changes taking place in the Protected Areas, through the analysis of remote sensing observations, in-situ data and gridded climatic datasets. Likewise, the project aims at providing estimates of the future ecosystem conditions in different climate and environmental change scenarios. In all such endeavours, one is faced with cross-scale issues: downscaling of climate information to drive ecosystem response, and upscaling of local ecosystem changes to larger scales. So far, the analysis has been conducted mainly by using traditional methods, but there is wide room for improvement by using more refined approaches. In particular, a crucial question is how to upscale the information gained at single-site scale to larger, regional or continental scale, an issue that could benefit from using, for example, complex network analysis.